Meteorological Contribution to Variability in Particulate Matter Concentrations

NASA Astrophysics Data System (ADS)

Woods, H. L.; Spak, S. N.; Holloway, T.

2006-12-01

Local concentrations of fine particulate matter (PM) are driven by a number of processes, including emissions of aerosols and gaseous precursors, atmospheric chemistry, and meteorology at local, regional, and global scales. We apply statistical downscaling methods, typically used for regional climate analysis, to estimate the contribution of regional scale meteorology to PM mass concentration variability at a range of sites in the Upper Midwestern U.S. Multiple years of daily PM10 and PM2.5 data, reported by the U.S. Environmental Protection Agency (EPA), are correlated with large-scale meteorology over the region from the National Centers for Environmental Prediction (NCEP) reanalysis data. We use two statistical downscaling methods (multiple linear regression, MLR, and analog) to identify which processes have the greatest impact on aerosol concentration variability. Empirical Orthogonal Functions of the NCEP meteorological data are correlated with PM timeseries at measurement sites. We examine which meteorological variables exert the greatest influence on PM variability, and which sites exhibit the greatest response to regional meteorology. To evaluate model performance, measurement data are withheld for limited periods, and compared with model results. Preliminary results suggest that regional meteorological processes account over 50% of aerosol concentration variability at study sites.

Regional Morphology Analysis Package (RMAP): Empirical Orthogonal Function Analysis, Background and Examples

DTIC Science & Technology

2007-10-01

1984. Complex principal component analysis : Theory and examples. Journal of Climate and Applied Meteorology 23: 1660-1673. Hotelling, H. 1933...Sediments 99. ASCE: 2,566-2,581. Von Storch, H., and A. Navarra. 1995. Analysis of climate variability. Applications of statistical techniques. Berlin...ERDC TN-SWWRP-07-9 October 2007 Regional Morphology Empirical Analysis Package (RMAP): Orthogonal Function Analysis , Background and Examples by

Comparative glacio-climatological analysis of mass balance variability along the geographical margin of Europe

NASA Astrophysics Data System (ADS)

Lehoczky, Annamária; Kern, Zoltán; Pongrácz, Rita

2014-05-01

Glacio-climatological studies recognise glacier mass balance changes as high-confident climate indicators. The climatic sensitivity of a glacier does not simply depend on regional climate variability but also influenced via large- and mesoscale atmospheric circulation patterns. This study focuses on recent changes in the mass balance using records from three border regions of Europe, and investigates the relationships between the seasonal mass balance components, regional climatic conditions, and distant atmospheric forcing. Since glaciers in different macro-climatological conditions (i.e., mid-latitudes or high-latitudes, dry-continental or maritime regions) may present strongly diverse mass balance characteristics, the three analysed regions were selected from different glacierised macroregions (using the database of the World Glacier Monitoring Service). These regions belong to the Caucasus Mountains (Central Europe macroregion), the Polar Ural (Northern Asia macroregion), and Svalbard (Arctic Islands macroregion). The analysis focuses on winter, summer, and annual mass balance series of eight glaciers. The climatic variables (atmospheric pressure, air temperature, precipitation) and indices of teleconnection patterns (e.g., North Atlantic Oscillation, Pacific Decadal Oscillation) are used from the gridded databases of the University of East Anglia, Climatic Research Unit and the National Oceanic and Atmospheric Administration, National Center for Environmental Prediction. However, the period and length of available mass balance data in the selected regions vary greatly (the first full record is in 1958, Polar Ural; the last is in 2010, Caucasus Mountains), a comparative analysis can be carried out for the period of 1968-1981. Since glaciers from different regions respond to large- and mesoscale climatic forcings differently, and because the mass balance of glaciers within a region often co-vary, our specific objectives are (i) to examine the variability and the integrative climatic signal in the averaged mass balance records of the selected regions; (ii) to analyse the possible coupling between the mass balance and climatic variables, including the dominant patterns of Northern Hemisphere climate variability; and (iii) to compare the main characteristics of the three regions. Furthermore, (iv) a short discussion is given considering the significant decreasing trend of the cumulative annual mass balances in every region under the detected climatic changes in the second half of the 20th century. Preliminary results suggest that the strongest teleconnection links could be between winter mass balance and winter NAO for the Polar Ural (r=0.46, p<0.05), and between annual mass balance and PDO for Svalbard (r=-0.43, p<0.05). Neither seasonal, nor annual mass balance records showed significant correlation with any of the examined circulation indices for the Caucasus.

A new approach in space-time analysis of multivariate hydrological data: Application to Brazil's Nordeste region rainfall

NASA Astrophysics Data System (ADS)

Sicard, Emeline; Sabatier, Robert; Niel, HéLèNe; Cadier, Eric

2002-12-01

The objective of this paper is to implement an original method for spatial and multivariate data, combining a method of three-way array analysis (STATIS) with geostatistical tools. The variables of interest are the monthly amounts of rainfall in the Nordeste region of Brazil, recorded from 1937 to 1975. The principle of the technique is the calculation of a linear combination of the initial variables, containing a large part of the initial variability and taking into account the spatial dependencies. It is a promising method that is able to analyze triple variability: spatial, seasonal, and interannual. In our case, the first component obtained discriminates a group of rain gauges, corresponding approximately to the Agreste, from all the others. The monthly variables of July and August strongly influence this separation. Furthermore, an annual study brings out the stability of the spatial structure of components calculated for each year.

Multispecies Fisheries in the Lower Amazon River and Its Relationship with the Regional and Global Climate Variability

PubMed Central

Buss de Souza, Ronald; Freire, Juan; Isaac, Victoria Judith

2016-01-01

This paper aims to describe the spatial-temporal variability in catch of the main fishery resources of the Amazon River and floodplain lakes of the Lower Amazon, as well as relating the Catch per Unit of Effort with anomalies of some of the Amazon River, atmosphere and Atlantic Ocean system variables, determining the influence of the environment on the Amazonian fishery resources. Finfish landings data from the towns and villages of the Lower Amazon for the fisheries of three sites (Óbidos, Santarém and Monte Alegre), were obtained for the period between January 1993 and December 2004. Analysis of variance, detrended correspondence analysis, redundancy analysis and multiple regression techniques were used for the statistical analysis of the distinct time series. Fisheries production in the Lower Amazon presents differences between the Amazon River and the floodplain lakes. Production in the Amazon River is approximately half of the one of the floodplain lakes. This variability occurs both along the Lower Amazon River region (longitudinal gradient) and laterally (latitudinal gradient) for every fishing ground studied here. The distinct environmental variables alone or in association act differently on the fishery stocks and the success of catches in each fishery group studied here. Important variables are the flooding events; the soil the sea surface temperatures; the humidity; the wind and the occurence of El Niño-Southern Oscillation events. Fishery productivity presents a large difference in quantity and distribution patterns between the river and floodplain lakes. This variability occurs in the region of the Lower Amazon as well as laterally for each fishery group studied, being dependent on the ecological characteristics and life strategies of each fish group considered here. PMID:27314951

Stratification of a cityscape using census and land use variables for inventory of building materials

USGS Publications Warehouse

Rosenfield, G.H.; Fitzpatrick-Lins, K.; Johnson, T.L.

1987-01-01

A cityscape (or any landscape) can be stratified into environmental units using multiple variables of information. For the purposes of sampling building materials, census and land use variables were used to identify similar strata. In the Metropolitan Statistical Area of a cityscape, the census tract is the smallest unit for which census data are summarized and digitized boundaries are available. For purposes of this analysis, census data on total population, total number of housing units, and number of singleunit dwellings were aggregated into variables of persons per square kilometer and proportion of housing units in single-unit dwellings. The level 2 categories of the U.S. Geological Survey's land use and land cover data base were aggregated into variables of proportion of residential land with buildings, proportion of nonresidential land with buildings, and proportion of open land. The cityscape was stratified, from these variables, into environmental strata of Urban Central Business District, Urban Livelihood Industrial Commercial, Urban Multi-Family Residential, Urban Single Family Residential, Non-Urban Suburbanizing, and Non-Urban Rural. The New England region was chosen as a region with commonality of building materials, and a procedure developed for trial classification of census tracts into one of the strata. Final stratification was performed by discriminant analysis using the trial classification and prior probabilities as weights. The procedure was applied to several cities, and the results analyzed by correlation analysis from a field sample of building materials. The methodology developed for stratification of a cityscape using multiple variables has application to many other types of environmental studies, including forest inventory, hydrologic unit management, waste disposal, transportation studies, and other urban studies. Multivariate analysis techniques have recently been used for urban stratification in England. ?? 1987 Annals of Regional Science.

Variability and trends of local/regional scale surface climate in northern Africa during the twentieth century

NASA Astrophysics Data System (ADS)

Djomou, Zéphirin Yepdo; Monkam, David; Woafo, Paul

2014-08-01

Four regions are detected in northern Africa (20° W-40° E, 0-30° N) by applying the cluster analysis method on the annual rainfall anomalies of the period 1901-2000. The first region (R1), an arid land, covers essentially the north of 17.75° N from west to east of the study zone. The second region (R2), a semiarid land with a Sahelian climate, less warm than the dry climate of R1, is centred on Chad, with almost regular extension to the west towards Mauritania, and to the east, including the north of the Central African Republic and the Sudan. The region 3 (R3), a wet land, is centred on the Ivory Coast and covers totally Liberia, the south part of Ghana, Togo, Benin and the southwest of Nigeria. The fourth region (R4), corresponding to the wet equatorial forest, covers a part of Senegal, the Central Africa, the south of Sudan and a part of Ethiopia. An analysis of observed temperature and precipitation variability and trends throughout the twentieth century over these regions is presented. Summer, winter and annual data are examined using a range of variability measures. Statistically, significant warming trends are found over the majority of regions. The trends have a magnitude of up to 1.5 K per century. Only a few precipitation trends are statistically significant. Regional temperature and precipitation show pronounced variability at scales from interannual to multi-decadal. The interannual variability shows significant variations and trends throughout the century, the latter being mostly negative for precipitation and both positive and negative for temperature. Temperature and precipitation anomalies show a chaotic-type behaviour in which the regional conditions oscillate around the long-term mean trend and occasionally fall into long-lasting (up to 10 years or more) anomaly regimes. A generally modest temporal correlation is found between anomalies of different regions and between temperature and precipitation anomalies for the same region. This correlation is mostly positive for temperature in cases of adjacent regions. Several cases of negative interregional precipitation anomaly correlation are found. The El Niño Southern Oscillation significantly affects the anomaly variability patterns over a number of regions, mainly regions 3 (R3) and 4 (R4), while the North Atlantic Oscillation significantly affects the variability over arid and semiarid regions, R1 and R2.

FUNGAL-SPECIFIC PCR PRIMERS DEVELOPED FOR ANALYSIS OF THE ITS REGION OF ENVIRONMENTAL DNA EXTRACTS

EPA Science Inventory

Background The Internal Transcribed Spacer (ITS) regions of fungal ribosomal DNA (rDNA) are highly variable sequences of great importance in distinguishing fungal species by PCR analysis. Previously published PCR primers available for amplifying these sequences from environmenta...

Urban Heat Wave Vulnerability Analysis Considering Climate Change

NASA Astrophysics Data System (ADS)

JE, M.; KIM, H.; Jung, S.

2017-12-01

Much attention has been paid to thermal environments in Seoul City in South Korea since 2016 when the worst heatwave in 22 years. It is necessary to provide a selective measure by singling out vulnerable regions in advance to cope with the heat wave-related damage. This study aims to analyze and categorize vulnerable regions of thermal environments in the Seoul and analyzes and discusses the factors and risk factors for each type. To do this, this study conducted the following processes: first, based on the analyzed various literature reviews, indices that can evaluate vulnerable regions of thermal environment are collated. The indices were divided into climate exposure index related to temperature, sensitivity index including demographic, social, and economic indices, and adaptation index related to urban environment and climate adaptation policy status. Second, significant variables were derived to evaluate a vulnerable region of thermal environment based on the summarized indices in the above. this study analyzed a relationship between the number of heat-related patients in Seoul and variables that affected the number using multi-variate statistical analysis to derive significant variables. Third, the importance of each variable was calculated quantitatively by integrating the statistical analysis results and analytic hierarchy process (AHP) method. Fourth, a distribution of data for each index was identified based on the selected variables and indices were normalized and overlapped. Fifth, For the climate exposure index, evaluations were conducted as same as the current vulnerability evaluation method by selecting future temperature of Seoul predicted through the representative concentration pathways (RCPs) climate change scenarios as an evaluation variable. The results of this study can be utilized as foundational data to establish a countermeasure against heatwave in Seoul. Although it is limited to control heatwave occurrences itself completely, improvements on environment for heatwave alleviation and response can be done. In particular, if vulnerable regions of heatwave can be identified and managed in advance, the study results are expected to be utilized as a basis of policy utilization in local communities accordingly.

A comprehensive analysis of coherent rainfall patterns in China and potential drivers. Part I: Interannual variability

NASA Astrophysics Data System (ADS)

Stephan, Claudia Christine; Klingaman, Nicholas Pappas; Vidale, Pier Luigi; Turner, Andrew George; Demory, Marie-Estelle; Guo, Liang

2018-06-01

Interannual rainfall variability in China affects agriculture, infrastructure and water resource management. To improve its understanding and prediction, many studies have associated precipitation variability with particular causes for specific seasons and regions. Here, a consistent and objective method, Empirical Orthogonal Teleconnection (EOT) analysis, is applied to 1951-2007 high-resolution precipitation observations over China in all seasons. Instead of maximizing the explained space-time variance, the method identifies regions in China that best explain the temporal variability in domain-averaged rainfall. The EOT method is validated by the reproduction of known relationships to the El Niño Southern Oscillation (ENSO): high positive correlations with ENSO are found in eastern China in winter, along the Yangtze River in summer, and in southeast China during spring. New findings include that wintertime rainfall variability along the southeast coast is associated with anomalous convection over the tropical eastern Atlantic and communicated to China through a zonal wavenumber-three Rossby wave. Furthermore, spring rainfall variability in the Yangtze valley is related to upper-tropospheric midlatitude perturbations that are part of a Rossby wave pattern with its origin in the North Atlantic. A circumglobal wave pattern in the northern hemisphere is also associated with autumn precipitation variability in eastern areas. The analysis is objective, comprehensive, and produces timeseries that are tied to specific locations in China. This facilitates the interpretation of associated dynamical processes, is useful for understanding the regional hydrological cycle, and allows the results to serve as a benchmark for assessing general circulation models.

Identification of genome regions determining semen quality in Holstein-Friesian bulls using information theory.

PubMed

Borowska, Alicja; Szwaczkowski, Tomasz; Kamiński, Stanisław; Hering, Dorota M; Kordan, Władysław; Lecewicz, Marek

2018-05-01

Use of information theory can be an alternative statistical approach to detect genome regions and candidate genes that are associated with livestock traits. The aim of this study was to verify the validity of the SNPs effects on some semen quality variables of bulls using entropy analysis. Records from 288 Holstein-Friesian bulls from one AI station were included. The following semen quality variables were analyzed: CASA kinematic variables of sperm (total motility, average path velocity, straight line velocity, curvilinear velocity, amplitude of lateral head displacement, beat cross frequency, straightness, linearity), sperm membrane integrity (plazmolema, mitochondrial function), sperm ATP content. Molecular data included 48,192 SNPs. After filtering (call rate = 0.95 and MAF = 0.05), 34,794 SNPs were included in the entropy analysis. The entropy and conditional entropy were estimated for each SNP. Conditional entropy quantifies the remaining uncertainty about values of the variable with the knowledge of SNP. The most informative SNPs for each variable were determined. The computations were performed using the R statistical package. A majority of the loci had relatively small contributions. The most informative SNPs for all variables were mainly located on chromosomes: 3, 4, 5 and 16. The results from the study indicate that important genome regions and candidate genes that determine semen quality variables in bulls are located on a number of chromosomes. Some detected clusters of SNPs were located in RNA (U6 and 5S_rRNA) for all the variables for which analysis occurred. Associations between PARK2 as well GALNT13 genes and some semen characteristics were also detected. Copyright © 2018 Elsevier B.V. All rights reserved.

Prediction of Biological Motion Perception Performance from Intrinsic Brain Network Regional Efficiency

PubMed Central

Wang, Zengjian; Zhang, Delong; Liang, Bishan; Chang, Song; Pan, Jinghua; Huang, Ruiwang; Liu, Ming

2016-01-01

Biological motion perception (BMP) refers to the ability to perceive the moving form of a human figure from a limited amount of stimuli, such as from a few point lights located on the joints of a moving body. BMP is commonplace and important, but there is great inter-individual variability in this ability. This study used multiple regression model analysis to explore the association between BMP performance and intrinsic brain activity, in order to investigate the neural substrates underlying inter-individual variability of BMP performance. The resting-state functional magnetic resonance imaging (rs-fMRI) and BMP performance data were collected from 24 healthy participants, for whom intrinsic brain networks were constructed, and a graph-based network efficiency metric was measured. Then, a multiple linear regression model was used to explore the association between network regional efficiency and BMP performance. We found that the local and global network efficiency of many regions was significantly correlated with BMP performance. Further analysis showed that the local efficiency rather than global efficiency could be used to explain most of the BMP inter-individual variability, and the regions involved were predominately located in the Default Mode Network (DMN). Additionally, discrimination analysis showed that the local efficiency of certain regions such as the thalamus could be used to classify BMP performance across participants. Notably, the association pattern between network nodal efficiency and BMP was different from the association pattern of static directional/gender information perception. Overall, these findings show that intrinsic brain network efficiency may be considered a neural factor that explains BMP inter-individual variability. PMID:27853427

Protocol for statistical analysis of vegetation changes at Catoctin Mountain Park

USGS Publications Warehouse

Hatfield, Jeff S.; Krafft, Cairn

2010-01-01

Vegetation data collected at Catoctin Mountain Park, Maryland, in a split-panel rotation design during 2004-2009 were analyzed for differences among three regions within the park and among years. Six plots were paired with plots fenced to exclude white-tailed deer (Odocoileus virginianus), and differences between open and exclosed plots were also investigated. Repeated measures analysis of variance (ANOVA) was used to test for differences in the following variables: percentage of twigs browsed, percentage of canopy cover, and number of tree and shrub seedlings in each of five height classes. Except for some differences in numbers of tree and shrub seedlings among height classes among the regions, no differences (P > 0.05) were found among the regions or over time in the variables measured. Recommendations for future sampling and analysis are discussed.

Analysis of the relationship between community characteristics and depression using geographically weighted regression.

PubMed

Choi, Hyungyun; Kim, Ho

2017-01-01

Achieving national health equity is currently a pressing issue. Large regional variations in the health determinants are observed. Depression, one of the most common mental disorders, has large variations in incidence among different populations, and thus must be regionally analyzed. The present study aimed at analyzing regional disparities in depressive symptoms and identifying the health determinants that require regional interventions. Using health indicators of depression in the Korea Community Health Survey 2011 and 2013, the Moran's I was calculated for each variable to assess spatial autocorrelation, and a validated geographically weighted regression analysis using ArcGIS version 10.1 of different domains: health behavior, morbidity, and the social and physical environments were created, and the final model included a combination of significant variables in these models. In the health behavior domain, the weekly breakfast intake frequency of 1-2 times was the most significantly correlated with depression in all regions, followed by exposure to secondhand smoke and the level of perceived stress in some regions. In the morbidity domain, the rate of lifetime diagnosis of myocardial infarction was the most significantly correlated with depression. In the social and physical environment domain, the trust environment within the local community was highly correlated with depression, showing that lower the level of trust, higher was the level of depression. A final model was constructed and analyzed using highly influential variables from each domain. The models were divided into two groups according to the significance of correlation of each variable with the experience of depression symptoms. The indicators of the regional health status are significantly associated with the incidence of depressive symptoms within a region. The significance of this correlation varied across regions.

Urban vs. Rural CLIL: An Analysis of Input-Related Variables, Motivation and Language Attainment

ERIC Educational Resources Information Center

Alejo, Rafael; Piquer-Píriz, Ana

2016-01-01

The present article carries out an in-depth analysis of the differences in motivation, input-related variables and linguistic attainment of the students at two content and language integrated learning (CLIL) schools operating within the same institutional and educational context, the Spanish region of Extremadura, and differing only in terms of…

Variables influencing allocation of capital expenditure in Indonesia

NASA Astrophysics Data System (ADS)

Muda, Iskandar; Naibaho, Revmianson

2018-03-01

The purpose of this study is to examine the factors affecting capital expenditure in Indonesia. The independent variables used are The Effects of Financing Surplus, Total Population and Regional Sizes and the dependent variable used is The Effects of Financing Surplus. This type of research is a causal associative research. The type of data used is secondary data in severals provinces in Indonesia with multiple regression analysis. The results show significantly the determinants of capital expenditure allocation in Indonesia are affected by Financing Surplus, Total Population and Regional Sizes.

Spatialization of Brazilian pig production: relationship between productive, physical, environmental, and socio-economic variables.

PubMed

da Silva, Isabel C M; Bremm, Bárbara; Teixeira, Jennifer L; Costa, Nathalia S; Barcellos, Júlio O J; Braccini, José; Cesconeto, Robson J; McManus, Concepta

2017-06-01

Brazilian pig production spans over a large territory encompassing regions of different climatic and socio-economic realities. Production, physical, socio-economic, and environmental data were used to characterize pig production in the country. Multivariate analysis evaluated indices including number productivity, production levels, and income from pigs, together with the average area of pig farm and socio-economic variables such as municipal human development index, technical guidance received from agricultural cooperatives and industrial companies, number of family farms, and offtake; and finally, environmental variables: latitude, longitude, annual temperature range, solar radiation index, as well as temperature and humidity index. The Southern region has the largest herd, number of pigs sold/sow, and offtake rate (p < 0.05), followed by the Midwest and Southeast. No significant correlations were seen between production rates and productivity with the socio-economic and environmental variables in the regions of Brazil. Production indexes, productivity, and offtake rate discriminated Northeast and Midwest and Northeast and Southeast regions. The Northern region, with a large area, has few and far-between farms that rear pigs for subsistence. The Northeast region has large herds, but low productivity. Number of slaughtered pigs has been variable over the past three decades, with few states responsible for maintaining high production in Brazil. However, the activity can be effective in any region of the country with technology and technical assistance adapted to regional characteristics.

[Comparative analysis of variable regions in the genomes of variola virus].

PubMed

Babkin, I V; Nepomniashchikh, T S; Maksiutov, R A; Gutorov, V V; Babkina, I N; Shchelkunov, S N

2008-01-01

Nucleotide sequences of two extended segments of the terminal variable regions in variola virus genome were determined. The size of the left segment was 13.5 kbp and of the right, 10.5 kbp. Totally, over 540 kbp were sequenced for 22 variola virus strains. The conducted phylogenetic analysis and the data published earlier allowed us to find the interrelations between 70 variola virus isolates, the character of their clustering, and the degree of intergroup and intragroup variations of the clusters of variola virus strains. The most polymorphic loci of the genome segments studied were determined. It was demonstrated that that these loci are localized to either noncoding genome regions or to the regions of destroyed open reading frames, characteristic of the ancestor virus. These loci are promising for development of the strategy for genotyping variola virus strains. Analysis of recombination using various methods demonstrated that, with the only exception, no statistically significant recombinational events in the genomes of variola virus strains studied were detectable.

The Regionalization of Africa in Undergraduate Geography of Africa Textbooks, 1953 to 2004

ERIC Educational Resources Information Center

Cole, Roy

2008-01-01

This study examines the regionalization of Africa through analysis of forty-two English-language geography of Africa texts written for undergraduates between 1953 and 2004. Authors identify regions with reference to one or more variables. Some authors provided no explanation for their regionalization; others labored mightily to justify their…

Mean annual runoff and peak flow estimates based on channel geometry of streams in northeastern and western Montana

USGS Publications Warehouse

Parrett, Charles; Omang, R.J.; Hull, J.A.

1983-01-01

Equations for estimating mean annual runoff and peak discharge from measurements of channel geometry were developed for western and northeastern Montana. The study area was divided into two regions for the mean annual runoff analysis, and separate multiple-regression equations were developed for each region. The active-channel width was determined to be the most important independent variable in each region. The standard error of estimate for the estimating equation using active-channel width was 61 percent in the Northeast Region and 38 percent in the West region. The study area was divided into six regions for the peak discharge analysis, and multiple regression equations relating channel geometry and basin characteristics to peak discharges having recurrence intervals of 2, 5, 10, 25, 50 and 100 years were developed for each region. The standard errors of estimate for the regression equations using only channel width as an independent variable ranged from 35 to 105 percent. The standard errors improved in four regions as basin characteristics were added to the estimating equations. (USGS)

Characterization of Lipooligosaccharide-Biosynthetic Loci of Campylobacter jejuni Reveals New Lipooligosaccharide Classes: Evidence of Mosaic Organizations▿ †

PubMed Central

Parker, Craig T.; Gilbert, Michel; Yuki, Nobuhiro; Endtz, Hubert P.; Mandrell, Robert E.

2008-01-01

The lipooligosaccharide (LOS) biosynthesis region is one of the more variable genomic regions between strains of Campylobacter jejuni. Indeed, eight classes of LOS biosynthesis loci have been established previously based on gene content and organization. In this study, we characterize additional classes of LOS biosynthesis loci and analyze various mechanisms that result in changes to LOS structures. To gain further insights into the genomic diversity of C. jejuni LOS biosynthesis region, we sequenced the LOS biosynthesis loci of 15 strains that possessed gene content that was distinct from the eight classes. This analysis identified 11 new classes of LOS loci that exhibited examples of deletions and insertions of genes and cassettes of genes found in other LOS classes or capsular biosynthesis loci leading to mosaic LOS loci. The sequence analysis also revealed both missense mutations leading to “allelic” glycosyltransferases and phase-variable and non-phase-variable gene inactivation by the deletion or insertion of bases. Specifically, we demonstrated that gene inactivation is an important mechanism for altering the LOS structures of strains possessing the same class of LOS biosynthesis locus. Together, these observations suggest that LOS biosynthesis region is a hotspot for genetic exchange and variability, often leading to changes in the LOS produced. PMID:18556784

Flood regionalization: A hybrid geographic and predictor-variable region-of-influence regression method

USGS Publications Warehouse

Eng, K.; Milly, P.C.D.; Tasker, Gary D.

2007-01-01

To facilitate estimation of streamflow characteristics at an ungauged site, hydrologists often define a region of influence containing gauged sites hydrologically similar to the estimation site. This region can be defined either in geographic space or in the space of the variables that are used to predict streamflow (predictor variables). These approaches are complementary, and a combination of the two may be superior to either. Here we propose a hybrid region-of-influence (HRoI) regression method that combines the two approaches. The new method was applied with streamflow records from 1,091 gauges in the southeastern United States to estimate the 50-year peak flow (Q50). The HRoI approach yielded lower root-mean-square estimation errors and produced fewer extreme errors than either the predictor-variable or geographic region-of-influence approaches. It is concluded, for Q50 in the study region, that similarity with respect to the basin characteristics considered (area, slope, and annual precipitation) is important, but incomplete, and that the consideration of geographic proximity of stations provides a useful surrogate for characteristics that are not included in the analysis. ?? 2007 ASCE.

The ichthyoplankton assemblage and the environmental variables off the NW and N Iberian Peninsula coasts, in early spring

NASA Astrophysics Data System (ADS)

Rodriguez, J. M.; Gonzalez-Nuevo, G.; Gonzalez-Pola, C.; Cabal, J.

2009-05-01

Ichthyoplankton and mesozooplankton were sampled and fluorescence and physical environmental variables were measured off the NW and N Iberian Peninsula coasts, during April 2005. A total of 51 species of fish larvae, belonging to 26 families, were recorded. Sardina pilchardus, with 43.8% and 58.7% of the total fish egg and larval catches, respectively, dominated the ichthyoplankton assemblage. The study area was divided by a cross-shelf frontal structure into two hydrographic regions that coincided with the Atlantic and Cantabrian geographic regions. Ichthyoplankton abundance was higher in the Cantabrian region while larval diversity was higher in the Atlantic region. This was the main alongshore variability in the structure of the larval fish assemblage. Nevertheless, the stronger variability, related with the presence of a shelf-slope front, was found in the central-eastern Cantabrian region where two major larval fish assemblages, an "outer" and a "coastal", were distinguished. The Atlantic region, where the shelf-slope front was not found, was inhabited by a single larval fish assemblage. Canonical correspondence analysis revealed that, off the NW and N Iberian Peninsula coasts, the horizontal distribution of larval fish species in early spring may be explained by a limited number of environmental variables. Of these, the most important were the physical variables depth and sea surface temperature.

T-tubule disease: Relationship between t-tubule organization and regional contractile performance in human dilated cardiomyopathy.

PubMed

Crossman, David J; Young, Alistair A; Ruygrok, Peter N; Nason, Guy P; Baddelely, David; Soeller, Christian; Cannell, Mark B

2015-07-01

Evidence from animal models suggest that t-tubule changes may play an important role in the contractile deficit associated with heart failure. However samples are usually taken at random with no regard as to regional variability present in failing hearts which leads to uncertainty in the relationship between contractile performance and possible t-tubule derangement. Regional contraction in human hearts was measured by tagged cine MRI and model fitting. At transplant, failing hearts were biopsy sampled in identified regions and immunocytochemistry was used to label t-tubules and sarcomeric z-lines. Computer image analysis was used to assess 5 different unbiased measures of t-tubule structure/organization. In regions of failing hearts that showed good contractile performance, t-tubule organization was similar to that seen in normal hearts, with worsening structure correlating with the loss of regional contractile performance. Statistical analysis showed that t-tubule direction was most highly correlated with local contractile performance, followed by the amplitude of the sarcomeric peak in the Fourier transform of the t-tubule image. Other area based measures were less well correlated. We conclude that regional contractile performance in failing human hearts is strongly correlated with the local t-tubule organization. Cluster tree analysis with a functional definition of failing contraction strength allowed a pathological definition of 't-tubule disease'. The regional variability in contractile performance and cellular structure is a confounding issue for analysis of samples taken from failing human hearts, although this may be overcome with regional analysis by using tagged cMRI and biopsy mapping. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multi-region statistical shape model for cochlear implantation

NASA Astrophysics Data System (ADS)

Romera, Jordi; Kjer, H. Martin; Piella, Gemma; Ceresa, Mario; González Ballester, Miguel A.

2016-03-01

Statistical shape models are commonly used to analyze the variability between similar anatomical structures and their use is established as a tool for analysis and segmentation of medical images. However, using a global model to capture the variability of complex structures is not enough to achieve the best results. The complexity of a proper global model increases even more when the amount of data available is limited to a small number of datasets. Typically, the anatomical variability between structures is associated to the variability of their physiological regions. In this paper, a complete pipeline is proposed for building a multi-region statistical shape model to study the entire variability from locally identified physiological regions of the inner ear. The proposed model, which is based on an extension of the Point Distribution Model (PDM), is built for a training set of 17 high-resolution images (24.5 μm voxels) of the inner ear. The model is evaluated according to its generalization ability and specificity. The results are compared with the ones of a global model built directly using the standard PDM approach. The evaluation results suggest that better accuracy can be achieved using a regional modeling of the inner ear.

Geostatistical Analysis of Mesoscale Spatial Variability and Error in SeaWiFS and MODIS/Aqua Global Ocean Color Data

NASA Astrophysics Data System (ADS)

Glover, David M.; Doney, Scott C.; Oestreich, William K.; Tullo, Alisdair W.

2018-01-01

Mesoscale (10-300 km, weeks to months) physical variability strongly modulates the structure and dynamics of planktonic marine ecosystems via both turbulent advection and environmental impacts upon biological rates. Using structure function analysis (geostatistics), we quantify the mesoscale biological signals within global 13 year SeaWiFS (1998-2010) and 8 year MODIS/Aqua (2003-2010) chlorophyll a ocean color data (Level-3, 9 km resolution). We present geographical distributions, seasonality, and interannual variability of key geostatistical parameters: unresolved variability or noise, resolved variability, and spatial range. Resolved variability is nearly identical for both instruments, indicating that geostatistical techniques isolate a robust measure of biophysical mesoscale variability largely independent of measurement platform. In contrast, unresolved variability in MODIS/Aqua is substantially lower than in SeaWiFS, especially in oligotrophic waters where previous analysis identified a problem for the SeaWiFS instrument likely due to sensor noise characteristics. Both records exhibit a statistically significant relationship between resolved mesoscale variability and the low-pass filtered chlorophyll field horizontal gradient magnitude, consistent with physical stirring acting on large-scale gradient as an important factor supporting observed mesoscale variability. Comparable horizontal length scales for variability are found from tracer-based scaling arguments and geostatistical decorrelation. Regional variations between these length scales may reflect scale dependence of biological mechanisms that also create variability directly at the mesoscale, for example, enhanced net phytoplankton growth in coastal and frontal upwelling and convective mixing regions. Global estimates of mesoscale biophysical variability provide an improved basis for evaluating higher resolution, coupled ecosystem-ocean general circulation models, and data assimilation.

TEC Longitude Difference Using GIMS and the IRI Model

NASA Astrophysics Data System (ADS)

Natali, Maria Paula; Meza, Amalia Margarita; Mendoza, Gastón

2016-07-01

The main geomagnetic field declination has a global distribution with positive and negative values showing maximum east-west differences over North America and Oceania and minimum differences over America and Asia. Several authors study one or more of these regions using TEC data derived from GNSS observations to describe variations in TEC. They reported a pronounced longitudinal variation respect to zero magnetic declination. One of the important factors that cause the longitude difference at mid-latitude is a combined effect of the longitude variations of magnetic declination and the variations of the zonal thermospheric winds with local time. We propose to study this effect using Global Ionospheric Maps (GIMs) and the respective TEC values generated from the International Reference Ionospheric (IRI) model, during a solar cycle, applying Principal Component Analysis (PCA). Our works is focused over different local times and regions at mid-latitude. PCA involves a mathematical procedure that transforms a number of correlated variables into a number of uncorrelated variables using the data itself. The spatial structure of the ionosphere variability and its temporal evolution, together are called modes, and there are ordered according to their percentage of the variability of data from highest to lowest. In this analysis the first mode has more than the 90 % of the variability, representing the nominal behavior of the ionosphere, and the second and third modes are the more important for our analysis, because they show the strong longitudinal variation in the different regions using either GIMs or the IRI model.

Exploring objective climate classification for the Himalayan arc and adjacent regions using gridded data sources

NASA Astrophysics Data System (ADS)

Forsythe, N.; Blenkinsop, S.; Fowler, H. J.

2015-05-01

A three-step climate classification was applied to a spatial domain covering the Himalayan arc and adjacent plains regions using input data from four global meteorological reanalyses. Input variables were selected based on an understanding of the climatic drivers of regional water resource variability and crop yields. Principal component analysis (PCA) of those variables and k-means clustering on the PCA outputs revealed a reanalysis ensemble consensus for eight macro-climate zones. Spatial statistics of input variables for each zone revealed consistent, distinct climatologies. This climate classification approach has potential for enhancing assessment of climatic influences on water resources and food security as well as for characterising the skill and bias of gridded data sets, both meteorological reanalyses and climate models, for reproducing subregional climatologies. Through their spatial descriptors (area, geographic centroid, elevation mean range), climate classifications also provide metrics, beyond simple changes in individual variables, with which to assess the magnitude of projected climate change. Such sophisticated metrics are of particular interest for regions, including mountainous areas, where natural and anthropogenic systems are expected to be sensitive to incremental climate shifts.

VoxelStats: A MATLAB Package for Multi-Modal Voxel-Wise Brain Image Analysis.

PubMed

Mathotaarachchi, Sulantha; Wang, Seqian; Shin, Monica; Pascoal, Tharick A; Benedet, Andrea L; Kang, Min Su; Beaudry, Thomas; Fonov, Vladimir S; Gauthier, Serge; Labbe, Aurélie; Rosa-Neto, Pedro

2016-01-01

In healthy individuals, behavioral outcomes are highly associated with the variability on brain regional structure or neurochemical phenotypes. Similarly, in the context of neurodegenerative conditions, neuroimaging reveals that cognitive decline is linked to the magnitude of atrophy, neurochemical declines, or concentrations of abnormal protein aggregates across brain regions. However, modeling the effects of multiple regional abnormalities as determinants of cognitive decline at the voxel level remains largely unexplored by multimodal imaging research, given the high computational cost of estimating regression models for every single voxel from various imaging modalities. VoxelStats is a voxel-wise computational framework to overcome these computational limitations and to perform statistical operations on multiple scalar variables and imaging modalities at the voxel level. VoxelStats package has been developed in Matlab(®) and supports imaging formats such as Nifti-1, ANALYZE, and MINC v2. Prebuilt functions in VoxelStats enable the user to perform voxel-wise general and generalized linear models and mixed effect models with multiple volumetric covariates. Importantly, VoxelStats can recognize scalar values or image volumes as response variables and can accommodate volumetric statistical covariates as well as their interaction effects with other variables. Furthermore, this package includes built-in functionality to perform voxel-wise receiver operating characteristic analysis and paired and unpaired group contrast analysis. Validation of VoxelStats was conducted by comparing the linear regression functionality with existing toolboxes such as glim_image and RMINC. The validation results were identical to existing methods and the additional functionality was demonstrated by generating feature case assessments (t-statistics, odds ratio, and true positive rate maps). In summary, VoxelStats expands the current methods for multimodal imaging analysis by allowing the estimation of advanced regional association metrics at the voxel level.

Comparative Molecular and Morphological Variation Analysis of Siderastrea (Anthozoa, Scleractinia) Reveals the Presence of Siderastrea stellata in the Gulf of Mexico.

PubMed

García, Norberto A Colín; Campos, Jorge E; Musi, José L Tello; Forsman, Zac H; Muñoz, Jorge L Montero; Reyes, Alejandro Monsalvo; González, Jesús E Arias

2017-02-01

The genus Siderastrea exhibits high levels of morphological variability. Some of its species share similar morphological characteristics with congeners, making their identification difficult. Siderastrea stellata has been reported as an intermediary of S. siderea and S. radians in the Brazilian reef ecosystem. In an earlier study conducted in Mexico, we detected Siderastrea colonies with morphological features that were not consistent with some siderastreid species previously reported in the Gulf of Mexico. Thus, we performed a combined morphological and molecular analysis to identify Siderastrea species boundaries from the Gulf of Mexico. Some colonies presented high morphologic variability, with characteristics that corresponded to Siderastrea stellata. Molecular analysis, using the nuclear ITS and ITS2 region, corroborated the morphological results, revealing low genetic variability between S. radians and S. stellata. Since the ITS sequences did not distinguish between Siderastrea species, we used the ITS2 region to differentiate S. stellata from S. radians. This is the first report of Siderastrea stellata and its variability in the Gulf of Mexico that is supported by morphological and molecular analyses.

Hydropower plans in eastern and southern Africa increase risk of concurrent climate-related electricity supply disruption

NASA Astrophysics Data System (ADS)

Conway, Declan; Dalin, Carole; Landman, Willem A.; Osborn, Timothy J.

2017-12-01

Hydropower comprises a significant and rapidly expanding proportion of electricity production in eastern and southern Africa. In both regions, hydropower is exposed to high levels of climate variability and regional climate linkages are strong, yet an understanding of spatial interdependences is lacking. Here we consider river basin configuration and define regions of coherent rainfall variability using cluster analysis to illustrate exposure to the risk of hydropower supply disruption of current (2015) and planned (2030) hydropower sites. Assuming completion of the dams planned, hydropower will become increasingly concentrated in the Nile (from 62% to 82% of total regional capacity) and Zambezi (from 73% to 85%) basins. By 2030, 70% and 59% of total hydropower capacity will be located in one cluster of rainfall variability in eastern and southern Africa, respectively, increasing the risk of concurrent climate-related electricity supply disruption in each region. Linking of nascent regional electricity sharing mechanisms could mitigate intraregional risk, although these mechanisms face considerable political and infrastructural challenges.

Strong influence of variable treatment on the performance of numerically defined ecological regions.

PubMed

Snelder, Ton; Lehmann, Anthony; Lamouroux, Nicolas; Leathwick, John; Allenbach, Karin

2009-10-01

Numerical clustering has frequently been used to define hierarchically organized ecological regionalizations, but there has been little robust evaluation of their performance (i.e., the degree to which regions discriminate areas with similar ecological character). In this study we investigated the effect of the weighting and treatment of input variables on the performance of regionalizations defined by agglomerative clustering across a range of hierarchical levels. For this purpose, we developed three ecological regionalizations of Switzerland of increasing complexity using agglomerative clustering. Environmental data for our analysis were drawn from a 400 m grid and consisted of estimates of 11 environmental variables for each grid cell describing climate, topography and lithology. Regionalization 1 was defined from the environmental variables which were given equal weights. We used the same variables in Regionalization 2 but weighted and transformed them on the basis of a dissimilarity model that was fitted to land cover composition data derived for a random sample of cells from interpretation of aerial photographs. Regionalization 3 was a further two-stage development of Regionalization 2 where specific classifications, also weighted and transformed using dissimilarity models, were applied to 25 small scale "sub-domains" defined by Regionalization 2. Performance was assessed in terms of the discrimination of land cover composition for an independent set of sites using classification strength (CS), which measured the similarity of land cover composition within classes and the dissimilarity between classes. Regionalization 2 performed significantly better than Regionalization 1, but the largest gains in performance, compared to Regionalization 1, occurred at coarse hierarchical levels (i.e., CS did not increase significantly beyond the 25-region level). Regionalization 3 performed better than Regionalization 2 beyond the 25-region level and CS values continued to increase to the 95-region level. The results show that the performance of regionalizations defined by agglomerative clustering are sensitive to variable weighting and transformation. We conclude that large gains in performance can be achieved by training classifications using dissimilarity models. However, these gains are restricted to a narrow range of hierarchical levels because agglomerative clustering is unable to represent the variation in importance of variables at different spatial scales. We suggest that further advances in the numerical definition of hierarchically organized ecological regionalizations will be possible with techniques developed in the field of statistical modeling of the distribution of community composition.

Temporal variability in wind-wave climate and its validation with ESSO-NIOT wave atlas for the head Bay of Bengal

NASA Astrophysics Data System (ADS)

Patra, Anindita; Bhaskaran, Prasad K.

2017-08-01

The head Bay region bordering the northern Bay of Bengal is a densely populated area with a complex geomorphologic setting, and highly vulnerable to extreme water levels along with other factors like sea level rise and impact of tropical cyclones. The influence of climate change on wind-wave regime from this region of Bay of Bengal is not known well and that requires special attention, and there is a need to perform its long-term assessment for societal benefits. This study provides a comprehensive analysis on the temporal variability in domain averaged wind speed, significant wave height (SWH) utilizing satellite altimeter data (1992-2012) and mean wave period using ECMWF reanalysis products ERA-Interim (1992-2012) and ERA-20C (1992-2010) over this region. The SWH derived from WAVEWATCH III (WW3) model along with the ERA-Interim reanalysis supplements the observed variability in satellite altimeter observations. Further, the study performs an extensive error estimation of SWH and mean wave period with ESSO-NIOT wave atlas that shows a high degree of under-estimation in the wave atlas mean wave period. Annual mean and wind speed maxima from altimeter show an increasing trend, and to a lesser extent in the SWH. Interestingly, the estimated trend is higher for maxima compared to the mean conditions. Analysis of decadal variability exhibits an increased frequency of higher waves in the present decade compared to the past. Linear trend analysis show significant upswing in spatially averaged ERA-20C mean wave period, whereas the noticed variations are marginal in the ERA-Interim data. A separate trend analysis for the wind-seas, swell wave heights and period from ERA-20C decipher the fact that distant swells governs the local wind-wave climatology over the head Bay region, and over time the swell activity have increased in this region.

A Study on Regional Rainfall Frequency Analysis for Flood Simulation Scenarios

NASA Astrophysics Data System (ADS)

Jung, Younghun; Ahn, Hyunjun; Joo, Kyungwon; Heo, Jun-Haeng

2014-05-01

Recently, climate change has been observed in Korea as well as in the entire world. The rainstorm has been gradually increased and then the damage has been grown. It is very important to manage the flood control facilities because of increasing the frequency and magnitude of severe rain storm. For managing flood control facilities in risky regions, data sets such as elevation, gradient, channel, land use and soil data should be filed up. Using this information, the disaster situations can be simulated to secure evacuation routes for various rainfall scenarios. The aim of this study is to investigate and determine extreme rainfall quantile estimates in Uijeongbu City using index flood method with L-moments parameter estimation. Regional frequency analysis trades space for time by using annual maximum rainfall data from nearby or similar sites to derive estimates for any given site in a homogeneous region. Regional frequency analysis based on pooled data is recommended for estimation of rainfall quantiles at sites with record lengths less than 5T, where T is return period of interest. Many variables relevant to precipitation can be used for grouping a region in regional frequency analysis. For regionalization of Han River basin, the k-means method is applied for grouping regions by variables of meteorology and geomorphology. The results from the k-means method are compared for each region using various probability distributions. In the final step of the regionalization analysis, goodness-of-fit measure is used to evaluate the accuracy of a set of candidate distributions. And rainfall quantiles by index flood method are obtained based on the appropriate distribution. And then, rainfall quantiles based on various scenarios are used as input data for disaster simulations. Keywords: Regional Frequency Analysis; Scenarios of Rainfall Quantile Acknowledgements This research was supported by a grant 'Establishing Active Disaster Management System of Flood Control Structures by using 3D BIM Technique' [NEMA-12-NH-57] from the Natural Hazard Mitigation Research Group, National Emergency Management Agency of Korea.

Spatial patterns of soil moisture connected to monthly-seasonal precipitation variability in a monsoon region

Treesearch

Yongqiang Liu

2003-01-01

The relations between monthly-seasonal soil moisture and precipitation variability are investigated by identifying the coupled patterns of the two hydrological fields using singular value decomposition (SVD). SVD is a technique of principal component analysis similar to empirical orthogonal knctions (EOF). However, it is applied to two variables simultaneously and is...

Arsenic concentrations, related environmental factors, and the predicted probability of elevated arsenic in groundwater in Pennsylvania

USGS Publications Warehouse

Gross, Eliza L.; Low, Dennis J.

2013-01-01

Logistic regression models were created to predict and map the probability of elevated arsenic concentrations in groundwater statewide in Pennsylvania and in three intrastate regions to further improve predictions for those three regions (glacial aquifer system, Gettysburg Basin, Newark Basin). Although the Pennsylvania and regional predictive models retained some different variables, they have common characteristics that can be grouped by (1) geologic and soils variables describing arsenic sources and mobilizers, (2) geochemical variables describing the geochemical environment of the groundwater, and (3) locally specific variables that are unique to each of the three regions studied and not applicable to statewide analysis. Maps of Pennsylvania and the three intrastate regions were produced that illustrate that areas most at risk are those with geology and soils capable of functioning as an arsenic source or mobilizer and geochemical groundwater conditions able to facilitate redox reactions. The models have limitations because they may not characterize areas that have localized controls on arsenic mobility. The probability maps associated with this report are intended for regional-scale use and may not be accurate for use at the field scale or when considering individual wells.

A comparison of small-area hospitalisation rates, estimated morbidity and hospital access.

PubMed

Shulman, H; Birkin, M; Clarke, G P

2015-11-01

Published data on hospitalisation rates tend to reveal marked spatial variations within a city or region. Such variations may simply reflect corresponding variations in need at the small-area level. However, they might also be a consequence of poorer accessibility to medical facilities for certain communities within the region. To help answer this question it is important to compare these variable hospitalisation rates with small-area estimates of need. This paper first maps hospitalisation rates at the small-area level across the region of Yorkshire in the UK to show the spatial variations present. Then the Health Survey of England is used to explore the characteristics of persons with heart disease, using chi-square and logistic regression analysis. Using the most significant variables from this analysis the authors build a spatial microsimulation model of morbidity for heart disease for the Yorkshire region. We then compare these estimates of need with the patterns of hospitalisation rates seen across the region. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Seabed mapping and characterization of sediment variability using the usSEABED data base

USGS Publications Warehouse

Goff, J.A.; Jenkins, C.J.; Jeffress, Williams S.

2008-01-01

We present a methodology for statistical analysis of randomly located marine sediment point data, and apply it to the US continental shelf portions of usSEABED mean grain size records. The usSEABED database, like many modern, large environmental datasets, is heterogeneous and interdisciplinary. We statistically test the database as a source of mean grain size data, and from it provide a first examination of regional seafloor sediment variability across the entire US continental shelf. Data derived from laboratory analyses ("extracted") and from word-based descriptions ("parsed") are treated separately, and they are compared statistically and deterministically. Data records are selected for spatial analysis by their location within sample regions: polygonal areas defined in ArcGIS chosen by geography, water depth, and data sufficiency. We derive isotropic, binned semivariograms from the data, and invert these for estimates of noise variance, field variance, and decorrelation distance. The highly erratic nature of the semivariograms is a result both of the random locations of the data and of the high level of data uncertainty (noise). This decorrelates the data covariance matrix for the inversion, and largely prevents robust estimation of the fractal dimension. Our comparison of the extracted and parsed mean grain size data demonstrates important differences between the two. In particular, extracted measurements generally produce finer mean grain sizes, lower noise variance, and lower field variance than parsed values. Such relationships can be used to derive a regionally dependent conversion factor between the two. Our analysis of sample regions on the US continental shelf revealed considerable geographic variability in the estimated statistical parameters of field variance and decorrelation distance. Some regional relationships are evident, and overall there is a tendency for field variance to be higher where the average mean grain size is finer grained. Surprisingly, parsed and extracted noise magnitudes correlate with each other, which may indicate that some portion of the data variability that we identify as "noise" is caused by real grain size variability at very short scales. Our analyses demonstrate that by applying a bias-correction proxy, usSEABED data can be used to generate reliable interpolated maps of regional mean grain size and sediment character. 

Information analysis of a spatial database for ecological land classification

NASA Technical Reports Server (NTRS)

Davis, Frank W.; Dozier, Jeff

1990-01-01

An ecological land classification was developed for a complex region in southern California using geographic information system techniques of map overlay and contingency table analysis. Land classes were identified by mutual information analysis of vegetation pattern in relation to other mapped environmental variables. The analysis was weakened by map errors, especially errors in the digital elevation data. Nevertheless, the resulting land classification was ecologically reasonable and performed well when tested with higher quality data from the region.

Molecular characterization of feline calicivirus variants from multicat household and public animal shelter in Rio de Janeiro, Brazil.

PubMed

Pereira, Joylson de Jesus; Baumworcel, Natasha; Fioretti, Júlia Monassa; Domingues, Cinthya Fonseca; Moraes, Laís Fernandes de; Marinho, Robson Dos Santos Souza; Vieira, Maria Clara Rodrigues; Pinto, Ana Maria Viana; de Castro, Tatiana Xavier

2018-02-28

The aim of this study was to perform the molecular characterization of conserved and variable regions of feline calicivirus capsid genome in order to investigate the molecular diversity of variants in Brazilian cat population. Twenty-six conjunctival samples from cats living in five public short-term animal shelters and three multicat life-long households were analyzed. Fifteen cats had conjunctivitis, three had oral ulceration, eight had respiratory signs (cough, sneeze and nasal discharge) and nine were asymptomatic. Feline calicivirus were isolated in CRFK cells and characterized by reverse transcription PCR target to both conserved and variable regions of open reading frame 2. The amplicons obtained were sequenced. A phylogenetic analysis along with most of the prototypes available in GenBank database and an amino acid analysis were performed. Phylogenetic analysis based on both conserved and variable region revealed two clusters with an aLTR value of 1.00 and 0.98 respectively and the variants from this study belong to feline calicivirus genogroup I. No association between geographical distribution and/or clinical signs and clustering in phylogenetic tree was observed. The variants circulating in public short-term animal shelter demonstrated a high variability because of the relatively rapid turnover of carrier cats constantly introduced of multiple viruses into this location over time. Copyright © 2018 Sociedade Brasileira de Microbiologia. Published by Elsevier Editora Ltda. All rights reserved.

Variability in precipitation in a watershed in the altiplano, Peru and modes of variation

NASA Astrophysics Data System (ADS)

Mazzarino, M.; Brown, C. M.

2012-12-01

This research examines system linkages between climate, water availability, pasture availability, camelids (llamas and alpacas) and indigenous herders in an Andean watershed in southern Peru. In this region, extreme meteorological events such as drought and flood, occur often and have the potential to negatively impact herding livelihoods. Predictability in the system is paramount to reducing risks associated with these events. In the altiplano, a large portion of variability in precipitation has been attributed to the influence of El Nino Southern Oscillation (ENSO). In light of climate change and observations by herders, this research returns to the question of teleconnections in the altiplano. We use December through March precipitation totals obtained from eight meteorological stations for 43 years (1964-2006) and sea surface temperatures (SSTs) in the equatorial Pacific and Atlantic to characterize the hydroclimatology in the watershed and determine modes of variability. Following principal components analysis, prevailing periodicities in regional precipitation were determined using wavelet analysis and spatial correlation and regression analysis were used to determine the relationship between SST anomalies (SSTA's) and precipitation events in the watershed. Results suggest a non-linear and non-stationary mode of variability. We draw three conclusions from the results: 1) Positive precipitation extremes are dominated by an ENSO signal in the Nino 2 region; 2) Post 1987 there is a weak relationship, if any, between anomalously dry years in the precipitation record and SSTA's in the equatorial Pacific; 3) There is a stronger relationship (inverse) between precipitation in the region and SSTA's in the tropical Atlantic than previously believed.

Statistical classification of hydrogeologic regions in the fractured rock area of Maryland and parts of the District of Columbia, Virginia, West Virginia, Pennsylvania, and Delaware

USGS Publications Warehouse

Fleming, Brandon J.; LaMotte, Andrew E.; Sekellick, Andrew J.

2013-01-01

Hydrogeologic regions in the fractured rock area of Maryland were classified using geographic information system tools with principal components and cluster analyses. A study area consisting of the 8-digit Hydrologic Unit Code (HUC) watersheds with rivers that flow through the fractured rock area of Maryland and bounded by the Fall Line was further subdivided into 21,431 catchments from the National Hydrography Dataset Plus. The catchments were then used as a common hydrologic unit to compile relevant climatic, topographic, and geologic variables. A principal components analysis was performed on 10 input variables, and 4 principal components that accounted for 83 percent of the variability in the original data were identified. A subsequent cluster analysis grouped the catchments based on four principal component scores into six hydrogeologic regions. Two crystalline rock hydrogeologic regions, including large parts of the Washington, D.C. and Baltimore metropolitan regions that represent over 50 percent of the fractured rock area of Maryland, are distinguished by differences in recharge, Precipitation minus Potential Evapotranspiration, sand content in soils, and groundwater contributions to streams. This classification system will provide a georeferenced digital hydrogeologic framework for future investigations of groundwater availability in the fractured rock area of Maryland.

Neural, electrophysiological and anatomical basis of brain-network variability and its characteristic changes in mental disorders.

PubMed

Zhang, Jie; Cheng, Wei; Liu, Zhaowen; Zhang, Kai; Lei, Xu; Yao, Ye; Becker, Benjamin; Liu, Yicen; Kendrick, Keith M; Lu, Guangming; Feng, Jianfeng

2016-08-01

SEE MATTAR ET AL DOI101093/AWW151 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: Functional brain networks demonstrate significant temporal variability and dynamic reconfiguration even in the resting state. Currently, most studies investigate temporal variability of brain networks at the scale of single (micro) or whole-brain (macro) connectivity. However, the mechanism underlying time-varying properties remains unclear, as the coupling between brain network variability and neural activity is not readily apparent when analysed at either micro or macroscales. We propose an intermediate (meso) scale analysis and characterize temporal variability of the functional architecture associated with a particular region. This yields a topography of variability that reflects the whole-brain and, most importantly, creates an analytical framework to establish the fundamental relationship between variability of regional functional architecture and its neural activity or structural connectivity. We find that temporal variability reflects the dynamical reconfiguration of a brain region into distinct functional modules at different times and may be indicative of brain flexibility and adaptability. Primary and unimodal sensory-motor cortices demonstrate low temporal variability, while transmodal areas, including heteromodal association areas and limbic system, demonstrate the high variability. In particular, regions with highest variability such as hippocampus/parahippocampus, inferior and middle temporal gyrus, olfactory gyrus and caudate are all related to learning, suggesting that the temporal variability may indicate the level of brain adaptability. With simultaneously recorded electroencephalography/functional magnetic resonance imaging and functional magnetic resonance imaging/diffusion tensor imaging data, we also find that variability of regional functional architecture is modulated by local blood oxygen level-dependent activity and α-band oscillation, and is governed by the ratio of intra- to inter-community structural connectivity. Application of the mesoscale variability measure to multicentre datasets of three mental disorders and matched controls involving 1180 subjects reveals that those regions demonstrating extreme, i.e. highest/lowest variability in controls are most liable to change in mental disorders. Specifically, we draw attention to the identification of diametrically opposing patterns of variability changes between schizophrenia and attention deficit hyperactivity disorder/autism. Regions of the default-mode network demonstrate lower variability in patients with schizophrenia, but high variability in patients with autism/attention deficit hyperactivity disorder, compared with respective controls. In contrast, subcortical regions, especially the thalamus, show higher variability in schizophrenia patients, but lower variability in patients with attention deficit hyperactivity disorder. The changes in variability of these regions are also closely related to symptom scores. Our work provides insights into the dynamic organization of the resting brain and how it changes in brain disorders. The nodal variability measure may also be potentially useful as a predictor for learning and neural rehabilitation. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A Decadal-scale Air-sea Interaction Theory for North Atlantic Multidecadal Variability: the NAT-NAO-AMOC-AMO Coupled Mode and Its Remote Influences

NASA Astrophysics Data System (ADS)

Li, Jianping; Sun, Cheng; Jin, Fei-Fei

2017-04-01

ABSTRACT North Atlantic region shows prominent multidecadal variability. Observational analysis shows that the North Atlantic Oscillation (NAO) leads the oceanic Atlantic Multidecadal Oscillation (AMO) by 15-20 years and the latter also leads the former by around 15 years. The mechanisms are investigated using simulations from a fully coupled model, and a NATNAO-AMOC-AMO Coupled Mode is proposed to explain the multidecadal variability in North Atlantic region. The NAT-NAO-AMO-AMOC coupled mode has important remote influences on regional climates. Observational analysis identifies a significant in-phase relationship between the AMV and Siberian warm season (May to October) precipitation. The physical mechanism for this relationship is investigated using both observations and numerical simulations. North Atlantic sea surface temperature (SST) warming associated with the positive AMV phase can excite an eastward propagating wave train response across the entire Eurasian continent, which includes an east-west dipole structure over Siberia. The dipole then leads to anomalous southerly winds bringing moisture northward to Siberia; the precipitation increases correspondingly. Furthermore, a prominent teleconnection pattern of multidecadal variability of cold season (November to April) upper-level atmospheric circulation over North Africa and Eurasia (NA-EA) is revealed by empirical orthogonal function analysis of the Twentieth Century Reanalysis data, and this teleconnection pattern is referred to as the Africa-Asia multidecadal teleconnection pattern (AAMT). A strong inphase relationship is observed between the AAMT and Atlantic multidecadal variability (AMV) and this connection is mainly due to Rossby wave dynamics. The AAMT acts as an atmospheric bridge conveying the influence of AMV onto the downstream multidecadal climate variability.

Relationship between the Names of People and Enterprises with Plant Origin with Phytotoponyms in Five Croatian Regions.

PubMed

Sindik, Joško; Carić, Tonko

2016-04-01

In this study, the first and last names of people (FN and LN), enterprises (EN) (with plants'species roots in their names) and phytotoponyms (PT) in five Croatian regions are analyzed, in their relationships. The goals of the study were: to determine the correlations between FN, LN, EN and PT; to determine the latent structure of these variables; to forecast number of PT (criterion) on the base of predictors (FN, LN, EN); to determine grouping of the places (within certain regions) as cases by two plants' categorizations; to determine grouping of the plants as cases by regions. We have analyzed 15 places, grouped in five regions, with 39 different plant species. The results revealed that the only principal component highly positively correlated with the variables last name and office name, while the projections for the variables first name (moderate high) and phytotoponyms (low size) were negative. Prediction of the criteria phytotoponyms is satisfactorily good, using three predictors: last name, first name and the office name. First cluster analysis revealed that phytotoponyms are mostly related with trees and deciduous plants, while names are related with trees, deciduous and herbaceous plants. Second cluster analysis obtained clear distinction between regions in dominant PTs, based on certain plants' names. The results indicate clear association between phytotoponyms and names of people.

Analysis of vegetation changes in Rock Creek Park, 1991-2007

USGS Publications Warehouse

Hatfield, Jeff S.; Krafft, Cairn

2009-01-01

Vegetation data collected at Rock Creek Park every 4 years during 1991-2007 were analyzed for differences among 3 regions within the park and among years. The variables measured and analyzed were percentage of twigs browsed, percentage of canopy cover, species richness of herbaceous plants, number of tree seedlings in each of 7 height classes, tree seedling stocking rate for low deer density and high deer density areas, percentage of tree and shrub cover < 2 m in height, mean diameter at breast height (DBH) of trees > 1 cm DBH, number of tree stems > 1 cm DBH, species richness of trees and shrubs, and mean height of the 5 tallest trees in each plot quadrant. Repeated measures analysis of variance (ANOVA) was used to test for differences and, except for some differences in tree species composition among the 3 regions, no differences (P > 0.01) were found among the 3 regions in the variables discussed above. Many of the variables showed very significant differences (P < 0.01) among years, and causative factors should be investigated further. In addition, importance values were calculated for the 10 most important tree species in each region and changes over time were reported. Future sampling recommendations are also discussed.

Droughts and governance impacts on water scarcity: an~analysis in the Brazilian semi-arid

NASA Astrophysics Data System (ADS)

Silva, A. C. S.; Galvão, C. O.; Silva, G. N. S.

2015-06-01

Extreme events are part of climate variability. Dealing with variability is still a challenge that might be increased due to climate change. However, impacts of extreme events are not only dependent on their variability, but also on management and governance. In Brazil, its semi-arid region is vulnerable to extreme events, especially droughts, for centuries. Actually, other Brazilian regions that have been mostly concerned with floods are currently also experiencing droughts. This article evaluates how a combination between climate variability and water governance might affect water scarcity and increase the impacts of extreme events on some regions. For this evaluation, Ostrom's framework for analyzing social-ecological systems (SES) was applied. Ostrom's framework is useful for understanding interactions between resource systems, governance systems and resource users. This study focuses on social-ecological systems located in a drought-prone region of Brazil. Two extreme events were selected, one in 1997-2000, when Brazil's new water policy was very young, and the other one in 2012-2015. The analysis of SES considering Ostrom's principle "Clearly defined boundaries" showed that deficiencies in water management cause the intensification of drought's impacts for the water users. The reasons are more related to water management and governance problems than to drought event magnitude or climate change. This is a problem that holdup advances in dealing with extreme events.

Investigation of summer monsoon rainfall variability in Pakistan

NASA Astrophysics Data System (ADS)

Hussain, Mian Sabir; Lee, Seungho

2016-08-01

This study analyzes the inter-annual and intra-seasonal rainfall variability in Pakistan using daily rainfall data during the summer monsoon season (June to September) recorded from 1980 to 2014. The variability in inter-annual monsoon rainfall ranges from 20 % in northeastern regions to 65 % in southwestern regions of Pakistan. The analysis reveals that the transition of the negative and positive anomalies was not uniform in the investigated dataset. In order to acquire broad observations of the intra-seasonal variability, an objective criterion, the pre-active period, active period and post-active periods of the summer monsoon rainfall have demarcated. The analysis also reveals that the rainfall in June has no significant contribution to the increase in intra-seasonal rainfall in Pakistan. The rainfall has, however, been enhanced in the summer monsoon in August. The rainfall of September demonstrates a sharp decrease, resulting in a high variability in the summer monsoon season. A detailed examination of the intra-seasonal rainfall also reveals frequent amplitude from late July to early August. The daily normal rainfall fluctuates significantly with its maximum in the Murree hills and its minimum in the northwestern Baluchistan.

Bayesian variable selection for post-analytic interrogation of susceptibility loci.

PubMed

Chen, Siying; Nunez, Sara; Reilly, Muredach P; Foulkes, Andrea S

2017-06-01

Understanding the complex interplay among protein coding genes and regulatory elements requires rigorous interrogation with analytic tools designed for discerning the relative contributions of overlapping genomic regions. To this aim, we offer a novel application of Bayesian variable selection (BVS) for classifying genomic class level associations using existing large meta-analysis summary level resources. This approach is applied using the expectation maximization variable selection (EMVS) algorithm to typed and imputed SNPs across 502 protein coding genes (PCGs) and 220 long intergenic non-coding RNAs (lncRNAs) that overlap 45 known loci for coronary artery disease (CAD) using publicly available Global Lipids Gentics Consortium (GLGC) (Teslovich et al., 2010; Willer et al., 2013) meta-analysis summary statistics for low-density lipoprotein cholesterol (LDL-C). The analysis reveals 33 PCGs and three lncRNAs across 11 loci with >50% posterior probabilities for inclusion in an additive model of association. The findings are consistent with previous reports, while providing some new insight into the architecture of LDL-cholesterol to be investigated further. As genomic taxonomies continue to evolve, additional classes such as enhancer elements and splicing regions, can easily be layered into the proposed analysis framework. Moreover, application of this approach to alternative publicly available meta-analysis resources, or more generally as a post-analytic strategy to further interrogate regions that are identified through single point analysis, is straightforward. All coding examples are implemented in R version 3.2.1 and provided as supplemental material. © 2016, The International Biometric Society.

Cloudy Windows: What GCM Ensembles, Reanalyses and Observations Tell Us About Uncertainty in Greenland's Future Climate and Surface Melting

NASA Astrophysics Data System (ADS)

Reusch, D. B.

2016-12-01

Any analysis that wants to use a GCM-based scenario of future climate benefits from knowing how much uncertainty the GCM's inherent variability adds to the development of climate change predictions. This is extra relevant in the polar regions due to the potential of global impacts (e.g., sea level rise) from local (ice sheet) climate changes such as more frequent/intense surface melting. High-resolution, regional-scale models using GCMs for boundary/initial conditions in future scenarios inherit a measure of GCM-derived externally-driven uncertainty. We investigate these uncertainties for the Greenland ice sheet using the 30-member CESM1.0-CAM5-BGC Large Ensemble (CESMLE) for recent (1981-2000) and future (2081-2100, RCP 8.5) decades. Recent simulations are skill-tested against the ERA-Interim reanalysis and AWS observations with results informing future scenarios. We focus on key variables influencing surface melting through decadal climatologies, nonlinear analysis of variability with self-organizing maps (SOMs), regional-scale modeling (Polar WRF), and simple melt models. Relative to the ensemble average, spatially averaged climatological July temperature anomalies over a Greenland ice-sheet/ocean domain are mostly between +/- 0.2 °C. The spatial average hides larger local anomalies of up to +/- 2 °C. The ensemble average itself is 2 °C cooler than ERA-Interim. SOMs extend our diagnostics by providing a concise, objective summary of model variability as a set of generalized patterns. For CESMLE, the SOM patterns summarize the variability of multiple realizations of climate. Changes in pattern frequency by ensemble member show the influence of initial conditions. For example, basic statistical analysis of pattern frequency yields interquartile ranges of 2-4% for individual patterns across the ensemble. In climate terms, this tells us about climate state variability through the range of the ensemble, a potentially significant source of melt-prediction uncertainty. SOMs can also capture the different trajectories of climate due to intramodel variability over time. Polar WRF provides higher resolution regional modeling with improved, polar-centric model physics. Simple melt models allow us to characterize impacts of the upstream uncertainties on estimates of surface melting.

Chlorophyll-a variability in the Seychelles-Chagos Thermocline Ridge: Analysis of a coupled biophysical model

NASA Astrophysics Data System (ADS)

Dilmahamod, A. F.; Hermes, J. C.; Reason, C. J. C.

2016-02-01

The biological variability of the upwelling region of the Seychelles-Chagos Thermocline Ridge (SCTR), both at surface and subsurface levels, is investigated using monthly outputs of a coupled biophysical model from 1958 to 2011. Owing to its large spatial distribution and sensitivity to climate variability, the SCTR is studied as three distinct regions; namely, sub-regions 1 (western; 5°S-12°S, 55°E-65°E), 2 (central; 5°S-12°S, 65°E-75°E) and 3 (eastern; 5°S-12°S, 75°E-90°E). Surface and subsurface chlorophyll-a (Chl-a) exhibit completely different response mechanisms in sub-region 3 compared to sub-regions 1 and 2 during El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events. During the intense 1997/1998 ENSO-IOD event, the high Chl-a tongue observed in the eastern Indian Ocean induces an increase in surface concentration in sub-region 3, whose subsurface variability is also substantially less (more) impacted by downwelling (upwelling) Rossby waves generated by El Niño (La Niña) forcing. After filtering out the annual signal, wavelet analysis of surface Chl-a revealed a significant 6 month periodicity in sub-regions 1 and 2 whereas a 5-year signal dominated in sub-region 3. The latter suggests that sub-region 3 is more prone to different ENSO/IOD influences, due to its proximity to the eastern Indian Ocean. In the unfiltered data, the subsurface Chl-a in sub-region 3 exhibits a strong signal near 1 year, with sub-regions 1 and 2 having a pronounced 6-year and 5-year signals respectively. These analyses show that the SCTR cannot be investigated as a single homogeneous region due to its large spatial distribution and different response mechanisms to climate events. Furthermore, changes in SST, thermocline depth, winds and Chl-a before and after the 1976-1977 climate shift differed across the SCTR, further highlighting the heterogeneity of this sensitive region in the Indian Ocean.

A comparison of regional flood frequency analysis approaches in a simulation framework

NASA Astrophysics Data System (ADS)

Ganora, D.; Laio, F.

2016-07-01

Regional frequency analysis (RFA) is a well-established methodology to provide an estimate of the flood frequency curve at ungauged (or scarcely gauged) sites. Different RFA approaches exist, depending on the way the information is transferred to the site of interest, but it is not clear in the literature if a specific method systematically outperforms the others. The aim of this study is to provide a framework wherein carrying out the intercomparison by building up a virtual environment based on synthetically generated data. The considered regional approaches include: (i) a unique regional curve for the whole region; (ii) a multiple-region model where homogeneous subregions are determined through cluster analysis; (iii) a Region-of-Influence model which defines a homogeneous subregion for each site; (iv) a spatially smooth estimation procedure where the parameters of the regional model vary continuously along the space. Virtual environments are generated considering different patterns of heterogeneity, including step change and smooth variations. If the region is heterogeneous, with the parent distribution changing continuously within the region, the spatially smooth regional approach outperforms the others, with overall errors 10-50% lower than the other methods. In the case of a step-change, the spatially smooth and clustering procedures perform similarly if the heterogeneity is moderate, while clustering procedures work better when the step-change is severe. To extend our findings, an extensive sensitivity analysis has been performed to investigate the effect of sample length, number of virtual stations, return period of the predicted quantile, variability of the scale parameter of the parent distribution, number of predictor variables and different parent distribution. Overall, the spatially smooth approach appears as the most robust approach as its performances are more stable across different patterns of heterogeneity, especially when short records are considered.

Velocity structure in long period variable star atmospheres

NASA Technical Reports Server (NTRS)

Pilachowski, C.; Wallerstein, G.; Willson, L. A.

1980-01-01

A regression analysis of the dependence of absorption line velocities on wavelength, line strength, excitation potential, and ionization potential is presented. The method determines the region of formation of the absorption lines for a given data and wavelength region. It is concluded that the scatter which is frequently found in velocity measurements of absorption lines in long period variables is probably the result of a shock of moderate amplitude located in or near the reversing layer and that the frequently observed correlation of velocity with excitation and ionization are a result of the velocity gradients produced by this shock in the atmosphere. A simple interpretation of the signs of the coefficients of the regression analysis is presented in terms of preshock, post shock, or across the shock, together with criteria for evaluating the validity of the fit. The amplitude of the reversing layer shock is estimated from an analysis of a series of plates for four long period variable stars along with the most probable stellar velocity for these stars.

Genetic analysis of West Nile virus isolates from an outbreak in Idaho, United States, 2006-2007.

PubMed

Grinev, Andriyan; Chancey, Caren; Añez, Germán; Ball, Christopher; Winkelman, Valerie; Williamson, Phillip; Foster, Gregory A; Stramer, Susan L; Rios, Maria

2013-09-23

West Nile virus (WNV) appeared in the U.S. in 1999 and has since become endemic, with yearly summer epidemics causing tens of thousands of cases of serious disease over the past 14 years. Analysis of WNV strains isolated during the 2006-2007 epidemic seasons demonstrates that a new genetic variant had emerged coincidentally with an intense outbreak in Idaho during 2006. The isolates belonging to the new variant carry a 13 nt deletion, termed ID-Δ13, located at the variable region of the 3'UTR, and are genetically related. The analysis of deletions and insertions in the 3'UTR of two major lineages of WNV revealed the presence of conserved repeats and two indel motifs in the variable region of the 3'UTR. One human and two bird isolates from the Idaho 2006-2007 outbreaks were sequenced using Illumina technology and within-host variability was analyzed. Continued monitoring of new genetic variants is important for public health as WNV continues to evolve.

Latitude of residence and position in time zone are predictors of cancer incidence, cancer mortality, and life expectancy at birth.

PubMed

Borisenkov, Mikhail F

2011-03-01

According to the hypothesis of circadian disruption, external factors that disturb the function of the circadian system can raise the risk of malignant neoplasm and reduce life span. Recent work has shown that the functionality of the circadian system is dependent not only on latitude of residence but also on the region's position in the time zone. The purpose of the present research was to examine the influence of latitude and time zone on cancer incidence, cancer mortality, and life expectancy at birth. A stepwise multiple regression analysis was carried out on residents of 59 regions of the European part of the Russian Federation (EPRF) using age-standardized parameters (per 100,000) of cancer incidence (CI), cancer mortality (CM), and life expectancy at birth (LE, yrs) as dependent variables. The geographical coordinates (latitude and position in the time zone) of the regions were used as independent variables, controlling for the level of economic development in the regions. The same analysis was carried out for LE in 31 regions in China. Latitude was the strongest predictor of LE in the EPRF population; it explained 48% and 45% of the variability in LE of women and men, respectively. Position within the time zone accounted for an additional 4% and 3% variability of LE in women and men, respectively. The highest values for LE were observed in the southeast of the EPRF. In China, latitude was not a predictor of LE, whereas position in the time zone explained 15% and 18% of the LE variability in women and men, respectively. The highest values of LE were observed in the eastern regions of China. Both latitude and position within the time zone were predictors for CI and CM of the EPRF population. Latitude was the best predictor of stomach CI and CM; this predictor explained 46% and 50% of the variability, respectively. Position within the time zone was the best predictor of female breast CM; it explained 15% of the variability. In most cases, CI and CM increased with increasing latitude of residence, from the eastern to the western border of the time zone, and with increasing level of economic development within the region. The dependence of CI, CM, and LE on the geographical coordinates of residence is in agreement with the hypothesis of circadian disruption.

The cross wavelet analysis of dengue fever variability influenced by meteorological conditions

NASA Astrophysics Data System (ADS)

Lin, Yuan-Chien; Yu, Hwa-Lung; Lee, Chieh-Han

2015-04-01

The multiyear variation of meteorological conditions induced by climate change causes the changing diffusion pattern of infectious disease and serious epidemic situation. Among them, dengue fever is one of the most serious vector-borne diseases distributed in tropical and sub-tropical regions. Dengue virus is transmitted by several species of mosquito and causing lots amount of human deaths every year around the world. The objective of this study is to investigate the impact of meteorological variables to the temporal variation of dengue fever epidemic in southern Taiwan. Several extreme and average indices of meteorological variables, i.e. temperature and humidity, were used for this analysis, including averaged, maximum and minimum temperature, and average rainfall, maximum 1-hr rainfall, and maximum 24-hr rainfall. This study plans to identify and quantify the nonlinear relationship of meteorological variables and dengue fever epidemic, finding the non-stationary time-frequency relationship and phase lag effects of those time series from 1998-2011 by using cross wavelet method. Results show that meteorological variables all have a significant time-frequency correlation region to dengue fever epidemic in frequency about one year (52 weeks). The associated phases can range from 0 to 90 degrees (0-13 weeks lag from meteorological factors to dengue incidences). Keywords: dengue fever, cross wavelet analysis, meteorological factor

Inter-annual Variability of Snowfall in the Lower Peninsula of Michigan, USA

NASA Astrophysics Data System (ADS)

Meng, L.

2016-12-01

Winter snowfall, particularly lake-effect snowfall, impacts all aspects of Michigan life in the wintertime, from motorsports and tourism to impacting the day-to-day lives of residents. Understanding the inter-annual variability of winter snowfall will provide sound basis for local community safety management and improve weather forecasting. This study attempts to understand the trend in winter snowfall and the influencing factors of winter snowfall variability in the Lower Peninsula of Michigan (LPM) using station snowfall measurements and statistical analysis. Our study demonstrates that snowfall has significantly increased from 1932 to 2015. Correlation analysis suggests that regionally average air temperatures have a strong negative relationship with snowfall in LPM. On average, approximately 27% of inter-annual variability in snowfall can be explained by regionally average air temperatures. ENSO events are also negatively related to snowfall in LPM and can explain 8% of inter-annual variability. North Atlantic Oscillation (NAO) does not have strong influence on snowfall. Composite analysis demonstrates that on annual basis, more winter snowfall occurs during the years with higher maximum ice cover (MIC) than during the years with lower MIC in Lake Michigan. Higher MIC is often associated with lower air temperatures which are negatively related to winter snowfall. This study could provide insight on future snow related climate model improvement and weather forecasting.

Regional prioritisation of flood risk in mountainous areas

NASA Astrophysics Data System (ADS)

Rogelis, M. C.; Werner, M.; Obregón, N.; Wright, G.

2015-07-01

A regional analysis of flood risk was carried out in the mountainous area surrounding the city of Bogotá (Colombia). Vulnerability at regional level was assessed on the basis of a principal component analysis carried out with variables recognised in literature to contribute to vulnerability; using watersheds as the unit of analysis. The area exposed was obtained from a simplified flood analysis at regional level to provide a mask where vulnerability variables were extracted. The vulnerability indicator obtained from the principal component analysis was combined with an existing susceptibility indicator, thus providing an index that allows the watersheds to be prioritised in support of flood risk management at regional level. Results show that the components of vulnerability can be expressed in terms of four constituent indicators; socio-economic fragility, which is composed of demography and lack of well-being; lack of resilience, which is composed of education, preparedness and response capacity, rescue capacity, social cohesion and participation; and physical exposure is composed of exposed infrastructure and exposed population. A sensitivity analysis shows that the classification of vulnerability is robust for watersheds with low and high values of the vulnerability indicator, while some watersheds with intermediate values of the indicator are sensitive to shifting between medium and high vulnerability. The complex interaction between vulnerability and hazard is evidenced in the case study. Environmental degradation in vulnerable watersheds shows the influence that vulnerability exerts on hazard and vice versa, thus establishing a cycle that builds up risk conditions.

Long-term hydrometeorological trends in the Midwest region based on a century long gridded hydrometeorological dataset and simulations from a macro-scale hydrology model

NASA Astrophysics Data System (ADS)

Chiu, C. M.; Hamlet, A. F.

2014-12-01

Climate change is likely to impact the Great Lakes region and Midwest region via changes in Great Lakes water levels, agricultural impacts, river flooding, urban stormwater impacts, drought, water temperature, and impacts to terrestrial and aquatic ecosystems. Self-consistent and temporally homogeneous long-term data sets of precipitation and temperature over the entire Great Lakes region and Midwest regions are needed to provide inputs to hydrologic models, assess historical trends in hydroclimatic variables, and downscale global and regional-scale climate models. To support these needs a new hybrid gridded meteorological forcing dataset at 1/16 degree resolution based on data from co-op station records, the U. S Historical Climatology Network (HCN) , the Historical Canadian Climate Database (HCCD), and Precipitation Regression on Independent Slopes Method (PRISM) has been assembled over the Great Lakes and Midwest region from 1915-2012 at daily time step. These data were then used as inputs to the macro-scale Variable Infiltration Capacity (VIC) hydrology model, implemented over the Midwest and Great Lakes region at 1/16 degree resolution, to produce simulated hydrologic variables that are amenable to long-term trend analysis. Trends in precipitation and temperature from the new meteorological driving data sets, as well as simulated hydrometeorological variables such as snowpack, soil moisture, runoff, and evaporation over the 20th century are presented and discussed.

Explaining Spatial Variability in Wellbore Impairment Risk for Pennsylvania Oil and Gas Wells, 2000-2014

NASA Astrophysics Data System (ADS)

Santoro, R.; Ingraffea, A. R.

2015-12-01

Previous modeling (ingraffea et al. PNAS, 2014) indicated roughly two-times higher cumulative risk for wellbore impairment in unconventional wells, relative to conventional wells, and large spatial variation in risk for oil and gas wells drilled in the state of Pennsylvania. Impairment risk for wells in the northeast portion of the state were found to be 8.5-times greater than that of wells drilled in the rest of the state. Here, we set out to explain this apparent regional variability through Boosted Regression Tree (BRT) analysis of geographic, developmental, and general well attributes. We find that regional variability is largely driven by the nature of the development, i.e. whether conventional or unconventional development is dominant. Oil and natural gas market prices and total well depths present as major influences in wellbore impairment, with moderate influences from well densities and geologic factors. The figure depicts influence paths for predictors of impairments for the state (top left), SW region (top right), unconventional/NE region (bottom left) and conventional/NW region (bottom right) models. Influences are scaled to reflect percent contributions in explaining variability in the model.

Analysis of the trade-off between high crop yield and low yield instability at the global scale

NASA Astrophysics Data System (ADS)

Ben-Ari, Tamara; Makowski, David

2016-10-01

Yield dynamics of major crops species vary remarkably among continents. Worldwide distribution of cropland influences both the expected levels and the interannual variability of global yields. An expansion of cultivated land in the most productive areas could theoretically increase global production, but also increase global yield instability if the most productive regions are characterized by high interannual yield variability. In this letter, we use portfolio analysis to quantify the tradeoff between the expected values and the interannual variance of global yield. We compute optimal frontiers for four crop species i.e., maize, rice, soybean and wheat and show how the distribution of cropland among large world regions can be optimized to either increase expected global crop production or decrease its interannual variability. We also show that a preferential allocation of cropland in the most productive regions can increase global expected yield at the expense of yield stability. Theoretically, optimizing the distribution of a small fraction of total cultivated areas can help find a good compromise between low instability and high crop yields at the global scale.

Airborne black carbon concentrations over an urban region in western India-temporal variability, effects of meteorology, and source regions.

PubMed

Bapna, Mukund; Sunder Raman, Ramya; Ramachandran, S; Rajesh, T A

2013-03-01

This study characterizes over 5 years of high time resolution (5 min), airborne black carbon (BC) concentrations (July 2003 to December 2008) measured over Ahmedabad, an urban region in western India. The data were used to obtain different time averages of BC concentrations, and these averages were then used to assess the diurnal, seasonal, and annual variability of BC over the study region. Assessment of diurnal variations revealed a strong association between BC concentrations and vehicular traffic. Peaks in BC concentration were co-incident with the morning (0730 to 0830, LST) and late evening (1930 to 2030, LST) rush hour traffic. Additionally, diurnal variability in BC concentrations during major festivals (Diwali and Dushera during the months of October/November) revealed an increase in BC concentrations due to fireworks displays. Maximum half hourly BC concentrations during the festival days were as high as 79.8 μg m(-3). However, the high concentrations rapidly decayed suggesting that local meteorology during the festive season was favorable for aerosol dispersion. A multiple linear regression (MLR) model with BC as the dependent variable and meteorological parameters as independent variables was fitted. The variability in temperature, humidity, wind speed, and wind direction accounted for about 49% of the variability in measured BC concentrations. Conditional probability function (CPF) analysis was used to identify the geographical location of local source regions contributing to the effective BC measured (at 880 nm) at the receptor site. The east north-east (ENE) direction to the receptor was identified as a major source region. National highway (NH8) and two coal-fired thermal power stations (at Gandhinagar and Sabarmati) were located in the identified direction, suggesting that local traffic and power plant emissions were likely contributors to the measured BC.

[From local studies to a regional perspective: pooled analysis of secondary data in a collaborative project on vulnerabilities associated with drug use in Argentina, Brazil and Uruguay (1998-2004)].

PubMed

Ralón, Gonzalo; Rossi, Diana; Vila, Marcelo; Latorre, Laura; Bastos, Francisco Inácio; Caiaffa, Waleska Teixeira

2012-12-01

This paper develops the methodological principles of pooled analysis design, using it to study situations of vulnerability among drug users at a regional level. Data from thirteen cross-sectional studies carried out in Argentina, Brazil and Uruguay between 1998 and 2004 were integrated. A critical review of the concept of data matrix which identifies four structural components, allowed us to: define the units of analysis spanning the different original populations; identify a core of common variables (social and demographic characteristics, drug use, sexual practices, serology of blood-borne and sexually transmitted diseases) with their respective values; examine the indicators, dimensions and procedures used to measure the variables; and establish their compatibility with a thematic and comparative analysis of data collection tools. The main result was a new data matrix with 3,534 cases. Multidisciplinary collaboration between teams and institutions from the three countries made it possible to maximize the available sources in order to analyze characteristics of the local contexts and of the overall regional.

ENSO controls interannual fire activity in southeast Australia

NASA Astrophysics Data System (ADS)

Mariani, M.; Fletcher, M.-S.; Holz, A.; Nyman, P.

2016-10-01

El Niño-Southern Oscillation (ENSO) is the main mode controlling the variability in the ocean-atmosphere system in the South Pacific. While the ENSO influence on rainfall regimes in the South Pacific is well documented, its role in driving spatiotemporal trends in fire activity in this region has not been rigorously investigated. This is particularly the case for the highly flammable and densely populated southeast Australian sector, where ENSO is a major control over climatic variability. Here we conduct the first region-wide analysis of how ENSO controls fire activity in southeast Australia. We identify a significant relationship between ENSO and both fire frequency and area burnt. Critically, wavelet analyses reveal that despite substantial temporal variability in the ENSO system, ENSO exerts a persistent and significant influence on southeast Australian fire activity. Our analysis has direct application for developing robust predictive capacity for the increasingly important efforts at fire management.

An evaluation of the effect of recent temperature variability on the prediction of coral bleaching events.

PubMed

Donner, Simon D

2011-07-01

Over the past 30 years, warm thermal disturbances have become commonplace on coral reefs worldwide. These periods of anomalous sea surface temperature (SST) can lead to coral bleaching, a breakdown of the symbiosis between the host coral and symbiotic dinoflagellates which reside in coral tissue. The onset of bleaching is typically predicted to occur when the SST exceeds a local climatological maximum by 1 degrees C for a month or more. However, recent evidence suggests that the threshold at which bleaching occurs may depend on thermal history. This study uses global SST data sets (HadISST and NOAA AVHRR) and mass coral bleaching reports (from Reefbase) to examine the effect of historical SST variability on the accuracy of bleaching prediction. Two variability-based bleaching prediction methods are developed from global analysis of seasonal and interannual SST variability. The first method employs a local bleaching threshold derived from the historical variability in maximum annual SST to account for spatial variability in past thermal disturbance frequency. The second method uses a different formula to estimate the local climatological maximum to account for the low seasonality of SST in the tropics. The new prediction methods are tested against the common globally fixed threshold method using the observed bleaching reports. The results find that estimating the bleaching threshold from local historical SST variability delivers the highest predictive power, but also a higher rate of Type I errors. The second method has the lowest predictive power globally, though regional analysis suggests that it may be applicable in equatorial regions. The historical data analysis suggests that the bleaching threshold may have appeared to be constant globally because the magnitude of interannual variability in maximum SST is similar for many of the world's coral reef ecosystems. For example, the results show that a SST anomaly of 1 degrees C is equivalent to 1.73-2.94 standard deviations of the maximum monthly SST for two-thirds of the world's coral reefs. Coral reefs in the few regions that experience anomalously high interannual SST variability like the equatorial Pacific could prove critical to understanding how coral communities acclimate or adapt to frequent and/or severe thermal disturbances.

RELATION OF ENVIRONMENTAL CHARACTERISTICS TO FISH ASSEMBLAGES IN THE UPPER FRENCH BROAD RIVER BASIN, NORTH CAROLINA

EPA Science Inventory

Fish assemblages at 16 sites in the upper French Broad River basin, North Carolina were related to environmental variables using detrended correspondence analysis (DCA) and linear regression. This study was conducted at the landscape scale because regional variables are controlle...

Analysis of penetration and mixing of gas jets in supersonic cross flow

NASA Technical Reports Server (NTRS)

Billig, F. S.; Schetz, J. A.

1992-01-01

The JETPEN analysis for gas jets in a supersonic cross flow developed earlier at APL/JHU has been extended in several important ways. First, the treatment of cases with injection at angles other than 90 deg has been redone. Next, the second of the three regions formerly treated has been eliminated. Third, the region downstream of the Mach disk for underexpanded cases has been reformulated such that turbulent entrainment of main stream fluid into the plume is modeled, and the equations of motion are solved marching downstream. These changes now permit prediction of the variation in composition, mixing area growth and all other flow variables along the plume. The analysis has been verified by comparison of predictions and experiment over a wide range of conditions. The result is an analysis capable of reliable predictions of the major flowfield variables that can be run on a PC.

Sea level anomaly in the North Atlantic and seas around Europe: Long-term variability and response to North Atlantic teleconnection patterns.

PubMed

Iglesias, Isabel; Lorenzo, M Nieves; Lázaro, Clara; Fernandes, M Joana; Bastos, Luísa

2017-12-31

Sea level anomaly (SLA), provided globally by satellite altimetry, is considered a valuable proxy for detecting long-term changes of the global ocean, as well as short-term and annual variations. In this manuscript, monthly sea level anomaly grids for the period 1993-2013 are used to characterise the North Atlantic Ocean variability at inter-annual timescales and its response to the North Atlantic main patterns of atmospheric circulation variability (North Atlantic Oscillation, Eastern Atlantic, Eastern Atlantic/Western Russia, Scandinavian and Polar/Eurasia) and main driven factors as sea level pressure, sea surface temperature and wind fields. SLA variability and long-term trends are analysed for the North Atlantic Ocean and several sub-regions (North, Baltic and Mediterranean and Black seas, Bay of Biscay extended to the west coast of the Iberian Peninsula, and the northern North Atlantic Ocean), depicting the SLA fluctuations at basin and sub-basin scales, aiming at representing the regions of maximum sea level variability. A significant correlation between SLA and the different phases of the teleconnection patterns due to the generated winds, sea level pressure and sea surface temperature anomalies, with a strong variability on temporal and spatial scales, has been identified. Long-term analysis reveals the existence of non-stationary inter-annual SLA fluctuations in terms of the temporal scale. Spectral density analysis has shown the existence of long-period signals in the SLA inter-annual component, with periods of ~10, 5, 4 and 2years, depending on the analysed sub-region. Also, a non-uniform increase in sea level since 1993 is identified for all sub-regions, with trend values between 2.05mm/year, for the Bay of Biscay region, and 3.98mm/year for the Baltic Sea (no GIA correction considered). The obtained results demonstrated a strong link between the atmospheric patterns and SLA, as well as strong long-period fluctuations of this variable in spatial and temporal scales. Copyright © 2017 Elsevier B.V. All rights reserved.

Finding stability regions for preserving efficiency classification of variable returns to scale technology in data envelopment analysis

NASA Astrophysics Data System (ADS)

Zamani, P.; Borzouei, M.

2016-12-01

This paper addresses issue of sensitivity of efficiency classification of variable returns to scale (VRS) technology for enhancing the credibility of data envelopment analysis (DEA) results in practical applications when an additional decision making unit (DMU) needs to be added to the set being considered. It also develops a structured approach to assisting practitioners in making an appropriate selection of variation range for inputs and outputs of additional DMU so that this DMU be efficient and the efficiency classification of VRS technology remains unchanged. This stability region is simply specified by the concept of defining hyperplanes of production possibility set of VRS technology and the corresponding halfspaces. Furthermore, this study determines a stability region for the additional DMU within which, in addition to efficiency classification, the efficiency score of a specific inefficient DMU is preserved and also using a simulation method, a region in which some specific efficient DMUs become inefficient is provided.

Genome-wide data reveal novel genes for methotrexate response in a large cohort of juvenile idiopathic arthritis cases.

PubMed

Cobb, J; Cule, E; Moncrieffe, H; Hinks, A; Ursu, S; Patrick, F; Kassoumeri, L; Flynn, E; Bulatović, M; Wulffraat, N; van Zelst, B; de Jonge, R; Bohm, M; Dolezalova, P; Hirani, S; Newman, S; Whitworth, P; Southwood, T R; De Iorio, M; Wedderburn, L R; Thomson, W

2014-08-01

Clinical response to methotrexate (MTX) treatment for children with juvenile idiopathic arthritis (JIA) displays considerable heterogeneity. Currently, there are no reliable predictors to identify non-responders: earlier identification could lead to a targeted treatment. We genotyped 759 JIA cases from the UK, the Netherlands and Czech Republic. Clinical variables were measured at baseline and 6 months after start of the treatment. In Phase I analysis, samples were analysed for the association with MTX response using ordinal regression of ACR-pedi categories and linear regression of change in clinical variables, and identified 31 genetic regions (P<0.001). Phase II analysis increased SNP density in the most strongly associated regions, identifying 14 regions (P<1 × 10(-5)): three contain genes of particular biological interest (ZMIZ1, TGIF1 and CFTR). These data suggest a role for novel pathways in MTX response and further investigations within associated regions will help to reach our goal of predicting response to MTX in JIA.

Analysis of health in health centers area in Depok using correspondence analysis and scan statistic

NASA Astrophysics Data System (ADS)

Basir, C.; Widyaningsih, Y.; Lestari, D.

2017-07-01

Hotspots indicate area that has a higher case intensity than others. For example, in health problems of an area, the number of sickness of a region can be used as parameter and condition of area that determined severity of an area. If this condition is known soon, it can be overcome preventively. Many factors affect the severity level of area. Some health factors to be considered in this study are the number of infant with low birth weight, malnourished children under five years old, under five years old mortality, maternal deaths, births without the help of health personnel, infants without handling the baby's health, and infant without basic immunization. The number of cases is based on every public health center area in Depok. Correspondence analysis provides graphical information about two nominal variables relationship. It create plot based on row and column scores and show categories that have strong relation in a close distance. Scan Statistic method is used to examine hotspot based on some selected variables that occurred in the study area; and Correspondence Analysis is used to picturing association between the regions and variables. Apparently, using SaTScan software, Sukatani health center is obtained as a point hotspot; and Correspondence Analysis method shows health centers and the seven variables have a very significant relationship and the majority of health centers close to all variables, except Cipayung which is distantly related to the number of pregnant mother death. These results can be used as input for the government agencies to upgrade the health level in the area.

Flood-frequency prediction methods for unregulated streams of Tennessee, 2000

USGS Publications Warehouse

Law, George S.; Tasker, Gary D.

2003-01-01

Up-to-date flood-frequency prediction methods for unregulated, ungaged rivers and streams of Tennessee have been developed. Prediction methods include the regional-regression method and the newer region-of-influence method. The prediction methods were developed using stream-gage records from unregulated streams draining basins having from 1 percent to about 30 percent total impervious area. These methods, however, should not be used in heavily developed or storm-sewered basins with impervious areas greater than 10 percent. The methods can be used to estimate 2-, 5-, 10-, 25-, 50-, 100-, and 500-year recurrence-interval floods of most unregulated rural streams in Tennessee. A computer application was developed that automates the calculation of flood frequency for unregulated, ungaged rivers and streams of Tennessee. Regional-regression equations were derived by using both single-variable and multivariable regional-regression analysis. Contributing drainage area is the explanatory variable used in the single-variable equations. Contributing drainage area, main-channel slope, and a climate factor are the explanatory variables used in the multivariable equations. Deleted-residual standard error for the single-variable equations ranged from 32 to 65 percent. Deleted-residual standard error for the multivariable equations ranged from 31 to 63 percent. These equations are included in the computer application to allow easy comparison of results produced by the different methods. The region-of-influence method calculates multivariable regression equations for each ungaged site and recurrence interval using basin characteristics from 60 similar sites selected from the study area. Explanatory variables that may be used in regression equations computed by the region-of-influence method include contributing drainage area, main-channel slope, a climate factor, and a physiographic-region factor. Deleted-residual standard error for the region-of-influence method tended to be only slightly smaller than those for the regional-regression method and ranged from 27 to 62 percent.

Global trends in visibility: Implications for dust sources

USGS Publications Warehouse

Mahowald, N.M.; Ballantine, J.A.; Feddema, J.; Ramankutty, N.

2007-01-01

There is a large uncertainty in the relative roles of human land use, climate change and carbon dioxide fertilization in changing desert dust source strength over the past 100 years, and the overall sign of human impacts on dust is not known. We used visibility data from meteorological stations in dusty regions to assess the anthropogenic impact on long term trends in desert dust emissions. Visibility data are available at thousands of stations globally from 1900 to the present, but we focused on 359 stations with more than 30 years of data in regions where mineral aerosols play a dominant role in visibility observations. We evaluated the 1974 to 2003 time period because most of these stations have reliable records only during this time. We first evaluated the visibility data against AERONET aerosol optical depth data, and found that only in dusty regions are the two moderately correlated. Correlation coefficients between visibility derived variables and AERONET optical depths indicate a moderate correlation (???0.47), consistent with capturing about 20% of the variability in optical depths. Two visibility derived variables appear to compare the best with AERONET observations: the fraction of observations with visibility less than 5 km (VIS5) and the surface extinction (EXT). Regional trends show that in many dusty places, VIS5 and EXT are statistically significantly correlated with the palmer drought severity index (based on precipitation and temperature) or surface wind speeds, consistent with dust temporal variability being largely driven by meteorology. This is especially true for North African and Chinese dust sources, but less true in the Middle East, Australia or South America, where there are not consistent patterns in the correlations. Climate indices such as El Nino or the North Atlantic Oscillation are not correlated with visibility derived variables in this analysis. There are few stations where visibility measures are correlated with cultivation or grazing estimates on a temporal basis, although this may be a function of the very coarse temporal resolution of the land use datasets. On the other hand, spatial analysis of the visibility data suggests that natural topographic lows are not correlated with visibility, but land use is correlated at a moderate level. This analysis is consistent with land use being important in some regions, but meteorology driving interannual variability during 1974-2003.

Spatial analysis of participation in the Waterloo Residential Energy Efficiency Project

NASA Astrophysics Data System (ADS)

Song, Ge Bella

Researchers are in broad agreement that energy-conserving actions produce economic as well as energy savings. Household energy rating systems (HERS) have been established in many countries to inform households of their house's current energy performance and to help reduce their energy consumption and greenhouse gas emissions. In Canada, the national EnerGuide for Houses (EGH) program is delivered by many local delivery agents, including non-profit green community organizations. Waterloo Region Green Solutions is the local non-profit that offers the EGH residential energy evaluation service to local households. The purpose of this thesis is to explore the determinants of household's participation in the residential energy efficiency program (REEP) in Waterloo Region, to explain the relationship between the explanatory variables and REEP participation, and to propose ways to improve this kind of program. A spatial (trend) analysis was conducted within a geographic information system (GIS) to determine the spatial patterns of the REEP participation in Waterloo Region from 1999 to 2006. The impact of sources of information on participation and relationships between participation rates and explanatory variables were identified. GIS proved successful in presenting a visual interpretation of spatial patterns of the REEP participation. In general, the participating households tend to be clustered in urban areas and scattered in rural areas. Different sources of information played significant roles in reaching participants in different years. Moreover, there was a relationship between each explanatory variable and the REEP participation rates. Statistical analysis was applied to obtain a quantitative assessment of relationships between hypothesized explanatory variables and participation in the REEP. The Poisson regression model was used to determine the relationship between hypothesized explanatory variables and REEP participation at the CDA level. The results show that all of the independent variables have a statistically significant positive relationship with REEP participation. These variables include level of education, average household income, employment rate, home ownership, population aged 65 and over, age of home, and number of eligible dwellings. The logistic regression model was used to assess the ability of the hypothesized explanatory variables to predict whether or not households would participate in a second follow-up evaluation after completing upgrades to their home. The results show all the explanatory variables have significant relationships with the dependent variable. The increased rating score, average household income, aged population, and age of home are positively related to the dependent variable. While the dwelling size and education has negative relationships with the dependent variable. In general, the contribution of this work provides a practical understanding of how the energy efficiency program operates, and insight into the type of variables that may be successful in bringing about changes in performance in the energy efficiency project in Waterloo Region. Secondly, with the completion of this research, future residential energy efficiency programs can use the information from this research and emulate or expand upon the efforts and lessons learned from the Residential Energy Efficiency Project in Waterloo Region case study. Thirdly, this research also contributes to practical experience on how to integrate different datasets using GIS.

Basin-scale heterogeneity in Antarctic precipitation and its impact on surface mass variability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fyke, Jeremy; Lenaerts, Jan T. M.; Wang, Hailong

Annually averaged precipitation in the form of snow, the dominant term of the Antarctic Ice Sheet surface mass balance, displays large spatial and temporal variability. Here we present an analysis of spatial patterns of regional Antarctic precipitation variability and their impact on integrated Antarctic surface mass balance variability simulated as part of a preindustrial 1800-year global, fully coupled Community Earth System Model simulation. Correlation and composite analyses based on this output allow for a robust exploration of Antarctic precipitation variability. We identify statistically significant relationships between precipitation patterns across Antarctica that are corroborated by climate reanalyses, regional modeling and icemore » core records. These patterns are driven by variability in large-scale atmospheric moisture transport, which itself is characterized by decadal- to centennial-scale oscillations around the long-term mean. We suggest that this heterogeneity in Antarctic precipitation variability has a dampening effect on overall Antarctic surface mass balance variability, with implications for regulation of Antarctic-sourced sea level variability, detection of an emergent anthropogenic signal in Antarctic mass trends and identification of Antarctic mass loss accelerations.« less

Basin-scale heterogeneity in Antarctic precipitation and its impact on surface mass variability

DOE PAGES

Fyke, Jeremy; Lenaerts, Jan T. M.; Wang, Hailong

2017-11-15

Annually averaged precipitation in the form of snow, the dominant term of the Antarctic Ice Sheet surface mass balance, displays large spatial and temporal variability. Here we present an analysis of spatial patterns of regional Antarctic precipitation variability and their impact on integrated Antarctic surface mass balance variability simulated as part of a preindustrial 1800-year global, fully coupled Community Earth System Model simulation. Correlation and composite analyses based on this output allow for a robust exploration of Antarctic precipitation variability. We identify statistically significant relationships between precipitation patterns across Antarctica that are corroborated by climate reanalyses, regional modeling and icemore » core records. These patterns are driven by variability in large-scale atmospheric moisture transport, which itself is characterized by decadal- to centennial-scale oscillations around the long-term mean. We suggest that this heterogeneity in Antarctic precipitation variability has a dampening effect on overall Antarctic surface mass balance variability, with implications for regulation of Antarctic-sourced sea level variability, detection of an emergent anthropogenic signal in Antarctic mass trends and identification of Antarctic mass loss accelerations.« less

Occurrence and multivariate exploratory analysis of the natural radioactivity anomaly in the south coastal region of Kenya

NASA Astrophysics Data System (ADS)

Kaniu, M. I.; Angeyo, K. H.; Darby, I. G.

2018-05-01

Characterized by a variety of rock formations, namely alkaline, igneous and sedimentary that contain significant deposits of monazite and pyrochlore ores, the south coastal region of Kenya may be regarded as highly heterogeneous with regard to its geochemistry, mineralogy as well as geological morphology. The region is one of the several alkaline carbonatite complexes of Kenya that are associated with high natural background radiation and therefore radioactivity anomaly. However, this high background radiation (HBR) anomaly has hardly been systematically assessed and delineated with regard to the spatial, geological, geochemical as well as anthropogenic variability and co-dependencies. We conducted wide-ranging in-situ gamma-ray spectrometric measurements in this area. The goal of the study was to assess the radiation exposure as well as determine the underlying natural radioactivity levels in the region. In this paper we report the occurrence, exploratory analysis and modeling to assess the multivariate geo-dependence and spatial variability of the radioactivity and associated radiation exposure. Unsupervised principal component analysis and ternary plots were utilized in the study. It was observed that areas which exhibit HBR anomalies are located along the south coast paved road and in the Mrima-Kiruku complex. These areas showed a trend towards enhanced levels of 232Th and 238U and low 40K. The spatial variability of the radioactivity anomaly was found to be mainly constrained by anthropogenic activities, underlying geology and geochemical processes in the terrestrial environment.

Spatial Durbin model analysis macroeconomic loss due to natural disasters

NASA Astrophysics Data System (ADS)

Kusrini, D. E.; Mukhtasor

2015-03-01

Magnitude of the damage and losses caused by natural disasters is huge for Indonesia, therefore this study aimed to analyze the effects of natural disasters for macroeconomic losses that occurred in 115 cities/districts across Java during 2012. Based on the results of previous studies it is suspected that it contains effects of spatial dependencies in this case, so that the completion of this case is performed using a regression approach to the area, namely Analysis of Spatial Durbin Model (SDM). The obtained significant predictor variable is population, and predictor variable with a significant weighting is the number of occurrences of disasters, i.e., disasters in the region which have an impact on other neighboring regions. Moran's I index value using the weighted Queen Contiguity also showed significant results, meaning that the incidence of disasters in the region will decrease the value of GDP in other.

Comparative Genome Analysis of Ciprofloxacin-Resistant Pseudomonas aeruginosa Reveals Genes Within Newly Identified High Variability Regions Associated With Drug Resistance Development

PubMed Central

Su, Hsun-Cheng; Khatun, Jainab; Kanavy, Dona M.

2013-01-01

The alarming rise of ciprofloxacin-resistant Pseudomonas aeruginosa has been reported in several clinical studies. Though the mutation of resistance genes and their role in drug resistance has been researched, the process by which the bacterium acquires high-level resistance is still not well understood. How does the genomic evolution of P. aeruginosa affect resistance development? Could the exposure of antibiotics to the bacteria enrich genomic variants that lead to the development of resistance, and if so, how are these variants distributed through the genome? To answer these questions, we performed 454 pyrosequencing and a whole genome analysis both before and after exposure to ciprofloxacin. The comparative sequence data revealed 93 unique resistance strain variation sites, which included a mutation in the DNA gyrase subunit A gene. We generated variation-distribution maps comparing the wild and resistant types, and isolated 19 candidates from three discrete resistance-associated high variability regions that had available transposon mutants, to perform a ciprofloxacin exposure assay. Of these region candidates with transposon disruptions, 79% (15/19) showed a reduction in the ability to gain high-level resistance, suggesting that genes within these high variability regions might enrich for certain functions associated with resistance development. PMID:23808957

Precipitation recycling in the Amazon basin

NASA Technical Reports Server (NTRS)

Eltahir, E. A. B.; Bras, R. L.

1994-01-01

Precipitation recycling is the contribution of evaporation within a region to precipitation in that same region. The recycling rate is a diagnostic measure of the potential for interactions between land surface hydrology and regional climate. In this paper we present a model for describing the seasonal and spatial variability of the recycling process. The precipitation recycling ratio, rho, is the basic variable in describing the recycling process. Rho is the fraction of precipitation at a certain location and time which is contributed by evaporation within the region under study. The recycling model is applied in studyiing the hydrologic cycle in the Amazon basin. It is estimated that about 25% of all the rain that falls in the Amazon basin is contributed by evaporation within the basin. This estimate is based on analysis of a data set supplied by the European Centre for Medium-range Weather Forecasts (ECMWF). The same analysis is repeated using a different data set from the Geophysical Fluid Dynamics Laboratory (GFDL). Based on this data set, the recycling ratio is estimated to be 35%. The seasonal variability of the recycling ratio is small compared with the yearly average. The new estimates of the recycling ratio are compared with results of previous studies, and the differences are explained.

Spatial Variability of Trace Gases During DISCOVER-AQ: Planning for Geostationary Observations of Atmospheric Composition

NASA Technical Reports Server (NTRS)

Follette-Cook, Melanie B.; Pickering, K.; Crawford, J.; Appel, W.; Diskin, G.; Fried, A.; Loughner, C.; Pfister, G.; Weinheimer, A.

2015-01-01

Results from an in-depth analysis of trace gas variability in MD indicated that the variability in this region was large enough to be observable by a TEMPO-like instrument. The variability observed in MD is relatively similar to the other three campaigns with a few exceptions: CO variability in CA was much higher than in the other regions; HCHO variability in CA and CO was much lower; MD showed the lowest variability in NO2All model simulations do a reasonable job simulating O3 variability. For CO, the CACO simulations largely under over estimate the variability in the observations. The variability in HCHO is underestimated for every campaign. NO2 variability is slightly overestimated in MD, more so in CO. The TX simulation underestimates the variability in each trace gas. This is most likely due to missing emissions sources (C. Loughner, manuscript in preparation).Future Work: Where reasonable, we will use these model outputs to further explore the resolvability from space of these key trace gases using analyses of tropospheric column amounts relative to satellite precision requirements, similar to Follette-Cook et al. (2015).

Intraseasonal variability in subtropical South America as depicted by precipitation data

NASA Astrophysics Data System (ADS)

González, P. L. M.; Vera, C. S.; Liebmann, B.; Kiladis, G.

2008-06-01

Daily precipitation data from three stations in subtropical Argentina are used to describe intraseasonal variability (20 90 days) during the austral summer. This variability is compared locally and regionally with that present in outgoing longwave radiation (OLR) data, in order to evaluate the performance of this variable as a proxy for convection in the region. The influence of the intraseasonal activity of the South American Seesaw (SASS) leading convection pattern on precipitation is also explored. Results show that intraseasonal variability explains a significant portion of summer precipitation variance, with a clear maximum in the vicinity of the SASS subtropical center. Correlation analysis reveals that OLR can explain only a small portion of daily precipitation variability, implying that it does not constitute a proper proxy for precipitation on daily timescales. On intraseasonal timescales, though, OLR is able to reproduce the main features of precipitation variability. The dynamical conditions that promote the development of intraseasonal variability in the region are further analyzed for selected summers. Seasons associated with a strong intraseasonal signal in precipitation variability show distinctive wet/dry intraseasonal periods in daily raw data, and are associated with a well defined SASS-like spatial pattern of convection. During these summers, strong large-scale forcing (such as warm El Niño/Southern Oscillation (ENSO) events and/or tropical intraseasonal convective activity), and Rossby-wave-like circulation anomalies extending across the Pacific Ocean, are also observed.

Decadal trend of precipitation and temperature patterns and impacts on snow-related variables in a semiarid region, Sierra Nevada, Spain.

NASA Astrophysics Data System (ADS)

José Pérez-Palazón, María; Pimentel, Rafael; Herrero, Javier; José Polo, María

2016-04-01

In the current context of global change, mountainous areas constitute singular locations in which these changes can be traced. Early detection of significant shifts of snow state variables in semiarid regions can help assess climate variability impacts and future snow dynamics in northern latitudes. The Sierra Nevada mountain range, in southern Spain, is a representative example of snow areas in Mediterranean-climate regions and both monitoring and modelling efforts have been performed to assess this variability and its significant scales. This work presents a decadal trend analysis throughout the 50-yr period 1960-2010 performed on some snow-related variables over Sierra Nevada, in Spain, which is included in the global climate change observatories network around the world. The study area comprises 4583 km2 distributed throughout the five head basins influenced by these mountains, with altitude values ranging from 140 to 3479 m.a.s.l., just 40 km from the Mediterranean coastline. Meteorological variables obtained from 44 weather stations from the National Meteorological Agency were studied and further used as input to the distributed hydrological model WiMMed (Polo et al., 2010), operational at the study area, to obtain selected snow variables. Decadal trends were obtained, together with their statistical significance, over the following variables, averaged over the whole study area: (1) annual precipitation; (2) annual snowfall; annual (3) mean, (4) maximum and (5) minimum daily temperature; annual (6) mean and (7) maximum daily fraction of snow covered areas; (8) annual number of days with snow cover; (9) mean and (10) maximum daily snow water equivalent; (11) annual number of extreme precipitation events; and (12) mean intensity of the annual extreme precipitation events. These variables were also studied over each of the five regions associated to each basin in the range. Globally decreasing decadal trends were obtained for all the meteorological variables, with the exception of the average annual mean and maximum daily temperature. In the case of the snow-related variables, no significant trends are observed at this time scale; nonetheless, a global decreasing rate is predominant in most of the variables. The torrential events are more frequent in the last decades of the study period, with an apparently increasing associated dispersion. This study constitutes a first sound analysis of the long-term observed trends of the snow regime in this area under the context of increasing temperature and decreasing precipitation regimes. The results highlight the complexity of non-linearity in environmental processes in Mediterranean regions, and point out to a significant shift in the precipitation and temperature regime, and thus on the snow-affected hydrological variables in the study area.

Model-Based Segmentation of Cortical Regions of Interest for Multi-subject Analysis of fMRI Data

NASA Astrophysics Data System (ADS)

Engel, Karin; Brechmann, Andr'e.; Toennies, Klaus

The high inter-subject variability of human neuroanatomy complicates the analysis of functional imaging data across subjects. We propose a method for the correct segmentation of cortical regions of interest based on the cortical surface. First results on the segmentation of Heschl's gyrus indicate the capability of our approach for correct comparison of functional activations in relation to individual cortical patterns.

Controlling for exogenous environmental variables when using data envelopment analysis for regional environmental assessments.

PubMed

Macpherson, Alexander J; Principe, Peter P; Shao, Yang

2013-04-15

Researchers are increasingly using data envelopment analysis (DEA) to examine the efficiency of environmental policies and resource allocations. An assumption of the basic DEA model is that decisionmakers operate within homogeneous environments. But, this assumption is not valid when environmental performance is influenced by variables beyond managerial control. Understanding the influence of these variables is important to distinguish between characterizing environmental conditions and identifying opportunities to improve environmental performance. While environmental assessments often focus on characterizing conditions, the point of using DEA is to identify opportunities to improve environmental performance and thereby prevent (or rectify) an inefficient allocation of resources. We examine the role of exogenous variables such as climate, hydrology, and topography in producing environmental impacts such as deposition, runoff, invasive species, and forest fragmentation within the United States Mid-Atlantic region. We apply a four-stage procedure to adjust environmental impacts in a DEA model that seeks to minimize environmental impacts while obtaining given levels of socioeconomic outcomes. The approach creates a performance index that bundles multiple indicators while adjusting for variables that are outside management control, offering numerous advantages for environmental assessment. Published by Elsevier Ltd.

Global trends in visibility: Implications for dust sources

USGS Publications Warehouse

Mahowald, N.M.; Ballantine, J.A.; Feddema, J.; Ramankutty, N.

2007-01-01

There is a large uncertainty in the relative roles of human land use, climate change and carbon dioxide fertilization in changing desert dust source strength over the past 100 years, and the overall sign of human impacts on dust is not known. We used visibility data from meteorological stations in dusty regions to assess the anthropogenic impact on long term trends in desert dust emissions. We did this by looking at time series of visibility derived variables and their correlations with precipitation, drought, winds, land use and grazing. Visibility data are available at thousands of stations globally from 1900 to the present, but we focused on 357 stations with more than 30 years of data in regions where mineral aerosols play a dominant role in visibility observations. We evaluated the 1974 to 2003 time period because most of these stations have reliable records only during this time. We first evaluated the visibility data against AERONET aerosol optical depth data, and found that only in dusty regions are the two moderately correlated. Correlation coefficients between visibility-derived variables and AERONET optical depths indicate a moderate correlation (0.47), consistent with capturing about 20% of the variability in optical depths. Two visibility-derived variables appear to compare the best with AERONET observations: the fraction of observations with visibility less than 5 km (VIS5) and the surface extinction (EXT). Regional trends show that in many dusty places, VIS5 and EXT are statistically significantly correlated with the Palmer drought severity index (based on precipitation and temperature) or surface wind speeds, consistent with dust temporal variability being largely driven by meteorology. This is especially true for North African and Chinese dust sources, but less true in the Middle East, Australia or South America, where there are not consistent patterns in the correlations. Climate indices such as El Nino or the North Atlantic Oscillation are not correlated with visibility-derived variables in this analysis. There are few stations where visibility measures are correlated with cultivation or grazing estimates on a temporal basis, although this may be a function of the very coarse temporal resolution of the land use datasets. On the other hand, spatial analysis of the visibility data suggests that natural topographic lows are not correlated with VIS5 or EXT, but land use is correlated at a moderate level. This analysis is consistent with land use being important in some regions, but meteorology driving interannual variability during 1974-2003.

Local-scale topoclimate effects on treeline elevations: a country-wide investigation of New Zealand's southern beech treelines.

PubMed

Case, Bradley S; Buckley, Hannah L

2015-01-01

Although treeline elevations are limited globally by growing season temperature, at regional scales treelines frequently deviate below their climatic limit. The cause of these deviations relate to a host of climatic, disturbance, and geomorphic factors that operate at multiple scales. The ability to disentangle the relative effects of these factors is currently hampered by the lack of reliable topoclimatic data, which describe how regional climatic characteristics are modified by topographic effects in mountain areas. In this study we present an analysis of the combined effects of local- and regional-scale factors on southern beech treeline elevation variability at 28 study areas across New Zealand. We apply a mesoscale atmospheric model to generate local-scale (200 m) meteorological data at these treelines and, from these data, we derive a set of topoclimatic indices that reflect possible detrimental and ameliorative influences on tree physiological functioning. Principal components analysis of meteorological data revealed geographic structure in how study areas were situated in multivariate space along gradients of topoclimate. Random forest and conditional inference tree modelling enabled us to tease apart the relative effects of 17 explanatory factors on local-scale treeline elevation variability. Overall, modelling explained about 50% of the variation in treeline elevation variability across the 28 study areas, with local landform and topoclimatic effects generally outweighing those from regional-scale factors across the 28 study areas. Further, the nature of the relationships between treeline elevation variability and the explanatory variables were complex, frequently non-linear, and consistent with the treeline literature. To our knowledge, this is the first study where model-generated meteorological data, and derived topoclimatic indices, have been developed and applied to explain treeline variation. Our results demonstrate the potential of such an approach for ecological research in mountainous environments.

Local-scale topoclimate effects on treeline elevations: a country-wide investigation of New Zealand’s southern beech treelines

PubMed Central

Buckley, Hannah L.

2015-01-01

Although treeline elevations are limited globally by growing season temperature, at regional scales treelines frequently deviate below their climatic limit. The cause of these deviations relate to a host of climatic, disturbance, and geomorphic factors that operate at multiple scales. The ability to disentangle the relative effects of these factors is currently hampered by the lack of reliable topoclimatic data, which describe how regional climatic characteristics are modified by topographic effects in mountain areas. In this study we present an analysis of the combined effects of local- and regional-scale factors on southern beech treeline elevation variability at 28 study areas across New Zealand. We apply a mesoscale atmospheric model to generate local-scale (200 m) meteorological data at these treelines and, from these data, we derive a set of topoclimatic indices that reflect possible detrimental and ameliorative influences on tree physiological functioning. Principal components analysis of meteorological data revealed geographic structure in how study areas were situated in multivariate space along gradients of topoclimate. Random forest and conditional inference tree modelling enabled us to tease apart the relative effects of 17 explanatory factors on local-scale treeline elevation variability. Overall, modelling explained about 50% of the variation in treeline elevation variability across the 28 study areas, with local landform and topoclimatic effects generally outweighing those from regional-scale factors across the 28 study areas. Further, the nature of the relationships between treeline elevation variability and the explanatory variables were complex, frequently non-linear, and consistent with the treeline literature. To our knowledge, this is the first study where model-generated meteorological data, and derived topoclimatic indices, have been developed and applied to explain treeline variation. Our results demonstrate the potential of such an approach for ecological research in mountainous environments. PMID:26528407

Variability in EIT Images of Lung Ventilation as a Function of Electrode Planes and Body Positions

PubMed Central

Zhang, Jie; Patterson, Robert

2014-01-01

This study is aimed at investigating the variability in resistivity changes in the lung region as a function of air volume, electrode plane and body position. Six normal subjects (33.8 ± 4.7 years, range from 26 to 37 years) were studied using the Sheffield Electrical Impedance Tomography (EIT) portable system. Three transverse planes at the level of second intercostal space, the level of the xiphisternal joint, and midway between upper and lower locations were chosen for measurements. For each plane, sixteen electrodes were uniformly positioned around the thorax. Data were collected with the breath held at end expiration and after inspiring 0.5, 1.0, or 1.5 liters of air from end expiration, with the subject in both the supine and sitting position. The average resistivity change in five regions, two 8x8 pixel local regions in the right lung, entire right, entire left and total lung regions, were calculated. The results show the resistivity change averaged over electrode positions and subject positions was 7-9% per liter of air, with a slightly larger resistivity change of 10 % per liter air in the lower electrode plane. There was no significant difference (p>0.05) between supine and sitting. The two 8x8 regions show a larger inter individual variability (coefficient of variation, CV, is from 30% to 382%) compared to the entire left, entire right and total lung (CV is from 11% to 51%). The results for the global regions are more consistent. The large inter individual variability appears to be a problem for clinical applications of EIT, such as regional ventilation. The variability may be mitigated by choosing appropriate electrode plane, body position and region of interest for the analysis. PMID:25110529

Variability in EIT Images of Lung Ventilation as a Function of Electrode Planes and Body Positions.

PubMed

Zhang, Jie; Patterson, Robert

2014-01-01

This study is aimed at investigating the variability in resistivity changes in the lung region as a function of air volume, electrode plane and body position. Six normal subjects (33.8 ± 4.7 years, range from 26 to 37 years) were studied using the Sheffield Electrical Impedance Tomography (EIT) portable system. Three transverse planes at the level of second intercostal space, the level of the xiphisternal joint, and midway between upper and lower locations were chosen for measurements. For each plane, sixteen electrodes were uniformly positioned around the thorax. Data were collected with the breath held at end expiration and after inspiring 0.5, 1.0, or 1.5 liters of air from end expiration, with the subject in both the supine and sitting position. The average resistivity change in five regions, two 8x8 pixel local regions in the right lung, entire right, entire left and total lung regions, were calculated. The results show the resistivity change averaged over electrode positions and subject positions was 7-9% per liter of air, with a slightly larger resistivity change of 10 % per liter air in the lower electrode plane. There was no significant difference (p>0.05) between supine and sitting. The two 8x8 regions show a larger inter individual variability (coefficient of variation, CV, is from 30% to 382%) compared to the entire left, entire right and total lung (CV is from 11% to 51%). The results for the global regions are more consistent. The large inter individual variability appears to be a problem for clinical applications of EIT, such as regional ventilation. The variability may be mitigated by choosing appropriate electrode plane, body position and region of interest for the analysis.

Brain Activity Unique to Orgasm in Women: An fMRI Analysis.

PubMed

Wise, Nan J; Frangos, Eleni; Komisaruk, Barry R

2017-11-01

Although the literature on imaging of regional brain activity during sexual arousal in women and men is extensive and largely consistent, that on orgasm is relatively limited and variable, owing in part to the methodologic challenges posed by variability in latency to orgasm in participants and head movement. To compare brain activity at orgasm (self- and partner-induced) with that at the onset of genital stimulation, immediately before the onset of orgasm, and immediately after the cessation of orgasm and to upgrade the methodology for obtaining and analyzing functional magnetic resonance imaging (fMRI) findings. Using fMRI, we sampled equivalent time points across female participants' variable durations of stimulation and orgasm in response to self- and partner-induced clitoral stimulation. The first 20-second epoch of orgasm was contrasted with the 20-second epochs at the beginning of stimulation and immediately before and after orgasm. Separate analyses were conducted for whole-brain and brainstem regions of interest. For a finer-grained analysis of the peri-orgasm phase, we conducted a time-course analysis on regions of interest. Head movement was minimized to a mean less than 1.3 mm using a custom-fitted thermoplastic whole-head and neck brace stabilizer. Ten women experienced orgasm elicited by self- and partner-induced genital stimulation in a Siemens 3-T Trio fMRI scanner. Brain activity gradually increased leading up to orgasm, peaked at orgasm, and then decreased. We found no evidence of deactivation of brain regions leading up to or during orgasm. The activated brain regions included sensory, motor, reward, frontal cortical, and brainstem regions (eg, nucleus accumbens, insula, anterior cingulate cortex, orbitofrontal cortex, operculum, right angular gyrus, paracentral lobule, cerebellum, hippocampus, amygdala, hypothalamus, ventral tegmental area, and dorsal raphe). Insight gained from the present findings could provide guidance toward a rational basis for treatment of orgasmic disorders, including anorgasmia. This is evidently the first fMRI study of orgasm elicited by self- and partner-induced genital stimulation in women. Methodologic solutions to the technical issues posed by excessive head movement and variable latencies to orgasm were successfully applied in the present study, enabling identification of brain regions involved in orgasm. Limitations include the small sample (N = 10), which combined self- and partner-induced stimulation datasets for analysis and which qualify the generalization of our conclusions. Extensive cortical, subcortical, and brainstem regions reach peak levels of activity at orgasm. Wise NJ, Frangos E, Komisaruk BR. Brain Activity Unique to Orgasm in Women: An fMRI Analysis. J Sex Med 2017;14:1380-1391. Copyright © 2017 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Examination of Relationships among Organizational Characteristics and Organizational Commitment of Nurses in Western and Eastern Region of Nepal.

PubMed

Joshi, A S; Namba, M; Pokharela, T

2015-01-01

The objective of this study is to identify relationships between three components of organizational commitment and organizational characteristics of nurses in the western and the eastern region of Nepal. A self-administrated questionnaire was used to collect data from 310 nurses currently working at various hospitals in the eastern and the western region of the country. The questionnaire included three sections namely 1) personal characteristics 2) organizational characteristics and 3) organizational commitments scale. Descriptive analysis and multiple regression analysis were performed to identify significance in various relationships. Out of the 240 completed questionnaires, 226 were found valid for analysis. The mean age was 27.4 years. For each depended variable affective, continuance and normative commitment, multiple regression analysis was performed with personal Characteristics and organizational characteristics as independent variables. All independent variables were found significantly related to each of the two dependent variables; affective commitment and normative commitment (R2 adjusted=0.24, p<0.01 and R2 adjusted=0.05, p<0.01 respectively). However, they were not significantly related to the continuance commitment. Both support from boss (β=0.138, p<0.05) and satisfaction with training (β=0.301, p<0.05) were found to be positive and significant with affective commitment. On the other hand, satisfaction with training (β=0.191, p<0.05) was also positive and significant with normative commitment. Since both support from boss and training program were found to be positive and significant with affective commitment, hospitals must encourage supervisors to provide more assistance to the subordinate nurses. Moreover, hospitals should develop more training programs to keep nurses motivated.

The analysis of the transient pressure response of the shuttle EPS-ECS cryogenic tanks with external pressurization systems

NASA Technical Reports Server (NTRS)

Barton, J. E.; Patterson, H. W.

1973-01-01

An analysis of transient pressures in externally pressurized cryogenic hydrogen and oxygen tanks was conducted and the effects of design variables on pressure response determined. The analysis was conducted with a computer program which solves the compressible viscous flow equations in two-dimensional regions representing the tank and external loop. The external loop volume, thermal mass, and heat leak were the dominant design variables affecting the system pressure response. No significant temperature stratification occurred in the fluid contained in the tank.

Weather analysis and interpretation procedures developed for the US/Canada wheat and barley exploratory experiment

NASA Technical Reports Server (NTRS)

Trenchard, M. H. (Principal Investigator)

1980-01-01

Procedures and techniques for providing analyses of meteorological conditions at segments during the growing season were developed for the U.S./Canada Wheat and Barley Exploratory Experiment. The main product and analysis tool is the segment-level climagraph which depicts temporally meteorological variables for the current year compared with climatological normals. The variable values for the segment are estimates derived through objective analysis of values obtained at first-order station in the region. The procedures and products documented represent a baseline for future Foreign Commodity Production Forecasting experiments.

Rocky Mountain spotted fever in Georgia, 1961-75: analysis of social and environmental factors affecting occurrence.

PubMed Central

Newhouse, V F; Choi, K; Holman, R C; Thacker, S B; D'Angelo, L J; Smith, J D

1986-01-01

For the period of 1961 through 1975, 10 geographic and sociologic variables in each of the 159 counties of Georgia were analyzed to determine how they were correlated with the occurrence of Rocky Mountain spotted fever (RMSF). Combinations of variables were transformed into a smaller number of factors using principal-component analysis. Based upon the relative values of these factors, geographic areas of similarity were delineated by cluster analysis. It was found by use of these analyses that the counties of the State formed four similarity clusters, which we called south, central, lower north and upper north. When the incidence of RMSF was subsequently calculated for each of these regions of similarity, the regions had differing RMSF incidence; low in the south and upper north, moderate in the central, and high in the lower north. The four similarity clusters agreed closely with the incidence of RMSF when both were plotted on a map. Thus, when analyzed simultaneously, the 10 variables selected could be used to predict the occurrence of RMSF. The most important variables were those of climate and geography. Of secondary, but still major importance, were the changes over the 15-year period in variables associated with humans and their environmental alterations. Detailed examination of these factors has permitted quantitative evaluation of the simultaneous impacts of the geographic and sociologic variables on the occurrence of RMSF in Georgia. These analyses could be updated to reflect changes in the relevant variables and tested as a means of identifying new high risk areas for RMSF in the State. More generally, this method might be adapted to clarify our understanding of the relative importance of individual variables in the ecology of other diseases or environmental health problems. PMID:3090609

Functional-anatomic correlates of individual differences in memory.

PubMed

Kirchhoff, Brenda A; Buckner, Randy L

2006-07-20

Memory abilities differ greatly across individuals. To explore a source of these differences, we characterized the varied strategies people adopt during unconstrained encoding. Participants intentionally encoded object pairs during functional MRI. Principal components analysis applied to a strategy questionnaire revealed that participants variably used four main strategies to aid learning. Individuals' use of verbal elaboration and visual inspection strategies independently correlated with their memory performance. Verbal elaboration correlated with activity in a network of regions that included prefrontal regions associated with controlled verbal processing, while visual inspection correlated with activity in a network of regions that included an extrastriate region associated with object processing. Activity in regions associated with use of these strategies was also correlated with memory performance. This study reveals functional-anatomic correlates of verbal and perceptual strategies that are variably used by individuals during encoding. These strategies engage distinct brain regions and may separately influence memory performance.

Genetic Analysis of West Nile Virus Isolates from an Outbreak in Idaho, United States, 2006–2007

PubMed Central

Grinev, Andriyan; Chancey, Caren; Añez, Germán; Ball, Christopher; Winkelman, Valerie; Williamson, Phillip; Foster, Gregory A.; Stramer, Susan L.; Rios, Maria

2013-01-01

West Nile virus (WNV) appeared in the U.S. in 1999 and has since become endemic, with yearly summer epidemics causing tens of thousands of cases of serious disease over the past 14 years. Analysis of WNV strains isolated during the 2006–2007 epidemic seasons demonstrates that a new genetic variant had emerged coincidentally with an intense outbreak in Idaho during 2006. The isolates belonging to the new variant carry a 13 nt deletion, termed ID-Δ13, located at the variable region of the 3′UTR, and are genetically related. The analysis of deletions and insertions in the 3′UTR of two major lineages of WNV revealed the presence of conserved repeats and two indel motifs in the variable region of the 3′UTR. One human and two bird isolates from the Idaho 2006–2007 outbreaks were sequenced using Illumina technology and within-host variability was analyzed. Continued monitoring of new genetic variants is important for public health as WNV continues to evolve. PMID:24065039

Multinational Corporate Penetration, Industrialism, Region, and Social Security Expenditures: A Cross-National Analysis.

ERIC Educational Resources Information Center

Clark, Roger; Filinson, Rachel

1991-01-01

Examined determinants of spending on social security programs, using data from 75 nations representative of core, semiperipheral, and peripheral nations. Industrialization variables had strong effects in models involving all nations, as did multinational corporate penetration in extraction, particularly when region was controlled; such penetration…

Spatial variability versus parameter uncertainty in freshwater fate and exposure factors of chemicals.

PubMed

Nijhof, Carl O P; Huijbregts, Mark A J; Golsteijn, Laura; van Zelm, Rosalie

2016-04-01

We compared the influence of spatial variability in environmental characteristics and the uncertainty in measured substance properties of seven chemicals on freshwater fate factors (FFs), representing the residence time in the freshwater environment, and on exposure factors (XFs), representing the dissolved fraction of a chemical. The influence of spatial variability was quantified using the SimpleBox model in which Europe was divided in 100 × 100 km regions, nested in a regional (300 × 300 km) and supra-regional (500 × 500 km) scale. Uncertainty in substance properties was quantified by means of probabilistic modelling. Spatial variability and parameter uncertainty were expressed by the ratio k of the 95%ile and 5%ile of the FF and XF. Our analysis shows that spatial variability ranges in FFs of persistent chemicals that partition predominantly into one environmental compartment was up to 2 orders of magnitude larger compared to uncertainty. For the other (less persistent) chemicals, uncertainty in the FF was up to 1 order of magnitude larger than spatial variability. Variability and uncertainty in freshwater XFs of the seven chemicals was negligible (k < 1.5). We found that, depending on the chemical and emission scenario, accounting for region-specific environmental characteristics in multimedia fate modelling, as well as accounting for parameter uncertainty, can have a significant influence on freshwater fate factor predictions. Therefore, we conclude that it is important that fate factors should not only account for parameter uncertainty, but for spatial variability as well, as this further increases the reliability of ecotoxicological impacts in LCA. Copyright © 2016 Elsevier Ltd. All rights reserved.

Attribution analysis of runoff decline in a semiarid region of the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Li, Binquan; Liang, Zhongmin; Zhang, Jianyun; Wang, Guoqing; Zhao, Weimin; Zhang, Hongyue; Wang, Jun; Hu, Yiming

2018-01-01

Climate variability and human activities are two main contributing attributions for runoff changes in the Yellow River, China. In the loess hilly-gully regions of the middle Yellow River, water shortage has been a serious problem, and this results in large-scale constructions of soil and water conservation (SWC) measures in the past decades in order to retain water for agricultural irrigation and industrial production. This disturbed the natural runoff characteristics. In this paper, we focused on a typical loess hilly-gully region (Wudinghe and Luhe River basins) and investigated the effects of SWC measures and climate variability on runoff during the period of 1961-2013, while the SWC measures were the main representative of human activities in this region. The nonparametric Mann-Kendall test was used to analyze the changes of annual precipitation, air temperature, potential evapotranspiration (PET), and runoff. The analysis revealed the decrease in precipitation, significant rise in temperature, and remarkable runoff reduction with a rate of more than 0.4 mm per year. It was found that runoff capacity in this region also decreased. Using the change point detection methods, the abrupt change point of annual runoff series was found at 1970, and thus, the study period was divided into the baseline period (1961-1970) and changed period (1971-2013). A conceptual framework based on four statistical runoff methods was used for attribution analysis of runoff decline in the Wudinghe and Luhe River basins (-37.3 and -56.4%, respectively). Results showed that runoff reduction can be explained by 85.2-90.3% (83.3-85.7%) with the SWC measures in the Wudinghe (Luhe) River basin while the remaining proportions were caused by climate variability. The findings suggested that the large-scale SWC measures demonstrated a dominant influence on runoff decline, and the change of precipitation extreme was also a promoting factor of the upward trending of SWC measures' contribution to runoff decline. This study enhances our understanding of runoff changes caused by SWC measures and climate variability in the typical semiarid region of Loess Plateau, China.

Analysis of variables affecting unemployment rate and detecting for cluster in West Java, Central Java, and East Java in 2012

NASA Astrophysics Data System (ADS)

Samuel, Putra A.; Widyaningsih, Yekti; Lestari, Dian

2016-02-01

The objective of this study is modeling the Unemployment Rate (UR) in West Java, Central Java, and East Java, with rate of disease, infant mortality rate, educational level, population size, proportion of married people, and GDRP as the explanatory variables. Spatial factors are also considered in the modeling since the closer the distance, the higher the correlation. This study uses the secondary data from BPS (Badan Pusat Statistik). The data will be analyzed using Moran I test, to obtain the information about spatial dependence, and using Spatial Autoregressive modeling to obtain the information, which variables are significant affecting UR and how great the influence of the spatial factors. The result is, variables proportion of married people, rate of disease, and population size are related significantly to UR. In all three regions, the Hotspot of unemployed will also be detected districts/cities using Spatial Scan Statistics Method. The results are 22 districts/cities as a regional group with the highest unemployed (Most likely cluster) in the study area; 2 districts/cities as a regional group with the highest unemployed in West Java; 1 district/city as a regional groups with the highest unemployed in Central Java; 15 districts/cities as a regional group with the highest unemployed in East Java.

In vivo short-term precision of hip structure analysis variables in comparison with bone mineral density using paired dual-energy X-ray absorptiometry scans from multi-center clinical trials.

PubMed

Khoo, Benjamin C C; Beck, Thomas J; Qiao, Qi-Hong; Parakh, Pallav; Semanick, Lisa; Prince, Richard L; Singer, Kevin P; Price, Roger I

2005-07-01

Hip structural analysis (HSA) is a technique for extracting strength-related structural dimensions of bone cross-sections from two-dimensional hip scan images acquired by dual energy X-ray absorptiometry (DXA) scanners. Heretofore the precision of the method has not been thoroughly tested in the clinical setting. Using paired scans from two large clinical trials involving a range of different DXA machines, this study reports the first precision analysis of HSA variables, in comparison with that of conventional bone mineral density (BMD) on the same scans. A key HSA variable, section modulus (Z), biomechanically indicative of bone strength during bending, had a short-term precision percentage coefficient of variation (CV%) in the femoral neck of 3.4-10.1%, depending on the manufacturer or model of the DXA equipment. Cross-sectional area (CSA), a determinant of bone strength during axial loading and closely aligned with conventional DXA bone mineral content, had a range of CV% from 2.8% to 7.9%. Poorer precision was associated with inadequate inclusion of the femoral shaft or femoral head in the DXA-scanned hip region. Precision of HSA-derived BMD varied between 2.4% and 6.4%. Precision of DXA manufacturer-derived BMD varied between 1.9% and 3.4%, arising from the larger analysis region of interest (ROI). The precision of HSA variables was not generally dependent on magnitude, subject height, weight, or conventional femoral neck densitometric variables. The generally poorer precision of key HSA variables in comparison with conventional DXA-derived BMD highlights the critical roles played by correct limb repositioning and choice of an adequate and appropriately positioned ROI.

Variability in Rheumatology day care hospitals in Spain: VALORA study.

PubMed

Hernández Miguel, María Victoria; Martín Martínez, María Auxiliadora; Corominas, Héctor; Sanchez-Piedra, Carlos; Sanmartí, Raimon; Fernandez Martinez, Carmen; García-Vicuña, Rosario

To describe the variability of the day care hospital units (DCHUs) of Rheumatology in Spain, in terms of structural resources and operating processes. Multicenter descriptive study with data from a self-completed questionnaire of DCHUs self-assessment based on DCHUs quality standards of the Spanish Society of Rheumatology. Structural resources and operating processes were analyzed and stratified by hospital complexity (regional, general, major and complex). Variability was determined using the coefficient of variation (CV) of the variable with clinical relevance that presented statistically significant differences when was compared by centers. A total of 89 hospitals (16 autonomous regions and Melilla) were included in the analysis. 11.2% of hospitals are regional, 22,5% general, 27%, major and 39,3% complex. A total of 92% of DCHUs were polyvalent. The number of treatments applied, the coordination between DCHUs and hospital pharmacy and the post graduate training process were the variables that showed statistically significant differences depending on the complexity of hospital. The highest rate of rheumatologic treatments was found in complex hospitals (2.97 per 1,000 population), and the lowest in general hospitals (2.01 per 1,000 population). The CV was 0.88 in major hospitals; 0.86 in regional; 0.76 in general, and 0.72 in the complex. there was variability in the number of treatments delivered in DCHUs, being greater in major hospitals and then in regional centers. Nonetheless, the variability in terms of structure and function does not seem due to differences in center complexity. Copyright © 2016 Elsevier España, S.L.U. and Sociedad Española de Reumatología y Colegio Mexicano de Reumatología. All rights reserved.

Association study of ERβ, AR, and CYP19A1 genes and MtF transsexualism.

PubMed

Fernández, Rosa; Esteva, Isabel; Gómez-Gil, Esther; Rumbo, Teresa; Almaraz, Mari Cruz; Roda, Ester; Haro-Mora, Juan-Jesús; Guillamón, Antonio; Pásaro, Eduardo

2014-12-01

The etiology of male-to-female (MtF) transsexualism is unknown. Both genetic and neurological factors may play an important role. To investigate the possible influence of the genetic factor on the etiology of MtF transsexualism. We carried out a cytogenetic and molecular analysis in 442 MtFs and 473 healthy, age- and geographical origin-matched XY control males. The karyotype was investigated by G-banding and by high-density array in the transsexual group. The molecular analysis involved three tandem variable regions of genes estrogen receptor β (ERβ) (CA tandem repeats in intron 5), androgen receptor (AR) (CAG tandem repeats in exon 1), and CYP19A1 (TTTA tandem repeats in intron 4). The allele and genotype frequencies, after division into short and long alleles, were obtained. We investigated the association between genotype and transsexualism by performing a molecular analysis of three variable regions of genes ERβ, AR, and CYP19A1 in 915 individuals (442 MtFs and 473 control males). Most MtFs showed an unremarkable 46,XY karyotype (97.96%). No specific chromosome aberration was associated with MtF transsexualism, and prevalence of aneuploidy (2.04%) was slightly higher than in the general population. Molecular analyses showed no significant difference in allelic or genotypic distribution of the genes examined between MtFs and controls. Moreover, molecular findings presented no evidence of an association between the sex hormone-related genes (ERβ, AR, and CYP19A1) and MtF transsexualism. The study suggests that the analysis of karyotype provides limited information in these subjects. Variable regions analyzed from ERβ, AR, and CYP19A1 are not associated with MtF transsexualism. Nevertheless, this does not exclude other polymorphic regions not analyzed. © 2014 International Society for Sexual Medicine.

Does mental health staffing level affect antipsychotic prescribing? Analysis of Italian national statistics.

PubMed

Starace, Fabrizio; Mungai, Francesco; Barbui, Corrado

2018-01-01

In mental healthcare, one area of major concern identified by health information systems is variability in antipsychotic prescribing. While most studies have investigated patient- and prescriber-related factors as possible reasons for such variability, no studies have investigated facility-level characteristics. The present study ascertained whether staffing level is associated with antipsychotic prescribing in community mental healthcare. A cross-sectional analysis of data extracted from the Italian national mental health information system was carried out. For each Italian region, it collects data on the availability and use of mental health facilities. The rate of individuals exposed to antipsychotic drugs was tested for evidence of association with the rate of mental health staff availability by means of univariate and multivariate analyses. In Italy there were on average nearly 60 mental health professionals per 100,000 inhabitants, with wide regional variations (range 21 to 100). The average rate of individuals prescribed antipsychotic drugs was 2.33%, with wide regional variations (1.04% to 4.01%). Univariate analysis showed that the rate of individuals prescribed antipsychotic drugs was inversely associated with the rate of mental health professionals available in Italian regions (Kendall's tau -0.438, p = 0.006), with lower rates of antipsychotic prescriptions in regions with higher rates of mental health professionals. After adjustment for possible confounders, the total availability of mental health professionals was still inversely associated with the rate of individuals exposed to antipsychotic drugs. The evidence that staffing level was inversely associated with antipsychotic prescribing indicates that any actions aimed at decreasing variability in antipsychotic prescribing need to take into account aspects related to the organization of the mental health system.

Early Parallel Activation of Semantics and Phonology in Picture Naming: Evidence from a Multiple Linear Regression MEG Study

PubMed Central

Miozzo, Michele; Pulvermüller, Friedemann; Hauk, Olaf

2015-01-01

The time course of brain activation during word production has become an area of increasingly intense investigation in cognitive neuroscience. The predominant view has been that semantic and phonological processes are activated sequentially, at about 150 and 200–400 ms after picture onset. Although evidence from prior studies has been interpreted as supporting this view, these studies were arguably not ideally suited to detect early brain activation of semantic and phonological processes. We here used a multiple linear regression approach to magnetoencephalography (MEG) analysis of picture naming in order to investigate early effects of variables specifically related to visual, semantic, and phonological processing. This was combined with distributed minimum-norm source estimation and region-of-interest analysis. Brain activation associated with visual image complexity appeared in occipital cortex at about 100 ms after picture presentation onset. At about 150 ms, semantic variables became physiologically manifest in left frontotemporal regions. In the same latency range, we found an effect of phonological variables in the left middle temporal gyrus. Our results demonstrate that multiple linear regression analysis is sensitive to early effects of multiple psycholinguistic variables in picture naming. Crucially, our results suggest that access to phonological information might begin in parallel with semantic processing around 150 ms after picture onset. PMID:25005037

Covariability in the Monthly Mean Convective and Radiative Diurnal Cycles in the Amazon

NASA Technical Reports Server (NTRS)

Dodson, Jason B.; Taylor, Patrick C.

2015-01-01

The diurnal cycle of convective clouds greatly influences the radiative energy balance in convectively active regions of Earth, through both direct presence, and the production of anvil and stratiform clouds. Previous studies show that the frequency and properties of convective clouds can vary on monthly timescales as a result of variability in the monthly mean atmospheric state. Furthermore, the radiative budget in convectively active regions also varies by up to 7 Wm-2 in convectively active regions. These facts suggest that convective clouds connect atmospheric state variability and radiation variability beyond clear sky effects alone. Previous research has identified monthly covariability between the diurnal cycle of CERES-observed top-of-atmosphere radiative fluxes and multiple atmospheric state variables from reanalysis over the Amazon region. ASVs that enhance (reduce) deep convection, such as CAPE (LTS), tend to shift the daily OLR and cloud albedo maxima earlier (later) in the day by 2-3 hr. We first test the analysis method using multiple reanalysis products for both the dry and wet seasons to further investigate the robustness of the preliminary results. We then use CloudSat data as an independent cloud observing system to further evaluate the relationships of cloud properties to variability in radiation and atmospheric states. While CERES can decompose OLR variability into clear sky and cloud effects, it cannot determine what variability in cloud properties lead to variability in the radiative cloud effects. Cloud frequency, cloud top height, and cloud microphysics all contribute to the cloud radiative effect, all of which are observable by CloudSat. In addition, CloudSat can also observe the presence and variability of deep convective cores responsible for the production of anvil clouds. We use these capabilities to determine the covariability of convective cloud properties and the radiative diurnal cycle.

Sensitivity of global terrestrial ecosystems to climate variability.

PubMed

Seddon, Alistair W R; Macias-Fauria, Marc; Long, Peter R; Benz, David; Willis, Kathy J

2016-03-10

The identification of properties that contribute to the persistence and resilience of ecosystems despite climate change constitutes a research priority of global relevance. Here we present a novel, empirical approach to assess the relative sensitivity of ecosystems to climate variability, one property of resilience that builds on theoretical modelling work recognizing that systems closer to critical thresholds respond more sensitively to external perturbations. We develop a new metric, the vegetation sensitivity index, that identifies areas sensitive to climate variability over the past 14 years. The metric uses time series data derived from the moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index, and three climatic variables that drive vegetation productivity (air temperature, water availability and cloud cover). Underlying the analysis is an autoregressive modelling approach used to identify climate drivers of vegetation productivity on monthly timescales, in addition to regions with memory effects and reduced response rates to external forcing. We find ecologically sensitive regions with amplified responses to climate variability in the Arctic tundra, parts of the boreal forest belt, the tropical rainforest, alpine regions worldwide, steppe and prairie regions of central Asia and North and South America, the Caatinga deciduous forest in eastern South America, and eastern areas of Australia. Our study provides a quantitative methodology for assessing the relative response rate of ecosystems--be they natural or with a strong anthropogenic signature--to environmental variability, which is the first step towards addressing why some regions appear to be more sensitive than others, and what impact this has on the resilience of ecosystem service provision and human well-being.

Sensitivity of global terrestrial ecosystems to climate variability

NASA Astrophysics Data System (ADS)

Seddon, Alistair W. R.; Macias-Fauria, Marc; Long, Peter R.; Benz, David; Willis, Kathy J.

2016-03-01

The identification of properties that contribute to the persistence and resilience of ecosystems despite climate change constitutes a research priority of global relevance. Here we present a novel, empirical approach to assess the relative sensitivity of ecosystems to climate variability, one property of resilience that builds on theoretical modelling work recognizing that systems closer to critical thresholds respond more sensitively to external perturbations. We develop a new metric, the vegetation sensitivity index, that identifies areas sensitive to climate variability over the past 14 years. The metric uses time series data derived from the moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index, and three climatic variables that drive vegetation productivity (air temperature, water availability and cloud cover). Underlying the analysis is an autoregressive modelling approach used to identify climate drivers of vegetation productivity on monthly timescales, in addition to regions with memory effects and reduced response rates to external forcing. We find ecologically sensitive regions with amplified responses to climate variability in the Arctic tundra, parts of the boreal forest belt, the tropical rainforest, alpine regions worldwide, steppe and prairie regions of central Asia and North and South America, the Caatinga deciduous forest in eastern South America, and eastern areas of Australia. Our study provides a quantitative methodology for assessing the relative response rate of ecosystems—be they natural or with a strong anthropogenic signature—to environmental variability, which is the first step towards addressing why some regions appear to be more sensitive than others, and what impact this has on the resilience of ecosystem service provision and human well-being.

Redundancy analysis allows improved detection of methylation changes in large genomic regions.

PubMed

Ruiz-Arenas, Carlos; González, Juan R

2017-12-14

DNA methylation is an epigenetic process that regulates gene expression. Methylation can be modified by environmental exposures and changes in the methylation patterns have been associated with diseases. Methylation microarrays measure methylation levels at more than 450,000 CpGs in a single experiment, and the most common analysis strategy is to perform a single probe analysis to find methylation probes associated with the outcome of interest. However, methylation changes usually occur at the regional level: for example, genomic structural variants can affect methylation patterns in regions up to several megabases in length. Existing DMR methods provide lists of Differentially Methylated Regions (DMRs) of up to only few kilobases in length, and cannot check if a target region is differentially methylated. Therefore, these methods are not suitable to evaluate methylation changes in large regions. To address these limitations, we developed a new DMR approach based on redundancy analysis (RDA) that assesses whether a target region is differentially methylated. Using simulated and real datasets, we compared our approach to three common DMR detection methods (Bumphunter, blockFinder, and DMRcate). We found that Bumphunter underestimated methylation changes and blockFinder showed poor performance. DMRcate showed poor power in the simulated datasets and low specificity in the real data analysis. Our method showed very high performance in all simulation settings, even with small sample sizes and subtle methylation changes, while controlling type I error. Other advantages of our method are: 1) it estimates the degree of association between the DMR and the outcome; 2) it can analyze a targeted or region of interest; and 3) it can evaluate the simultaneous effects of different variables. The proposed methodology is implemented in MEAL, a Bioconductor package designed to facilitate the analysis of methylation data. We propose a multivariate approach to decipher whether an outcome of interest alters the methylation pattern of a region of interest. The method is designed to analyze large target genomic regions and outperforms the three most popular methods for detecting DMRs. Our method can evaluate factors with more than two levels or the simultaneous effect of more than one continuous variable, which is not possible with the state-of-the-art methods.

Biological-Physical Coupling in the Gulf of Maine: Satellite and Model Studies of Phytoplankton Variability

NASA Technical Reports Server (NTRS)

Thomas, Andrew C.; Chai, F.; Townsend, D. W.; Xue, H.

2002-01-01

The goals of this project were to acquire, process, QC, archive and analyze SeaWiFS chlorophyll fields over the Gulf of Maine and Scotia Shelf region. The focus of the analysis effort was to calculate and quantify seasonality and interannual. variability of SeaWiFS-measured phytoplankton biomass in the study area and compare these to physical forcing and hydrography. An additional focus within this effort was on regional differences within the heterogeneous biophysical regions of the Gulf of Maine / Scotia Shelf. Overall goals were approached through the combined use of SeaWiFS and AVHRR data and the development of a coupled biology-physical numerical model.

Diurnal variability of regional cloud and clear-sky radiative parameters derived from GOES data. I - Analysis method. II - November 1978 cloud distributions. III - November 1978 radiative parameters

NASA Technical Reports Server (NTRS)

Minnis, P.; Harrison, E. F.

1984-01-01

Cloud cover is one of the most important variables affecting the earth radiation budget (ERB) and, ultimately, the global climate. The present investigation is concerned with several aspects of the effects of extended cloudiness, taking into account hourly visible and infrared data from the Geostationary Operational Environmental Satelite (GOES). A methodology called the hybrid bispectral threshold method is developed to extract regional cloud amounts at three levels in the atmosphere, effective cloud-top temperatures, clear-sky temperature and cloud and clear-sky visible reflectance characteristics from GOES data. The diurnal variations are examined in low, middle, high, and total cloudiness determined with this methodology for November 1978. The bulk, broadband radiative properties of the resultant cloud and clear-sky data are estimated to determine the possible effect of the diurnal variability of regional cloudiness on the interpretation of ERB measurements.

First-order Probabilistic Analysis of the Effects of Heterogeneity on Pore-water Pressure in a Hillslope

NASA Astrophysics Data System (ADS)

Cai, J.; Yan, E.; Yeh, T. C. J.

2015-12-01

Pore-water pressure in a hillslope is a critical control of its stability. The main objective of this paper is to introduce a first-order moment analysis to investigate the pressure head variability within a hypothetical hillslope, induced by steady rainfall infiltration. This approach accounts for the uncertainties and spatial variation of the hydraulic conductivity, and is based on a first-order Taylor approximation of pressure perturbations calculated by a variably saturated, finite element flow model. Using this approach, the effects of variance (σ2lnKs) and spatial structure anisotropy (λh/λv) of natural logarithm of saturated hydraulic conductivity, and normalized vertical infiltration flux (q/ks) on the hillslope pore-water pressure are evaluated. We found that the responses of pressure head variability (σ2p) are quite different between unsaturated region and saturated region divided by the phreatic surface. Above the phreatic surface, a higher variability in pressure head is obtained from a higher σ2lnKs, a higher λh/λv and a smaller q/ks; while below the phreatic surface, a higher σ2lnKs, a lower λh/λv or a larger q/ks would lead to a higher variability in pressure head, and greater range of fluctuation of the phreatic surface within the hillslope. σ2lnKs has greatest impact on σ2p within the slope and λh/λv has smallest impact. All three variables have greater influence on maximum σ2p within the saturated region below the phreatic surface than that within the unsaturated region above the phreatic surface. The results obtained from this study are useful to understand the influence of hydraulic conductivity variations on slope seepage and stability under different slope conditions and material spatial distributions.

Association of genetic and phenotypic variability with geography and climate in three southern California oaks.

PubMed

Riordan, Erin C; Gugger, Paul F; Ortego, Joaquín; Smith, Carrie; Gaddis, Keith; Thompson, Pam; Sork, Victoria L

2016-01-01

Geography and climate shape the distribution of organisms, their genotypes, and their phenotypes. To understand historical and future evolutionary and ecological responses to climate, we compared the association of geography and climate of three oak species (Quercus engelmannii, Quercus berberidifolia, and Quercus cornelius-mulleri) in an environmentally heterogeneous region of southern California at three organizational levels: regional species distributions, genetic variation, and phenotypic variation. We identified climatic variables influencing regional distribution patterns using species distribution models (SDMs), and then tested whether those individual variables are important in shaping genetic (microsatellite) and phenotypic (leaf morphology) variation. We estimated the relative contributions of geography and climate using multivariate redundancy analyses (RDA) with variance partitioning. The modeled distribution of each species was influenced by climate differently. Our analysis of genetic variation using RDA identified small but significant associations between genetic variation with climate and geography in Q. engelmannii and Q. cornelius-mulleri, but not in Q. berberidifolia, and climate explained more of the variation. Our analysis of phenotypic variation in Q. engelmannii indicated that climate had more impact than geography, but not in Q. berberidifolia. Throughout our analyses, we did not find a consistent pattern in effects of individual climatic variables. Our comparative analysis illustrates that climate influences tree response at all organizational levels, but the important climate factors vary depending on the level and on the species. Because of these species-specific and level-specific responses, today's sympatric species are unlikely to have similar distributions in the future. © 2016 Botanical Society of America.

SeqFIRE: a web application for automated extraction of indel regions and conserved blocks from protein multiple sequence alignments.

PubMed

Ajawatanawong, Pravech; Atkinson, Gemma C; Watson-Haigh, Nathan S; Mackenzie, Bryony; Baldauf, Sandra L

2012-07-01

Analyses of multiple sequence alignments generally focus on well-defined conserved sequence blocks, while the rest of the alignment is largely ignored or discarded. This is especially true in phylogenomics, where large multigene datasets are produced through automated pipelines. However, some of the most powerful phylogenetic markers have been found in the variable length regions of multiple alignments, particularly insertions/deletions (indels) in protein sequences. We have developed Sequence Feature and Indel Region Extractor (SeqFIRE) to enable the automated identification and extraction of indels from protein sequence alignments. The program can also extract conserved blocks and identify fast evolving sites using a combination of conservation and entropy. All major variables can be adjusted by the user, allowing them to identify the sets of variables most suited to a particular analysis or dataset. Thus, all major tasks in preparing an alignment for further analysis are combined in a single flexible and user-friendly program. The output includes a numbered list of indels, alignments in NEXUS format with indels annotated or removed and indel-only matrices. SeqFIRE is a user-friendly web application, freely available online at www.seqfire.org/.

Behavior of variable V3 region from 16S rDNA of lactic acid bacteria in denaturing gradient gel electrophoresis.

PubMed

Ercolini, D; Moschetti, G; Blaiotta, G; Coppola, S

2001-03-01

Separation of amplified V3 region from 16S rDNA by denaturing gradient gel electrophoresis (DGGE) was tested as a tool for differentiation of lactic acid bacteria commonly isolated from food. Variable V3 regions of 21 reference strains and 34 wild strains referred to species belonging to the genera Pediococcus, Enterococcus, Lactococcus, Lactobacillus, Leuconostoc, Weissella, and Streptococcus were analyzed. DGGE profiles obtained were species-specific for most of the cultures tested. Moreover, it was possible to group the remaining LAB reference strains according to the migration of their 16S V3 region in the denaturing gel. The results are discussed with reference to their potential in the analysis of LAB communities in food, besides shedding light on taxonomic aspects.

Regional patterns of dead wood in forested habitats of Oregon and Washington.

Treesearch

Janet L. Ohmann; Karen L. Waddell

2002-01-01

We describe regional patterns of variation in dead wood across 20 million ha of upland forests of all ownerships in Oregon and Washington, based on an analysis of data on snags and down wood collected on over 16,000 field plots. Current patterns of dead wood are highly variable and complex. The strongest differences were among nine habitats that reflect strong regional...

Variability and transmission by Aphis glycines of North American and Asian Soybean mosaic virus isolates.

PubMed

Domier, L L; Latorre, I J; Steinlage, T A; McCoppin, N; Hartman, G L

2003-10-01

The variability of North American and Asian strains and isolates of Soybean mosaic virus was investigated. First, polymerase chain reaction (PCR) products representing the coat protein (CP)-coding regions of 38 SMVs were analyzed for restriction fragment length polymorphisms (RFLP). Second, the nucleotide and predicted amino acid sequence variability of the P1-coding region of 18 SMVs and the helper component/protease (HC/Pro) and CP-coding regions of 25 SMVs were assessed. The CP nucleotide and predicted amino acid sequences were the most similar and predicted phylogenetic relationships similar to those obtained from RFLP analysis. Neither RFLP nor sequence analyses of the CP-coding regions grouped the SMVs by geographical origin. The P1 and HC/Pro sequences were more variable and separated the North American and Asian SMV isolates into two groups similar to previously reported differences in pathogenic diversity of the two sets of SMV isolates. The P1 region was the most informative of the three regions analyzed. To assess the biological relevance of the sequence differences in the HC/Pro and CP coding regions, the transmissibility of 14 SMV isolates by Aphis glycines was tested. All field isolates of SMV were transmitted efficiently by A. glycines, but the laboratory isolates analyzed were transmitted poorly. The amino acid sequences from most, but not all, of the poorly transmitted isolates contained mutations in the aphid transmission-associated DAG and/or KLSC amino acid sequence motifs of CP and HC/Pro, respectively.

IG and TR single chain fragment variable (scFv) sequence analysis: a new advanced functionality of IMGT/V-QUEST and IMGT/HighV-QUEST.

PubMed

Giudicelli, Véronique; Duroux, Patrice; Kossida, Sofia; Lefranc, Marie-Paule

2017-06-26

IMGT®, the international ImMunoGeneTics information system® ( http://www.imgt.org ), was created in 1989 in Montpellier, France (CNRS and Montpellier University) to manage the huge and complex diversity of the antigen receptors, and is at the origin of immunoinformatics, a science at the interface between immunogenetics and bioinformatics. Immunoglobulins (IG) or antibodies and T cell receptors (TR) are managed and described in the IMGT® databases and tools at the level of receptor, chain and domain. The analysis of the IG and TR variable (V) domain rearranged nucleotide sequences is performed by IMGT/V-QUEST (online since 1997, 50 sequences per batch) and, for next generation sequencing (NGS), by IMGT/HighV-QUEST, the high throughput version of IMGT/V-QUEST (portal begun in 2010, 500,000 sequences per batch). In vitro combinatorial libraries of engineered antibody single chain Fragment variable (scFv) which mimic the in vivo natural diversity of the immune adaptive responses are extensively screened for the discovery of novel antigen binding specificities. However the analysis of NGS full length scFv (~850 bp) represents a challenge as they contain two V domains connected by a linker and there is no tool for the analysis of two V domains in a single chain. The functionality "Analyis of single chain Fragment variable (scFv)" has been implemented in IMGT/V-QUEST and, for NGS, in IMGT/HighV-QUEST for the analysis of the two V domains of IG and TR scFv. It proceeds in five steps: search for a first closest V-REGION, full characterization of the first V-(D)-J-REGION, then search for a second V-REGION and full characterization of the second V-(D)-J-REGION, and finally linker delimitation. For each sequence or NGS read, positions of the 5'V-DOMAIN, linker and 3'V-DOMAIN in the scFv are provided in the 'V-orientated' sense. Each V-DOMAIN is fully characterized (gene identification, sequence description, junction analysis, characterization of mutations and amino changes). The functionality is generic and can analyse any IG or TR single chain nucleotide sequence containing two V domains, provided that the corresponding species IMGT reference directory is available. The "Analysis of single chain Fragment variable (scFv)" implemented in IMGT/V-QUEST and, for NGS, in IMGT/HighV-QUEST provides the identification and full characterization of the two V domains of full-length scFv (~850 bp) nucleotide sequences from combinatorial libraries. The analysis can also be performed on concatenated paired chains of expressed antigen receptor IG or TR repertoires.

GALA: group analysis leads to accuracy, a novel approach for solving the inverse problem in exploratory analysis of group MEG recordings

PubMed Central

Kozunov, Vladimir V.; Ossadtchi, Alexei

2015-01-01

Although MEG/EEG signals are highly variable between subjects, they allow characterizing systematic changes of cortical activity in both space and time. Traditionally a two-step procedure is used. The first step is a transition from sensor to source space by the means of solving an ill-posed inverse problem for each subject individually. The second is mapping of cortical regions consistently active across subjects. In practice the first step often leads to a set of active cortical regions whose location and timecourses display a great amount of interindividual variability hindering the subsequent group analysis. We propose Group Analysis Leads to Accuracy (GALA)—a solution that combines the two steps into one. GALA takes advantage of individual variations of cortical geometry and sensor locations. It exploits the ensuing variability in electromagnetic forward model as a source of additional information. We assume that for different subjects functionally identical cortical regions are located in close proximity and partially overlap and their timecourses are correlated. This relaxed similarity constraint on the inverse solution can be expressed within a probabilistic framework, allowing for an iterative algorithm solving the inverse problem jointly for all subjects. A systematic simulation study showed that GALA, as compared with the standard min-norm approach, improves accuracy of true activity recovery, when accuracy is assessed both in terms of spatial proximity of the estimated and true activations and correct specification of spatial extent of the activated regions. This improvement obtained without using any noise normalization techniques for both solutions, preserved for a wide range of between-subject variations in both spatial and temporal features of regional activation. The corresponding activation timecourses exhibit significantly higher similarity across subjects. Similar results were obtained for a real MEG dataset of face-specific evoked responses. PMID:25954141

[Spatio-temporal analysis of the biophysical and ecological conditions of Triatoma dimidiata (Hemiptera: Reduviidae: Triatominae) in the northeast region of Colombia].

PubMed

Badel-Mogollón, Jaime; Rodríguez-Figueroa, Laura; Parra-Henao, Gabriel

2017-03-29

Due to the lack of information regarding biophysical and spatio-temporal conditions (hydrometheorologic and vegetal coverage density) in areas with Triatoma dimidiata in the Colombian departments of Santander and Boyacá, there is a need to elucidate the association patterns of these variables to determine the distribution and control of this species. To make a spatio-temporal analysis of biophysical variables related to the distribution of T. dimidiate observed in the northeast region of Colombia. We used the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC SRES) data bases registering vector presence and hydrometheorologic data. We studied the variables of environmental temperature, relative humidity, rainfall and vegetal coverage density at regional and local levels, and we conducted spatial geostatistic, descriptive statistical and Fourier temporal series analyses. Temperatures two meters above the ground and on covered surface ranged from 14,5°C to 18,8°C in the areas with the higher density of T. dimidiata. The environmental temperature fluctuated between 30 and 32°C. Vegetal coverage density and rainfall showed patterns of annual and biannual peaks. Relative humidity values fluctuated from 66,8 to 85,1%. Surface temperature and soil coverage were the variables that better explained the life cycle of T. dimidiata in the area. High relative humidity promoted the seek of shelters and an increase of the geographic distribution in the annual and biannual peaks of regional rainfall. The ecologic and anthropic conditions suggest that T. dimidiata is a highly resilient species.

Towards an automatic statistical model for seasonal precipitation prediction and its application to Central and South Asian headwater catchments

NASA Astrophysics Data System (ADS)

Gerlitz, Lars; Gafurov, Abror; Apel, Heiko; Unger-Sayesteh, Katy; Vorogushyn, Sergiy; Merz, Bruno

2016-04-01

Statistical climate forecast applications typically utilize a small set of large scale SST or climate indices, such as ENSO, PDO or AMO as predictor variables. If the predictive skill of these large scale modes is insufficient, specific predictor variables such as customized SST patterns are frequently included. Hence statistically based climate forecast models are either based on a fixed number of climate indices (and thus might not consider important predictor variables) or are highly site specific and barely transferable to other regions. With the aim of developing an operational seasonal forecast model, which is easily transferable to any region in the world, we present a generic data mining approach which automatically selects potential predictors from gridded SST observations and reanalysis derived large scale atmospheric circulation patterns and generates robust statistical relationships with posterior precipitation anomalies for user selected target regions. Potential predictor variables are derived by means of a cellwise correlation analysis of precipitation anomalies with gridded global climate variables under consideration of varying lead times. Significantly correlated grid cells are subsequently aggregated to predictor regions by means of a variability based cluster analysis. Finally for every month and lead time, an individual random forest based forecast model is automatically calibrated and evaluated by means of the preliminary generated predictor variables. The model is exemplarily applied and evaluated for selected headwater catchments in Central and South Asia. Particularly the for winter and spring precipitation (which is associated with westerly disturbances in the entire target domain) the model shows solid results with correlation coefficients up to 0.7, although the variability of precipitation rates is highly underestimated. Likewise for the monsoonal precipitation amounts in the South Asian target areas a certain skill of the model could be detected. The skill of the model for the dry summer season in Central Asia and the transition seasons over South Asia is found to be low. A sensitivity analysis by means on well known climate indices reveals the major large scale controlling mechanisms for the seasonal precipitation climate of each target area. For the Central Asian target areas, both, the El Nino Southern Oscillation and the North Atlantic Oscillation are identified as important controlling factors for precipitation totals during moist spring season. Drought conditions are found to be triggered by a warm ENSO phase in combination with a positive phase of the NAO. For the monsoonal summer precipitation amounts over Southern Asia, the model suggests a distinct negative response to El Nino events.

Climate Drivers of Spatiotemporal Variability of Precipitation in the Source Region of Yangtze River

NASA Astrophysics Data System (ADS)

Du, Y.; Berndtsson, R.; An, D.; Yuan, F.

2017-12-01

Variability of precipitation regime has significant influence on the environment sustainability in the source region of Yangtze River, especially when the vegetation degradation and biodiversity reduction have already occurred. Understanding the linkage between variability of local precipitation and global teleconnection patterns is essential for water resources management. Based on physical reasoning, indices of the climate drivers can provide a practical way of predicting precipitation. Due to high seasonal variability of precipitation, climate drivers of the seasonal precipitation also varies. However, few reports have gone through the teleconnections between large scale patterns with seasonal precipitation in the source region of Yangtze River. The objectives of this study are therefore (1) assessment of temporal trend and spatial variability of precipitation in the source region of Yangtze River; (2) identification of climate indices with strong influence on seasonal precipitation anomalies; (3) prediction of seasonal precipitation based on revealed climate indices. Principal component analysis and Spearman rank correlation were used to detect significant relationships. A feed-forward artificial neural network(ANN) was developed to predict seasonal precipitation using significant correlated climate indices. Different influencing climate indices were revealed for precipitation in each season, with significant level and lag times. Significant influencing factors were selected to be the predictors for ANN model. With correlation coefficients between observed and simulated precipitation over 0.5, the results were eligible to predict the precipitation of spring, summer and winter using teleconnections, which can improve integrated water resources management in the source region of Yangtze River.

Regionalization of precipitation characteristics in Iran's Lake Urmia basin

NASA Astrophysics Data System (ADS)

Fazel, Nasim; Berndtsson, Ronny; Uvo, Cintia Bertacchi; Madani, Kaveh; Kløve, Bjørn

2018-04-01

Lake Urmia in northwest Iran, once one of the largest hypersaline lakes in the world, has shrunk by almost 90% in area and 80% in volume during the last four decades. To improve the understanding of regional differences in water availability throughout the region and to refine the existing information on precipitation variability, this study investigated the spatial pattern of precipitation for the Lake Urmia basin. Daily rainfall time series from 122 precipitation stations with different record lengths were used to extract 15 statistical descriptors comprising 25th percentile, 75th percentile, and coefficient of variation for annual and seasonal total precipitation. Principal component analysis in association with cluster analysis identified three main homogeneous precipitation groups in the lake basin. The first sub-region (group 1) includes stations located in the center and southeast; the second sub-region (group 2) covers mostly northern and northeastern part of the basin, and the third sub-region (group 3) covers the western and southern edges of the basin. Results of principal component (PC) and clustering analyses showed that seasonal precipitation variation is the most important feature controlling the spatial pattern of precipitation in the lake basin. The 25th and 75th percentiles of winter and autumn are the most important variables controlling the spatial pattern of the first rotated principal component explaining about 32% of the total variance. Summer and spring precipitation variations are the most important variables in the second and third rotated principal components, respectively. Seasonal variation in precipitation amount and seasonality are explained by topography and influenced by the lake and westerly winds that are related to the strength of the North Atlantic Oscillation. Despite using incomplete time series with different lengths, the identified sub-regions are physically meaningful.

IRAS variables as galactic structure tracers - Classification of the bright variables

NASA Technical Reports Server (NTRS)

Allen, L. E.; Kleinmann, S. G.; Weinberg, M. D.

1993-01-01

The characteristics of the 'bright infrared variables' (BIRVs), a sample consisting of the 300 brightest stars in the IRAS Point Source Catalog with IRAS variability index VAR of 98 or greater, are investigated with the purpose of establishing which of IRAS variables are AGB stars (e.g., oxygen-rich Miras and carbon stars, as was assumed by Weinberg (1992)). Results of the analysis of optical, infrared, and microwave spectroscopy of these stars indicate that, out of 88 stars in the BIRV sample identified with cataloged variables, 86 can be classified as Miras. Results of a similar analysis performed for a color-selected sample of stars, using the color limits employed by Habing (1988) to select AGB stars, showed that, out of 52 percent of classified stars, 38 percent are non-AGB stars, including H II regions, planetary nebulae, supergiants, and young stellar objects, indicating that studies using color-selected samples are subject to misinterpretation.

Hydroclimatic variability in the Lake Mondsee region and its relationships with large-scale climate anomaly patterns

NASA Astrophysics Data System (ADS)

Rimbu, Norel; Ionita, Monica; Swierczynski, Tina; Brauer, Achim; Kämpf, Lucas; Czymzik, Markus

2017-04-01

Flood triggered detrital layers in varved sediments of Lake Mondsee, located at the northern fringe of the European Alps (47°48'N,13°23'E), provide an important archive of regional hydroclimatic variability during the mid- to late Holocene. To improve the interpretation of the flood layer record in terms of large-scale climate variability, we investigate the relationships between observational hydrological records from the region, like the Mondsee lake level, the runoff of the lake's main inflow Griesler Ache, with observed precipitation and global climate patterns. The lake level shows a strong positive linear trend during the observational period in all seasons. Additionally, lake level presents important interannual to multidecadal variations. These variations are associated with distinct seasonal atmospheric circulation patterns. A pronounced anomalous anticyclonic center over the Iberian Peninsula is associated with high lake levels values during winter. This center moves southwestward during spring, summer and autumn. In the same time, a cyclonic anomaly center is recorded over central and western Europe. This anomalous circulation extends southwestward from winter to autumn. Similar atmospheric circulation patterns are associated with river runoff and precipitation variability from the region. High lake levels are associated with positive local precipitation anomalies in all seasons as well as with negative local temperature anomalies during spring, summer and autumn. A correlation analysis reveals that lake level, runoff and precipitation variability is related to large-scale sea surface temperature anomaly patterns in all seasons suggesting a possible impact of large-scale climatic modes, like the North Atlantic Oscillation and Atlantic Multidecadal Oscillation on hydroclimatic variability in the Lake Mondsee region. The results presented in this study can be used for a more robust interpretation of the long flood layer record from Lake Mondsee sediments in terms of regional and large-scale climate variability during the past.

A site specific model and analysis of the neutral somatic mutation rate in whole-genome cancer data.

PubMed

Bertl, Johanna; Guo, Qianyun; Juul, Malene; Besenbacher, Søren; Nielsen, Morten Muhlig; Hornshøj, Henrik; Pedersen, Jakob Skou; Hobolth, Asger

2018-04-19

Detailed modelling of the neutral mutational process in cancer cells is crucial for identifying driver mutations and understanding the mutational mechanisms that act during cancer development. The neutral mutational process is very complex: whole-genome analyses have revealed that the mutation rate differs between cancer types, between patients and along the genome depending on the genetic and epigenetic context. Therefore, methods that predict the number of different types of mutations in regions or specific genomic elements must consider local genomic explanatory variables. A major drawback of most methods is the need to average the explanatory variables across the entire region or genomic element. This procedure is particularly problematic if the explanatory variable varies dramatically in the element under consideration. To take into account the fine scale of the explanatory variables, we model the probabilities of different types of mutations for each position in the genome by multinomial logistic regression. We analyse 505 cancer genomes from 14 different cancer types and compare the performance in predicting mutation rate for both regional based models and site-specific models. We show that for 1000 randomly selected genomic positions, the site-specific model predicts the mutation rate much better than regional based models. We use a forward selection procedure to identify the most important explanatory variables. The procedure identifies site-specific conservation (phyloP), replication timing, and expression level as the best predictors for the mutation rate. Finally, our model confirms and quantifies certain well-known mutational signatures. We find that our site-specific multinomial regression model outperforms the regional based models. The possibility of including genomic variables on different scales and patient specific variables makes it a versatile framework for studying different mutational mechanisms. Our model can serve as the neutral null model for the mutational process; regions that deviate from the null model are candidates for elements that drive cancer development.

Analysis of monthly, winter, and annual temperatures in Zagreb, Croatia, from 1864 to 2010: the 7.7-year cycle and the North Atlantic Oscillation

NASA Astrophysics Data System (ADS)

Sen, Asok K.; Ogrin, Darko

2016-02-01

Long instrumental records of meteorological variables such as temperature and precipitation are very useful for studying regional climate in the past, present, and future. They can also be useful for understanding the influence of large-scale atmospheric circulation processes on the regional climate. This paper investigates the monthly, winter, and annual temperature time series obtained from the instrumental records in Zagreb, Croatia, for the period 1864-2010. Using wavelet analysis, the dominant modes of variability in these temperature series are identified, and the time intervals over which these modes may persist are delineated. The results reveal that all three temperature records exhibit low-frequency variability with a dominant periodicity at around 7.7 years. The 7.7-year cycle has also been observed in the temperature data recorded at several other stations in Europe, especially in Northern and Western Europe, and may be linked to the North Atlantic Oscillation (NAO) and/or solar/geomagnetic activity.

Decreasing spatial variability in precipitation extremes in southwestern China and the local/large-scale influencing factors

NASA Astrophysics Data System (ADS)

Liu, Meixian; Xu, Xianli; Sun, Alex

2015-07-01

Climate extremes can cause devastating damage to human society and ecosystems. Recent studies have drawn many conclusions about trends in climate extremes, but few have focused on quantitative analysis of their spatial variability and underlying mechanisms. By using the techniques of overlapping moving windows, the Mann-Kendall trend test, correlation, and stepwise regression, this study examined the spatial-temporal variation of precipitation extremes and investigated the potential key factors influencing this variation in southwestern (SW) China, a globally important biodiversity hot spot and climate-sensitive region. Results showed that the changing trends of precipitation extremes were not spatially uniform, but the spatial variability of these precipitation extremes decreased from 1959 to 2012. Further analysis found that atmospheric circulations rather than local factors (land cover, topographic conditions, etc.) were the main cause of such precipitation extremes. This study suggests that droughts or floods may become more homogenously widespread throughout SW China. Hence, region-wide assessments and coordination are needed to help mitigate the economic and ecological impacts.

Long-term rise of the Water Table in the Northeast US: Climate Variability, Land-Use Change, or Angry Beavers?

NASA Astrophysics Data System (ADS)

Boutt, D. F.

2011-12-01

The scientific evidence that humans are directly influencing the Earth's natural climate is increasingly compelling. Numerous studies suggest that climate change will lead to changes in the seasonality of surface water availability thereby increasing the need for groundwater development to offset those shortages. Research suggests that the Northeast region of the U.S. is experiencing significant changes to its' natural climate and hydrologic systems. Previous analysis of a long-term regional compilation of the water table response to the last 60 years of climate variability in New England documented a wide range of variability. The investigation evaluated the physical mechanisms, natural variability and response of aquifers in New England using 100 long term groundwater monitoring stations with 20 or more years of data coupled with 67 stream gages, 75 precipitation stations, and 43 temperature stations. Groundwater trends were calculated as normalized anomalies and analyzed with respect to regional compiled precipitation, temperature, and streamflow anomalies to understand the sensitivity of the aquifer systems to change. Interestingly, a trend and regression analysis demonstrate that water level fluctuations are producing statistically significant results with increasing water levels over at least the past thirty years at most (80 out of 100) well sites. In this contribution we investigate the causal mechanisms behind the observed ground water level trends using site-by-site land-use change assessments, cluster analysis, and spatial analysis of beaver populations (a possible proxy for beaver activity). Regionally, average annual precipitation has been slightly increasing since 1900, with 95% of the stations having statistically significant positive trends. Despite this, no correlation is observed between the magnitude of the annual precipitation trends and the magnitude of the groundwater level changes. Land-use change throughout the region has primarily taken place in and around existing urban centers with an overall increase in the percentage of forested land. Individual analysis of well sites in areas with documented land-use change from agriculture and forested land cover to urban land use suggests a positive correlation with increasing water levels. Recently, beaver populations been begun to rise that has led to local increases in wetland areas. These regions also show a high positive correlation to the magnitude of water table rise. Local factors such as land-use change and beaver activity appear to overprint and mask the impact of consistent increases in annual precipitation. Rising water tables have major implications for not only water management but also the agriculture, forestry, fishing, and tourism industries as they all depend on the quantity and quality of water resources of the region.

Insight on invasions and resilience derived from spatiotemporal discontinuities of biomass at local and regional scales

USGS Publications Warehouse

Angeler, David G.; Allen, Criag R.; Johnson, Richard K.

2012-01-01

Understanding the social and ecological consequences of species invasions is complicated by nonlinearities in processes, and differences in process and structure as scale is changed. Here we use discontinuity analyses to investigate nonlinear patterns in the distribution of biomass of an invasive nuisance species that could indicate scale-specific organization. We analyze biomass patterns in the flagellate Gonyostomum semen (Raphidophyta) in 75 boreal lakes during an 11-year period (1997-2007). With simulations using a unimodal null model and cluster analysis, we identified regional groupings of lakes based on their biomass patterns. We evaluated the variability of membership of individual lakes in regional biomass groups. Temporal trends in local and regional discontinuity patterns were analyzed using regressions and correlations with environmental variables that characterize nutrient conditions, acidity status, temperature variability, and water clarity. Regionally, there was a significant increase in the number of biomass groups over time, indicative of an increased number of scales at which algal biomass organizes across lakes. This increased complexity correlated with the invasion history of G. semen and broad-scale environmental change (recovery from acidification). Locally, no consistent patterns of lake membership to regional biomass groups were observed, and correlations with environmental variables were lake specific. The increased complexity of regional biomass patterns suggests that processes that act within or between scales reinforce the presence of G. semen and its potential to develop high-biomass blooms in boreal lakes. Emergent regional patterns combined with locally stochastic dynamics suggest a bleak future for managing G. semen, and more generally why invasive species can be ecologically successful.

Impact of climate variability on various Rabi crops over Northwest India

NASA Astrophysics Data System (ADS)

Nageswararao, M. M.; Dhekale, B. S.; Mohanty, U. C.

2018-01-01

The Indian agriculture with its two prominent cropping seasons [summer ( Kharif) and winter ( Rabi)] is the mainstay of the rural economy. Northwest India (NWI) is an important region for the cultivation of Rabi crops grown during the period from October to April. In the present study, state wise impact analysis is carried out to ascertain the influence of climate indices Nino3.4 region Sea Surface Temperature (SST), Southern Oscillation Index (SOI), Arctic Oscillation (AO), North Atlantic Oscillation (NAO) and local precipitation, soil moisture, minimum ( T min), maximum ( T max) and mean ( T mean) temperatures on different Rabi crops (wheat, gram, rapeseed-mustard, oilseeds, and total Rabi food grains) over NWI during the years 1966-2011. To study the impact of climate variability on different Rabi crops, firstly, the influence of technology on the productivity of these crops has been removed by using linear function, as linear trend has noticed in all the time series. Correlation analysis provides an indication of the influence of local precipitation, soil moisture, T min, T max and T mean and some of its potential predictors (Nino3.4 region SST, SOI, AO, and NAO) on the productivity of different Rabi crops. Overall impact analysis indicates that the productivity of different Rabi crops in most of the places of NWI is most likely influenced by variability in local temperatures. Moreover, Nino3.4 region SST (SOI) positively (negatively) affects the productivity of gram, rapeseed-mustard, and total Rabi oilseeds in most of the states. The results of this study are useful in determining the strategies for increasing sustainable production through better agronomic practices.

Analysis of meteorological variables in the Australasian region using ground- and space-based GPS techniques

NASA Astrophysics Data System (ADS)

Kuleshov, Yuriy; Choy, Suelynn; Fu, Erjiang Frank; Chane-Ming, Fabrice; Liou, Yuei-An; Pavelyev, Alexander G.

2016-07-01

Results of analysis of meteorological variables (temperature and moisture) in the Australasian region using the global positioning system (GPS) radio occultation (RO) and GPS ground-based observations verified with in situ radiosonde (RS) data are presented. The potential of using ground-based GPS observations for retrieving column integrated precipitable water vapour (PWV) over the Australian continent has been demonstrated using the Australian ground-based GPS reference stations network. Using data from the 15 ground-based GPS stations, the state of the atmosphere over Victoria during a significant weather event, the March 2010 Melbourne storm, has been investigated, and it has been shown that the GPS observations has potential for monitoring the movement of a weather front that has sharp moisture contrast. Temperature and moisture variability in the atmosphere over various climatic regions (the Indian and the Pacific Oceans, the Antarctic and Australia) has been examined using satellite-based GPS RO and in situ RS observations. Investigating recent atmospheric temperature trends over Antarctica, the time series of the collocated GPS RO and RS data were examined, and strong cooling in the lower stratosphere and warming through the troposphere over Antarctica has been identified, in agreement with outputs of climate models. With further expansion of the Global Navigation Satellite Systems (GNSS) system, it is expected that GNSS satellite- and ground-based measurements would be able to provide an order of magnitude larger amount of data which in turn could significantly advance weather forecasting services, climate monitoring and analysis in the Australasian region.

An analysis of long and medium-haul air passenger demand, volume 1

NASA Technical Reports Server (NTRS)

Eriksen, S. E.

1978-01-01

A basic model was developed which is a two equation pair econometric system in which air passenger demand and airline level-of-service are the endogenous variables. The model aims to identify the relationship between each of these two variables and its determining factors, and to identify the interaction of demand and level-of-service with each other. The selected variable for the measure of air passenger traffic activity in a given pair market is defined as the number of passengers in a given time that originate in one region and fly to the other region for purposes other than to make a connection to a third region. For medium and long haul markets, the model seems to perform better for larger markets. This is due to a specification problem regarding the route structure variable. In larger markets, a greater percentage of nonlocal passengers are accounted for by this variable. Comparing the estimated fare elasticities of long and medium haul markets, it appears that air transportation demand is more price elastic in longer haul markets. Long haul markets demand will saturate with a fewer number of departures than will demand in medium haul markets.

INTEGRATED ENVIRONMENTAL ASSESSMENT OF THE MID-ATLANTIC REGION WITH ANALYTICAL NETWORK PROCESS

EPA Science Inventory

A decision analysis method for integrating environmental indicators was developed. This was a combination of Principal Component Analysis (PCA) and the Analytic Network Process (ANP). Being able to take into account interdependency among variables, the method was capable of ran...

Drivers of Variability in Public-Supply Water Use Across the Contiguous United States

NASA Astrophysics Data System (ADS)

Worland, Scott C.; Steinschneider, Scott; Hornberger, George M.

2018-03-01

This study explores the relationship between municipal water use and an array of climate, economic, behavioral, and policy variables across the contiguous U.S. The relationship is explored using Bayesian-hierarchical regression models for over 2,500 counties, 18 covariates, and three higher-level grouping variables. Additionally, a second analysis is included for 83 cities where water price and water conservation policy information is available. A hierarchical model using the nine climate regions (product of National Oceanic and Atmospheric Administration) as the higher-level groups results in the best out-of-sample performance, as estimated by the Widely Available Information Criterion, compared to counties grouped by urban continuum classification or primary economic activity. The regression coefficients indicate that the controls on water use are not uniform across the nation: e.g., counties in the Northeast and Northwest climate regions are more sensitive to social variables, whereas counties in the Southwest and East North Central climate regions are more sensitive to environmental variables. For the national city-level model, it appears that arid cities with a high cost of living and relatively low water bills sell more water per customer, but as with the county-level model, the effect of each variable depends heavily on where a city is located.

Bankfull discharge and channel characteristics of streams in New York State

USGS Publications Warehouse

Mulvihill, Christiane I.; Baldigo, Barry P.; Miller, Sarah J.; DeKoskie, Douglas; DuBois, Joel

2009-01-01

Equations that relate drainage area to bankfull discharge and channel characteristics (such as width, depth, and cross-sectional area) at gaged sites are needed to help define bankfull discharge and channel characteristics at ungaged sites and can be used in stream-restoration and protection projects, stream-channel classification, and channel assessments. These equations are intended to serve as a guide for streams in areas of similar hydrologic, climatic, and physiographic conditions. New York State contains eight hydrologic regions that were previously delineated on the basis of high-flow (flood) characteristics. This report seeks to increase understanding of the factors affecting bankfull discharge and channel characteristics to drainage-area size relations in New York State by providing an in-depth analysis of seven previously published regional bankfull-discharge and channel-characteristics curves.Stream-survey data and discharge records from 281 cross sections at 82 streamflow-gaging stations were used in regression analyses to relate drainage area to bankfull discharge and bankfull-channel width, depth, and cross-sectional area. The R2 and standard errors of estimate of each regional equation were compared to the R2 and standard errors of estimate for the statewide (pooled) model to determine if regionalizing data reduced model variability. It was found that regional models typically yield less variable results than those obtained using pooled statewide equations, which indicates statistically significant regional differences in bankfull-discharge and channel-characteristics relations.Statistical analysis of bankfull-discharge relations found that curves for regions 4 and 7 fell outside the 95-percent confidence interval bands of the statewide model and had intercepts that were significantly diferent (p≤0.10) from the other five hydrologic regions.Analysis of channel-characteristics relations found that the bankfull width, depth, and cross-sectional area curves for region 3 were significantly different p(≤0.05) from the other six regions.It was hypothesized that some regional variability could be reduced by creating models for streams with similar physiographic and climatic characteristics. Available data on streamflow patterns and previous regional-curve research suggested that mean annual runoff, Rosgen stream type, and water-surface slope were the variables most likely to influence regional bankfull discharge and channel characteristics to drainage-area size relations. Results showed that although all of these factors had an influence on regional relations, most stratified models have lower 2 values and higher standard errors of estimate than the regional models.The New York statewide (pooled) bankfull-discharge equation and equations for regions 4 and 7 were compared with equations for four other regions in the Northeast to evaluate region-to-region differences, and assess the ability of individual curves to produce results more accurate than those that would be obtained from one model of the northeastern United States. Results indicated that model slopes lack significant diferences, though intercepts are significantly different. Comparison of bankfull-discharge estimates using different models shows that results could vary by as much as 100 percent depending on which model was used and indicated that regionalization improved model accuracy.

Decadal climate variability and the spatial organization of deep hydrological drought

NASA Astrophysics Data System (ADS)

Barros, Ana P.; Hodes, Jared L.; Arulraj, Malarvizhi

2017-10-01

Empirical Orthogonal Function (EOF), wavelet, and wavelet coherence analysis of baseflow time-series from 126 streamgauges (record-length > 50 years; small and mid-size watersheds) in the US South Atlantic (USSA) region reveal three principal modes of space-time variability: (1) a region-wide dominant mode tied to annual precipitation that exhibits non-stationary decadal variability after the mid 1990s concurrent with the warming of the AMO (Atlantic Multidecadal Oscillation); (2) two spatial modes, east and west of the Blue Ridge, exhibiting nonstationary seasonal to sub-decadal variability before and after 1990 attributed to complex nonlinear interactions between ENSO and AMO impacting precipitation and recharge; and (3) deep (decadal) and shallow (< 6 years) space-time modes of groundwater variability separating basins with high and low annual mean baseflow fraction (MBF) by physiographic region. The results explain the propagation of multiscale climate variability into the regional groundwater system through recharge modulated by topography, geomorphology, and geology to determine the spatial organization of baseflow variability at decadal (and longer) time-scales, that is, deep hydrologic drought. Further, these findings suggest potential for long-range predictability of hydrological drought in small and mid-size watersheds, where baseflow is a robust indicator of nonstationary yield capacity of the underlying groundwater basins. Predictive associations between climate mode indices and deep baseflow (e.g. persistent decreases of the decadal-scale components of baseflow during the cold phase of the AMO in the USSA) can be instrumental toward improving forecast lead-times and long-range mitigation of severe drought.

Analysis of biophysical and anthropogenic variables and their relation to the regional spatial variation of aboveground biomass illustrated for North and East Kalimantan, Borneo.

PubMed

Van der Laan, Carina; Verweij, Pita A; Quiñones, Marcela J; Faaij, André Pc

2014-12-01

Land use and land cover change occurring in tropical forest landscapes contributes substantially to carbon emissions. Better insights into the spatial variation of aboveground biomass is therefore needed. By means of multiple statistical tests, including geographically weighted regression, we analysed the effects of eight variables on the regional spatial variation of aboveground biomass. North and East Kalimantan were selected as the case study region; the third largest carbon emitting Indonesian provinces. Strong positive relationships were found between aboveground biomass and the tested variables; altitude, slope, land allocation zoning, soil type, and distance to the nearest fire, road, river and city. Furthermore, the results suggest that the regional spatial variation of aboveground biomass can be largely attributed to altitude, distance to nearest fire and land allocation zoning. Our study showed that in this landscape, aboveground biomass could not be explained by one single variable; the variables were interrelated, with altitude as the dominant variable. Spatial analyses should therefore integrate a variety of biophysical and anthropogenic variables to provide a better understanding of spatial variation in aboveground biomass. Efforts to minimise carbon emissions should incorporate the identified factors, by 1) the maintenance of lands with high AGB or carbon stocks, namely in the identified zones at the higher altitudes; and 2) regeneration or sustainable utilisation of lands with low AGB or carbon stocks, dependent on the regeneration capacity of the vegetation. Low aboveground biomass densities can be found in the lowlands in burned areas, and in non-forest zones and production forests.

Species composition of the genus Saprolegnia in fin fish aquaculture environments, as determined by nucleotide sequence analysis of the nuclear rDNA ITS regions.

PubMed

de la Bastide, Paul Y; Leung, Wai Lam; Hintz, William E

2015-01-01

The ITS region of the rDNA gene was compared for Saprolegnia spp. in order to improve our understanding of nucleotide sequence variability within and between species of this genus, determine species composition in Canadian fin fish aquaculture facilities, and to assess the utility of ITS sequence variability in genetic marker development. From a collection of more than 400 field isolates, ITS region nucleotide sequences were studied and it was determined that there was sufficient consistent inter-specific variation to support the designation of species identity based on ITS sequence data. This non-subjective approach to species identification does not rely upon transient morphological features. Phylogenetic analyses comparing our ITS sequences and species designations with data from previous studies generally supported the clade scheme of Diéguez-Uribeondo et al. (2007) and found agreement with the molecular taxonomic cluster system of Sandoval-Sierra et al. (2014). Our Canadian ITS sequence collection will thus contribute to the public database and assist the clarification of Saprolegnia spp. taxonomy. The analysis of ITS region sequence variability facilitated genus- and species-level identification of unknown samples from aquaculture facilities and provided useful information on species composition. A unique ITS-RFLP for the identification of S. parasitica was also described. Copyright © 2014 The British Mycological Society. Published by Elsevier Ltd. All rights reserved.

Reconstructing the leading mode of multi-decadal North Atlantic variability over the last two millenia using functional paleoclimate networks

NASA Astrophysics Data System (ADS)

Franke, Jasper G.; Werner, Johannes; Donner, Reik V.

2017-04-01

The increasing availability of high-resolution North Atlantic paleoclimate proxies allows to not only study local climate variations in time, but also temporal changes in spatial variability patterns across the entire region possibly controlled by large-scale coherent variability modes such as the North Atlantic Oscillation (NAO) and Atlantic Multidecadal Oscillation. In this study, we use functional paleoclimate network analysis [1,2] to investigate changes in the statistical similarity patterns among an ensemble of high-resolution terrestrial paleoclimate records from Northern Europe included in the Arctic 2k data base. Specifically, we construct complex networks capturing the mutual statistical similarity of inter-annual temperature variability recorded in tree ring records, ice cores and lake sediments for multidecadal time windows covering the last two millenia. The observed patterns of co-variability are ultimately connected to the North Atlantic atmospheric circulation and most prominently to multidecadal variations of the NAO. Based on the inferred networks, we study the dynamical similarity between regional clusters of archives defined according to present-day inter-annual temperature variations across the study region. This analysis identifies those time-dependent inter-regional linkages that are most informative about the leading-order North Atlantic climate variability according to a recent NAO reconstruction for the last millenium [3]. Based on these linkages, we extend the existing reconstruction to obtain qualitative information on multidecadal to centennial scale North Atlantic climate variability over the last two millenia. In general, we find a tendency towards a dominating positive NAO phase interrupted by pronounced and extended intervals of negative NAO. Relatively rapid transitions between both types of behaviour are present during distinct periods including the Little Ice Age, the Medieval Climate Anomaly and for the Dark Ages Little Ice Age. [1] K. Rehfeld, N. Marwan, S.F.M. Breitenbach, J. Kurths: Late Holocene Asian summer monsoon dynamics from small but complex networks of paleoclimate data. Climate Dynamics 41, 3-19, 2013 [2] J.L. Oster, N.P. Kelley: Tracking regional and global teleconnections recorded by western North American speleothem records. Quaternary Science Reviews 149, 18-33, 2016 [3] P. Ortega, F. Lehner, D. Swingedouw, V. Masson-Delmotte, C.C. Raible, M. Casado, P. Yiou: A model-tested North Atlantic Oscillation reconstruction for the past millenium. Nature 523, 71-74, 2015

Variability of the recent climate of eastern Africa

NASA Astrophysics Data System (ADS)

Schreck, Carl J., III; Semazzi, Fredrick H. M.

2004-05-01

The primary objective of this study is to investigate the recent variability of the eastern African climate. The region of interest is also known as the Greater Horn of Africa (GHA), and comprises the countries of Burundi, Djibouti, Eritrea, Ethiopia, Kenya, Rwanda, Somalia, Sudan, Uganda, and Tanzania.The analysis was based primarily on the construction of empirical orthogonal functions (EOFs) of gauge rainfall data and on CPC Merged Analysis of Precipitation (CMAP) data, derived from a combination of rain-gauge observations and satellite estimates. The investigation is based on the period 1961-2001 for the short rains season of eastern Africa of October through to December. The EOF analysis was supplemented by projection of National Centers for Environmental Prediction wind data onto the rainfall eigenmodes to understand the rainfall-circulation relationships. Furthermore, correlation and composite analyses have been performed with the Climatic Research Unit globally averaged surface-temperature time series to explore the potential relationship between the climate of eastern Africa and global warming.The most dominant mode of variability (EOF1) based on CMAP data over eastern Africa corresponds to El Niño-southern oscillation (ENSO) climate variability. It is associated with above-normal rainfall amounts during the short rains throughout the entire region, except for Sudan. The corresponding anomalous low-level circulation is dominated by easterly inflow from the Indian Ocean, and to a lesser extent the Congo tropical rain forest, into the positive rainfall anomaly region that extends across most of eastern Africa. The easterly inflow into eastern Africa is part of diffluent outflow from the maritime continent during the warm ENSO events. The second eastern African EOF (trend mode) is associated with decadal variability. In distinct contrast from the ENSO mode pattern, the trend mode is characterized by positive rainfall anomalies over the northern sector of eastern Africa and opposite conditions over the southern sector. This rainfall trend mode eluded detection in previous studies that did not include recent decades of data, because the signal was still relatively weak. The wind projection onto this mode indicates that the primary flow that feeds the positive anomaly region over the northern part of eastern Africa emanates primarily from the rainfall-deficient southern region of eastern Africa and Sudan. Although we do not assign attribution of the trend mode to global warming (in part because of the relatively short period of analysis), the evidence, based on our results and previous studies, strongly suggests a potential connection.

Differentially Variable Component Analysis (dVCA): Identifying Multiple Evoked Components using Trial-to-Trial Variability

NASA Technical Reports Server (NTRS)

Knuth, Kevin H.; Shah, Ankoor S.; Truccolo, Wilson; Ding, Ming-Zhou; Bressler, Steven L.; Schroeder, Charles E.

2003-01-01

Electric potentials and magnetic fields generated by ensembles of synchronously active neurons in response to external stimuli provide information essential to understanding the processes underlying cognitive and sensorimotor activity. Interpreting recordings of these potentials and fields is difficult as each detector records signals simultaneously generated by various regions throughout the brain. We introduce the differentially Variable Component Analysis (dVCA) algorithm, which relies on trial-to-trial variability in response amplitude and latency to identify multiple components. Using simulations we evaluate the importance of response variability to component identification, the robustness of dVCA to noise, and its ability to characterize single-trial data. Finally, we evaluate the technique using visually evoked field potentials recorded at incremental depths across the layers of cortical area VI, in an awake, behaving macaque monkey.

Line formation in the hot spot region of cataclysmic variable accretion disks

NASA Technical Reports Server (NTRS)

Elitzur, Moshe; Clarke, John T.; Kallman, T. R.

1988-01-01

The paper presents a theoretical analysis of the emission lines observed in the cataclysmic variable A0 Psc (=H2252-035), including detailed modeling of the hydrogen Balmer line emission. The analysis makes it possible to deduce the physical conditions in the so called 'hot spot', or 'bulge' region where the accretion column hits the rim of the accretion disk. It is concluded that the bulge is optically thick to the ionizing disk radiation. Consequently, its disk illuminated face is fully ionized whereas the side facing away from the disk is neutral, resulting in modulation of the observed emission lines with the orbital period. The density in the hot spot is about 5 x 10 to the 12th to 10 to the 13th/cu cm.

ENSO and PDO-related climate variability impacts on Midwestern United States crop yields.

PubMed

Henson, Chasity; Market, Patrick; Lupo, Anthony; Guinan, Patrick

2017-05-01

An analysis of crop yields for the state of Missouri was completed to determine if an interannual or multidecadal variability existed as a result of the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO). Corn and soybean yields were recorded in kilograms per hectare for each of the six climate regions of Missouri. An analysis using the Mokhov "method of cycles" demonstrated interannual, interdecadal, and multidecadal variations in crop yields. Cross-spectral analysis was used to determine which region was most impacted by ENSO and PDO influenced seasonal (April-September) temperature and precipitation. Interannual (multidecadal) variations found in the spectral analysis represent a relationship to ENSO (PDO) phase, while interdecadal variations represent a possible interaction between ENSO and PDO. Average crop yields were then calculated for each combination of ENSO and PDO phase, displaying a pronounced increase in corn and soybean yields when ENSO is warm and PDO is positive. Climate regions 1, 2, 4, and 6 displayed significant differences (p value of 0.10 or less) in yields between El Niño and La Niña years, representing 55-70 % of Missouri soybean and corn productivity, respectively. Final results give the opportunity to produce seasonal predictions of corn and soybean yields, specific to each climate region in Missouri, based on the combination of ENSO and PDO phases.

Spatial and temporal variability of Mediterranean drought events

NASA Astrophysics Data System (ADS)

Trigo, R.; Sousa, P.; Nieto, R.; Gimeno, L.

2009-04-01

The original Palmer Drought Severity Index (PDSI) and a recent adaptation to European soil characteristics, the Self Calibrated PDSI (or scPDSI) proposed by Schrier et al (2005) were used. We have computed monthly, seasonal and annual trends between 1901 and 2000 but also for the first and second halves of the 20th century. Results were represented only when achieving a minimum level of statistical significance (either 5% or 10% using a Mann-Kendall test) and confirm that the majority of the western and central Mediterranean is getting drier in the last decades of the 20th century while Turkey is generally getting wetter (Trigo et al., 2006). The spatio-temporal variability of these indices was evaluated with an EOF analysis, in order to reduce the large dimensionality of the fields under analysis. Spatial representation of the first EOF patterns shows that EOF 1 covers the entire Mediterranean basin (16.4% of EV), while EOF2 is dominated by a W-E dipole (10% EV). The following EOF patterns present smaller scale features, and explain smaller amounts of variance. The EOF patterns have also facilitated the definition of four sub-regions with large socio-economic relevance: 1) Iberia, 2) Italian Peninsula, 3) Balkans and 4) Turkey. The inter-annual variability of the regional spatial droughts indices for each region was analyzed separately. We have also performed an evaluation of their eventual links with large-scale atmospheric circulation indices that affect the Mediterranean basin, namely the NAO, EA, and SCAND. Finally we have evaluated the main sources of moisture affecting two drought prone areas in the western (Iberia) and eastern (Balkans) Mediterranean. This analysis was performed by means of backward tracking the air masses that ultimately reach these two regions using the Lagrangian particle dispersion model FLEXPART (Stohl et al., 1998) and meteorological analysis data from the ECMWF to track atmospheric moisture. This was done for a five-year period (2000-2004) and using ECMWF operational analysis available every six hours (00, 06, 12 and 18 UTC) with a 1°x1° resolution (Sthol et al., 2004). Following the approach used by the authors for the Sahel (Nieto et al., 2006) and Tropical south America (Nieto et al., 2008) we traced (E-P) backwards from both regions, limiting the transport times to 10 days, which is the average time that water vapor resides in the atmosphere. In order to evaluate possible shifts in the origin of the moisture sources (between wet and dry years) this analysis was performed independently for dry and wet winter seasons. Nieto R., Gimeno L., Trigo R.M. (2006) A Lagrangian identification of major sources of Sahel moisture. Geophys. Res. Letters, 33, L18707, doi:10.1029/2006GL027232. Nieto R., Ribera P., Trigo R.M. , Gallego D., Gimeno L.(2008) Dynamic identification of moisture sources in the Orinoco Basin. Hydrological Sciences Journal, 53, 602-612. Schrier G, Briffa KR, Jones PD, Osborn TJ. (2005). Summer moisture variability across Europe. Journal of Climate, 19, 2818-2834. Stohl, A., M. Hittenberger, and G. Wotawa (1998), Validation of the Lagrangian particle dispersion model FLEXPART against large scale tracer experiment data, Atmos. Environ., 32, 4245- 4264. Stohl, A., and P. James (2004), A Lagrangian analysis of the atmospheric branch of the global water cycle. Part 1: Method description, validation, and demonstration for the August 2002 flooding in central Europe. J. Hydrometeor., 5, 656-678. Trigo, R. and 21 authors (2006) Relations between variability in the Mediterranean region and mid-latitude variability. In: P. Lionello, P. Malanotte-Rizzoli & R. Boscolo (Eds), Mediterranean Climate Variability, Amsterdam: Elsevier, pp. 179-226.

Analysis of the in vivo confocal Raman spectral variability in human skin

NASA Astrophysics Data System (ADS)

Mogilevych, Borys; dos Santos, Laurita; Rangel, Joao L.; Grancianinov, Karen J. S.; Sousa, Mariane P.; Martin, Airton A.

2015-06-01

Biochemical composition of the skin changes in each layer and, therefore, the skin spectral profile vary with the depth. In this work, in vivo Confocal Raman spectroscopy studies were performed at different skin regions and depth profile (from the surface down to 10 μm) of the stratum corneum, to verify the variability and reproducibility of the intra- and interindividual Raman data. The Raman spectra were collected from seven healthy female study participants using a confocal Raman system from Rivers Diagnostic, with 785 nm excitation line and a CCD detector. Measurements were performed in the volar forearm region, at three different points at different depth, with the step of 2 μm. For each depth point, three spectra were acquired. Data analysis included the descriptive statistics (mean, standard deviation and residual) and Pearson's correlation coefficient calculation. Our results show that inter-individual variability is higher than intraindividual variability, and variability inside the SC is higher than on the skin surface. In all these cases we obtained r values, higher than 0.94, which correspond to high correlation between Raman spectra. It reinforces the possibility of the data reproducibility and direct comparison of in vivo results obtained with different study participants of the same age group and phototype.

Tannat grape composition responses to spatial variability of temperature in an Uruguay's coastal wine region

NASA Astrophysics Data System (ADS)

Fourment, Mercedes; Ferrer, Milka; González-Neves, Gustavo; Barbeau, Gérard; Bonnardot, Valérie; Quénol, Hervé

2017-09-01

Spatial variability of temperature was studied in relation to the berry basic composition and secondary compounds of the Tannat cultivar at harvest from vineyards located in Canelones and Montevideo, the most important wine region of Uruguay. Monitoring of berries and recording of temperature were performed in 10 commercial vineyards of Tannat situated in the southern coastal wine region of the country for three vintages (2012, 2013, and 2014). Results from a multivariate correlation analysis between berry composition and temperature over the three vintages showed that (1) Tannat responses to spatial variability of temperature were different over the vintages, (2) correlations between secondary metabolites and temperature were higher than those between primary metabolites, and (3) correlation values between berry composition and climate variables increased when ripening occurred under dry conditions (below average rainfall). For a particular studied vintage (2013), temperatures explained 82.5% of the spatial variability of the berry composition. Daily thermal amplitude was found to be the most important spatial mode of variability with lower values recorded at plots nearest to the sea and more exposed to La Plata River. The highest levels in secondary compounds were found in berries issued from plots situated as far as 18.3 km from La Plata River. The increasing knowledge of temperature spatial variability and its impact on grape berry composition contributes to providing possible issues to adapt grapevine to climate change.

A study about the photometric variability in the M42 region

NASA Astrophysics Data System (ADS)

Lima, G. H. R. A.; Vaz, L. P. R.; Reipurth, B.

2003-08-01

The M42 region in Orion is one of the most active regarding stellar formation in the neighborhood of the solar system. At a distance of 450pc, it gives us an excellent oportunity to study star formation processes. By studying 22 films of this region, covering an area of 5 by 5 degrees, taken in almost regular intervals through 2.5 years by ESO 1m Schimdt Telescope, in La Silla, Chile, we seek to discover variable stars among the young stars. These films were digitalized by the SuperCOSMOS (the most precise scientific scanner today) team, and each film were exposed for 30 minutes. Our knowledge about the variability of low-mass young variable stars were outdated, and were based on old photographic plates, which were studied by the so called blink comparators and Iris photometers. Now we developed a process to study these data and identify possible candidate stars to be constants or variables, and developed some softwares based on this process. We also used some softwares supplied by the SuperCosmos team to help our analysis of the dataset. After identifying the stars, which we, definitively, can consider variables, we will study more deeply these ones in hope to obtain more data about the formation process. We expect to detect thousands of new variables within our data as also the light curves for each star detected.

Quantification and regionalization of groundwater recharge in South-Central Kansas: Integrating field characterization, statistical analysis, and GIS

USGS Publications Warehouse

Sophocleous, M.

2000-01-01

A practical methodology for recharge characterization was developed based on several years of field-oriented research at 10 sites in the Great Bend Prairie of south-central Kansas. This methodology combines the soil-water budget on a storm-by-storm year-round basis with the resulting watertable rises. The estimated 1985-1992 average annual recharge was less than 50mm/year with a range from 15 mm/year (during the 1998 drought) to 178 mm/year (during the 1993 flood year). Most of this recharge occurs during the spring months. To regionalize these site-specific estimates, an additional methodology based on multiple (forward) regression analysis combined with classification and GIS overlay analyses was developed and implemented. The multiple regression analysis showed that the most influential variables were, in order of decreasing importance, total annual precipitation, average maximum springtime soil-profile water storage, average shallowest springtime depth to watertable, and average springtime precipitation rate. Therefore, four GIS (ARC/INFO) data "layers" or coverages were constructed for the study region based on these four variables, and each such coverage was classified into the same number of data classes to avoid biasing the results. The normalized regression coefficients were employed to weigh the class rankings of each recharge-affecting variable. This approach resulted in recharge zonations that agreed well with the site recharge estimates. During the "Great Flood of 1993," when rainfall totals exceeded normal levels by -200% in the northern portion of the study region, the developed regionalization methodology was tested against such extreme conditions, and proved to be both practical, based on readily available or easily measurable data, and robust. It was concluded that the combination of multiple regression and GIS overlay analyses is a powerful and practical approach to regionalizing small samples of recharge estimates.

Effects of land use, climate, topography and soil properties on regional soil organic carbon and total nitrogen in the upstream watershed of Miyun Reservoir, North China.

PubMed

Wang, Shufang; Wang, Xiaoke; Ouyang, Zhiyun

2012-01-01

Soil organic carbon (SOC) and total nitrogen (TN) contents as well as their relationships with site characteristics are of profound importance in assessing current regional, continental and global soil C and N stocks and potentials for C sequestration and N conservation to offset anthropogenic emissions of greenhouse gases. This study investigated contents and distribution of SOC and TN under different land uses, and the quantitative relationships between SOC or TN and site characteristics in the Upstream Watershed of Miyun Reservoir, North China. Overall, both SOC and TN contents in natural secondary forests and grasslands were much higher than in plantations and croplands. Land use alone explained 37.2% and 38.4% of variations in SOC and TN contents, respectively. The optimal models for SOC and TN, achieved by multiple regression analysis combined with principal component analysis (PCA) to remove the multicollinearity among site variables, showed that elevation, slope, soil clay and water contents were the most significant factors controlling SOC and TN contents, jointly explaining 70.3% of SOC and 67.1% of TN contents variability. Only does additional 1.9% and 3% increase in the interpretations of SOC and TN contents variability respectively when land use was added to regressions, probably due to environment factors determine land use. Therefore, environmental variables were more important for SOC and TN variability than land use in the study area, and should be taken into consideration in properly evaluating effects of future land use changes on SOC and TN on a regional scale.

Analysis of the long-term surface wind variability over complex terrain using a high spatial resolution WRF simulation

NASA Astrophysics Data System (ADS)

Jiménez, Pedro A.; González-Rouco, J. Fidel; Montávez, Juan P.; García-Bustamante, E.; Navarro, J.; Dudhia, J.

2013-04-01

This work uses a WRF numerical simulation from 1960 to 2005 performed at a high horizontal resolution (2 km) to analyze the surface wind variability over a complex terrain region located in northern Iberia. A shorter slice of this simulation has been used in a previous study to demonstrate the ability of the WRF model in reproducing the observed wind variability during the period 1992-2005. Learning from that validation exercise, the extended simulation is herein used to inspect the wind behavior where and when observations are not available and to determine the main synoptic mechanisms responsible for the surface wind variability. A principal component analysis was applied to the daily mean wind. Two principal modes of variation accumulate a large percentage of the wind variability (83.7%). The first mode reflects the channeling of the flow between the large mountain systems in northern Iberia modulated by the smaller topographic features of the region. The second mode further contributes to stress the differentiated wind behavior over the mountains and valleys. Both modes show significant contributions at the higher frequencies during the whole analyzed period, with different contributions at lower frequencies during the different decades. A strong relationship was found between these two modes and the zonal and meridional large scale pressure gradients over the area. This relationship is described in the context of the influence of standard circulation modes relevant in the European region like the North Atlantic Oscillation, the East Atlantic pattern, East Atlantic/Western Russia pattern, and the Scandinavian pattern.

Dominant modes of variability in large-scale Birkeland currents

NASA Astrophysics Data System (ADS)

Cousins, E. D. P.; Matsuo, Tomoko; Richmond, A. D.; Anderson, B. J.

2015-08-01

Properties of variability in large-scale Birkeland currents are investigated through empirical orthogonal function (EOF) analysis of 1 week of data from the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE). Mean distributions and dominant modes of variability are identified for both the Northern and Southern Hemispheres. Differences in the results from the two hemispheres are observed, which are attributed to seasonal differences in conductivity (the study period occurred near solstice). A universal mean and set of dominant modes of variability are obtained through combining the hemispheric results, and it is found that the mean and first three modes of variability (EOFs) account for 38% of the total observed squared magnetic perturbations (δB2) from both hemispheres. The mean distribution represents a standard Region 1/Region 2 (R1/R2) morphology of currents and EOF 1 captures the strengthening/weakening of the average distribution and is well correlated with the north-south component of the interplanetary magnetic field (IMF). EOF 2 captures a mixture of effects including the expansion/contraction and rotation of the (R1/R2) currents; this mode correlates only weakly with possible external driving parameters. EOF 3 captures changes in the morphology of the currents in the dayside cusp region and is well correlated with the dawn-dusk component of the IMF. The higher-order EOFs capture more complex, smaller-scale variations in the Birkeland currents and appear generally uncorrelated with external driving parameters. The results of the EOF analysis described here are used for describing error covariance in a data assimilation procedure utilizing AMPERE data, as described in a companion paper.

Climate change but not unemployment explains the changing suicidality in Thessaloniki Greece (2000-2012).

PubMed

Fountoulakis, Konstantinos N; Savopoulos, Christos; Zannis, Prodromos; Apostolopoulou, Martha; Fountoukidis, Ilias; Kakaletsis, Nikolaos; Kanellos, Ilias; Dimellis, Dimos; Hyphantis, Thomas; Tsikerdekis, Athanasios; Pompili, Maurizio; Hatzitolios, Apostolos I

2016-03-15

Recently there was a debate concerning the etiology behind attempts and completed suicides. The aim of the current study was to search for possible correlations between the rates of attempted and completed suicide and climate variables and regional unemployment per year in the county of Thessaloniki, Macedonia, northern Greece, for the years 2000-12. The regional rates of suicide and attempted suicide as well as regional unemployment were available from previous publications of the authors. The climate variables were calculated from the daily E-OBS gridded dataset which is based on observational data Only the male suicide rates correlate significantly with high mean annual temperature but not with unemployment. The multiple linear regression analysis results suggest that temperature is the only variable that determines male suicides and explains 51% of their variance. Unemployment fails to contribute significantly to the model. There seems to be a seasonal distribution for attempts with mean rates being higher for the period from May to October and the rates clearly correlate with temperature. The highest mean rates were observed during May and August and the lowest during December and February. Multiple linear regression analysis suggests that temperature also determines the female attempts rate although the explained variable is significant but very low (3-5%) Climate variables and specifically high temperature correlate both with suicide and attempted suicide rates but with a different way between males and females. The climate effect was stronger than the effect of unemployment. Copyright © 2016 Elsevier B.V. All rights reserved.

Regions of pollution with particulate matter in Poland

NASA Astrophysics Data System (ADS)

Rawicki, Kacper; Czarnecka, Małgorzata; Nidzgorska-Lencewicz, Jadwiga

2018-01-01

The study presents the temporal and spatial variability of particulate matter concentration in Poland in the calendar winter season (December-February). The basis for the study were the hourly and daily values of particulate matter PM10 concentration from the period 2005/06 - 2014/15, obtained from 33 air pollution monitoring stations. In Poland, the obligation to monitor the concentration of the finer fraction of particles smaller than 2.5µm in aerodynamic diameter was introduced only in 2010. Consequently, data on PM2.5 concentration refer to a shorter period, i.e. 2009/10 - 2014/15, and were obtained from 23 stations. Using the cluster analysis (k-means method), three regions of comparable variability of particulate matter concentration were delineated. The largest region, i.e. Region I, comprises the northern and eastern central area of Poland, and its southern boundary is along the line Gorzów Wlkp-Bydgoszcz-Konin-Łódź-Kielce-Lublin. Markedly smaller Region II is located to the south of Region I. By far the smallest area was designated to Region III which covers the south west area of Poland. The delineated regions show a marked variability in terms of mean concentration of both PM fractions in winter (PM10: region I - 33 µg·m-3, region II - 55 µg·m-3, region III - 83 µg·m-3; PM2,5: region I - 35 µg·m-3, region II - 50 µg·m-3, region III - 60 µg·m-3) and, in the case of PM10, the frequency of excessive daily limit value.

Diversity of Salmonella enterica serovar Typhi strains collected from india using variable number tandem repeat (VNTR)-PCR analysis.

PubMed

Sankar, Sathish; Kuppanan, Suresh; Nandagopal, Balaji; Sridharan, Gopalan

2013-08-01

Typhoid fever is endemic in India, and a seasonal increase of cases is observed annually. In spite of effective therapies and the availability of vaccines, morbidity is widespread owing to the circulation of multiple genetic variants, frequent migration of asymptomatic carriers, unhygienic food practices and the emergence of multidrug resistance and thus continues to be a major public health problem in developing countries, particularly in India. Classical methods of strain typing such as pulsed-field gel electrophoresis, ribotyping, random amplification of polymorphic DNA and amplified fragment length polymorphism are either laborious and technically complicated or less discriminatory. We investigated the molecular diversity of Indian strains of Salmonella enterica serovar Typhi (S. Typhi) isolated from humans from different parts of India to establish the molecular epidemiology of the organism using the variable number tandem repeat (VNTR)-PCR analysis. The electrophoretic band pattern was analysed using the GelCompar II software program. Of the 94 strains tested for three VNTRs loci, 75 VNTR genotypes were obtained. Of the three VNTRs tested in this study, VNTR1 was amplified in all the strains except one and found to be predominant. VNTR2 was amplified only in 57 strains with a Simpson diversity index of 0.93 indicating the high variability of this region within the strains. VNTR3 was amplified in 90 strains. The discriminatory power of this typing tool has been greatly enhanced by this VNTR2 region as the other two regions could not discriminate strains significantly. In our study, about 55 % of the strains amplified all three VNTR regions and 39 % of the strains lacked the VNTR2 region. Among the three VNTR regions tested, the majority of the strains produced similar banding pattern for any two regions grouped into a cluster. The strains grouped as a genotype were from the same geographical location. Strains collected from each geographical region were also highly heterogeneous. Such analysis is important to identify the genetic clones of the pathogen associated with sporadic infections and disease outbreak to identify the common source and implement public health measures.

Methane over South Asian region from GOSAT observations and ACTM simulations

NASA Astrophysics Data System (ADS)

Chandra, N.; Hayashida, S.; Patra, P. K.; Saeki, T.

2017-12-01

Methane (CH4) is one of the most important short-lived climate forcers. About 8% of global CH4 emissions are estimated from South Asia, covering less than 1% of global land. However, large uncertainty prevails in the sectorial CH4 emissions because of the lack of measurements. With the availability of total column methane (XCH4) observations by satellites, variability in XCH4 have been captured for most parts of the global land with major emissions, which were otherwise not covered by the surface observation network. However, direct use of satellite data for estimating emissions by inversion analysis is highly ambiguous, unlike the in-situ measurements near the source region, XCH4 values are controlled by surface emission and CH4 abundances at all altitudes. Therefore, understanding the role of transport along with the emissions on XCH4 is necessary before using the XCH4 data for the inversion analysis. We analyzed XCH4 observed by the GHGs Observation SATellite (GOSAT) and simulations over the South Asia region using the JAMSTEC's atmospheric chemistry-transport model (ACTM). The analysis suggests that distinct XCH4 seasonal cycle over northern and southern regions of India is governed by the both heterogeneous distributions of surface emissions and variability in partial CH4 column in the upper troposphere. Using ACTM simulations, we find that over most part of the northern Indian regions up to 40% of the seasonal peak during the southwest (SW) monsoon is attributed to the lower troposphere ( 1000-600 hPa), while 40% to uplifted high-CH4 air masses in the upper troposphere ( 600-200 hPa). In contrast, XCH4 seasonal enhancement over the semi-arid region, with extremely low CH4 emissions, is attributed mainly ( 70%) to partial XCH4 variability in the upper troposphere. The lower tropospheric region contributes up to 60% in the XCH4 seasonal enhancement over the southern peninsula and oceanic region. These differences arise from the complex atmospheric transport mechanisms, caused by the seasonally varying monsoon.

Compositional variability in Mediterranean archaeofaunas from Upper Paleolithic Southwest Europe

NASA Astrophysics Data System (ADS)

Jones, Emily Lena

2018-03-01

Recent meta-analyses of Upper Paleolithic Southwestern European archaeofaunas (Jones, 2015, 2016) have identified a consistent "Mediterranean" cluster from the Last Glacial Maximum through the early Holocene, suggesting similarities in environment and/or consistency in hunting strategy across this region through time despite radical changes in climate. However, while these archaeofaunas from this cluster all derive from sites located within today's Mediterranean bioclimatic region, many of them are from locations far from the Mediterranean Sea - Atlantic Portugal, the Spanish Meseta - which today differ significantly from each other in biotic composition. In this paper, I explore clustering (through cluster analysis and non-metric multidimensional scaling) within the Mediterranean archaeofaunal group. I test for the influence of sample size as well as the geographic variables of site elevation, latitude, and longitude on variability in the large mammal portions of archaeofaunal assemblages. ANOVA shows no relationship between cluster-defined groups and site elevation or longitude; instead, site latitude appears to be a primary contributor to patterning. However, the overall compositional similarity of the Mediterranean archaeofaunas in this dataset suggests more consistency than variability in Upper Paleolithic hunting strategy in this region.

Full-Length Characterization of Hepatitis C Virus Subtype 3a Reveals Novel Hypervariable Regions under Positive Selection during Acute Infection▿

PubMed Central

Humphreys, Isla; Fleming, Vicki; Fabris, Paolo; Parker, Joe; Schulenberg, Bodo; Brown, Anthony; Demetriou, Charis; Gaudieri, Silvana; Pfafferott, Katja; Lucas, Michaela; Collier, Jane; Huang, Kuan-Hsiang Gary; Pybus, Oliver G.; Klenerman, Paul; Barnes, Eleanor

2009-01-01

Hepatitis C virus subtype 3a is a highly prevalent and globally distributed strain that is often associated with infection via injection drug use. This subtype exhibits particular phenotypic characteristics. In spite of this, detailed genetic analysis of this subtype has rarely been performed. We performed full-length viral sequence analysis in 18 patients with chronic HCV subtype 3a infection and assessed genomic viral variability in comparison to other HCV subtypes. Two novel regions of intragenotypic hypervariability within the envelope protein E2, of HCV genotype 3a, were identified. We named these regions HVR495 and HVR575. They consisted of flanking conserved hydrophobic amino acids and central variable residues. A 5-amino-acid insertion found only in genotype 3a and a putative glycosylation site is contained within HVR575. Evolutionary analysis of E2 showed that positively selected sites within genotype 3a infection were largely restricted to HVR1, HVR495, and HVR575. Further analysis of clonal viral populations within single hosts showed that viral variation within HVR495 and HVR575 were subject to intrahost positive selecting forces. Longitudinal analysis of four patients with acute HCV subtype 3a infection sampled at multiple time points showed that positively selected mutations within HVR495 and HVR575 arose early during primary infection. HVR495 and HVR575 were not present in HCV subtypes 1a, 1b, 2a, or 6a. Some variability that was not subject to positive selection was present in subtype 4a HVR575. Further defining the functional significance of these regions may have important implications for genotype 3a E2 virus-receptor interactions and for vaccine studies that aim to induce cross-reactive anti-E2 antibodies. PMID:19740991

Photospheric Magnetic Field Properties of Flaring versus Flare-quiet Active Regions. II. Discriminant Analysis

NASA Astrophysics Data System (ADS)

Leka, K. D.; Barnes, G.

2003-10-01

We apply statistical tests based on discriminant analysis to the wide range of photospheric magnetic parameters described in a companion paper by Leka & Barnes, with the goal of identifying those properties that are important for the production of energetic events such as solar flares. The photospheric vector magnetic field data from the University of Hawai'i Imaging Vector Magnetograph are well sampled both temporally and spatially, and we include here data covering 24 flare-event and flare-quiet epochs taken from seven active regions. The mean value and rate of change of each magnetic parameter are treated as separate variables, thus evaluating both the parameter's state and its evolution, to determine which properties are associated with flaring. Considering single variables first, Hotelling's T2-tests show small statistical differences between flare-producing and flare-quiet epochs. Even pairs of variables considered simultaneously, which do show a statistical difference for a number of properties, have high error rates, implying a large degree of overlap of the samples. To better distinguish between flare-producing and flare-quiet populations, larger numbers of variables are simultaneously considered; lower error rates result, but no unique combination of variables is clearly the best discriminator. The sample size is too small to directly compare the predictive power of large numbers of variables simultaneously. Instead, we rank all possible four-variable permutations based on Hotelling's T2-test and look for the most frequently appearing variables in the best permutations, with the interpretation that they are most likely to be associated with flaring. These variables include an increasing kurtosis of the twist parameter and a larger standard deviation of the twist parameter, but a smaller standard deviation of the distribution of the horizontal shear angle and a horizontal field that has a smaller standard deviation but a larger kurtosis. To support the ``sorting all permutations'' method of selecting the most frequently occurring variables, we show that the results of a single 10-variable discriminant analysis are consistent with the ranking. We demonstrate that individually, the variables considered here have little ability to differentiate between flaring and flare-quiet populations, but with multivariable combinations, the populations may be distinguished.

Estimating flood magnitude and frequency at gaged and ungaged sites on streams in Alaska and conterminous basins in Canada, based on data through water year 2012

USGS Publications Warehouse

Curran, Janet H.; Barth, Nancy A.; Veilleux, Andrea G.; Ourso, Robert T.

2016-03-16

Estimates of the magnitude and frequency of floods are needed across Alaska for engineering design of transportation and water-conveyance structures, flood-insurance studies, flood-plain management, and other water-resource purposes. This report updates methods for estimating flood magnitude and frequency in Alaska and conterminous basins in Canada. Annual peak-flow data through water year 2012 were compiled from 387 streamgages on unregulated streams with at least 10 years of record. Flood-frequency estimates were computed for each streamgage using the Expected Moments Algorithm to fit a Pearson Type III distribution to the logarithms of annual peak flows. A multiple Grubbs-Beck test was used to identify potentially influential low floods in the time series of peak flows for censoring in the flood frequency analysis.For two new regional skew areas, flood-frequency estimates using station skew were computed for stations with at least 25 years of record for use in a Bayesian least-squares regression analysis to determine a regional skew value. The consideration of basin characteristics as explanatory variables for regional skew resulted in improvements in precision too small to warrant the additional model complexity, and a constant model was adopted. Regional Skew Area 1 in eastern-central Alaska had a regional skew of 0.54 and an average variance of prediction of 0.45, corresponding to an effective record length of 22 years. Regional Skew Area 2, encompassing coastal areas bordering the Gulf of Alaska, had a regional skew of 0.18 and an average variance of prediction of 0.12, corresponding to an effective record length of 59 years. Station flood-frequency estimates for study sites in regional skew areas were then recomputed using a weighted skew incorporating the station skew and regional skew. In a new regional skew exclusion area outside the regional skew areas, the density of long-record streamgages was too sparse for regional analysis and station skew was used for all estimates. Final station flood frequency estimates for all study streamgages are presented for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities.Regional multiple-regression analysis was used to produce equations for estimating flood frequency statistics from explanatory basin characteristics. Basin characteristics, including physical and climatic variables, were updated for all study streamgages using a geographical information system and geospatial source data. Screening for similar-sized nested basins eliminated hydrologically redundant sites, and screening for eligibility for analysis of explanatory variables eliminated regulated peaks, outburst peaks, and sites with indeterminate basin characteristics. An ordinary least‑squares regression used flood-frequency statistics and basin characteristics for 341 streamgages (284 in Alaska and 57 in Canada) to determine the most suitable combination of basin characteristics for a flood-frequency regression model and to explore regional grouping of streamgages for explaining variability in flood-frequency statistics across the study area. The most suitable model for explaining flood frequency used drainage area and mean annual precipitation as explanatory variables for the entire study area as a region. Final regression equations for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probability discharge in Alaska and conterminous basins in Canada were developed using a generalized least-squares regression. The average standard error of prediction for the regression equations for the various annual exceedance probabilities ranged from 69 to 82 percent, and the pseudo-coefficient of determination (pseudo-R2) ranged from 85 to 91 percent.The regional regression equations from this study were incorporated into the U.S. Geological Survey StreamStats program for a limited area of the State—the Cook Inlet Basin. StreamStats is a national web-based geographic information system application that facilitates retrieval of streamflow statistics and associated information. StreamStats retrieves published data for gaged sites and, for user-selected ungaged sites, delineates drainage areas from topographic and hydrographic data, computes basin characteristics, and computes flood frequency estimates using the regional regression equations.

Baseflow recession analysis in a large shale play: Climate variability and anthropogenic alterations mask effects of hydraulic fracturing

NASA Astrophysics Data System (ADS)

Arciniega-Esparza, Saúl; Breña-Naranjo, Jose Agustín; Hernández-Espriú, Antonio; Pedrozo-Acuña, Adrián; Scanlon, Bridget R.; Nicot, Jean Philippe; Young, Michael H.; Wolaver, Brad D.; Alcocer-Yamanaka, Victor Hugo

2017-10-01

Water resources development and landscape alteration exert marked impacts on water-cycle dynamics, including areas subjected to hydraulic fracturing (HF) for exploitation of unconventional oil and gas resources found in shale or tight sandstones. Here we apply a conceptual framework for linking baseflow analysis to changes in water demands from different sectors (e.g. oil/gas extraction, irrigation, and municipal consumption) and climatic variability in the semiarid Eagle Ford play in Texas, USA. We hypothesize that, in water-limited regions, baseflow (Qb) changes are partly due (along with climate variability) to groundwater abstraction. For a more realistic assessment, the analysis was conducted in two different sets of unregulated catchments, located outside and inside the Eagle Ford play. Three periods were considered in the analysis related to HF activities: pre-development (1980-2000), moderate (2001-2008) and intensive (2009-2015) periods. Results indicate that in the Eagle Ford play region, temporal changes in baseflow cannot be directly related to the increase in hydraulic fracturing. Instead, substantial baseflow declines during the intensive period of hydraulic fracturing represent the aggregated effects from the combination of: (1) a historical exceptional drought during 2011-2012; (2) increased groundwater-based irrigation; and (3) an intensive hydraulic fracturing activity.

The Signature of Southern Hemisphere Atmospheric Circulation Patterns in Antarctic Precipitation

PubMed Central

Thompson, David W. J.; van den Broeke, Michiel R.

2017-01-01

Abstract We provide the first comprehensive analysis of the relationships between large‐scale patterns of Southern Hemisphere climate variability and the detailed structure of Antarctic precipitation. We examine linkages between the high spatial resolution precipitation from a regional atmospheric model and four patterns of large‐scale Southern Hemisphere climate variability: the southern baroclinic annular mode, the southern annular mode, and the two Pacific‐South American teleconnection patterns. Variations in all four patterns influence the spatial configuration of precipitation over Antarctica, consistent with their signatures in high‐latitude meridional moisture fluxes. They impact not only the mean but also the incidence of extreme precipitation events. Current coupled‐climate models are able to reproduce all four patterns of atmospheric variability but struggle to correctly replicate their regional impacts on Antarctic climate. Thus, linking these patterns directly to Antarctic precipitation variability may allow a better estimate of future changes in precipitation than using model output alone. PMID:29398735

Morphological comparison of archaic Homo sapiens crania from China and Africa.

PubMed

Wu, X; Bräuer, G

1993-12-01

Regional features play a great role in the analysis of the differentiations of Homo erectus and Homo sapiens. However, this poses the question how widespread and variable these features are. In order to examine this with regard to the features commonly seen in China their occurrence and variability were determined in Chinese as well as in African crania of archaic and late Pleistocene/Holocene modern Homo sapiens. Furthermore, some features known from Africa were examined with regard to their occurrence and variability in China. Although the variability might change due to new finds, the present results for some features point to larger morphological spectra in the African than in the Chinese archaic Homo sapiens. It is furthermore remarkable that the early modern Chinese in many features show deviations from the pattern of archaic Homo sapiens of this region and exhibit broader spectra similar to those seen in African archaic and early modern Homo sapiens.

Ionospheric responses during equinox and solstice periods over Turkey

NASA Astrophysics Data System (ADS)

Karatay, Secil; Cinar, Ali; Arikan, Feza

2017-11-01

Ionospheric electron density is the determining variable for investigation of the spatial and temporal variations in the ionosphere. Total Electron Content (TEC) is the integral of the electron density along a ray path that indicates the total variability through the ionosphere. Global Positioning System (GPS) recordings can be utilized to estimate the TEC, thus GPS proves itself as a useful tool in monitoring the total variability of electron distribution within the ionosphere. This study focuses on the analysis of the variations of ionosphere over Turkey that can be grouped into anomalies during equinox and solstice periods using TEC estimates obtained by a regional GPS network. It is observed that noon time depletions in TEC distributions predominantly occur in winter for minimum Sun Spots Numbers (SSN) in the central regions of Turkey which also exhibit high variability due to midlatitude winter anomaly. TEC values and ionospheric variations at solstice periods demonstrate significant enhancements compared to those at equinox periods.

An assessment of precipitation and surface air temperature over China by regional climate models

NASA Astrophysics Data System (ADS)

Wang, Xueyuan; Tang, Jianping; Niu, Xiaorui; Wang, Shuyu

2016-12-01

An analysis of a 20-year summer time simulation of present-day climate (1989-2008) over China using four regional climate models coupled with different land surface models is carried out. The climatic means, interannual variability, linear trends, and extremes are examined, with focus on precipitation and near surface air temperature. The models are able to reproduce the basic features of the observed summer mean precipitation and temperature over China and the regional detail due to topographic forcing. Overall, the model performance is better for temperature than that of precipitation. The models reasonably grasp the major anomalies and standard deviations over China and the five subregions studied. The models generally reproduce the spatial pattern of high interannual variability over wet regions, and low variability over the dry regions. The models also capture well the variable temperature gradient increase to the north by latitude. Both the observed and simulated linear trend of precipitation shows a drying tendency over the Yangtze River Basin and wetting over South China. The models capture well the relatively small temperature trends in large areas of China. The models reasonably simulate the characteristics of extreme precipitation indices of heavy rain days and heavy precipitation fraction. Most of the models also performed well in capturing both the sign and magnitude of the daily maximum and minimum temperatures over China.

Broadband short term X-ray variability of the quasar PDS 456

NASA Astrophysics Data System (ADS)

Matzeu, G. A.; Reeves, J. N.; Nardini, E.; Braito, V.; Costa, M. T.; Tombesi, F.; Gofford, J.

2016-05-01

We present a detailed analysis of a recent 500 ks net exposure Suzaku observation, carried out in 2013, of the nearby (z=0.184) luminous (L_bol˜1047 erg s-1) quasar PDS 456 in which the X-ray flux was unusually low. The short term X-ray spectral variability has been interpreted in terms of variable absorption and/or intrinsic continuum changes. In the former scenario, the spectral variability is due to variable covering factors of two regions of partially covering absorbers. We find that these absorbers are characterised by an outflow velocity comparable to that of the highly ionised wind, i.e. ˜ 0.25 c, at the 99.9% (3.26σ) confidence level. This suggests that the partially absorbing clouds may be the denser clumpy part of the inhomogeneous wind. Following an obscuration event we obtained a direct estimate of the size of the X-ray emitting region, to be not larger than 20 R_g in PDS 456.

Water Vapor Tacers as Diagnostics of the Regional Atmospheric Hydrologic Cycle

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Schubert, Siegfried D.; Einaudi, Franco (Technical Monitor)

2000-01-01

Understanding of the local and remote sources of water vapor can be a valuable diagnostic in understanding the regional atmospheric hydrologic cycle, especially in North America where moisture transport and local evaporation are important sources of water for precipitation. In the present study, we have implemented passive tracers as prognostic variables to follow water vapor evaporated in predetermined regions until the water tracer precipitates. All evaporative sources of water are accounted for by tracers, and the water vapor variable provides the validation of the tracer water and the formulation of the sources and sinks. The Geostationary Operational Environmental Satellites General Circulation Model (GEOS GCM) is used to simulate several summer periods to determine the source regions of precipitation for the United States and India. Using this methodology, a detailed analysis of the recycling of water, interannual variability of the sources of water and links to the Great Plains low-level jet and North American monsoon will be presented. Potential uses in GCM sensitivity studies, predictability studies and data assimilation especially regarding the North American monsoon and GEWEX America Prediction Project (GAPP) will be discussed.

Advanced development of the boundary element method for elastic and inelastic thermal stress analysis. Ph.D. Thesis, 1987 Final Report

NASA Technical Reports Server (NTRS)

Henry, Donald P., Jr.

1991-01-01

The focus of this dissertation is on advanced development of the boundary element method for elastic and inelastic thermal stress analysis. New formulations for the treatment of body forces and nonlinear effects are derived. These formulations, which are based on particular integral theory, eliminate the need for volume integrals or extra surface integrals to account for these effects. The formulations are presented for axisymmetric, two and three dimensional analysis. Also in this dissertation, two dimensional and axisymmetric formulations for elastic and inelastic, inhomogeneous stress analysis are introduced. The derivatives account for inhomogeneities due to spatially dependent material parameters, and thermally induced inhomogeneities. The nonlinear formulation of the present work are based on an incremental initial stress approach. Two inelastic solutions algorithms are implemented: an iterative; and a variable stiffness type approach. The Von Mises yield criterion with variable hardening and the associated flow rules are adopted in these algorithms. All formulations are implemented in a general purpose, multi-region computer code with the capability of local definition of boundary conditions. Quadratic, isoparametric shape functions are used to model the geometry and field variables of the boundary (and domain) of the problem. The multi-region implementation permits a body to be modeled in substructured parts, thus dramatically reducing the cost of analysis. Furthermore, it allows a body consisting of regions of different (homogeneous) material to be studied. To test the program, results obtained for simple test cases are checked against their analytic solutions. Thereafter, a range of problems of practical interest are analyzed. In addition to displacement and traction loads, problems with body forces due to self-weight, centrifugal, and thermal loads are considered.

Impact of region contouring variability on image-based focal therapy evaluation

NASA Astrophysics Data System (ADS)

Gibson, Eli; Donaldson, Ian A.; Shah, Taimur T.; Hu, Yipeng; Ahmed, Hashim U.; Barratt, Dean C.

2016-03-01

Motivation: Focal therapy is an emerging low-morbidity treatment option for low-intermediate risk prostate cancer; however, challenges remain in accurately delivering treatment to specified targets and determining treatment success. Registered multi-parametric magnetic resonance imaging (MPMRI) acquired before and after treatment can support focal therapy evaluation and optimization; however, contouring variability, when defining the prostate, the clinical target volume (CTV) and the ablation region in images, reduces the precision of quantitative image-based focal therapy evaluation metrics. To inform the interpretation and clarify the limitations of such metrics, we investigated inter-observer contouring variability and its impact on four metrics. Methods: Pre-therapy and 2-week-post-therapy standard-of-care MPMRI were acquired from 5 focal cryotherapy patients. Two clinicians independently contoured, on each slice, the prostate (pre- and post-treatment) and the dominant index lesion CTV (pre-treatment) in the T2-weighted MRI, and the ablated region (post-treatment) in the dynamic-contrast- enhanced MRI. For each combination of clinician contours, post-treatment images were registered to pre-treatment images using a 3D biomechanical-model-based registration of prostate surfaces, and four metrics were computed: the proportion of the target tissue region that was ablated and the target:ablated region volume ratio for each of two targets (the CTV and an expanded planning target volume). Variance components analysis was used to measure the contribution of each type of contour to the variance in the therapy evaluation metrics. Conclusions: 14-23% of evaluation metric variance was attributable to contouring variability (including 6-12% from ablation region contouring); reducing this variability could improve the precision of focal therapy evaluation metrics.

Spatial and temporal analysis of drought variability at several time scales in Syria during 1961-2012

NASA Astrophysics Data System (ADS)

Mathbout, Shifa; Lopez-Bustins, Joan A.; Martin-Vide, Javier; Bech, Joan; Rodrigo, Fernando S.

2018-02-01

This paper analyses the observed spatiotemporal characteristics of drought phenomenon in Syria using the Standardised Precipitation Index (SPI) and the Standardised Precipitation Evapotranspiration Index (SPEI). Temporal variability of drought is calculated for various time scales (3, 6, 9, 12, and 24 months) for 20 weather stations over the 1961-2012 period. The spatial patterns of drought were identified by applying a Principal Component Analysis (PCA) to the SPI and SPEI values at different time scales. The results revealed three heterogeneous and spatially well-defined regions with different temporal evolution of droughts: 1) Northeastern (inland desert); 2) Southern (mountainous landscape); 3) Northwestern (Mediterranean coast). The evolutionary characteristics of drought during 1961-2012 were analysed including spatial and temporal variability of SPI and SPEI, the frequency distribution, and the drought duration. The results of the non-parametric Mann-Kendall test applied to the SPI and SPEI series indicate prevailing significant negative trends (drought) at all stations. Both drought indices have been correlated both on spatial and temporal scales and they are highly comparable, especially, over a 12 and 24 month accumulation period. We concluded that the temporal and spatial characteristics of the SPI and SPEI can be used for developing a drought intensity - areal extent - and frequency curve that assesses the variability of regional droughts in Syria. The analysis of both indices suggests that all three regions had a severe drought in the 1990s, which had never been observed before in the country. Furthermore, the 2007-2010 drought was the driest period in the instrumental record, happening just before the onset of the recent conflict in Syria.

Simulation of regional ground-water flow in the Cambrian-Ordovician aquifer system in the northern Midwest, United States: in Regional aquifer-system analysis

USGS Publications Warehouse

Mandle, R.J.; Kontis, A.L.

1992-01-01

Results of variable-density simulations indicate that the rate of ground-water movement is small in areas where ground water is highly mineralized. The rates and directions are controlled by the intrinsic permeability of the rock, freshwater head gradients, and gravitational force.

30,000 years of hydroclimatic variability in the coastal southwest United States: regional synthesis and forcings analysis.

NASA Astrophysics Data System (ADS)

Kirby, M. E.

2015-12-01

The coastal southwest United States is characterized by a winter dominated hydroclimate. Far from dependable, this region's supply of winter precipitation is highly variable and often characterized by hydrologic opposites - droughts and floods. Predicting future precipitation and hydrologic dynamics requires a paleoperspective. Here, we present an up-to-date synthesis of hydroclimatic variability over the past 30,000 years. A variety of terrestrial-based studies are examined and compared to understand patterns of regional hydroclimatic change. This comparison is extended into the San Joaquin Basin of California where future climate change will impact the region's agricultural stability and economy. Particularly interesting is the apparent role that Pacific sea surface temperatures (SSTs) play in modulating the region's hydroclimate over a variety of timescales. Are past periods of above average Pacific SSTs analogs for future global warming? If yes, the region might expect an increase in winter precipitation as SSTs rise in response to global warming. However, how this potential precipitation increase is manifest is unknown. For example, will the intensity of precipitation events increase and thus present increased flood hazards and diminished freshwater capture? Finally, we present evidence for changes in the source of winter precipitation over time as well as ecological responses to past hydrologic change.

Residential expansion as a continental threat to U.S. coastal ecosystems

Treesearch

J.G. Bartlett; D.M. Mageean; R.J. O' Connor

2000-01-01

Spatially extensive analysis of satellite, climate, and census data reveals human-environment interactions of regional or continental concern in the United States. A grid-based principal components analysis of Bureau of Census variables revealed two independent demographic phenomena, a-settlement reflecting traditional human settlement patterns and p-settlement...

An analysis of the determinants of maternal mortality in sub-Saharan Africa.

PubMed

Buor, Daniel; Bream, Kent

2004-10-01

To establish what population characteristics affect the high maternal mortality rate in the sub-Saharan Africa region and to propose possible solutions to reduce this rate. This study is a secondary analysis of existing data sources from the World Bank, the World Health Organization (WHO), as well as direct and indirect sources from UNAIDS, the United Nations, Demographic and Health Surveys (DHS), Macro International, and national statistical offices. Instead of looking at continentwide or individual nation models, it develops a regional model. Sociodemographic population variables are used as independent variables to predict the dependent variable, maternal mortality. Additionally, a new country-specific political stability independent variable is introduced into the model. Data from 28 sub-Saharan African countries are used. Bivariate correlations are used to establish associations among the variables, whereas cross-tabulations, using Kendall's tau-c values, and regression lines are used to establish impacts. In the sub-Saharan Africa region, births attended by skilled health personnel and life expectancy at birth strongly correlate with maternal mortality. Gross national product (GNP) per capita and health expenditure per capita also have strong association with maternal mortality. The availability of skilled delivery personnel, life expectancy, national economic wealth, and health expenditure per capita predict the maternal mortality rate of a country. Based on these findings, it is recommended that structural arrangements be made to train skilled health personnel to take care of maternal health problems. In view of the high cost of training physicians, middle-level health personnel may offer an affordable alternative to handle emergency obstetrical cases to address the shortage of physicians. In addition, the allocation of adequate resources to the health sector could improve maternal mortality. The economic wealth of a country and life expectancy at birth are less modifiable through short-term specific interventions. Additionally, it is recommended that country-specific interventions are needed to correct the problem of lack of critical data for analysis.

Physicochemical fingerprinting of thermal waters of Beira Interior region of Portugal.

PubMed

Araujo, A R T S; Sarraguça, M C; Ribeiro, M P; Coutinho, P

2017-06-01

Mineral natural waters and spas have been used for therapeutic purposes for centuries, with Portugal being a very rich country in thermal waters and spas that are mainly distributed by northern and central regions where Beira Interior region is located. The use of thermal waters for therapeutic purposes has always been aroused a continuous interest, being dependent on physicochemical fingerprinting of this type of waters the indication for a treatment in a specific pathological condition. In the present work, besides a literature review about the physicochemical composition of the thermal waters of the Beira Interior region and its therapeutic indications, it was carried out an exhaustive multivariate analysis-principal component analysis and cluster analysis-to assess the correlation between different physicochemical parameters and the therapeutic indications claims described for these spas and thermal waters. These statistical methods used for data analysis enables classification of thermal waters compositions into different groups, regarding to the different variable selected, making possible an interpretation of variables affecting water compositions. Actually, Monfortinho and Longroiva are clearly quite different of the others, and Cró and Fonte Santa de Almeida appear together in all analysis, suggesting a strong resemblance between these waters. Thereafter, the results obtained allow us to demonstrate the role of major components of the studied thermal waters on a particular therapeutic purpose/indication and hence based on compositional and physicochemical properties partially explain their therapeutic qualities and beneficial effects on human health. This classification agreed with the results obtained for the therapeutic indications approved by the Portuguese National Health Authority and proved to be a valuable tool for the regional typology of mineral medicinal waters, constituting an important guide of the therapeutic armamentarium for well and specific-oriented pathological disturbs.

Analysis of whole genome sequences of 16 strains of rubella virus from the United States, 1961-2009.

PubMed

Abernathy, Emily; Chen, Min-hsin; Bera, Jayati; Shrivastava, Susmita; Kirkness, Ewen; Zheng, Qi; Bellini, William; Icenogle, Joseph

2013-01-25

Rubella virus is the causative agent of rubella, a mild rash illness, and a potent teratogenic agent when contracted by a pregnant woman. Global rubella control programs target the reduction and elimination of congenital rubella syndrome. Phylogenetic analysis of partial sequences of rubella viruses has contributed to virus surveillance efforts and played an important role in demonstrating that indigenous rubella viruses have been eliminated in the United States. Sixteen wild-type rubella viruses were chosen for whole genome sequencing. All 16 viruses were collected in the United States from 1961 to 2009 and are from 8 of the 13 known rubella genotypes. Phylogenetic analysis of 30 whole genome sequences produced a maximum likelihood tree giving high bootstrap values for all genotypes except provisional genotype 1a. Comparison of the 16 new complete sequences and 14 previously sequenced wild-type viruses found regions with clusters of variable amino acids. The 5' 250 nucleotides of the genome are more conserved than any other part of the genome. Genotype specific deletions in the untranslated region between the non-structural and structural open reading frames were observed for genotypes 2B and genotype 1G. No evidence was seen for recombination events among the 30 viruses. The analysis presented here is consistent with previous reports on the genetic characterization of rubella virus genomes. Conserved and variable regions were identified and additional evidence for genotype specific nucleotide deletions in the intergenic region was found. Phylogenetic analysis confirmed genotype groupings originally based on structural protein coding region sequences, which provides support for the WHO nomenclature for genetic characterization of wild-type rubella viruses.

Nuclear and mitochondrial rDNA variability in Crinipellis perniciosa from different geographic origins and hosts.

PubMed

de Arruda, Maricília C C; Ferreira, Marisa A S V; Miller, Robert N G; Resende, Mário Lúcio V; Felipe, Maria Sueli S

2003-01-01

Genetic variability in Crinipellis perniciosa, the causal organism of witches' broom disease in Theobroma cacao, was determined in strains originating from T. cacao and other susceptible host species Heteropterys acutifolia and Solanum lycocarpum in Brazil, in order to clarify host specificity and geographical variability. RFLP analysis of the ribosomal DNA ITS regions (rDNA ITS), and the mitochondrial DNA small subunit ribosomal DNA gene (mtDNA SSU rDNA) did not reveal any genetic variability in 120 tested strains, possibly serving only as species level markers. Genetic variability was observed in the ribosomal DNA IGS spacer region, in terms of IGS size, RFLPs and sequence data. Phylogenetic analyses (using CLUSTAL W, PHYLIP and TREEVIEW) indicated considerable differences between C. perniciosa strains from T. cacao and those from H. acutifolia (85-86%) and S. lycocarpum (95-96%). Sequence differences also indicated that C. perniciosa from T. cacao in Bahia is less variable (98%) when compared to the pathogen on T. cacao in Amazonas (97-98%), perhaps reflecting a recent introduction to T. cacao in Bahia.

Evaluating the spatiotemporal variations of water budget across China over 1951-2006 using IBIS model

USGS Publications Warehouse

Zhu, Q.; Jiang, H.; Liu, J.; Wei, X.; Peng, C.; Fang, X.; Liu, S.; Zhou, G.; Yu, S.; Ju, W.

2010-01-01

The Integrated Biosphere Simulator is used to evaluate the spatial and temporal patterns of the crucial hydrological variables [run-off and actual evapotranspiration (AET)] of the water balance across China for the period 1951–2006 including a precipitation analysis. Results suggest three major findings. First, simulated run-off captured 85% of the spatial variability and 80% of the temporal variability for 85 hydrological gauges across China. The mean relative errors were within 20% for 66% of the studied stations and within 30% for 86% of the stations. The Nash–Sutcliffe coefficients indicated that the quantity pattern of run-off was also captured acceptably except for some watersheds in southwestern and northwestern China. The possible reasons for underestimation of run-off in the Tibetan plateau include underestimation of precipitation and uncertainties in other meteorological data due to complex topography, and simplified representations of the soil depth attribute and snow processes in the model. Second, simulated AET matched reasonably with estimated values calculated as the residual of precipitation and run-off for watersheds controlled by the hydrological gauges. Finally, trend analysis based on the Mann–Kendall method indicated that significant increasing and decreasing patterns in precipitation appeared in the northwest part of China and the Yellow River region, respectively. Significant increasing and decreasing trends in AET were detected in the Southwest region and the Yangtze River region, respectively. In addition, the Southwest region, northern China (including the Heilongjiang, Liaohe, and Haihe Basins), and the Yellow River Basin showed significant decreasing trends in run-off, and the Zhemin hydrological region showed a significant increasing trend.

Simulated atmospheric response to Gulf Stream variability

NASA Astrophysics Data System (ADS)

Hand, Ralf; Keenlyside, Noel; Omrani, Nour-Eddine; Latif, Mojib; Minobe, Shoshiro

2010-05-01

Though the ocean variability has a distinct low-frequent component on interannual to interdecadal timescales, a better understanding of the main features of air-sea interaction in the extratropical ocean might increase the predictive skill of climate models significantly. An insufficiently understood region in this context are the sharp SST-fronts connected to western boundary currents, which interact with the overlaying atmosphere by forcing low-level winds and evaporation. Recent studies show, that this response extends beyond the marine boundary layer and so might influence also the large-scale atmospheric circulation. In this work a 5 member ensemble of model runs from the AGCM ECHAM5 was analyzed focussing on the atmospheric response to the Gulf Stream. The analyzed experiment covered a time period of 138 years from 1870 to 2007 and was forced by observed SSTs and sea-ice concentration from the HadISST dataset. The experiment was performed at T106 horizontal resolution (~100km) and with 31 vertical levels up to 1 hPa. Simulated seasonal mean circulation indicate a convective response of the atmosphere in the Gulf Stream region similar to observations, with distinct low-level wind convergence, strong upward motion, and low-pressure over the warm SST flank of the Gulf Stream. An analysis of variance (ANOVA) suggests, that up to 25-30% of the variability of the summer precipitation in the Gulf Stream region are connected to the boundary conditions. The link between oceanic and atmospheric variability on seasonal to interannual timescales is investigated with composite and linear regression analysis. Results indicate that increased (decreased) precipitation is associated with stronger (weaker) low-level wind convergence, enhanced (reduced) upward motion, low (high) pressure, and warm (cold) SST anomalies in the region of the Gulf Stream. Currently sensitivity experiments with the same AGCM configuration are in progress.

Genome variability of foot-and-mouth disease virus during the short period of the 2010 epidemic in Japan.

PubMed

Nishi, Tatsuya; Yamada, Manabu; Fukai, Katsuhiko; Shimada, Nobuaki; Morioka, Kazuki; Yoshida, Kazuo; Sakamoto, Kenichi; Kanno, Toru; Yamakawa, Makoto

2017-02-01

Foot-and-mouth disease virus (FMDV) is highly contagious and has a high mutation rate, leading to extensive genetic variation. To investigate how FMDV genetically evolves over a short period of an epidemic after initial introduction into an FMD-free area, whole L-fragment sequences of 104 FMDVs isolated from the 2010 epidemic in Japan, which continued for less than three months were determined and phylogenetically and comparatively analyzed. Phylogenetic analysis of whole L-fragment sequences showed that these isolates were classified into a single group, indicating that FMDV was introduced into Japan in the epidemic via a single introduction. Nucleotide sequences of 104 virus isolates showed more than 99.56% pairwise identity rates without any genetic deletion or insertion, although no sequences were completely identical with each other. These results indicate that genetic substitutions of FMDV occurred gradually and constantly during the epidemic and generation of an extensive mutant virus could have been prevented by rapid eradication strategy. From comparative analysis of variability of each FMDV protein coding region, VP4 and 2C regions showed the highest average identity rates and invariant rates, and were confirmed as highly conserved. In contrast, the protein coding regions VP2 and VP1 were confirmed to be highly variable regions with the lowest average identity rates and invariant rates, respectively. Our data demonstrate the importance of rapid eradication strategy in an FMD epidemic and provide valuable information on the genome variability of FMDV during the short period of an epidemic. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Health inequalities in Germany: do regional-level variables explain differentials in cardiovascular risk?

PubMed Central

Breckenkamp, Juergen; Mielck, Andreas; Razum, Oliver

2007-01-01

Background Socioeconomic status is a predictor not only of mortality, but also of cardiovascular risk and morbidity. An ongoing debate in the field of social inequalities and health focuses on two questions: 1) Is individual health status associated with individual income as well as with income inequality at the aggregate (e. g. regional) level? 2) If there is such an association, does it operate via a psychosocial pathway (e.g. stress) or via a "neo-materialistic" pathway (e.g. systematic under-investment in societal infrastructures)? For the first time in Germany, we here investigate the association between cardiovascular health status and income inequality at the area level, controlling for individual socio-economic status. Methods Individual-level explanatory variables (age, socio-economic status) and outcome data (body mass index, blood pressure, cholesterol level) as well as the regional-level variable (proportion of relative poverty) were taken from the baseline survey of the German Cardiovascular Prevention Study, a cross-sectional, community-based, multi-center intervention study, comprising six socio-economically diverse intervention regions, each with about 1800 participants aged 25–69 years. Multilevel modeling was used to examine the effects of individual and regional level variables. Results Regional effects are small compared to individual effects for all risk factors analyzed. Most of the total variance is explained at the individual level. Only for diastolic blood pressure in men and for cholesterol in both men and women is a statistically significant effect visible at the regional level. Conclusion Our analysis does not support the assumption that in Germany cardiovascular risk factors were to a large extent associated with income inequality at regional level. PMID:17603918

Variability among the Most Rapidly Evolving Plastid Genomic Regions is Lineage-Specific: Implications of Pairwise Genome Comparisons in Pyrus (Rosaceae) and Other Angiosperms for Marker Choice

PubMed Central

Ter-Voskanyan, Hasmik; Allgaier, Martin; Borsch, Thomas

2014-01-01

Plastid genomes exhibit different levels of variability in their sequences, depending on the respective kinds of genomic regions. Genes are usually more conserved while noncoding introns and spacers evolve at a faster pace. While a set of about thirty maximum variable noncoding genomic regions has been suggested to provide universally promising phylogenetic markers throughout angiosperms, applications often require several regions to be sequenced for many individuals. Our project aims to illuminate evolutionary relationships and species-limits in the genus Pyrus (Rosaceae)—a typical case with very low genetic distances between taxa. In this study, we have sequenced the plastid genome of Pyrus spinosa and aligned it to the already available P. pyrifolia sequence. The overall p-distance of the two Pyrus genomes was 0.00145. The intergenic spacers between ndhC–trnV, trnR–atpA, ndhF–rpl32, psbM–trnD, and trnQ–rps16 were the most variable regions, also comprising the highest total numbers of substitutions, indels and inversions (potentially informative characters). Our comparative analysis of further plastid genome pairs with similar low p-distances from Oenothera (representing another rosid), Olea (asterids) and Cymbidium (monocots) showed in each case a different ranking of genomic regions in terms of variability and potentially informative characters. Only two intergenic spacers (ndhF–rpl32 and trnK–rps16) were consistently found among the 30 top-ranked regions. We have mapped the occurrence of substitutions and microstructural mutations in the four genome pairs. High AT content in specific sequence elements seems to foster frequent mutations. We conclude that the variability among the fastest evolving plastid genomic regions is lineage-specific and thus cannot be precisely predicted across angiosperms. The often lineage-specific occurrence of stem-loop elements in the sequences of introns and spacers also governs lineage-specific mutations. Sequencing whole plastid genomes to find markers for evolutionary analyses is therefore particularly useful when overall genetic distances are low. PMID:25405773

Regional Variation in Antenatal Corticosteroid Use: A Network-Level Quality Improvement Study

PubMed Central

Goldstein, B.A.; Tamaresis, J.; Kan, P.; Lee, H.C.

2015-01-01

BACKGROUND AND OBJECTIVES: Examination of regional care patterns in antenatal corticosteroid use (ACU) rates may be salient for the development of targeted interventions. Our objective was to assess network-level variation using California perinatal care regions as a proxy. We hypothesized that (1) significant variation in ACU exists within and between California perinatal care regions, and (2) lower performing regions exhibit greater NICU-level variability in ACU than higher performing regions. METHODS: We undertook cross-sectional analysis of 33 610 very low birth weight infants cared for at 120 hospitals in 11 California perinatal care regions from 2005 to 2011. We computed risk-adjusted median ACU rates and interquartile ranges (IQR) for each perinatal care region. The degree of variation was assessed using hierarchical multivariate regression analysis with NICU as a random effect and region as a fixed effect. RESULTS: From 2005 to 2011, mean ACU rates across California increased from 82% to 87.9%. Regional median (IQR) ACU rates ranged from 68.4% (24.3) to 92.9% (4.8). We found significant variation in ACU rates among regions (P < .0001). Compared with Level IV NICUs, care in a lower level of care was a strongly significant predictor of lower odds of receiving antenatal corticosteroids in a multilevel model (Level III, 0.65 [0.45–0.95]; Level II, 0.39 [0.24–0.64]; P < .001). Regions with lower performance in ACU exhibited greater variability in performance. CONCLUSIONS: We found significant variation in ACU rates among California perinatal regions. Regional quality improvement approaches may offer a new avenue to spread best practice. PMID:25601974

Medieval Warm Period Archives Preserved in Limpet Shells (Patella Vulgata) From Viking Deposits, United Kingdom

NASA Astrophysics Data System (ADS)

Mobilia, M.; Surge, D.

2008-12-01

The Medieval Warm Period (700-1100 YBP) represents a recent period of warm climate, and as such provides a powerful comparison to today's continuing warming trend. However, the spatial and temporal variability inherent in the Medieval Warm Period (MWP) makes it difficult to differentiate between global climate trends and regional variability. The continued study of this period will allow for the better understanding of temperature variability, both regional and global, during this climate interval. Our study is located in the Orkney Islands, Scotland, which is a critical area to understand climate dynamics. The North Atlantic Oscillation and Gulf Stream heavily influence climate in this region, and the study of climate intervals during the MWP will improve our understanding of the behavior of these climate mechanisms during this interval. Furthermore, the vast majority of the climate archive has been derived from either deep marine or arctic environments. Studying a coastal environment will offer valuable insight into the behavior of maritime climate during the MWP. Estimated seasonal sea surface temperature data were derived through isotopic analysis of limpet shells (Patella vulgata). Analysis of modern shells confirms that growth temperature tracks seasonal variation in ambient water temperature. Preliminary data from MWP shells record a seasonal temperature range comparable to that observed in the modern temperature data. We will extend the range of temperature data from the 10th through 14th centuries to advance our knowledge of seasonal temperature variability during the late Holocene.

Seasonal, interannual and long-term variabilities and tendencies of water vapour in the upper stratosphere and mesospheric region over tropics (30°N-30°S)

NASA Astrophysics Data System (ADS)

Nath, Oindrila; Sridharan, S.; Naidu, C. V.

2018-01-01

Tropical water vapour volume mixing ratio (WVMR) data for October 2004-September 2015 obtained from the Microwave Limb Sounder are used to study its long-term variabilities and tendencies in the height region 12.1-0.002 hPa. Above 0.01 hPa, the WVMR shows minimum March-May and September-November (∼0.7-0.8 ppmv) and maximum during June-August. It shows a large interannual variability at 31-64 km. The results from multivariate regression analysis show an increasing trend with maximum value of ∼0.045 ppmv/yr at 1.21-0.41 hPa. It shows a significant negative solar cycle response at mesospheric heights.

Yield of bedrock wells in the Nashoba terrane, central and eastern Massachusetts

USGS Publications Warehouse

DeSimone, Leslie A.; Barbaro, Jeffrey R.

2012-01-01

The yield of bedrock wells in the fractured-bedrock aquifers of the Nashoba terrane and surrounding area, central and eastern Massachusetts, was investigated with analyses of existing data. Reported well yield was compiled for 7,287 wells from Massachusetts Department of Environmental Protection and U.S. Geological Survey databases. Yield of these wells ranged from 0.04 to 625 gallons per minute. In a comparison with data from 103 supply wells, yield and specific capacity from aquifer tests were well correlated, indicating that reported well yield was a reasonable measure of aquifer characteristics in the study area. Statistically significant relations were determined between well yield and a number of cultural and hydrogeologic factors. Cultural variables included intended water use, well depth, year of construction, and method of yield measurement. Bedrock geology, topography, surficial geology, and proximity to surface waters were statistically significant hydrogeologic factors. Yield of wells was higher in areas of granites, mafic intrusive rocks, and amphibolites than in areas of schists and gneisses or pelitic rocks; higher in valleys and low-slope areas than on hills, ridges, or high slopes; higher in areas overlain by stratified glacial deposits than in areas overlain by till; and higher in close proximity to streams, ponds, and wetlands than at greater distances from these surface-water features. Proximity to mapped faults and to lineaments from aerial photographs also were related to well yield by some measures in three quadrangles in the study area. Although the statistical significance of these relations was high, their predictive power was low, and these relations explained little of the variability in the well-yield data. Similar results were determined from a multivariate regression analysis. Multivariate regression models for the Nashoba terrane and for a three-quadrangle subarea included, as significant variables, many of the cultural and hydrogeologic factors that were individually related to well yield, in ways that are consistent with conceptual understanding of their effects, but the models explained only 21 percent (regional model for the entire terrane) and 30 percent (quadrangle model) of the overall variance in yield. Moreover, most of the explained variance was due to well characteristics rather than hydrogeologic factors. Hydrogeologic factors such as topography and geology are likely important. However, the overall high variability in the well-yield data, which results from the high variability in aquifer hydraulic properties as well as from limitations of the dataset, would make it difficult to use hydrogeologic factors to predict well yield in the study area. Geostatistical analysis (variograms), on the other hand, indicated that, although highly variable, the well-yield data are spatially correlated. The spatial continuity appears greater in the northeast-southwest direction and less in the southeast-northwest direction, directions that are parallel and perpendicular, respectively, to the regional geologic structural trends. Geostatistical analysis (kriging), used to estimate yield values throughout the study area, identified regional-scale areas of higher and lower yield that may be related to regional structural features—in particular, to a northeast-southwest trending regional fault zone within the Nashoba terrane. It also would be difficult to use kriging to predict yield at specific locations, however, because of the spatial variability in yield, particularly at small scales. The regional-scale analyses in this study, both with hydrogeologic variables and geostatistics, provide a context for understanding the variability in well yield, rather a basis for precise predictions, and site-specific information would be needed to understand local conditions.

Reconstructing Late Holocene North Atlantic atmospheric circulation changes using functional paleoclimate networks

NASA Astrophysics Data System (ADS)

Franke, Jasper G.; Werner, Johannes P.; Donner, Reik V.

2017-11-01

Obtaining reliable reconstructions of long-term atmospheric circulation changes in the North Atlantic region presents a persistent challenge to contemporary paleoclimate research, which has been addressed by a multitude of recent studies. In order to contribute a novel methodological aspect to this active field, we apply here evolving functional network analysis, a recently developed tool for studying temporal changes of the spatial co-variability structure of the Earth's climate system, to a set of Late Holocene paleoclimate proxy records covering the last two millennia. The emerging patterns obtained by our analysis are related to long-term changes in the dominant mode of atmospheric circulation in the region, the North Atlantic Oscillation (NAO). By comparing the time-dependent inter-regional linkage structures of the obtained functional paleoclimate network representations to a recent multi-centennial NAO reconstruction, we identify co-variability between southern Greenland, Svalbard, and Fennoscandia as being indicative of a positive NAO phase, while connections from Greenland and Fennoscandia to central Europe are more pronounced during negative NAO phases. By drawing upon this correspondence, we use some key parameters of the evolving network structure to obtain a qualitative reconstruction of the NAO long-term variability over the entire Common Era (last 2000 years) using a linear regression model trained upon the existing shorter reconstruction.

Mapping cortical brain asymmetry in 17,141 healthy individuals worldwide via the ENIGMA Consortium.

PubMed

Kong, Xiang-Zhen; Mathias, Samuel R; Guadalupe, Tulio; Glahn, David C; Franke, Barbara; Crivello, Fabrice; Tzourio-Mazoyer, Nathalie; Fisher, Simon E; Thompson, Paul M; Francks, Clyde

2018-05-29

Hemispheric asymmetry is a cardinal feature of human brain organization. Altered brain asymmetry has also been linked to some cognitive and neuropsychiatric disorders. Here, the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium presents the largest-ever analysis of cerebral cortical asymmetry and its variability across individuals. Cortical thickness and surface area were assessed in MRI scans of 17,141 healthy individuals from 99 datasets worldwide. Results revealed widespread asymmetries at both hemispheric and regional levels, with a generally thicker cortex but smaller surface area in the left hemisphere relative to the right. Regionally, asymmetries of cortical thickness and/or surface area were found in the inferior frontal gyrus, transverse temporal gyrus, parahippocampal gyrus, and entorhinal cortex. These regions are involved in lateralized functions, including language and visuospatial processing. In addition to population-level asymmetries, variability in brain asymmetry was related to sex, age, and intracranial volume. Interestingly, we did not find significant associations between asymmetries and handedness. Finally, with two independent pedigree datasets ( n = 1,443 and 1,113, respectively), we found several asymmetries showing significant, replicable heritability. The structural asymmetries identified and their variabilities and heritability provide a reference resource for future studies on the genetic basis of brain asymmetry and altered laterality in cognitive, neurological, and psychiatric disorders.

Regional investigations of soil and overburden analysis and plant uptake of metals

USGS Publications Warehouse

Gough, L.P.

1984-01-01

Regional studies on the bioavailability of metals at native and disturbed sites were conducted over the past seven years by the USGS. The work was concentrated in the Fort Union, Powder River, and Green River coal resource regions where measures of extractable metals in soils were found to have limited use in predicting metal levels in plants. Correlations between Cu, Fe, and Zn in plants and extractable (DTPA, EDTA, and oxalate) or total levels in native A- and C-horizons of soil were occasionally significant. A simple linear model is generally not adequate, however, in estimating element uptake by plants. Prediction capabilities were improved when a number of soil chemical and physical parameters were included as independent variables in a stepwise linear multiple regression analysis; however, never more than 54% of the total variability in the data was explained by the equations for these metals. Soil pH was the most important variable relating soil chemistry to plant chemistry. This relation was always positive and apparently a response to soil levels of metal carbonates and not Fe and Mn oxides. Studies that compared the metal uptake by rehabilitation species to extractable (DTPA) metal levels in mice soils produced similar results. ?? 1984 Science and Technology Letters.

Climatic variability of river outflow in the Pantanal region and the influence of sea surface temperature

NASA Astrophysics Data System (ADS)

Silva, Carlos Batista; Silva, Maria Elisa Siqueira; Ambrizzi, Tércio

2017-07-01

This paper investigates possible linear relationships between climate, hydrology, and oceanic surface variability in the Pantanal region (in South America's central area), over interannual and interdecadal time ranges. In order to verify the mentioned relations, lagged correlation analysis and linear adjustment between river discharge at the Pantanal region and sea surface temperature were used. Composite analysis for atmospheric fields, air humidity flux divergence, and atmospheric circulation at low and high levels, for the period between 1970 and 2003, was analyzed. Results suggest that the river discharge in the Pantanal region is linearly associated with interdecadal and interannual oscillations in the Pacific and Atlantic oceans, making them good predictors to continental hydrological variables. Considering oceanic areas, 51 % of the annual discharge in the Pantanal region can be linearly explained by mean sea surface temperature (SST) in the Subtropical North Pacific, Tropical North Pacific, Extratropical South Pacific, and Extratropical North Atlantic over the period. Considering a forecast approach in seasonal scale, 66 % of the monthly discharge variance in Pantanal, 3 months ahead of SST, is explained by the oceanic variables, providing accuracy around 65 %. Annual discharge values in the Pantanal region are strongly related to the Pacific Decadal Oscillation (PDO) variability (with 52 % of linear correlation), making it possible to consider an interdecadal variability and a consequent subdivision of the whole period in three parts: 1st (1970-1977), 2nd (1978-1996), and 3rd (1997-2003) subperiods. The three subperiods coincide with distinct PDO phases: negative, positive, and negative, respectively. Convergence of humidity flux at low levels and the circulation pattern at high levels help to explain the drier and wetter subperiods. During the wetter 2nd subperiod, the air humidity convergence at low levels is much more evident than during the other two drier subperiods, which mostly show air humidity divergence. While the drier periods are particularly characterized by the strengthening of northerly wind over the center of South America, including the Pantanal region, the wetter period is characterized by its weakening. The circulation pattern at 850 hPa levels during the drier subperiods shows anticyclonic anomalies centered over east central South America. Also, the drier subperiods (1st and 3rd) are characterized by negative stream function anomalies over southeastern South America and adjacent South Atlantic, and the wetter subperiod is characterized by positive stream function anomalies. In the three subperiods, one can see mean atmospheric patterns associated with Rossby wave propagation coming from the South Pacific basin—similar to the Pacific South America pattern, but with reverse signals between the wetter and the drier periods. This result suggests a possible relationship between climatic patterns over southeastern South America regions and the Pacific conditions in a decadal scale.

Relative spatial soil geochemical variability along two transects across the United States and Canada

USGS Publications Warehouse

Garrett, Robert G.

2009-01-01

The patterns of relative variability differ by transect and horizon. The N–S transect A-horizon soils show significant between-40-km scale variability for 29 elements, with only 4 elements (Ca, Mg, Pb and Sr) showing in excess of 50% of their variability at the within-40-km and ‘at-site’ scales. In contrast, the C-horizon data demonstrate significant between-40-km scale variability for 26 elements, with 21 having in excess of 50% of their variability at the within-40-km and ‘at-site’ scales. In 36 instances, the ‘at-site’ variability is statistically significant in terms of the sample preparation and analysis variability. It is postulated that this contrast between the A- and C- horizons along the N–S transect, that is dominated by agricultural land uses, is due to the local homogenization of Ap-horizon soils by tillage reducing the ‘at-site’ variability. The spatial variability is distributed similarly between scales for the A- and C-horizon soils of the E–W transect. For all elements, there is significant variability at the within-40-km scale. Notwithstanding this, there is significant between-40-km variability for 28 and 20 of the elements in the A- and C-horizon data, respectively. The differences between the two transects are attributed to (1) geology, the N–S transect runs generally parallel to regional strikes, whereas the E–W transect runs across regional structures and lithologies; and (2) land use, with agricultural tillage dominating along the N–S transect. The spatial analysis of the transect data indicates that continental-scale maps demonstrating statistically significant patterns of geochemical variability may be prepared for many elements from data on soil samples collected on a 40 x 40 km grid or similar sampling designs resulting in a sample density of 1 site per 1600 km2.

Investigating the role of the land surface in explaining the interannual variation of the net radiation balance over the Western Sahara and sub-Sahara

NASA Technical Reports Server (NTRS)

Smith, Eric A.; Nicholson, Sharon

1987-01-01

The status of the data sets is discussed. Progress was made in both data analysis and modeling areas. The atmospheric and land surface contributions to the net radiation budget over the Sahara-Sahel region is being decoupled. The interannual variability of these two processes was investigated and this variability related to seasonal rainfall fluctuations. A modified Barnes objective analysis scheme was developed which uses an eliptic scan pattern and a 3-pass iteration of the difference fields.

Summer weather characteristics and periodicity observed over the period 1888-2013 in the region of Belgrade, Serbia

NASA Astrophysics Data System (ADS)

Vujović, Dragana; Todorović, Nedeljko; Paskota, Mira

2018-04-01

With the goal of finding summer climate patterns in the region of Belgrade (Serbia) over the period 1888-2013, different techniques of multivariate statistical analysis were used in order to analyze the simultaneous changes of a number of climatologic parameters. An increasing trend of the mean daily minimum temperature was detected. In the recent decades (1960-2013), this increase was much more pronounced. The number of days with the daily minimum temperature greater or equal to 20 °C also increased significantly. Precipitation had no statistically significant trend. Spectral analysis showed a repetitive nature of the climatologic parameters which had periods that roughly can be classified into three groups, with the durations of the following: (1) 6 to 7 years, (2) 10 to 18 years, and (3) 21, 31, and 41 years. The temperature variables mainly had one period of repetitiveness of 5 to 7 years. Among other variables, the correlations of regional fluctuations of the temperature and precipitation and atmospheric circulation indices were analyzed. The North Atlantic oscillation index had the same periodicity as that of the precipitation, and it was not correlated to the temperature variables. Atlantic multidecadal oscillation index correlated well to the summer mean daily minimum and summer mean temperatures. The underlying structure of the data was analyzed by principal component analysis, which detected the following four easily interpreted dimensions: More sunshine-Higher temperature, Precipitation, Extreme heats, and Changeable summer.

Modelling social vulnerability in sub-Saharan West Africa using a geographical information system

PubMed Central

Arokoyu, Samuel B.

2015-01-01

In recent times, disasters and risk management have gained significant attention, especially with increasing awareness of the risks and increasing impact of natural and other hazards especially in the developing world. Vulnerability, the potential for loss of life or property from disaster, has biophysical or social dimensions. Social vulnerability relates to societal attributes which has negative impacts on disaster outcomes. This study sought to develop a spatially explicit index of social vulnerability, thus addressing the dearth of research in this area in sub-Saharan Africa. Nineteen variables were identified covering various aspects. Descriptive analysis of these variables revealed high heterogeneity across the South West region of Nigeria for both the state and the local government areas (LGAs). Feature identification using correlation analysis identified six important variables. Factor analysis identified two dimensions, namely accessibility and socioeconomic conditions, from this subset. A social vulnerability index (SoVI) showed that Ondo and Ekiti have more vulnerable LGAs than other states in the region. About 50% of the LGAs in Osun and Ogun have a relatively low social vulnerability. Distribution of the SoVI shows that there are great differences within states as well as across regions. Scores of population density, disability and poverty have a high margin of error in relation to mean state scores. The study showed that with a geographical information system there are opportunities to model social vulnerability and monitor its evolution and dynamics across the continent.

Spring distributions and relationships with land cover and hydrogeologic strata in a karst landscape in Winona County, Minnesota, USA

USGS Publications Warehouse

Williams, M.A.; Vondracek, B.

2010-01-01

Karst aquifers are important groundwater resources, but are vulnerable to contamination due to relatively rapid subsurface transport. Springs, points where the landscape and water table intersect and cold groundwater discharges, link aquifer systems with land surfaces and water bodies. As such, in many regions, they are critical to the viability of lakes, streams and cold-water fish communities. An understanding of where springs are located is important to watershed, fishery and environmental management efforts in karst regions. To better understand spatial distribution of springs and as a potential method for identifying variables that characterize locations of springs for improved land and watershed management, a nearest-neighbor analysis and a discriminant function analysis (DFA) of springs were conducted in Winona County, Minnesota USA, a karst landscape. Nearestneighbor analysis examined the spatial spring distribution. Twenty-two variables describing the locations of springs were analyzed to ascertain their ability to discriminate correct aquifer unit or bedrock unit classification for each spring. Springs were clumped with the highest densities in the lowest elevations. Springs were correctly assigned to aquifer units and bedrock units with eight and 11 landscape variables, respectively. Forest land cover was the only land cover type contributing to spring discrimination. Consideration of upland human activities, particularly in forested areas, on spring discharge along with a better understanding of characteristics describing spring locations could lead to better management activities that locate and protect springs and their important contributions to regional ecohydrology. ?? 2010 Springer-Verlag.

Spring distribution in Winona County, Minnesota, USA and the relationship with geologic strata in a karst landscape

USGS Publications Warehouse

Vondracek, Bruce C.; Williams, Mary A.

2010-01-01

Karst aquifers are important groundwater resources, but are vulnerable to contamination due to relatively rapid subsurface transport. Springs, points where the landscape and water table intersect and cold groundwater discharges, link aquifer systems with land surfaces and water bodies. As such, in many regions, they are critical to the viability of lakes, streams and cold-water fish communities. An understanding of where springs are located is important to watershed, fishery and environmental management efforts in karst regions. To better understand spatial distribution of springs and as a potential method for identifying variables that characterize locations of springs for improved land and watershed management, a nearest-neighbor analysis and a discriminant function analysis (DFA) of springs were conducted in Winona County, Minnesota, USA, a karst landscape. Nearest-neighbor analysis examined the spatial spring distribution. Twenty-two variables describing the locations of springs were analyzed to ascertain their ability to discriminate correct aquifer unit or bedrock unit classification for each spring. Springs were clumped with the highest densities in the lowest elevations. Springs were correctly assigned to aquifer units and bedrock units with eight and 11 landscape variables, respectively. Forest land cover was the only land cover type contributing to spring discrimination. Consideration of upland human activities, particularly in forested areas, on spring discharge along with a better understanding of characteristics describing spring locations could lead to better management activities that locate and protect springs and their important contributions to regional ecohydrology.

Modeling of local sea level rise and its future projection under climate change using regional information through EOF analysis

NASA Astrophysics Data System (ADS)

Naren, A.; Maity, Rajib

2017-12-01

Sea level rise is one of the manifestations of climate change and may cause a threat to the coastal regions. Estimates from global circulation models (GCMs) are either not available on coastal locations due to their coarse spatial resolution or not reliable since the mismatch between (interpolated) GCM estimates at coastal locations and actual observation over historical period is significantly different. We propose a semi-empirical framework to model the local sea level rise (SLR) using the possibly existing relationship between local SLR and regional atmospheric/oceanic variables. Selection of set of input variables mostly based on the literature bears the signature of both atmospheric and oceanic variables that possibly have an effect on SLR. The proposed approach offers a method to extract the combined information hidden in the regional fields of atmospheric/oceanic variables for a specific target coastal location. Generality of the approach ensures the inclusion of more variables in the set of inputs depending on the geographical location of any coastal station. For demonstration, 14 coastal locations along the Indian coast and islands are considered and a set of regional atmospheric and oceanic variables are considered. After development and validation of the model at each coastal location with the historical data, the model is further used for future projection of local SLR up to the year 2100 for three different future emission scenarios represented by representative concentration pathways (RCPs)—RCP2.6, RCP4.5, and RCP8.5. The maximum projected SLR is found to vary from 260.65 to 393.16 mm (RCP8.5) by the end of 2100 among the locations considered. Outcome of the proposed approach is expected to be useful in regional coastal management and in developing mitigation strategies in a changing climate.

Creating Near-Term Climate Scenarios for AgMIP

NASA Astrophysics Data System (ADS)

Goddard, L.; Greene, A. M.; Baethgen, W.

2012-12-01

For the next assessment report of the IPCC (AR5), attention is being given to development of climate information that is appropriate for adaptation, such as decadal-scale and near-term predictions intended to capture the combined effects of natural climate variability and the emerging climate change signal. While the science and practice evolve for the production and use of dynamic decadal prediction, information relevant to agricultural decision-makers can be gained from analysis of past decadal-scale trends and variability. Statistical approaches that mimic the characteristics of observed year-to-year variability can indicate the range of possibilities and their likelihood. In this talk we present work towards development of near-term climate scenarios, which are needed to engage decision-makers and stakeholders in the regions in current decision-making. The work includes analyses of decadal-scale variability and trends in the AgMIP regions, and statistical approaches that capture year-to-year variability and the associated persistence of wet and dry years. We will outline the general methodology and some of the specific considerations in the regional application of the methodology for different AgMIP regions, such those for Western Africa versus southern Africa. We will also show some examples of quality checks and informational summaries of the generated data, including (1) metrics of information quality such as probabilistic reliability for a suite of relevant climate variables and indices important for agriculture; (2) quality checks relative to the use of this climate data in crop models; and, (3) summary statistics (e.g., for 5-10-year periods or across given spatial scales).

A systematic intercomparison of regional flood frequency analysis models in a simulation framework

NASA Astrophysics Data System (ADS)

Ganora, Daniele; Laio, Francesco; Claps, Pierluigi

2015-04-01

Regional frequency analysis (RFA) is a well-established methodology to provide an estimate of the flood frequency curve (or other discharge-related variables), based on the fundamental concept of substituting temporal information at a site (no data or short time series) by exploiting observations at other sites (spatial information). Different RFA paradigms exist, depending on the way the information is transferred to the site of interest. Despite the wide use of such methodology, a systematic comparison between these paradigms has not been performed. The aim of this study is to provide a framework wherein carrying out the intercomparison: we thus synthetically generate data through Monte Carlo simulations for a number of (virtual) stations, following a GEV parent distribution; different scenarios can be created to represent different spatial heterogeneity patterns by manipulating the parameters of the parent distribution at each station (e.g. with a linear variation in space of the shape parameter of the GEV). A special case is the homogeneous scenario where each station record is sampled from the same parent distribution. For each scenario and each simulation, different regional models are applied to evaluate the 200-year growth factor at each station. Results are than compared to the exact growth factor of each station, which is known in our virtual world. Considered regional approaches include: (i) a single growth curve for the whole region; (ii) a multiple-region model based on cluster analysis which search for an adequate number of homogeneous subregions; (iii) a Region-of-Influence model which defines a homogeneous subregion for each site; (iv) a spatially-smooth estimation procedure based on linear regressions.. A further benchmark model is the at-site estimate based on the analysis of the local record. A comprehensive analysis of the results of the simulations shows that, if the scenario is homogeneous (no spatial variability), all the regional approaches have comparable performances. Moreover, as expected, regional estimates are much more reliable than the at-site estimates. If the scenario is heterogeneous, the performances of the regional models depend on the pattern of heterogeneity; in general, however, the spatially-smooth regional approach performs better than the others, and its performances improve for increasing record lengths. For heterogeneous scenarios, the at-site estimates appear to be comparably more efficient than in the homogeneous case, and in general less biased than the regional estimates.

Agricultural Adaptation to Climate Change

NASA Astrophysics Data System (ADS)

Tam, A.; Jain, M.

2016-12-01

This research includes two projects pertaining to agricultural systems' adaption to climate change. The first research project focuses on the wheat yielding regions of India. Wheat is a major staple crop and many rural households and smallholder farmers rely on crop yields for survival. We examine the impacts of weather variability and groundwater depletion on agricultural systems, using geospatial analysis and satellite-based analysis and household-based and census data sets. We use these methods to estimate the crop yields and identify what factors are associated with low versus high yielding regions. This can help identify strategies that should be further promoted to increase crop yields. The second research project is a literature review. We conduct a meta-analysis and synthetic review on literature about agricultural adaptation to climate change. We sort through numerous articles to identify and examine articles that associate socio-economic, biophysical, and perceptional factors to farmers' adaption to climate change. Our preliminary results show that researchers tend to associate few factors to a farmers' vulnerability and adaptive capacity, and most of the research conducted is concentrated in North America, whereas tropical regions that are highly vulnerable to weather variability are underrepresented by literature. There are no conclusive results in both research projects as of so far.

THESEUS: maximum likelihood superpositioning and analysis of macromolecular structures

PubMed Central

Theobald, Douglas L.; Wuttke, Deborah S.

2008-01-01

Summary THESEUS is a command line program for performing maximum likelihood (ML) superpositions and analysis of macromolecular structures. While conventional superpositioning methods use ordinary least-squares (LS) as the optimization criterion, ML superpositions provide substantially improved accuracy by down-weighting variable structural regions and by correcting for correlations among atoms. ML superpositioning is robust and insensitive to the specific atoms included in the analysis, and thus it does not require subjective pruning of selected variable atomic coordinates. Output includes both likelihood-based and frequentist statistics for accurate evaluation of the adequacy of a superposition and for reliable analysis of structural similarities and differences. THESEUS performs principal components analysis for analyzing the complex correlations found among atoms within a structural ensemble. PMID:16777907

Manipulation of Length and Lexicality Localizes the Functional Neuroanatomy of Phonological Processing in Adult Readers

PubMed Central

Church, Jessica A.; Balota, David A.; Petersen, Steven E.; Schlaggar, Bradley L.

2010-01-01

In a previous study of single word reading, regions in the left supramarginal gyrus and left angular gyrus showed positive BOLD activity in children but significantly less activity in adults for high-frequency words. This developmental decrease may reflect decreased reliance on phonological processing for familiar stimuli in adults. Therefore, in the present study, variables thought to influence phonological demand (string length and lexicality) were manipulated. Length and lexicality effects in the brain were explored using both ROI and whole-brain approaches. In the ROI analysis, the supramarginal and angular regions from the previous study were applied to this study. The supramarginal region showed a significant positive effect of length, consistent with a role in phonological processing, whereas the angular region showed only negative deflections from baseline with a strong effect of lexicality and other weaker effects. At the whole-brain level, varying effects of length and lexicality and their interactions were observed in 85 regions throughout the brain. The application of hierarchical clustering analysis to the BOLD time course data derived from these regions revealed seven clusters, with potentially revealing anatomical locations. Of note, a left angular gyrus region was the sole constituent of one cluster. Taken together, these findings in adult readers (1) provide support for a widespread set of brain regions affected by lexical variables, (2) corroborate a role for phonological processing in the left supramarginal gyrus, and (3) do not support a strong role for phonological processing in the left angular gyrus. PMID:20433237

Comparison of the seasonal and interannual variability of phytoplankton pigment concentrations in the Peru and California Current systems

NASA Technical Reports Server (NTRS)

Thomas, A. C.; Huang, F.; Strub, P. T.; James, C.

1994-01-01

Monthly composite images from the global coastal zone color scanner (CZCS) data set are used to provide an initial illustration and comparison of seasonal and interannual variability of phytoplankton pigment concentration along the western coasts of South and North America in the Peru Current system (PCS) and California Current system (CCS). The analysis utilizes the entire time series of available data (November 1978 to June 1986) to form a mean annual cycle and an index of interannual variability for a series of both latitudinal and cross-shelf regions within each current system. Within 100 km of the coast, the strongest seasonal cycles in the CCS are in two regions, one between 34 deg and 45 deg N and the second between 24 deg and 29 deg N, each with maximum concentrations (greater than 3.0 mg m(exp-3)) in May-June. Weaker seasonal variability is present north of 45 deg N and in the Southern California Bight region (32 deg N). Within the PCS, in the same 100-km-wide coastal region, highest (greater than 45 deg S) and lowest (less than 20 deg S) latitude regions have a similar seasonal cycle with maximum concentrations (greater than 1.5 mg m(exp -3)) during the austral spring, summer, and fall, matching that evident throughout the CCS. Between these regions, off northern and central Chile, the seasonal maximum occurs during July-August (austral winter), contrary to the influence of upwelling favorable winds. Within the CCS, the dominant feature of interannual variability in the 8-year time series is a strong negative concentration anomaly in 1983, an El Nino year. The relative value of this negative anomaly is strongest off central California and is followed by an even stronger negative anomaly is strongest off central California and is followed by an even stronger negative anomaly in 1984 off Baja, California. In the PCS, strong negative anomalies during the 1982-1983 El Nino period are evident only off the Peruvian coast and are evident there only in the regions 100 km or more from the coast. Although negative anomalies associated with the El Nino were not present at higher latitudes (more than approximately 20 deg S) in the PCS, the extremely sparse sampling weakens our confidence in the results of the interannual analysis in this region. An upper estimate of the systematic winter bias remaining in the global CZCS data after reprocessing with the multiple scattering algorithm is given in the appendix.

Analysis of the contribution of experimental bias, experimental noise, and inter-subject biological variability on the assessment of developmental trajectories in diffusion MRI studies of the brain.

PubMed

Sadeghi, Neda; Nayak, Amritha; Walker, Lindsay; Okan Irfanoglu, M; Albert, Paul S; Pierpaoli, Carlo

2015-04-01

Metrics derived from the diffusion tensor, such as fractional anisotropy (FA) and mean diffusivity (MD) have been used in many studies of postnatal brain development. A common finding of previous studies is that these tensor-derived measures vary widely even in healthy populations. This variability can be due to inherent inter-individual biological differences as well as experimental noise. Moreover, when comparing different studies, additional variability can be introduced by different acquisition protocols. In this study we examined scans of 61 individuals (aged 4-22 years) from the NIH MRI study of normal brain development. Two scans were collected with different protocols (low and high resolution). Our goal was to separate the contributions of biological variability and experimental noise to the overall measured variance, as well as to assess potential systematic effects related to the use of different protocols. We analyzed FA and MD in seventeen regions of interest. We found that biological variability for both FA and MD varies widely across brain regions; biological variability is highest for FA in the lateral part of the splenium and body of the corpus callosum along with the cingulum and the superior longitudinal fasciculus, and for MD in the optic radiations and the lateral part of the splenium. These regions with high inter-individual biological variability are the most likely candidates for assessing genetic and environmental effects in the developing brain. With respect to protocol-related effects, the lower resolution acquisition resulted in higher MD and lower FA values for the majority of regions compared with the higher resolution protocol. However, the majority of the regions did not show any age-protocol interaction, indicating similar trajectories were obtained irrespective of the protocol used. Published by Elsevier Inc.

Hospitalizations for ambulatory care sensitive conditions and quality of primary care: their relation with socioeconomic and health care variables in the Madrid regional health service (Spain).

PubMed

Magán, Purificación; Alberquilla, Angel; Otero, Angel; Ribera, José Manuel

2011-01-01

Hospitalizations for ambulatory care sensitive conditions (ACSH) have been proposed as an indirect indicator of the effectiveness and quality of care provided by primary health care. To investigate the association of ACSH rates with population socioeconomic factors and with characteristics of primary health care. Cross-sectional, ecologic study. Using hospital discharge data, ACSH were selected from the list of conditions validated for Spain. All 34 health districts in the Region of Madrid, Spain. Individuals aged 65 years or older residing in the region of Madrid between 2001 and 2003, inclusive. Age- and gender-adjusted ACSH rates in each health district. The adjusted ACSH rate per 1000 population was 35.37 in men and 20.45 in women. In the Poisson regression analysis, an inverse relation was seen between ACSH rates and the socioeconomic variables. Physician workload was the only health care variable with a statistically significant relation (rate ratio of 1.066 [95% CI; 1.041-1.091]). These results were similar in the analyses disaggregated by gender. In the multivariate analyses that included health care variables, none of the health care variables were statistically significant. ACSH may be more closely related with socioeconomic variables than with characteristics of primary care activity. Therefore, other factors outside the health system must be considered to improve health outcomes in the population.

Reconstruction of regional climate and climate change in past decades

NASA Astrophysics Data System (ADS)

von Storch, H.; Feser, F.; Weisse, R.; Zahn, M.

2009-12-01

Regional climate models, which are constrained by large scale information (spectral nudging) provided by re-analyses, allow for the construction of a mostly homogeneous description of regional weather statistics since about 1950. The potential of this approach has been demonstrated for Northern Europe. That data set, named CoastDat, does not only contain hourly data on atmospheric variables, in particular wind, but also on marine weather, i.e., short term water level, current and sea state variations. Another example is the multi-decadal variability of Polar Lows in the subarctic waters. The utility of such data sets is broad, from risk assessments related to coastal wind and wave conditions, assessment of determining the causes for regional climate change, a-posteriori analysis of the efficiency of environmental legislation (example: lead). In the paper, the methodology is outlined, examples are provided and the utility of the product discussed.

Synoptic variability in the nudged version of LMDZ over the West African monsoon region during the AMMA campaign.

NASA Astrophysics Data System (ADS)

Ly, M.; Roca, R.; Hourdin, F.

2009-04-01

The Laboratoire de Météorologie Dynamique General circulation Model (LMDz) is ran in a nudged mode using various sets of atmospheric analysis during the wet season of 2006. The zoom capability of the model is used and reaches a mesh size of around 80km over the whole West African region. Sensitivity experiments have been performed in order to highlight the behaviour of the nudged model under a wide range of conditions: spatial and vertical resolution, zoom intensity, surface scheme formulation as well as for the forcing and driving parameters: relaxation time, type of analysis (ECMWF, NCEP/GFS, Sea Surface Temperature (climatology vs. 2006) and the nudging variables (wind, temperature, and combination). A combination of satellite data (E.g., GPCP rain estimates, METEOSAT Free tropospheric humidity,…) and in-situ observations acquired during the AMMA campaign (temperature and humidity profiles from radiosondes, GPS precipitable water,…) are all used to evaluate the simulations. The analysis is focused on the representation of the synoptic variability by the model in terms of rainfall and water vapour variability. It is shown that the model captures the free troposphere water vapour variability reasonably well with highly significant correlations between the radiosondes and the simulated fields. In the lowest levels of the atmosphere and in the upper troposphere, the agreement is less good. When the fields are filtered using a pass-band filter between 3-10 days, the correlation overall increases. Detailed of the sensitivity of these results to the simulation configuration mentioned above will be further discussed at the conference.

Explaining the road accident risk: weather effects.

PubMed

Bergel-Hayat, Ruth; Debbarh, Mohammed; Antoniou, Constantinos; Yannis, George

2013-11-01

This research aims to highlight the link between weather conditions and road accident risk at an aggregate level and on a monthly basis, in order to improve road safety monitoring at a national level. It is based on some case studies carried out in Work Package 7 on "Data analysis and synthesis" of the EU-FP6 project "SafetyNet-Building the European Road Safety Observatory", which illustrate the use of weather variables for analysing changes in the number of road injury accidents. Time series analysis models with explanatory variables that measure the weather quantitatively were used and applied to aggregate datasets of injury accidents for France, the Netherlands and the Athens region, over periods of more than 20 years. The main results reveal significant correlations on a monthly basis between weather variables and the aggregate number of injury accidents, but the magnitude and even the sign of these correlations vary according to the type of road (motorways, rural roads or urban roads). Moreover, in the case of the interurban network in France, it appears that the rainfall effect is mainly direct on motorways--exposure being unchanged, and partly indirect on main roads--as a result of changes in exposure. Additional results obtained on a daily basis for the Athens region indicate that capturing the within-the-month variability of the weather variables and including it in a monthly model highlights the effects of extreme weather. Such findings are consistent with previous results obtained for France using a similar approach, with the exception of the negative correlation between precipitation and the number of injury accidents found for the Athens region, which is further investigated. The outlook for the approach and its added value are discussed in the conclusion. Copyright © 2013. Published by Elsevier Ltd.

Phenology Analysis of Forest Vegetation to Environmental Variables during - and Post-Monsoon Seasons in Western Himalayan Region of India

NASA Astrophysics Data System (ADS)

Khare, S.; Latifi, H.; Ghosh, K.

2016-06-01

To assess the phenological changes in Moist Deciduous Forest (MDF) of western Himalayan region of India, we carried out NDVI time series analysis from 2013 to 2015 using Landsat 8 OLI data. We used the vegetation index differencing method to calculate the change in NDVI (NDVIchange) during pre and post monsoon seasons and these changes were used to assess the phenological behaviour of MDF by taking the effect of a set of environmental variables into account. To understand the effect of environmental variables on change in phenology, we designed a linear regression analysis with sample-based NDVIchange values as the response variable and elevation aspect, and Land Surface Temperature (LST) as explanatory variables. The Landsat-8 derived phenology transition stages were validated by calculating the phenology variation from Nov 2008 to April 2009 using Landsat-7 which has the same spatial resolution as Landsat-8. The Landsat-7 derived NDVI trajectories were plotted in accordance with MODIS derived phenology stages (from Nov 2008 to April 2009) of MDF. Results indicate that the Landsat -8 derived NDVI trajectories describing the phenology variation of MDF during spring, monsoon autumn and winter seasons agreed closely with Landsat-7 and MODIS derived phenology transition from Nov 2008 to April 2009. Furthermore, statistical analysis showed statistically significant correlations (p < 0.05) amongst the environmental variables and the NDVIchange between full greenness and maximum frequency stage of Onset of Greenness (OG) activity.. The major change in NDVI was observed in medium (600 to 650 m) and maximum (650 to 750 m) elevation areas. The change in LST showed also to be highly influential. The results of this study can be used for large scale monitoring of difficult-to-reach mountainous forests, with additional implications in biodiversity assessment. By means of a sufficient amount of available cloud-free imagery, detailed phenological trends across mountainous forests could be explained.

Exploring the relationship between vegetation spectra and eco-geo-environmental conditions in karst region, Southwest China.

PubMed

Yue, Yuemin; Wang, Kelin; Zhang, Bing; Chen, Zhengchao; Jiao, Quanjun; Liu, Bo; Chen, Hongsong

2010-01-01

Remote sensing of local environmental conditions is not accessible if substrates are covered with vegetation. This study explored the relationship between vegetation spectra and karst eco-geo-environmental conditions. Hyperspectral remote sensing techniques showed that there were significant differences between spectral features of vegetation mainly distributed in karst and non-karst regions, and combination of 1,300- to 2,500-nm reflectance and 400- to 680-nm first-derivative spectra could delineate karst and non-karst vegetation groups. Canonical correspondence analysis (CCA) successfully assessed to what extent the variation of vegetation spectral features can be explained by associated eco-geo-environmental variables, and it was found that soil moisture and calcium carbonate contents had the most significant effects on vegetation spectral features in karst region. Our study indicates that vegetation spectra is tightly linked to eco-geo-environmental conditions and CCA is an effective means of studying the relationship between vegetation spectral features and eco-geo-environmental variables. Employing a combination of spectral and spatial analysis, it is anticipated that hyperspectral imagery can be used in interpreting or mapping eco-geo-environmental conditions covered with vegetation in karst region.

Regionalizing Africa: Patterns of Precipitation Variability in Observations and Global Climate Models

NASA Technical Reports Server (NTRS)

Badr, Hamada S.; Dezfuli, Amin K.; Zaitchik, Benjamin F.; Peters-Lidard, Christa D.

2016-01-01

Many studies have documented dramatic climatic and environmental changes that have affected Africa over different time scales. These studies often raise questions regarding the spatial extent and regional connectivity of changes inferred from observations and proxies and/or derived from climate models. Objective regionalization offers a tool for addressing these questions. To demonstrate this potential, applications of hierarchical climate regionalizations of Africa using observations and GCM historical simulations and future projections are presented. First, Africa is regionalized based on interannual precipitation variability using Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data for the period 19812014. A number of data processing techniques and clustering algorithms are tested to ensure a robust definition of climate regions. These regionalization results highlight the seasonal and even month-to-month specificity of regional climate associations across the continent, emphasizing the need to consider time of year as well as research question when defining a coherent region for climate analysis. CHIRPS regions are then compared to those of five GCMs for the historic period, with a focus on boreal summer. Results show that some GCMs capture the climatic coherence of the Sahel and associated teleconnections in a manner that is similar to observations, while other models break the Sahel into uncorrelated subregions or produce a Sahel-like region of variability that is spatially displaced from observations. Finally, shifts in climate regions under projected twenty-first-century climate change for different GCMs and emissions pathways are examined. A projected change is found in the coherence of the Sahel, in which the western and eastern Sahel become distinct regions with different teleconnections. This pattern is most pronounced in high-emissions scenarios.

Effects of spinal manipulation and myofascial techniques on heart rate variability: A systematic review.

PubMed

Amoroso Borges, Bruno Luis; Bortolazzo, Gustavo Luiz; Neto, Hugo Pasin

2018-01-01

The analysis of heart rate variability is important to the investigation of stimuli from the autonomic nervous system. Osteopathy is a form of treatment that can influence this system in healthy individuals as well as those with a disorder or disease. The aim of the present study was to perform a systematic review of the literature regarding the effect of spinal manipulation and myofascial techniques on heart rate variability. Searches were performed of the Pubmed, Scielo, Lilacs, PEDro, Ibesco, Cochrane and Scopus databases for relevant studies. The PEDro scale was used to assess the methodological quality of each study selected. A total of 505 articles were retrieved during the initial search. After an analysis of the abstracts, nine studies were selected for the present review. Based on the findings, osteopathy exerts an influence on the autonomic nervous system depending on the stimulation site and type. A greater parasympathetic response was found when stimulation was performed in the cervical and lumbar regions, whereas a greater sympathetic response was found when stimulation was performed in the thoracic region. Copyright © 2017 Elsevier Ltd. All rights reserved.

Intraseasonal variability of winter precipitation over central asia and the western tibetan plateau from 1979 to 2013 and its relationship with the North Atlantic Oscillation

NASA Astrophysics Data System (ADS)

Liu, Heng; Liu, Xiaodong; Dong, Buwen

2017-09-01

Winter precipitation over Central Asia and the western Tibetan Plateau (CAWTP) is mainly a result of the interaction between the westerly circulation and the high mountains around the plateau. Empirical Orthogonal Functions (EOFs), Singular Value Decomposition (SVD), linear regression and composite analysis were used to analyze winter daily precipitation and other meteorological elements in this region from 1979 to 2013, in order to understand how interactions between the regional circulation and topography affect the intraseasonal variability in precipitation. The SVD analysis shows that the winter daily precipitation variability distribution is characterized by a dipole pattern with opposite signs over the northern Pamir Plateau and over the Karakoram Himalaya, similar to the second mode of EOF analysis. This dipole pattern of precipitation anomaly is associated with local anomalies in both the 700 hPa moisture transport and the 500 hPa geopotential height and is probably caused by oscillations in the regional and large-scale circulations, which can influence the westerly disturbance tracks and water vapor transport. The linear regression shows that the anomalous mid-tropospheric circulation over CAWTP corresponds to an anti-phase variation of the 500 hPa geopotential height anomalies over the southern and northern North Atlantic 10 days earlier (at 95% significance level), that bears a similarity to the North Atlantic Oscillation (NAO). The composite analysis reveals that the NAO impacts the downstream regions including CAWTP by controlling south-north two branches of the middle latitude westerly circulation around the Eurasian border. During the positive phases of the NAO, the northern branch of the westerly circulation goes around the northwest Tibetan Plateau, whereas the southern branch encounters the southwest Tibetan Plateau, which leads to reduced precipitation over the northern Pamir Plateau and increased precipitation over the Karakoram Himalaya, and vice versa.

Global patterns of kelp forest change over the past half-century.

PubMed

Krumhansl, Kira A; Okamoto, Daniel K; Rassweiler, Andrew; Novak, Mark; Bolton, John J; Cavanaugh, Kyle C; Connell, Sean D; Johnson, Craig R; Konar, Brenda; Ling, Scott D; Micheli, Fiorenza; Norderhaug, Kjell M; Pérez-Matus, Alejandro; Sousa-Pinto, Isabel; Reed, Daniel C; Salomon, Anne K; Shears, Nick T; Wernberg, Thomas; Anderson, Robert J; Barrett, Nevell S; Buschmann, Alejandro H; Carr, Mark H; Caselle, Jennifer E; Derrien-Courtel, Sandrine; Edgar, Graham J; Edwards, Matt; Estes, James A; Goodwin, Claire; Kenner, Michael C; Kushner, David J; Moy, Frithjof E; Nunn, Julia; Steneck, Robert S; Vásquez, Julio; Watson, Jane; Witman, Jon D; Byrnes, Jarrett E K

2016-11-29

Kelp forests (Order Laminariales) form key biogenic habitats in coastal regions of temperate and Arctic seas worldwide, providing ecosystem services valued in the range of billions of dollars annually. Although local evidence suggests that kelp forests are increasingly threatened by a variety of stressors, no comprehensive global analysis of change in kelp abundances currently exists. Here, we build and analyze a global database of kelp time series spanning the past half-century to assess regional and global trends in kelp abundances. We detected a high degree of geographic variation in trends, with regional variability in the direction and magnitude of change far exceeding a small global average decline (instantaneous rate of change = -0.018 y -1 ). Our analysis identified declines in 38% of ecoregions for which there are data (-0.015 to -0.18 y -1 ), increases in 27% of ecoregions (0.015 to 0.11 y -1 ), and no detectable change in 35% of ecoregions. These spatially variable trajectories reflected regional differences in the drivers of change, uncertainty in some regions owing to poor spatial and temporal data coverage, and the dynamic nature of kelp populations. We conclude that although global drivers could be affecting kelp forests at multiple scales, local stressors and regional variation in the effects of these drivers dominate kelp dynamics, in contrast to many other marine and terrestrial foundation species.

Global patterns of kelp forest change over the past half-century

PubMed Central

Krumhansl, Kira A.; Okamoto, Daniel K.; Rassweiler, Andrew; Novak, Mark; Bolton, John J.; Cavanaugh, Kyle C.; Connell, Sean D.; Johnson, Craig R.; Konar, Brenda; Ling, Scott D.; Micheli, Fiorenza; Norderhaug, Kjell M.; Pérez-Matus, Alejandro; Sousa-Pinto, Isabel; Reed, Daniel C.; Salomon, Anne K.; Shears, Nick T.; Wernberg, Thomas; Anderson, Robert J.; Barrett, Nevell S.; Buschmann, Alejandro H.; Carr, Mark H.; Caselle, Jennifer E.; Derrien-Courtel, Sandrine; Edgar, Graham J.; Edwards, Matt; Estes, James A.; Goodwin, Claire; Kenner, Michael C.; Kushner, David J.; Nunn, Julia; Steneck, Robert S.; Vásquez, Julio; Watson, Jane; Witman, Jon D.

2016-01-01

Kelp forests (Order Laminariales) form key biogenic habitats in coastal regions of temperate and Arctic seas worldwide, providing ecosystem services valued in the range of billions of dollars annually. Although local evidence suggests that kelp forests are increasingly threatened by a variety of stressors, no comprehensive global analysis of change in kelp abundances currently exists. Here, we build and analyze a global database of kelp time series spanning the past half-century to assess regional and global trends in kelp abundances. We detected a high degree of geographic variation in trends, with regional variability in the direction and magnitude of change far exceeding a small global average decline (instantaneous rate of change = −0.018 y−1). Our analysis identified declines in 38% of ecoregions for which there are data (−0.015 to −0.18 y−1), increases in 27% of ecoregions (0.015 to 0.11 y−1), and no detectable change in 35% of ecoregions. These spatially variable trajectories reflected regional differences in the drivers of change, uncertainty in some regions owing to poor spatial and temporal data coverage, and the dynamic nature of kelp populations. We conclude that although global drivers could be affecting kelp forests at multiple scales, local stressors and regional variation in the effects of these drivers dominate kelp dynamics, in contrast to many other marine and terrestrial foundation species. PMID:27849580

Regional variability of farmer decision making and irrigation water use: insights from a data-scarce region of North India

NASA Astrophysics Data System (ADS)

O'Keeffe, Jimmy; Buytaert, Wouter; Brozović, Nick; Mijic, Ana

2014-05-01

Over the last fifty years, changes in agriculture brought about by the Green Revolution have transformed India from a famine-prone, drought-susceptible country into the worlds' third largest grain producer and one of the most intensively irrigated parts of the globe. Regionally, cheap energy, subsidised seeds and fertilisers, and in some areas Government purchase guarantees for grain promote the intensification of farming. While this allows farmers to survive, it also aggravates the drain agriculture is having on resources, particularly energy and water. Analysis at a regional scale, however, masks the considerable spatial variability that exists on a more localised level and must be taken into consideration to understand correctly aggregate system response to policy, hydrologic, and climatic change. In this study we present and analyse the results from over 100 farmer interviews conducted in the data-scarce districts of Jalaun and Sitapur on the Gangetic Plains of Uttar Pradesh during the post monsoon period of 2013. Variables such as the volumes and timing of irrigation water applied, sources of water, methods of abstraction and irrigation, and costs incurred are mapped, using qualitative data analysis and GIS. Large differences between the districts emerge, for instance in the region of Jalaun where cheaper canal water is available in addition to groundwater. This has enabled farmers to afford more water efficient technologies such as sprinklers, a practice not found in Sitapur which depends almost exclusively on more expensive diesel pumps. Results are used to delineate the spatial variability in water use practices, along with farmer behaviour and decision making. The primary data are compared with socio-economic information taken from regionally produced statistical abstracts. The combined data are used to identify the main drivers that influence farmer decision-making, which is in turn leading to groundwater overdraught in many parts of North India. Finally, the importance of understanding and modelling farmer behaviour for policy development, and the significance of this in the face of growing population, changes in socio-economic conditions, and climate change are discussed. Taking these variables into account is necessary in creating a transparent, socially acceptable and economically viable balance between sustainable water resources and farmer livelihoods.

A comprehensive overview of the spatial and temporal variability of apple bud dormancy release and blooming phenology in Western Europe

NASA Astrophysics Data System (ADS)

Legave, Jean Michel; Blanke, Michael; Christen, Danilo; Giovannini, Daniela; Mathieu, Vincent; Oger, Robert

2013-03-01

In the current context of global warming, an analysis is required of spatially-extensive and long-term blooming data in fruit trees to make up for insufficient information on regional-scale blooming changes and determinisms that are key to the phenological adaptation of these species. We therefore analysed blooming dates over long periods at climate-contrasted sites in Western Europe, focusing mainly on the Golden Delicious apple that is grown worldwide. On average, blooming advances were more pronounced in northern continental (10 days) than in western oceanic (6-7 days) regions, while the shortest advance was found on the Mediterranean coastline. Temporal trends toward blooming phase shortenings were also observed in continental regions. These regional differences in temporal variability across Western Europe resulted in a decrease in spatial variability, i.e. shorter time intervals between blooming dates in contrasted regions (8-10-day decrease for full bloom between Mediterranean and continental regions). Fitted sequential models were used to reproduce phenological changes. Marked trends toward shorter simulated durations of forcing period (bud growth from dormancy release to blooming) and high positive correlations between these durations and observed blooming dates support the notion that blooming advances and shortenings are mainly due to faster satisfaction of the heating requirement. However, trends toward later dormancy releases were also noted in oceanic and Mediterranean regions. This could tend toward blooming delays and explain the shorter advances in these regions despite similar or greater warming. The regional differences in simulated chilling and forcing periods were consistent with the regional differences in temperature increases.

Space-Time Variability in River Flow Regimes of Northeast Turkey

NASA Astrophysics Data System (ADS)

Saris, F.; Hannah, D. M.; Eastwood, W. J.

2011-12-01

The northeast region of Turkey is characterised by relatively high annual precipitation totals and river flow. It is a mountainous region with high ecological status and also it is of prime interest to the energy sector. These characteristics make this region an important area for a hydroclimatology research in terms of future availability and management of water resources. However, there is not any previous research identifying hydroclimatological variability across the region. This study provides first comprehensive and detailed information on river flow regimes of northeast Turkey which is delimited by two major river basins namely East Black Sea (EBS) and Çoruh River (ÇRB) basins. A novel river flow classification is used that yields a large-scale perspective on hydroclimatology patterns of the region and allows interpretations regarding the controlling factors on river flow variability. River flow regimes are classified (with respect to timing and magnitude of flow) to examine spatial variability based on long-term average regimes, and also by grouping annual regimes for each station-year to identify temporal (between-year) variability. Results indicate that rivers in northeast Turkey are characterised by marked seasonal flow variation with an April-May-June maximum flow period. Spatial variability in flow regime seasonality is dependent largely on the topography of the study area. The EBS Basin, for which the North Anatolian Mountains cover the eastern part, is characterised by a May-June peak; whereas the ÇRB is defined by an April-May flow peak. The timing of river flows indicates that snowmelt is an important process and contributor of river flow maxima for both basins. The low flow season is January and February. Intermediate and low regime magnitude classes dominate in ÇRB and EBS basins, respectively, while high flow magnitude class is observed for one station only across the region. Result of regime stability analysis (year-to-year variation) shows that April-May and May-June peak shape classes together with low and intermediate magnitude classes are the most frequent and persistent flow regimes. This research has advanced understanding of hydroclimatological processes in northeast Turkey by identifying river flow regimes and together with explanations regarding the controlling factors on river flow variability.

The role of ENSO in understanding changes in Colombia's annual malaria burden by region, 1960–2006

PubMed Central

Mantilla, Gilma; Oliveros, Hugo; Barnston, Anthony G

2009-01-01

Background Malaria remains a serious problem in Colombia. The number of malaria cases is governed by multiple climatic and non-climatic factors. Malaria control policies, and climate controls such as rainfall and temperature variations associated with the El Niño/Southern Oscillation (ENSO), have been associated with malaria case numbers. Using historical climate data and annual malaria case number data from 1960 to 2006, statistical models are developed to isolate the effects of climate in each of Colombia's five contrasting geographical regions. Methods Because year to year climate variability associated with ENSO causes interannual variability in malaria case numbers, while changes in population and institutional control policy result in more gradual trends, the chosen predictors in the models are annual indices of the ENSO state (sea surface temperature [SST] in the tropical Pacific Ocean) and time reference indices keyed to two major malaria trends during the study period. Two models were used: a Poisson and a Negative Binomial regression model. Two ENSO indices, two time reference indices, and one dummy variable are chosen as candidate predictors. The analysis was conducted using the five geographical regions to match the similar aggregation used by the National Institute of Health for its official reports. Results The Negative Binomial regression model is found better suited to the malaria cases in Colombia. Both the trend variables and the ENSO measures are significant predictors of malaria case numbers in Colombia as a whole, and in two of the five regions. A one degree Celsius change in SST (indicating a weak to moderate ENSO event) is seen to translate to an approximate 20% increase in malaria cases, holding other variables constant. Conclusion Regional differentiation in the role of ENSO in understanding changes in Colombia's annual malaria burden during 1960–2006 was found, constituting a new approach to use ENSO as a significant predictor of the malaria cases in Colombia. These results naturally point to additional needed work: (1) refining the regional and seasonal dependence of climate on the ENSO state, and of malaria on the climate variables; (2) incorporating ENSO-related climate variability into dynamic malaria models. PMID:19133152

Underrepresentation of Women in the Academic Profession: A Comparative Analysis of the North American Region

ERIC Educational Resources Information Center

Metcalfe, Amy Scott; Gonzalez, Laura Padilla

2013-01-01

The present study addresses women's underrepresentation in the academic profession, as well as the need for policies and practices aimed at this issue. It compares underrepresentation of academic women in North American countries, and explores, throughout a bivariate analysis, personal, professional, as well as institutional variables related to…

Application of a multilocus variable number of tandem repeats analysis to regional outbreak surveillance of Enterohemorrhagic Escherichia coli O157:H7 infections.

PubMed

Konno, Takayuki; Yatsuyanagi, Jun; Saito, Shioko

2011-01-01

A total of 18 strains of EHEC O157:H7 were isolated from distinct cases in Akita Prefecture, Japan from July to September 2007. The genetic relatedness of these isolates was investigated by performing a multilocus variable number of tandem repeats analysis (MLVA) and a pulsed-field gel electrophoresis (PFGE) analysis using XbaI. The PFGE analyses allowed us to group these 18 isolates into three major clusters. The MLVA results correlated closely with those obtained by PFGE, although some variants were found within the clusters obtained by PFGE, thus highlighting the utility of this technique for determining a precise classification when it is difficult to differentiate between isolates with indistinguishable or very similar PFGE patterns. In addition, MLVA is a much easier and more rapid method than PFGE for analysis of the genetic relatedness of strains. Thus, as a second molecular epidemiological subtyping method, MLVA is useful for the regional outbreak surveillance of EHEC O157:H7 infections.

The Technical Efficiency of Specialised Milk Farms: A Regional View

PubMed Central

Špička, Jindřich; Smutka, Luboš

2014-01-01

The aim of the article is to evaluate production efficiency and its determinants of specialised dairy farming among the EU regions. In the most of European regions, there is a relatively high significance of small specialised farms including dairy farms. The DEAVRS method (data envelopment analysis with variable returns to scale) reveals efficient and inefficient regions including the scale efficiency. In the next step, the two-sample t-test determines differences of economic and structural indicators between efficient and inefficient regions. The research reveals that substitution of labour by capital/contract work explains the variability of the farm net value added per AWU (annual work unit) income indicator by more than 30%. The significant economic determinants of production efficiency in specialised dairy farming are farm size, herd size, crop output per hectare, productivity of energy, and capital (at α = 0.01). Specialised dairy farms in efficient regions have significantly higher farm net value added per AWU than inefficient regions. Agricultural enterprises in inefficient regions have a more extensive structure and produce more noncommodity output (public goods). Specialised dairy farms in efficient regions have a slightly higher milk yield, specific livestock costs of feed, bedding, and veterinary services per livestock unit. PMID:25050408

Comparative and Evolutionary Analyses of Meloidogyne spp. Based on Mitochondrial Genome Sequences

PubMed Central

García, Laura Evangelina; Sánchez-Puerta, M. Virginia

2015-01-01

Molecular taxonomy and evolution of nematodes have been recently the focus of several studies. Mitochondrial sequences were proposed as an alternative for precise identification of Meloidogyne species, to study intraspecific variability and to follow maternal lineages. We characterized the mitochondrial genomes (mtDNAs) of the root knot nematodes M. floridensis, M. hapla and M. incognita. These were AT rich (81–83%) and highly compact, encoding 12 proteins, 2 rRNAs, and 22 tRNAs. Comparisons with published mtDNAs of M. chitwoodi, M. incognita (another strain) and M. graminicola revealed that they share protein and rRNA gene order but differ in the order of tRNAs. The mtDNAs of M. floridensis and M. incognita were strikingly similar (97–100% identity for all coding regions). In contrast, M. floridensis, M. chitwoodi, M. hapla and M. graminicola showed 65–84% nucleotide identity for coding regions. Variable mitochondrial sequences are potentially useful for evolutionary and taxonomic studies. We developed a molecular taxonomic marker by sequencing a highly-variable ~2 kb mitochondrial region, nad5-cox1, from 36 populations of root-knot nematodes to elucidate relationships within the genus Meloidogyne. Isolates of five species formed monophyletic groups and showed little intraspecific variability. We also present a thorough analysis of the mitochondrial region cox2-rrnS. Phylogenies based on either mitochondrial region had good discrimination power but could not discriminate between M. arenaria, M. incognita and M. floridensis. PMID:25799071

Evaluation of the CORDEX-Africa multi-RCM hindcast: systematic model errors

NASA Astrophysics Data System (ADS)

Kim, J.; Waliser, Duane E.; Mattmann, Chris A.; Goodale, Cameron E.; Hart, Andrew F.; Zimdars, Paul A.; Crichton, Daniel J.; Jones, Colin; Nikulin, Grigory; Hewitson, Bruce; Jack, Chris; Lennard, Christopher; Favre, Alice

2014-03-01

Monthly-mean precipitation, mean (TAVG), maximum (TMAX) and minimum (TMIN) surface air temperatures, and cloudiness from the CORDEX-Africa regional climate model (RCM) hindcast experiment are evaluated for model skill and systematic biases. All RCMs simulate basic climatological features of these variables reasonably, but systematic biases also occur across these models. All RCMs show higher fidelity in simulating precipitation for the west part of Africa than for the east part, and for the tropics than for northern Sahara. Interannual variation in the wet season rainfall is better simulated for the western Sahel than for the Ethiopian Highlands. RCM skill is higher for TAVG and TMAX than for TMIN, and regionally, for the subtropics than for the tropics. RCM skill in simulating cloudiness is generally lower than for precipitation or temperatures. For all variables, multi-model ensemble (ENS) generally outperforms individual models included in ENS. An overarching conclusion in this study is that some model biases vary systematically for regions, variables, and metrics, posing difficulties in defining a single representative index to measure model fidelity, especially for constructing ENS. This is an important concern in climate change impact assessment studies because most assessment models are run for specific regions/sectors with forcing data derived from model outputs. Thus, model evaluation and ENS construction must be performed separately for regions, variables, and metrics as required by specific analysis and/or assessments. Evaluations using multiple reference datasets reveal that cross-examination, quality control, and uncertainty estimates of reference data are crucial in model evaluations.

Spatiotemporal Phylogenetic Analysis and Molecular Characterisation of Infectious Bursal Disease Viruses Based on the VP2 Hyper-Variable Region

PubMed Central

Dolz, Roser; Valle, Rosa; Perera, Carmen L.; Bertran, Kateri; Frías, Maria T.; Majó, Natàlia; Ganges, Llilianne; Pérez, Lester J.

2013-01-01

Background Infectious bursal disease is a highly contagious and acute viral disease caused by the infectious bursal disease virus (IBDV); it affects all major poultry producing areas of the world. The current study was designed to rigorously measure the global phylogeographic dynamics of IBDV strains to gain insight into viral population expansion as well as the emergence, spread and pattern of the geographical structure of very virulent IBDV (vvIBDV) strains. Methodology/Principal Findings Sequences of the hyper-variable region of the VP2 (HVR-VP2) gene from IBDV strains isolated from diverse geographic locations were obtained from the GenBank database; Cuban sequences were obtained in the current work. All sequences were analysed by Bayesian phylogeographic analysis, implemented in the Bayesian Evolutionary Analysis Sampling Trees (BEAST), Bayesian Tip-association Significance testing (BaTS) and Spatial Phylogenetic Reconstruction of Evolutionary Dynamics (SPREAD) software packages. Selection pressure on the HVR-VP2 was also assessed. The phylogeographic association-trait analysis showed that viruses sampled from individual countries tend to cluster together, suggesting a geographic pattern for IBDV strains. Spatial analysis from this study revealed that strains carrying sequences that were linked to increased virulence of IBDV appeared in Iran in 1981 and spread to Western Europe (Belgium) in 1987, Africa (Egypt) around 1990, East Asia (China and Japan) in 1993, the Caribbean Region (Cuba) by 1995 and South America (Brazil) around 2000. Selection pressure analysis showed that several codons in the HVR-VP2 region were under purifying selection. Conclusions/Significance To our knowledge, this work is the first study applying the Bayesian phylogeographic reconstruction approach to analyse the emergence and spread of vvIBDV strains worldwide. PMID:23805195

Spatiotemporal Phylogenetic Analysis and Molecular Characterisation of Infectious Bursal Disease Viruses Based on the VP2 Hyper-Variable Region.

PubMed

Alfonso-Morales, Abdulahi; Martínez-Pérez, Orlando; Dolz, Roser; Valle, Rosa; Perera, Carmen L; Bertran, Kateri; Frías, Maria T; Majó, Natàlia; Ganges, Llilianne; Pérez, Lester J

2013-01-01

Infectious bursal disease is a highly contagious and acute viral disease caused by the infectious bursal disease virus (IBDV); it affects all major poultry producing areas of the world. The current study was designed to rigorously measure the global phylogeographic dynamics of IBDV strains to gain insight into viral population expansion as well as the emergence, spread and pattern of the geographical structure of very virulent IBDV (vvIBDV) strains. Sequences of the hyper-variable region of the VP2 (HVR-VP2) gene from IBDV strains isolated from diverse geographic locations were obtained from the GenBank database; Cuban sequences were obtained in the current work. All sequences were analysed by Bayesian phylogeographic analysis, implemented in the Bayesian Evolutionary Analysis Sampling Trees (BEAST), Bayesian Tip-association Significance testing (BaTS) and Spatial Phylogenetic Reconstruction of Evolutionary Dynamics (SPREAD) software packages. Selection pressure on the HVR-VP2 was also assessed. The phylogeographic association-trait analysis showed that viruses sampled from individual countries tend to cluster together, suggesting a geographic pattern for IBDV strains. Spatial analysis from this study revealed that strains carrying sequences that were linked to increased virulence of IBDV appeared in Iran in 1981 and spread to Western Europe (Belgium) in 1987, Africa (Egypt) around 1990, East Asia (China and Japan) in 1993, the Caribbean Region (Cuba) by 1995 and South America (Brazil) around 2000. Selection pressure analysis showed that several codons in the HVR-VP2 region were under purifying selection. To our knowledge, this work is the first study applying the Bayesian phylogeographic reconstruction approach to analyse the emergence and spread of vvIBDV strains worldwide.

PubMed

La Torre, Giuseppe; Verrengia, Giovanna; Saulle, Rossella; Kheiraoui, Flavia; Mannocci, Alice

2017-06-28

To identify the determinants of the regional differences in work injuries and mortality rates in Italy. Several linear regression models were built assessing the association between regional differences in work mortality and injury rates (as dependent variables) and socio-demographic factors (occupation and population) and variables describing alcohol consumption, mean age and availability of health care (as independent variables). Data sources are from ISTAT, INAIL, Health for All database and the national report Osservasalute. The analysis was carried out using data coming from all the Italian Regions. The mean work mortality rate for the period 2006-2014 was 7.73 (DS 1.85) per 100,000 workers, while the injury rate was 4503.1 (DS 1413.5) per 100,000 workers. Socio-demographic variables and that related to health care (TC availability) were inversely associated with mortality rates, while for the work injury rates, significant associations with alcohol were found, while Gross domestic product and TC availability were inversely associated. The study pointed out the extreme heterogeneity between different geographical areas in the field of work injury, due to different socio-demographic and economic factors. In the future, health surveillance and work injury and mortality rates could be improved in areas at high risk.

A method for analyzing temporal patterns of variability of a time series from Poincare plots.

PubMed

Fishman, Mikkel; Jacono, Frank J; Park, Soojin; Jamasebi, Reza; Thungtong, Anurak; Loparo, Kenneth A; Dick, Thomas E

2012-07-01

The Poincaré plot is a popular two-dimensional, time series analysis tool because of its intuitive display of dynamic system behavior. Poincaré plots have been used to visualize heart rate and respiratory pattern variabilities. However, conventional quantitative analysis relies primarily on statistical measurements of the cumulative distribution of points, making it difficult to interpret irregular or complex plots. Moreover, the plots are constructed to reflect highly correlated regions of the time series, reducing the amount of nonlinear information that is presented and thereby hiding potentially relevant features. We propose temporal Poincaré variability (TPV), a novel analysis methodology that uses standard techniques to quantify the temporal distribution of points and to detect nonlinear sources responsible for physiological variability. In addition, the analysis is applied across multiple time delays, yielding a richer insight into system dynamics than the traditional circle return plot. The method is applied to data sets of R-R intervals and to synthetic point process data extracted from the Lorenz time series. The results demonstrate that TPV complements the traditional analysis and can be applied more generally, including Poincaré plots with multiple clusters, and more consistently than the conventional measures and can address questions regarding potential structure underlying the variability of a data set.

Giovanni: The Bridge between Data and Science

NASA Technical Reports Server (NTRS)

Shen, Suhung; Lynnes, Christopher; Kempler, Steven J.

2012-01-01

NASA Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a web-based remote sensing and model data visualization and analysis system developed by the Goddard Earth Sciences Data and Information Services Center (GES DISC). This web-based tool facilitates data discovery, exploration and analysis of large amount of global and regional data sets, covering atmospheric dynamics, atmospheric chemistry, hydrology, oceanographic, and land surface. Data analysis functions include Lat-Lon map, time series, scatter plot, correlation map, difference, cross-section, vertical profile, and animation etc. Visualization options enable comparisons of multiple variables and easier refinement. Recently, new features have been developed, such as interactive scatter plots and maps. The performance is also being improved, in some cases by an order of magnitude for certain analysis functions with optimized software. We are working toward merging current Giovanni portals into a single omnibus portal with all variables in one (virtual) location to help users find a variable easily and enhance the intercomparison capability

Quantitative Ultrasound Using Texture Analysis of Myofascial Pain Syndrome in the Trapezius.

PubMed

Kumbhare, Dinesh A; Ahmed, Sara; Behr, Michael G; Noseworthy, Michael D

2018-01-01

Objective-The objective of this study is to assess the discriminative ability of textural analyses to assist in the differentiation of the myofascial trigger point (MTrP) region from normal regions of skeletal muscle. Also, to measure the ability to reliably differentiate between three clinically relevant groups: healthy asymptomatic, latent MTrPs, and active MTrP. Methods-18 and 19 patients were identified with having active and latent MTrPs in the trapezius muscle, respectively. We included 24 healthy volunteers. Images were obtained by research personnel, who were blinded with respect to the clinical status of the study participant. Histograms provided first-order parameters associated with image grayscale. Haralick, Galloway, and histogram-related features were used in texture analysis. Blob analysis was conducted on the regions of interest (ROIs). Principal component analysis (PCA) was performed followed by multivariate analysis of variance (MANOVA) to determine the statistical significance of the features. Results-92 texture features were analyzed for factorability using Bartlett's test of sphericity, which was significant. The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.94. PCA demonstrated rotated eigenvalues of the first eight components (each comprised of multiple texture features) explained 94.92% of the cumulative variance in the ultrasound image characteristics. The 24 features identified by PCA were included in the MANOVA as dependent variables, and the presence of a latent or active MTrP or healthy muscle were independent variables. Conclusion-Texture analysis techniques can discriminate between the three clinically relevant groups.

Characterizing the Influence of the General Circulation on Marine Boundary Layer Clouds

NASA Technical Reports Server (NTRS)

Rozendaal, Margaret A.; Rossow, William B.; Hansen, James E. (Technical Monitor)

2001-01-01

The seasonal and intraseasonal variability of boundary layer cloud in the subtropical eastern oceans are studied using combined data from the International Satellite Cloud Climatology Project (ISCCP) and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis. Spectral analysis reveals that most of the time variability of cloud properties occurs on seasonal to annual time scales. The variance decreases one to two orders of magnitude for each decade of time scale decrease, indicating that daily to monthly time scales have smaller, but non-negligible variability. The length of these dominant time scales suggests that the majority of the variability is influenced by the general circulation and its interaction with boundary layer turbulence, rather than a product of boundary layer turbulence alone. Previous datasets have lacked the necessary resolution in either time or in space to properly characterize variability on synoptic scales; this is remedied by using global satellite-retrieved cloud properties. We characterize the intraseasonal subtropical cloud variability in both hemispheres and in different seasons. In addition to cloud fraction, we examine variability of cloud optical thickness - cloud top pressure frequency distributions. Despite the large concentration of research on the variability of Northern Hemisphere (NH) regions during summer, it is noted that the largest amplitude intraseasonal variability in the NH regions occurs during local winter. The effect of intraseasonal variability on the calculation and interpretation of seasonal results is investigated. Decreases in seasonally averaged cloud cover, optical thickness and cloud top pressure from the May-through-September season to the November-through-March season are most apparent in the NH regions. Further analysis indicates that these changes are due to an increase in frequency, but a decrease in the persistence of synoptic events. In addition, changes in cloud top pressure and optical thickness characteristics from the summer to winter seasons indicate that the NH subtropics undergo a change in dynamic regime with season. This change appears in the cloud fields as a shift from the more commonly seen lower-altitude, thicker optical thickness clouds to higher-altitude, thinner clouds. The latter cloud-type is associated with the lower sea level pressure, upward vertical velocity phase of the synoptic wave. Intraseasonal changes in cloud properties in the Southern Hemisphere and NH summer are much smaller in amplitude. Although they also appear to be linked to changes in the large-scale dynamics, similarly to NH winter variations, the relationships are more ambiguous due to the small amplitudes and longer time scales. We attempt to interpret some of these relationships using the results of the Betts and Ridgway (1989) box model. However, these results cannot consistently explain the patterns when results from all regions are considered, implying that this model may not adequately explain all the processes involved in the variability.

Air Pollutants, Climate, and the Prevalence of Pediatric Asthma in Urban Areas of China

PubMed Central

Zhang, Juanjuan; Yan, Li; Fu, Wenlong; Yi, Jing; Chen, Yuzhi; Liu, Chuanhe; Xu, Dongqun; Wang, Qiang

2016-01-01

Background. Prevalence of childhood asthma varies significantly among regions, while its reasons are not clear yet with only a few studies reporting relevant causes for this variation. Objective. To investigate the potential role of city-average levels of air pollutants and climatic factors in order to distinguish differences in asthma prevalence in China and explain their reasons. Methods. Data pertaining to 10,777 asthmatic patients were obtained from the third nationwide survey of childhood asthma in China's urban areas. Annual mean concentrations of air pollutants and other climatic factors were obtained for the same period from several government departments. Data analysis was implemented with descriptive statistics, Pearson correlation coefficient, and multiple regression analysis. Results. Pearson correlation analysis showed that the situation of childhood asthma was strongly linked with SO2, relative humidity, and hours of sunshine (p < 0.05). Multiple regression analysis indicated that, among the predictor variables in the final step, SO2 was found to be the most powerful predictor variable amongst all (β = −19.572, p < 0.05). Furthermore, results had shown that hours of sunshine (β = −0.014, p < 0.05) was a significant component summary predictor variable. Conclusion. The findings of this study do not suggest that air pollutants or climate, at least in terms of children, plays a major role in explaining regional differences in asthma prevalence in China. PMID:27556031

ENSO modulation of tropical Indian Ocean subseasonal variability

NASA Astrophysics Data System (ADS)

Jung, Eunsil; Kirtman, Ben P.

2016-12-01

In this study, we use 30 years of retrospective climate model forecasts and observational estimates to show that El Niño/Southern Oscillation (ENSO) affects the amplitude of subseasonal variability of sea surface temperature (SST) in the southwest Indian Ocean, an important Tropical Intraseasonal Oscillation (TISO) onset region. The analysis shows that deeper background mixed-layer depths and warmer upper ocean conditions during El Niño reduce the amplitude of the subseasonal SST variability over Seychelles-Chagos Thermocline Ridge (SCTR), which may reduce SST-wind coupling and the amplitude of TISO variability. The opposite holds for La Niña where the shallower mixed-layer depth enhances SST variability over SCTR, which may increase SST-wind coupling and the amplitude of TISO variability.

Validity analysis on merged and averaged data using within and between analysis: focus on effect of qualitative social capital on self-rated health.

PubMed

Shin, Sang Soo; Shin, Young-Jeon

2016-01-01

With an increasing number of studies highlighting regional social capital (SC) as a determinant of health, many studies are using multi-level analysis with merged and averaged scores of community residents' survey responses calculated from community SC data. Sufficient examination is required to validate if the merged and averaged data can represent the community. Therefore, this study analyzes the validity of the selected indicators and their applicability in multi-level analysis. Within and between analysis (WABA) was performed after creating community variables using merged and averaged data of community residents' responses from the 2013 Community Health Survey in Korea, using subjective self-rated health assessment as a dependent variable. Further analysis was performed following the model suggested by WABA result. Both E-test results (1) and WABA results (2) revealed that single-level analysis needs to be performed using qualitative SC variable with cluster mean centering. Through single-level multivariate regression analysis, qualitative SC with cluster mean centering showed positive effect on self-rated health (0.054, p<0.001), although there was no substantial difference in comparison to analysis using SC variables without cluster mean centering or multi-level analysis. As modification in qualitative SC was larger within the community than between communities, we validate that relational analysis of individual self-rated health can be performed within the group, using cluster mean centering. Other tests besides the WABA can be performed in the future to confirm the validity of using community variables and their applicability in multi-level analysis.

Potential Impact of North Atlantic Climate Variability on Ocean Biogeochemical Processes

NASA Astrophysics Data System (ADS)

Liu, Y.; Muhling, B.; Lee, S. K.; Muller-Karger, F. E.; Enfield, D. B.; Lamkin, J. T.; Roffer, M. A.

2016-02-01

Previous studies have shown that upper ocean circulations largely determine primary production in the euphotic layers, here the global ocean model with biogeochemistry (GFDL's Modular Ocean Model with TOPAZ biogeochemistry) forced with the ERA-Interim is used to simulate the natural variability of biogeochemical processes in global ocean during 1979-present. Preliminary results show that the surface chlorophyll is overall underestimated in MOM-TOPAZ, but its spatial pattern is fairly realistic. Relatively high chlorophyll variability is shown in the subpolar North Atlantic, northeastern tropical Atlantic, and equatorial Atlantic. Further analysis suggests that the chlorophyll variability in the North Atlantic Ocean is affected by long-term climate variability. For the subpolar North Atlantic region, the chlorophyll variability is light-limited and is significantly correlated with North Atlantic Oscillation. A dipole pattern of chlorophyll variability is found between the northeastern tropical Atlantic and equatorial Atlantic. For the northeastern North Atlantic, the chlorophyll variability is significantly correlated with Atlantic Meridional Mode (AMM) and Atlantic Multidecadal Oscillation (AMO). During the negative phase of AMM and AMO, the increased trade wind in the northeast North Atlantic can lead to increased upwelling of nutrients. In the equatorial Atlantic region, the chlorophyll variability is largely link to Atlantic-Niño and associated equatorial upwelling of nutrients. The potential impact of climate variability on the distribution of pelagic fishes (i.e. yellowfin tuna) are discussed.

Bacterial diversity of Taxus rhizosphere: culture-independent and culture-dependent approaches.

PubMed

Hao, Da Cheng; Ge, Guang Bo; Yang, Ling

2008-07-01

The regional variability of Taxus rhizosphere bacterial community composition and diversity was studied by comparative analysis of three large 16S rRNA gene clone libraries from the Taxus rhizosphere in different regions of China (subtropical and temperate regions). One hundred and forty-six clones were screened for three libraries. Phylogenetic analysis of 16S rRNA gene sequences demonstrated that the abundance of sequences affiliated with Gammaproteobacteria, Betaproteobacteria, and Actinobacteria was higher in the library from the T. xmedia rhizosphere of the temperate region compared with the subtropical Taxus mairei rhizosphere. On the other hand, Acidobacteria was more abundant in libraries from the subtropical Taxus mairei rhizosphere. Richness estimates and diversity indices of three libraries revealed major differences, indicating a higher richness in the Taxus rhizosphere bacterial communities of the subtropical region and considerable variability in the bacterial community composition within this region. By enrichment culture, a novel Actinobacteria strain DICP16 was isolated from the T. xmedia rhizosphere of the temperate region and was identified as Leifsonia shinshuensis sp. via 16S rRNA gene and gyrase B sequence analyses. DICP16 was able to remove the xylosyl group from 7-xylosyl-10-deacetylbaccatin III and 7-xylosyl-10-deacetylpaclitaxel, thereby making the xylosyltaxanes available as sources of 10-deacetylbaccatin III and the anticancer drug paclitaxel. Taken together, the present studies provide, for the first time, the knowledge of the biodiversity of microorganisms populating Taxus rhizospheres.

A meta-analysis of plant facilitation in coastal dune systems: responses, regions, and research gaps.

PubMed

Castanho, Camila de Toledo; Lortie, Christopher J; Zaitchik, Benjamin; Prado, Paulo Inácio

2015-01-01

Empirical studies in salt marshes, arid, and alpine systems support the hypothesis that facilitation between plants is an important ecological process in severe or 'stressful' environments. Coastal dunes are both abiotically stressful and frequently disturbed systems. Facilitation has been documented, but the evidence to date has not been synthesized. We did a systematic review with meta-analysis to highlight general research gaps in the study of plant interactions in coastal dunes and examine if regional and local factors influence the magnitude of facilitation in these systems. The 32 studies included in the systematic review were done in coastal dunes located in 13 countries around the world but the majority was in the temperate zone (63%). Most of the studies adopt only an observational approach to make inferences about facilitative interactions, whereas only 28% of the studies used both observational and experimental approaches. Among the factors we tested, only geographic region mediates the occurrence of facilitation more broadly in coastal dune systems. The presence of a neighbor positively influenced growth and survival in the tropics, whereas in temperate and subartic regions the effect was neutral for both response variables. We found no evidence that climatic and local factors, such as life-form and life stage of interacting plants, affect the magnitude of facilitation in coastal dunes. Overall, conclusions about plant facilitation in coastal dunes depend on the response variable measured and, more broadly, on the geographic region examined. However, the high variability and the limited number of studies, especially in tropical region, indicate we need to be cautious in the generalization of the conclusions. Anyway, coastal dunes provide an important means to explore topical issues in facilitation research including context dependency, local versus regional drivers of community structure, and the importance of gradients in shaping the outcome of net interactions.

A segmentation approach for a delineation of terrestrial ecoregions

NASA Astrophysics Data System (ADS)

Nowosad, J.; Stepinski, T.

2017-12-01

Terrestrial ecoregions are the result of regionalization of land into homogeneous units of similar ecological and physiographic features. Terrestrial Ecoregions of the World (TEW) is a commonly used global ecoregionalization based on expert knowledge and in situ observations. Ecological Land Units (ELUs) is a global classification of 250 meters-sized cells into 4000 types on the basis of the categorical values of four environmental variables. ELUs are automatically calculated and reproducible but they are not a regionalization which makes them impractical for GIS-based spatial analysis and for comparison with TEW. We have regionalized terrestrial ecosystems on the basis of patterns of the same variables (land cover, soils, landform, and bioclimate) previously used in ELUs. Considering patterns of categorical variables makes segmentation and thus regionalization possible. Original raster datasets of the four variables are first transformed into regular grids of square-sized blocks of their cells called eco-sites. Eco-sites are elementary land units containing local patterns of physiographic characteristics and thus assumed to contain a single ecosystem. Next, eco-sites are locally aggregated using a procedure analogous to image segmentation. The procedure optimizes pattern homogeneity of all four environmental variables within each segment. The result is a regionalization of the landmass into land units characterized by uniform pattern of land cover, soils, landforms, climate, and, by inference, by uniform ecosystem. Because several disjoined segments may have very similar characteristics, we cluster the segments to obtain a smaller set of segment types which we identify with ecoregions. Our approach is automatic, reproducible, updatable, and customizable. It yields the first automatic delineation of ecoregions on the global scale. In the resulting vector database each ecoregion/segment is described by numerous attributes which make it a valuable GIS resource for global ecological and conservation studies.

[Variability in the in-hospital management of acute myocardial infarction in Spain. IBERICA Study (Investigación, Búsqueda Específica y Registro de Isquemia Coronaria Aguda)].

PubMed

Fiol, M; Cabadés, A; Sala, J; Marrugat, J; Elosua, R; Vega, G; José Tormo Díaz, M; Segura, A; Aldasoro, E; Moreno-Iribas, C; Muñiz, J; Hurtado de Saracho, I; García, J

2001-04-01

Introduction and objective. Although some in-hospital studies have described the management of acute myocardial infarction (MI) patients in Spain, none has been able to guarantee the exhaustiveness of patient registry. This study sought to determine the clinical characteristics and in-hospital management of patients with MI in eight Spanish population registries.Methods. The IBERICA study is a population-based MI registry carried out in the 25 to 74 year-old population, in eight Spanish regions in 1997. A standardized methodology was used to register and investigate all MI arriving alive to a hospital. Clinical characteristics, cardiovascular risk factors prevalence, pharmacological treatment, invasive and non-invasive procedures performed and complications at 28 days of evolution were recorded. A descriptive analysis was performed and the variation coefficient (VC) was calculated.Results. In 1997, 4,041 MI patients were registered, 79.9% were men with a mean age of 61.1 years. Although 10.9% (95% CI: 9.9-11.9%) were not admitted to the coronary care unit, a large variability existed among different areas (VC = 53%). There was a high variability in the utilization and performance of non-invasive and invasive procedures among regions, as well as in the use of pharmacological treatment. Only the use of antiaggregants (91.5%) and thrombolytic therapy (41.8%) showed a low variability (VC < 10%). Twenty-eight day mortality was 16.2% (95% CI: 15.1-17.4%) with a high variability being observed among the different regions (VC = 20.6%).Conclusion. Patient characteristics vary among the different Spanish regions. The differences in management and prognosis suggest a lack of equality in the health care provided to MI patients in the different regions in Spain.

Thin-film hermeticity - A quantitative analysis of diamondlike carbon using variable angle spectroscopic ellipsometry

NASA Technical Reports Server (NTRS)

Orzeszko, S.; De, Bhola N.; Woollam, John A.; Pouch, John J.; Alterovitz, Samuel A.

1988-01-01

This paper reports on the successful application of variable-angle spectroscopic ellipsometry to quantitative thin-film hermeticity evaluation. It is shown that, under a variety of film preparations and moisture introduction conditions, water penetrates only a very thin diamondlike carbon (DLC) top surface-roughness region. Thus, DLC is an excellent candidate for use as protective coatings in adverse chemical and aqueous environments.

North Atlantic storm track variability and its association to the North Atlantic oscillation and climate variability of northern Europe

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rogers, J.C.

The primary mode of North Atlantic track variability is identified using rotated principal component analysis (RPCA) on monthly fields of root-mean-squares of daily high-pass filtered (2-8-day periods) sea level pressures (SLP) for winters (December-February) 1900-92. It is examined in terms of its association with (1) monthly mean SLP fields, (2) regional low-frequency teleconnections, and (3) the seesaw in winter temperatures between Greenland and northern Europe. 32 refs., 9 figs.

Temporary disaster debris management site identification using binomial cluster analysis and GIS.

PubMed

Grzeda, Stanislaw; Mazzuchi, Thomas A; Sarkani, Shahram

2014-04-01

An essential component of disaster planning and preparation is the identification and selection of temporary disaster debris management sites (DMS). However, since DMS identification is a complex process involving numerous variable constraints, many regional, county and municipal jurisdictions initiate this process during the post-disaster response and recovery phases, typically a period of severely stressed resources. Hence, a pre-disaster approach in identifying the most likely sites based on the number of locational constraints would significantly contribute to disaster debris management planning. As disasters vary in their nature, location and extent, an effective approach must facilitate scalability, flexibility and adaptability to variable local requirements, while also being generalisable to other regions and geographical extents. This study demonstrates the use of binomial cluster analysis in potential DMS identification in a case study conducted in Hamilton County, Indiana. © 2014 The Author(s). Disasters © Overseas Development Institute, 2014.

Surface-air mercury fluxes across Western North America: A synthesis of spatial trends and controlling variables

USGS Publications Warehouse

Eckley, Chris S.; Tate, Michael T.; Lin, Che-Jen; Gustin, Mae S.; Dent, Stephen; Eagles-Smith, Collin A.; Lutz, Michelle A; Wickland, Kimberly; Wang, Bronwen; Gray, John E.; Edwards, Grant; Krabbenhoft, David P.; Smith, David

2016-01-01

Mercury (Hg) emission and deposition can occur to and from soils, and are an important component of the global atmospheric Hg budget. This paper focuses on synthesizing existing surface-air Hg flux data collected throughout the Western North American region and is part of a series of geographically focused Hg synthesis projects. A database of existing Hg flux data collected using the dynamic flux chamber (DFC) approach from almost a thousand locations was created for the Western North America region. Statistical analysis was performed on the data to identify the important variables controlling Hg fluxes and to allow spatiotemporal scaling. The results indicated that most of the variability in soil-air Hg fluxes could be explained by variations in soil-Hg concentrations, solar radiation, and soil moisture. This analysis also identified that variations in DFC methodological approaches were detectable among the field studies, with the chamber material and sampling flushing flow rate influencing the magnitude of calculated emissions. The spatiotemporal scaling of soil-air Hg fluxes identified that the largest emissions occurred from irrigated agricultural landscapes in California. Vegetation was shown to have a large impact on surface-air Hg fluxes due to both a reduction in solar radiation reaching the soil as well as from direct uptake of Hg in foliage. Despite high soil Hg emissions from some forested and other heavily vegetated regions, the net ecosystem flux (soil flux + vegetation uptake) was low. Conversely, sparsely vegetated regions showed larger net ecosystem emissions, which were similar in magnitude to atmospheric Hg deposition (except for the Mediterranean California region where soil emissions were higher). The net ecosystem flux results highlight the important role of landscape characteristics in effecting the balance between Hg sequestration and (re-)emission to the atmosphere.

Surface-Air Mercury Fluxes Across Western North America: A Synthesis of Spatial Trends and Controlling Variables.

NASA Astrophysics Data System (ADS)

Eckley, C.; Tate, M.; Lin, C. J.; Gustin, M. S.; Dent, S.; Eagles-Smith, C.; Lutz, M.; Wickland, K.; Wang, B.; Gray, J.; Edwards, G. C.; Krabbenhoft, D. P.; Smith, D. B.

2016-12-01

Mercury (Hg) emission and deposition can occur to and from soils and are an important component of the global atmospheric Hg budget. This presentation focuses on synthesizing existing surface-air Hg flux data collected throughout the Western North American region and is part of a series of geographically focused Hg synthesis projects. A database of existing Hg flux data collected using the dynamic flux chamber (DFC) approach from almost a thousand locations was created for the Western North America region. Statistical analysis was performed on the data to identify the important variables controlling Hg fluxes and to allow spatiotemporal scaling. The results indicated that most of the variability in soil-air Hg fluxes could be explained by variations in soil-Hg concentrations, solar radiation, and soil moisture. This analysis also identified that variations in DFC methodological approaches were detectable among the field studies, with the chamber material and sampling flushing flow rate influencing the magnitude of calculated emissions. The spatiotemporal scaling of soil-air Hg fluxes identified that the largest emissions occurred from irrigated agricultural landscapes in California. Vegetation was shown to have a large impact on surface-air Hg fluxes due to both a reduction in solar radiation reaching the soil as well as from direct uptake of Hg in foliage. Despite high soil Hg emissions from some forested and other heavily vegetated regions, the net ecosystem flux (soil flux + vegetation uptake) was low. Conversely, sparsely vegetated regions showed larger net ecosystem emissions, which were similar in magnitude to atmospheric Hg deposition (except for the Mediterranean California region where soil emissions were higher). The net ecosystem flux results highlight the important role of landscape characteristics in effecting the balance between Hg sequestration and (re-)emission to the atmosphere.

Land Change Trends in the Great Plains: Linkages to Climate Variability and Socioeconomic Drivers

NASA Astrophysics Data System (ADS)

Drummond, M. A.

2009-12-01

Land use and land cover change have complex linkages to climate variability and change, socioeconomic driving forces, and land management challenges. To assess these land change dynamics and their driving forces in the Great Plains, we compare and contrast contemporary land conversion across seventeen ecoregions using Landsat remote sensing data and statistical analysis. Large area change analysis in agricultural regions is often hampered by the potential for substantial change detection error and the tendency for land conversions to occur in relatively small patches at the local level. To facilitate a regional scale analysis, a statistical sampling design of randomly selected 10-km by 10-km blocks is used in order to efficiently identify the types and rates of land conversions for four time periods between 1972 and 2000, stratified by relatively homogenous ecoregions. Results show a range of rates and processes of land change that vary by ecoregion contingent on the prevailing interactions between socioeconomic and environmental factors such as climate variability, water availability, and land quality. Ecoregions have differential climate and biophysical advantages for agricultural production and other land use change. Human actions further strengthen or dampen the characteristics of change through farm policy, technological advances, economic opportunities, population and demographic shifts, and surface and groundwater irrigation.

The Influence of ENSO to the Rainfall Variability in North Sumatra Province

NASA Astrophysics Data System (ADS)

Irwandi, H.; Pusparini, N.; Ariantono, J. Y.; Kurniawan, R.; Tari, C. A.; Sudrajat, A.

2018-04-01

The El Niño Southern Oscillation (ENSO) is a global phenomenon that affects the variability of rainfall in North Sumatra. The influence of ENSO will be different for each region. This review will analyse the influence of ENSO activity on seasonal and annual rainfall variability. In this research, North Sumatra Province will be divided into 4 (four) regions based on topographical conditions, such as: East Coast (EC), East Slope (ES), Mountains (MT), and West Coast (WC). The method used was statistical and descriptive analysis. Data used in this research were rainfall data from 15 stations / climate observation posts which spread in North Sumatera region and also anomaly data of Nino 3.4 region from period 1981-2016. The results showed that the active El Niño had an effect on the decreasing the rainfall during the period of DJF, JJA and SON in East Coast, East Slope, and Mountains with the decreasing of average percentage of annual rainfall up to 7%. On the contrary, the active La Nina had an effect on the addition of rainfall during the period DJF and JJA in the East Coast and Mountains with the increasing of average percentage of annual rainfall up to 6%.

Annual precipitation in the Yellowstone National Park region since AD 1173

USGS Publications Warehouse

Gray, Stephen T.; Graumlich, Lisa J.; Betancourt, Julio L.

2007-01-01

Cores and cross sections from 133 limber pine (Pinus flexilis James) and Douglas fir (Pseudotsuga menziesii (Mirbel) Franco) at four sites were used to estimate annual (July to June) precipitation in the Yellowstone National Park region for the period from AD 1173 to 1998. Examination of the long-term record shows that the early 20th century was markedly wet compared to the previous 700 yr. Extreme wet and dry years within the instrumental period fall within the range of past variability, and the magnitude of the worst-case droughts of the 20th century (AD 1930s and 1950s) was likely equaled or exceeded on numerous occasions before AD 1900. Spectral analysis showed significant decadal to multidecadal precipitation variability. At times this lower frequency variability produces strong regime-like behavior in regional precipitation, with the potential for rapid, high-amplitude switching between predominately wet and predominately dry conditions. Over multiple time scales, strong Yellowstone region precipitation anomalies were almost always associated with spatially extensive events spanning various combinations of the central and southern U.S. Rockies, the northern U.S.-Southern Canadian Rockies and the Pacific Northwest.

Annual precipitation in the Yellowstone National Park region since AD 1173

USGS Publications Warehouse

Gray, S.T.; Graumlich, L.J.; Betancourt, J.L.

2007-01-01

Cores and cross sections from 133 limber pine (Pinus flexilis James) and Douglas fir (Pseudotsuga menziesii (Mirbel) Franco) at four sites were used to estimate annual (July to June) precipitation in the Yellowstone National Park region for the period from AD 1173 to 1998. Examination of the long-term record shows that the early 20th century was markedly wet compared to the previous 700??yr. Extreme wet and dry years within the instrumental period fall within the range of past variability, and the magnitude of the worst-case droughts of the 20th century (AD 1930s and 1950s) was likely equaled or exceeded on numerous occasions before AD 1900. Spectral analysis showed significant decadal to multidecadal precipitation variability. At times this lower frequency variability produces strong regime-like behavior in regional precipitation, with the potential for rapid, high-amplitude switching between predominately wet and predominately dry conditions. Over multiple time scales, strong Yellowstone region precipitation anomalies were almost always associated with spatially extensive events spanning various combinations of the central and southern U.S. Rockies, the northern U.S.-Southern Canadian Rockies and the Pacific Northwest. ?? 2007 University of Washington.

Perceptions of primary health care service users regarding dental team practices in Brazil.

PubMed

Baumgarten, Alexandre; Veiga, Rochelle Santos Da; Bulgarelli, Patricia Tavora; Diesel, Vitor Motta; Bulgarelli, Alexandre Favero

2018-05-01

The Unified Health System (SUS) is the Brazilian set of public health services that offers global access to health care and disease treatments for all citizens. These services have been evaluated by means of a national survey assessing the users' perceptions.AimTo explore and characterize the SUS users' perceptions regarding primary dental team practices in the five Brazilian geographical regions. Descriptive study. The sample consisted of 37 262 subjects. Data were collected by means of the Ministry of Health survey, conducted between 2012 and 2014. Variables used in the present study are associated with SUS users' perspectives of satisfaction, access, and use of services. The study utilized bivariate data analysis, and dichotomous variables were derived for analysis following 95% reliability.FindingsThis study observed similarities and proportionality of perceptions in the Brazilian territory. In most macro-regions, dental teams did not develop an active search for dental treatment absentees. However, the SUS users reported very good and good perceptions, which were homogeneously distributed across five Brazilian regions, thereby showing an overall positive perception of primary dental treatment.

Internal Variability-Generated Uncertainty in East Asian Climate Projections Estimated with 40 CCSM3 Ensembles.

PubMed

Yao, Shuai-Lei; Luo, Jing-Jia; Huang, Gang

2016-01-01

Regional climate projections are challenging because of large uncertainty particularly stemming from unpredictable, internal variability of the climate system. Here, we examine the internal variability-induced uncertainty in precipitation and surface air temperature (SAT) trends during 2005-2055 over East Asia based on 40 member ensemble projections of the Community Climate System Model Version 3 (CCSM3). The model ensembles are generated from a suite of different atmospheric initial conditions using the same SRES A1B greenhouse gas scenario. We find that projected precipitation trends are subject to considerably larger internal uncertainty and hence have lower confidence, compared to the projected SAT trends in both the boreal winter and summer. Projected SAT trends in winter have relatively higher uncertainty than those in summer. Besides, the lower-level atmospheric circulation has larger uncertainty than that in the mid-level. Based on k-means cluster analysis, we demonstrate that a substantial portion of internally-induced precipitation and SAT trends arises from internal large-scale atmospheric circulation variability. These results highlight the importance of internal climate variability in affecting regional climate projections on multi-decadal timescales.

Relative Sea Level Trends Along the Coast of the Bay of Bengal

NASA Astrophysics Data System (ADS)

Becker, M.; Calmant, S.; Papa, F.; Delebecque, C.; Islam, A. S.; Shum, C. K.

2016-12-01

In the coastal belt of the Bay of Bengal, the sea level rise is one of a major threat, linked to climate change, which drastically affects the livelihoods of millions of people. A comprehensive understanding of sea level trends and its variability in this region is therefore crucial and should help to anticipate the impacts of climate change and implement adaptation strategies. This region is bordered mostly by Bangladesh, India, Malaysia, Myanmar, and Thailand. Here, we revisit the sea level changes in the Bay of Bengal region from tide gauges and satellite altimetry over the period 1993-2014. The 23 monthly mean tide gauge records, used in this study, are retrieved from PSMSL (15 records) and supplemented with Bangladeshi observations (8 records). We show that, over the satellite altimetry era, the sea level interannual/decadal variability is mainly due to ocean thermal expansion variability driven by IOD/ENSO events and their low frequency modulation. We focus on relative sea level rise at major coastal cities and try to separate the climatic signal (long term trend plus interannual/decadal variability) from local effects, in particular vertical land movements. Results from GPS are analysed where available. When no such data exist, vertical land movements are deduced from the combined use of tide gauge and altimetry data. While the analysis is performed over the whole region, a particular attention is given to the low-lyingBangladesh's coastal area.

Importance of Viral Sequence Length and Number of Variable and Informative Sites in Analysis of HIV Clustering.

PubMed

Novitsky, Vlad; Moyo, Sikhulile; Lei, Quanhong; DeGruttola, Victor; Essex, M

2015-05-01

To improve the methodology of HIV cluster analysis, we addressed how analysis of HIV clustering is associated with parameters that can affect the outcome of viral clustering. The extent of HIV clustering and tree certainty was compared between 401 HIV-1C near full-length genome sequences and subgenomic regions retrieved from the LANL HIV Database. Sliding window analysis was based on 99 windows of 1,000 bp and 45 windows of 2,000 bp. Potential associations between the extent of HIV clustering and sequence length and the number of variable and informative sites were evaluated. The near full-length genome HIV sequences showed the highest extent of HIV clustering and the highest tree certainty. At the bootstrap threshold of 0.80 in maximum likelihood (ML) analysis, 58.9% of near full-length HIV-1C sequences but only 15.5% of partial pol sequences (ViroSeq) were found in clusters. Among HIV-1 structural genes, pol showed the highest extent of clustering (38.9% at a bootstrap threshold of 0.80), although it was significantly lower than in the near full-length genome sequences. The extent of HIV clustering was significantly higher for sliding windows of 2,000 bp than 1,000 bp. We found a strong association between the sequence length and proportion of HIV sequences in clusters, and a moderate association between the number of variable and informative sites and the proportion of HIV sequences in clusters. In HIV cluster analysis, the extent of detectable HIV clustering is directly associated with the length of viral sequences used, as well as the number of variable and informative sites. Near full-length genome sequences could provide the most informative HIV cluster analysis. Selected subgenomic regions with a high extent of HIV clustering and high tree certainty could also be considered as a second choice.

Importance of Viral Sequence Length and Number of Variable and Informative Sites in Analysis of HIV Clustering

PubMed Central

Novitsky, Vlad; Moyo, Sikhulile; Lei, Quanhong; DeGruttola, Victor

2015-01-01

Abstract To improve the methodology of HIV cluster analysis, we addressed how analysis of HIV clustering is associated with parameters that can affect the outcome of viral clustering. The extent of HIV clustering and tree certainty was compared between 401 HIV-1C near full-length genome sequences and subgenomic regions retrieved from the LANL HIV Database. Sliding window analysis was based on 99 windows of 1,000 bp and 45 windows of 2,000 bp. Potential associations between the extent of HIV clustering and sequence length and the number of variable and informative sites were evaluated. The near full-length genome HIV sequences showed the highest extent of HIV clustering and the highest tree certainty. At the bootstrap threshold of 0.80 in maximum likelihood (ML) analysis, 58.9% of near full-length HIV-1C sequences but only 15.5% of partial pol sequences (ViroSeq) were found in clusters. Among HIV-1 structural genes, pol showed the highest extent of clustering (38.9% at a bootstrap threshold of 0.80), although it was significantly lower than in the near full-length genome sequences. The extent of HIV clustering was significantly higher for sliding windows of 2,000 bp than 1,000 bp. We found a strong association between the sequence length and proportion of HIV sequences in clusters, and a moderate association between the number of variable and informative sites and the proportion of HIV sequences in clusters. In HIV cluster analysis, the extent of detectable HIV clustering is directly associated with the length of viral sequences used, as well as the number of variable and informative sites. Near full-length genome sequences could provide the most informative HIV cluster analysis. Selected subgenomic regions with a high extent of HIV clustering and high tree certainty could also be considered as a second choice. PMID:25560745

A genetic variant in the LDLR promoter is responsible for part of the LDL-cholesterol variability in primary hypercholesterolemia

PubMed Central

2014-01-01

Background GWAS have consistently revealed that LDLR locus variability influences LDL-cholesterol in general population. Severe LDLR mutations are responsible for familial hypercholesterolemia (FH). However, most primary hypercholesterolemias are polygenic diseases. Although Cis-regulatory regions might be the cause of LDL-cholesterol variability; an extensive analysis of the LDLR distal promoter has not yet been performed. We hypothesized that genetic variants in this region are responsible for the LDLR association with LDL-cholesterol found in GWAS. Methods Four-hundred seventy-seven unrelated subjects with polygenic hypercholesterolemia (PH) and without causative FH-mutations and 525 normolipemic subjects were selected. A 3103 pb from LDLR (-625 to +2468) was sequenced in 125 subjects with PH. All subjects were genotyped for 4 SNPs (rs17242346, rs17242739, rs17248720 and rs17249120) predicted to be potentially involved in transcription regulation by in silico analysis. EMSA and luciferase assays were carried out for the rs17248720 variant. Multivariable linear regression analysis using LDL-cholesterol levels as the dependent variable were done in order to find out the variables that were independently associated with LDL-cholesterol. Results The sequencing of the 125 PH subjects did not show variants with minor allele frequency ≥ 10%. The T-allele from g.3131C > T (rs17248720) had frequencies of 9% (PH) and 16.4% (normolipemic), p < 0.00001. Studies of this variant with EMSA and luciferase assays showed a higher affinity for transcription factors and an increase of 2.5 times in LDLR transcriptional activity (T-allele vs C-allele). At multivariate analysis, this polymorphism with the lipoprotein(a) and age explained ≈ 10% of LDL-cholesterol variability. Conclusion Our results suggest that the T-allele at the g.3131 T > C SNP is associated with LDL-cholesterol levels, and explains part of the LDL-cholesterol variability. As a plausible cause, the T-allele produces an increase in LDLR transcriptional activity and lower LDL-cholesterol levels. PMID:24708769

Interannual and cyclone-driven variability in phytoplankton communities of a tropical coastal lagoon.

PubMed

Srichandan, Suchismita; Kim, Ji Yoon; Kumar, Abhishek; Mishra, Deepak R; Bhadury, Punyasloke; Muduli, Pradipta R; Pattnaik, Ajit K; Rastogi, Gurdeep

2015-12-15

One of the main challenges in phytoplankton ecology is to understand their variability at different spatiotemporal scales. We investigated the interannual and cyclone-derived variability in phytoplankton communities of Chilika, the largest tropical coastal lagoon in Asia and the underlying mechanisms in relation to environmental forcing. Between July 2012 and June 2013, Cyanophyta were most prolific in freshwater northern region of the lagoon. A category-5 very severe cyclonic storm (VSCS) Phailin struck the lagoon on 12th October 2013 and introduced additional variability into the hydrology and phytoplankton communities. Freshwater Cyanophyta further expanded their territory and occupied the northern as well as central region of the lagoon. Satellite remote sensing imagery revealed that the phytoplankton biomass did not change much due to high turbidity prevailing in the lagoon after Phailin. Modeling analysis of species-salinity relationship identified specific responses of phytoplankton taxa to the different salinity regime of lagoon. Copyright © 2015 Elsevier Ltd. All rights reserved.

Measuring Zonal Transport Variability of the Antarctic Circumpolar Current Using GRACE Ocean Bottom Pressure

NASA Astrophysics Data System (ADS)

Makowski, J.; Chambers, D. P.; Bonin, J. A.

2012-12-01

Previous studies have suggested that ocean bottom pressure (OBP) can be used to measure the transport variability of the Antarctic Circumpolar Current (ACC). Using OBP data from the JPL ECCO model and the Gravity Recovery and Climate Experiment (GRACE), we examine the zonal transport variability of the ACC integrated between the major fronts between 2003-2010. The JPL ECCO data are used to determine average front positions for the time period studies, as well as where transport is mainly zonal. Statistical analysis will be conducted to determine the uncertainty of the GRACE observations using a simulated data set. We will also begin looking at low frequency changes and how coherent transport variability is from region to region of the ACC. Correlations with bottom pressure south of the ACC and the average basin transports will also be calculated to determine the probability of using bottom pressure south of the ACC as a means for describing the ACC dynamics and transport.

The role of visual representations during the lexical access of spoken words

PubMed Central

Lewis, Gwyneth; Poeppel, David

2015-01-01

Do visual representations contribute to spoken word recognition? We examine, using MEG, the effects of sublexical and lexical variables at superior temporal (ST) areas and the posterior middle temporal gyrus (pMTG) compared with that of word imageability at visual cortices. Embodied accounts predict early modulation of visual areas by imageability - concurrently with or prior to modulation of pMTG by lexical variables. Participants responded to speech stimuli varying continuously in imageability during lexical decision with simultaneous MEG recording. We employed the linguistic variables in a new type of correlational time course analysis to assess trial-by-trial activation in occipital, ST, and pMTG regions of interest (ROIs). The linguistic variables modulated the ROIs during different time windows. Critically, visual regions reflected an imageability effect prior to effects of lexicality on pMTG. This surprising effect supports a view on which sensory aspects of a lexical item are not a consequence of lexical activation. PMID:24814579

Change in IgHV Mutational Status of CLL Suggests Origin From Multiple Clones.

PubMed

Osman, Afaf; Gocke, Christopher D; Gladstone, Douglas E

2017-02-01

Fluorescence in situ hybridization and immunoglobulin (Ig) heavy-chain variable-region (IgHV) mutational status are used to predict outcome in chronic lymphocytic leukemia (CLL). Although DNA aberrations change over time, IgHV sequences and mutational status are considered stable. In a retrospective review, 409 CLL patients, between 2008 and 2015, had IgHV analysis: 56 patients had multiple analyses performed. Seven patients' IgHV results changed: 2 from unmutated to mutated and 5 from mutated to unmutated IgHV sequence. Three concurrently changed their variable heavy-chain sequence. Secondary to allelic exclusion, 2 of the new variable heavy chains produced were biologically nonplausible. The existence of these new nonplausible heavy-chain variable regions suggests either the CLL cancer stem-cell maintains the ability to rearrange a previously silenced IgH allele or more likely that the cancer stem-cell produced at least 2 subclones, suggesting that the CLL cancer stem cell exists before the process of allelic exclusion occurs. Copyright © 2016 Elsevier Inc. All rights reserved.

The role of visual representations during the lexical access of spoken words.

PubMed

Lewis, Gwyneth; Poeppel, David

2014-07-01

Do visual representations contribute to spoken word recognition? We examine, using MEG, the effects of sublexical and lexical variables at superior temporal (ST) areas and the posterior middle temporal gyrus (pMTG) compared with that of word imageability at visual cortices. Embodied accounts predict early modulation of visual areas by imageability--concurrently with or prior to modulation of pMTG by lexical variables. Participants responded to speech stimuli varying continuously in imageability during lexical decision with simultaneous MEG recording. We employed the linguistic variables in a new type of correlational time course analysis to assess trial-by-trial activation in occipital, ST, and pMTG regions of interest (ROIs). The linguistic variables modulated the ROIs during different time windows. Critically, visual regions reflected an imageability effect prior to effects of lexicality on pMTG. This surprising effect supports a view on which sensory aspects of a lexical item are not a consequence of lexical activation. Copyright © 2014 Elsevier Inc. All rights reserved.

A Study on Regional Frequency Analysis using Artificial Neural Network - the Sumjin River Basin

NASA Astrophysics Data System (ADS)

Jeong, C.; Ahn, J.; Ahn, H.; Heo, J. H.

2017-12-01

Regional frequency analysis means to make up for shortcomings in the at-site frequency analysis which is about a lack of sample size through the regional concept. Regional rainfall quantile depends on the identification of hydrologically homogeneous regions, hence the regional classification based on hydrological homogeneous assumption is very important. For regional clustering about rainfall, multidimensional variables and factors related geographical features and meteorological figure are considered such as mean annual precipitation, number of days with precipitation in a year and average maximum daily precipitation in a month. Self-Organizing Feature Map method which is one of the artificial neural network algorithm in the unsupervised learning techniques solves N-dimensional and nonlinear problems and be shown results simply as a data visualization technique. In this study, for the Sumjin river basin in South Korea, cluster analysis was performed based on SOM method using high-dimensional geographical features and meteorological factor as input data. then, for the results, in order to evaluate the homogeneity of regions, the L-moment based discordancy and heterogeneity measures were used. Rainfall quantiles were estimated as the index flood method which is one of regional rainfall frequency analysis. Clustering analysis using SOM method and the consequential variation in rainfall quantile were analyzed. This research was supported by a grant(2017-MPSS31-001) from Supporting Technology Development Program for Disaster Management funded by Ministry of Public Safety and Security(MPSS) of the Korean government.

Retail Infrastructure Costs Comparison for Hydrogen and Electricity for Light-Duty Vehicles: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Melaina, M.; Sun, Y.; Bush, B.

2014-08-01

Both hydrogen and plug-in electric vehicles offer significant social benefits to enhance energy security and reduce criteria and greenhouse gas emissions from the transportation sector. However, the rollout of electric vehicle supply equipment (EVSE) and hydrogen retail stations (HRS) requires substantial investments with high risks due to many uncertainties. We compare retail infrastructure costs on a common basis - cost per mile, assuming fueling service to 10% of all light-duty vehicles in a typical 1.5 million person city in 2025. Our analysis considers three HRS sizes, four distinct types of EVSE and two distinct EVSE scenarios. EVSE station costs, includingmore » equipment and installation, are assumed to be 15% less than today's costs. We find that levelized retail capital costs per mile are essentially indistinguishable given the uncertainty and variability around input assumptions. Total fuel costs per mile for battery electric vehicle (BEV) and plug-in hybrid vehicle (PHEV) are, respectively, 21% lower and 13% lower than that for hydrogen fuel cell electric vehicle (FCEV) under the home-dominant scenario. Including fuel economies and vehicle costs makes FCEVs and BEVs comparable in terms of costs per mile, and PHEVs are about 10% less than FCEVs and BEVs. To account for geographic variability in energy prices and hydrogen delivery costs, we use the Scenario Evaluation, Regionalization and Analysis (SERA) model and confirm the aforementioned estimate of cost per mile, nationally averaged, but see a 15% variability in regional costs of FCEVs and a 5% variability in regional costs for BEVs.« less

Temporal variability of gravity wave drag - vertical coupling and possible climate links

NASA Astrophysics Data System (ADS)

Miksovsky, Jiri; Sacha, Petr; Kuchar, Ales; Pisoft, Petr

2017-04-01

In the atmosphere, the internal gravity waves (IGW) are one of the fastest ways of natural information transfer in the vertical direction. Tropospheric changes that result in modification of sourcing, propagation or breaking conditions for IGWs almost immediately influence the distribution of gravity wave drag in the stratosphere. So far most of the related studies deal with IGW impacts higher in the upper stratospheric/mesospheric region and with the modulation of IGWs by planetary waves. This is most likely due to the fact that IGWs induce highest accelerations in the mesosphere and lower thermosphere region. However, the imposed drag force is much bigger in the stratosphere. In the presented analysis, we have assessed the relationship between the gravity wave activity in the stratosphere and other climatic phenomena through statistical techniques. Multivariable regression has been applied to investigate the IGW-related eastward and northward wind tendencies in the CMAM30-SD data, subject to the explanatory variables involving local circulation characteristics (derived from regional configuration of the thermobaric field) as well as the phases of the large-scale internal climate variability modes (ENSO, NAO, QBO). Our tests have highlighted several geographical areas with statistically significant responses of the orographic gravity waves effect to each of the variability modes under investigation; additional experiments have also indicated distinct signs of nonlinearity in some of the links uncovered. Furthermore, we have also applied composite analysis of displaced and split stratospheric polar vortex events (SPV) from CMAM30-SD to focus on how the strength and occurrence of the IGW hotspots can play a role in SPV occurrence and frequency.

Prevalence of common mental disorders in mothers in the semiarid region of Alagoas and its relationship with nutritional status.

PubMed

Paffer, Adriana Toledo de; Ferreira, Haroldo da Silva; Cabral Júnior, Cyro Rego; Miranda, Claudio Torres de

2012-01-01

Compromised maternal mental health (MMH) is considered to be a risk factor for child malnutrition in low income areas. Psychosocial variables associated with MMH are potentially different between urban and rural environments. The aim here was to investigate whether associations existed between MMH and selected sociodemographic risk factors and whether specific to urban or rural settings. Cross-sectional study on a representative population sample of mothers from the semiarid region of Alagoas. Multistage sampling was used. The subjects were mothers of children aged up to 60 months. MMH was evaluated through the Self-Reporting Questionnaire-20. Mothers' nutritional status was assessed using the body mass index and waist circumference. Univariate analysis used odds ratios (OR) and chi-square. Logistic regression was performed separately for urban and rural subsamples using MMH as the dependent variable. The sample comprised 288 mothers. The prevalences of common mental disorders (CMD) in rural and urban areas were 56.2% and 43.8%, respectively (OR = 1.03; 95% CI: 0.64-1.63). In univariate analysis and logistic regression, the variable of education remained associated with MMH (OR = 2.2; 95% CI: 1.03-4.6) in urban areas. In rural areas, the variable of lack of partner remained associated (OR = 2.6; 95% CI: 1.01-6.7). The prevalence of CMD is high among mothers of children aged up to two years in the semiarid region of Alagoas. This seems to be associated with lower educational level in urban settings and lack of partner in rural settings.

Interannual Variability of Regional Hadley Circulation Intensity Over Western Pacific During Boreal Winter and Its Climatic Impact Over Asia-Australia Region

NASA Astrophysics Data System (ADS)

Huang, Ruping; Chen, Shangfeng; Chen, Wen; Hu, Peng

2018-01-01

This study investigates interannual variability of boreal winter regional Hadley circulation over western Pacific (WPHC) and its climatic impacts. A WPHC intensity index (WPHCI) is defined as the vertical shear of the divergent meridional winds. It shows that WPHCI correlates well with the El Niño-Southern Oscillation (ENSO). To investigate roles of the ENSO-unrelated part of WPHCI (WPHCIres), variables that are linearly related to the Niño-3 index have been removed. It reveals that meridional sea surface temperature gradient over the western Pacific plays an essential role in modulating the WPHCIres. The climatic impacts of WPHCIres are further investigated. Below-normal (above-normal) precipitation appears over south China (North Australia) when WPHCIres is stronger. This is due to the marked convergence (divergence) anomalies at the upper troposphere, divergence (convergence) at the lower troposphere, and the accompanied downward (upward) motion over south China (North Australia), which suppresses (enhances) precipitation there. In addition, a pronounced increase in surface air temperature (SAT) appears over south and central China when WPHCIres is stronger. A temperature diagnostic analysis suggests that the increase in SAT tendency over central China is primarily due to the warm zonal temperature advection and subsidence-induced adiabatic heating. In addition, the increase in SAT tendency over south China is primarily contributed by the warm meridional temperature advection. Further analysis shows that the correlation of WPHCIres with the East Asian winter monsoon (EAWM) is weak. Thus, this study may provide additional sources besides EAWM and ENSO to improve understanding of the Asia-Australia climate variability.

Tropical cyclone-related socio-economic losses in the western North Pacific region

NASA Astrophysics Data System (ADS)

Welker, C.; Faust, E.

2013-01-01

The western North Pacific (WNP) is the area of the world most frequently affected by tropical cyclones (TCs). However, little is known about the socio-economic impacts of TCs in this region, probably because of the limited relevant loss data. Here, loss data from Munich RE's NatCatSERVICE database is used, a high-quality and widely consulted database of natural disasters. In the country-level loss normalisation technique we apply, the original loss data are normalised to present-day exposure levels by using the respective country's nominal gross domestic product at purchasing power parity as a proxy for wealth. The main focus of our study is on the question of whether the decadal-scale TC variability observed in the Northwest Pacific region in recent decades can be shown to manifest itself economically in an associated variability in losses. It is shown that since 1980 the frequency of TC-related loss events in the WNP exhibited, apart from seasonal and interannual variations, interdecadal variability with a period of about 22 yr - driven primarily by corresponding variations of Northwest Pacific TCs. Compared to the long-term mean, the number of loss events was found to be higher (lower) by 14% (9%) in the positive (negative) phase of the decadal-scale WNP TC frequency variability. This was identified for the period 1980-2008 by applying a wavelet analysis technique. It was also possible to demonstrate the same low-frequency variability in normalised direct economic losses from TCs in the WNP region. The identification of possible physical mechanisms responsible for the observed decadal-scale Northwest Pacific TC variability will be the subject of future research, even if suggestions have already been made in earlier studies.

Interannual drivers of the seasonal cycle of CO2 in the Southern Ocean

NASA Astrophysics Data System (ADS)

Gregor, Luke; Kok, Schalk; Monteiro, Pedro M. S.

2018-04-01

Resolving and understanding the drivers of variability of CO2 in the Southern Ocean and its potential climate feedback is one of the major scientific challenges of the ocean-climate community. Here we use a regional approach on empirical estimates of pCO2 to understand the role that seasonal variability has in long-term CO2 changes in the Southern Ocean. Machine learning has become the preferred empirical modelling tool to interpolate time- and location-restricted ship measurements of pCO2. In this study we use an ensemble of three machine-learning products: support vector regression (SVR) and random forest regression (RFR) from Gregor et al. (2017), and the self-organising-map feed-forward neural network (SOM-FFN) method from Landschützer et al. (2016). The interpolated estimates of ΔpCO2 are separated into nine regions in the Southern Ocean defined by basin (Indian, Pacific, and Atlantic) and biomes (as defined by Fay and McKinley, 2014a). The regional approach shows that, while there is good agreement in the overall trend of the products, there are periods and regions where the confidence in estimated ΔpCO2 is low due to disagreement between the products. The regional breakdown of the data highlighted the seasonal decoupling of the modes for summer and winter interannual variability. Winter interannual variability had a longer mode of variability compared to summer, which varied on a 4-6-year timescale. We separate the analysis of the ΔpCO2 and its drivers into summer and winter. We find that understanding the variability of ΔpCO2 and its drivers on shorter timescales is critical to resolving the long-term variability of ΔpCO2. Results show that ΔpCO2 is rarely driven by thermodynamics during winter, but rather by mixing and stratification due to the stronger correlation of ΔpCO2 variability with mixed layer depth. Summer pCO2 variability is consistent with chlorophyll a variability, where higher concentrations of chlorophyll a correspond with lower pCO2 concentrations. In regions of low chlorophyll a concentrations, wind stress and sea surface temperature emerged as stronger drivers of ΔpCO2. In summary we propose that sub-decadal variability is explained by summer drivers, while winter variability contributes to the long-term changes associated with the SAM. This approach is a useful framework to assess the drivers of ΔpCO2 but would greatly benefit from improved estimates of ΔpCO2 and a longer time series.

Forced Atlantic Multidecadal Variability Over the Past Millennium

NASA Astrophysics Data System (ADS)

Halloran, P. R.; Reynolds, D.; Scourse, J. D.; Hall, I. R.

2016-02-01

Paul R. Halloran, David J. Reynolds, Ian R. Hall and James D. Scourse Multidecadal variability in Atlantic sea surface temperatures (SSTs) plays a first order role in determining regional atmospheric circulation and moisture transport, with major climatic consequences. These regional climate impacts range from drought in the Sahel and South America, though increased hurricane activity and temperature extremes, to modified monsoonal rainfall. Multidecadal Atlantic SST variability could arise through internal variability in the Atlantic Meridional Overturning Circulation (AMOC) (e.g., Knight et al., 2006), or through externally forced change (e.g. Booth et al., 2012). It is critical that we know whether internal or external forcing dominates if we are to provide useful near-term climate projections in the Atlantic region. A persuasive argument that internal variability plays an important role in Atlantic Multidecadal Variability is that periodic SST variability has been observed throughout much of the last millennium (Mann et al., 2009), and the hypothesized external forcing of historical Atlantic Multidecadal Variability (Booth et al., 2012) is largely anthropogenic in origin. Here we combine the first annually-resolved millennial marine reconstruction with multi-model analysis, to show that the Atlantic SST variability of the last millennium can be explained by a combination of direct volcanic forcing, and indirect, forced, AMOC variability. Our results indicate that whilst climate models capture the timing of both the directly forced SST and forced AMOC-mediated SST variability, the models fail to capture the magnitude of the forced AMOC change. Does this mean that models underestimate the 21st century reduction in AMOC strength? J. Knight, C. Folland and A. Scaife., Climate impacts of the Atlantic Multidecadal Oscillation, GRL, 2006 B.B.B Booth, N. Dunstone, P.R. Halloran et al., Aerosols implicated as a prime driver of twentieth-century North Atlantic climate variability, Nature, 2012 M.E. Mann, Z. Zhang, S. Rutherford et al., Global Signatures and Dynamical Origins of the Little Ice Age and Medieval Climate Anomaly, Science, 2009

Verification of an acoustic transmission matrix analysis of sound propagation in a variable area duct without flow

NASA Technical Reports Server (NTRS)

Miles, J. H.

1981-01-01

A predicted standing wave pressure and phase angle profile for a hard wall rectangular duct with a region of converging-diverging area variation is compared to published experimental measurements in a study of sound propagation without flow. The factor of 1/2 area variation used is sufficient magnitude to produce large reflections. The prediction is based on a transmission matrix approach developed for the analysis of sound propagation in a variable area duct with and without flow. The agreement between the measured and predicted results is shown to be excellent.

Variable Selection through Correlation Sifting

NASA Astrophysics Data System (ADS)

Huang, Jim C.; Jojic, Nebojsa

Many applications of computational biology require a variable selection procedure to sift through a large number of input variables and select some smaller number that influence a target variable of interest. For example, in virology, only some small number of viral protein fragments influence the nature of the immune response during viral infection. Due to the large number of variables to be considered, a brute-force search for the subset of variables is in general intractable. To approximate this, methods based on ℓ1-regularized linear regression have been proposed and have been found to be particularly successful. It is well understood however that such methods fail to choose the correct subset of variables if these are highly correlated with other "decoy" variables. We present a method for sifting through sets of highly correlated variables which leads to higher accuracy in selecting the correct variables. The main innovation is a filtering step that reduces correlations among variables to be selected, making the ℓ1-regularization effective for datasets on which many methods for variable selection fail. The filtering step changes both the values of the predictor variables and output values by projections onto components obtained through a computationally-inexpensive principal components analysis. In this paper we demonstrate the usefulness of our method on synthetic datasets and on novel applications in virology. These include HIV viral load analysis based on patients' HIV sequences and immune types, as well as the analysis of seasonal variation in influenza death rates based on the regions of the influenza genome that undergo diversifying selection in the previous season.

Independent variable complexity for regional regression of the flow duration curve in ungauged basins

NASA Astrophysics Data System (ADS)

Fouad, Geoffrey; Skupin, André; Hope, Allen

2016-04-01

The flow duration curve (FDC) is one of the most widely used tools to quantify streamflow. Its percentile flows are often required for water resource applications, but these values must be predicted for ungauged basins with insufficient or no streamflow data. Regional regression is a commonly used approach for predicting percentile flows that involves identifying hydrologic regions and calibrating regression models to each region. The independent variables used to describe the physiographic and climatic setting of the basins are a critical component of regional regression, yet few studies have investigated their effect on resulting predictions. In this study, the complexity of the independent variables needed for regional regression is investigated. Different levels of variable complexity are applied for a regional regression consisting of 918 basins in the US. Both the hydrologic regions and regression models are determined according to the different sets of variables, and the accuracy of resulting predictions is assessed. The different sets of variables include (1) a simple set of three variables strongly tied to the FDC (mean annual precipitation, potential evapotranspiration, and baseflow index), (2) a traditional set of variables describing the average physiographic and climatic conditions of the basins, and (3) a more complex set of variables extending the traditional variables to include statistics describing the distribution of physiographic data and temporal components of climatic data. The latter set of variables is not typically used in regional regression, and is evaluated for its potential to predict percentile flows. The simplest set of only three variables performed similarly to the other more complex sets of variables. Traditional variables used to describe climate, topography, and soil offered little more to the predictions, and the experimental set of variables describing the distribution of basin data in more detail did not improve predictions. These results are largely reflective of cross-correlation existing in hydrologic datasets, and highlight the limited predictive power of many traditionally used variables for regional regression. A parsimonious approach including fewer variables chosen based on their connection to streamflow may be more efficient than a data mining approach including many different variables. Future regional regression studies may benefit from having a hydrologic rationale for including different variables and attempting to create new variables related to streamflow.

Spatial distribution of sand fly species (Psychodidae: Phlebtominae), ecological niche, and climatic regionalization in zoonotic foci of cutaneous leishmaniasis, southwest of Iran.

PubMed

Ebrahimi, Sahar; Bordbar, Ali; Rastaghi, Ahmad R Esmaeili; Parvizi, Parviz

2016-06-01

Cutaneous leishmaniasis (CL) is a complex vector-borne disease caused by Leishmania parasites that are transmitted by the bite of several species of infected female phlebotomine sand flies. Monthly factor analysis of climatic variables indicated fundamental variables. Principal component-based regionalization was used for recognition of climatic zones using a clustering integrated method that identified five climatic zones based on factor analysis. To investigate spatial distribution of the sand fly species, the kriging method was used as an advanced geostatistical procedure in the ArcGIS modeling system that is beneficial to design measurement plans and to predict the transmission cycle in various regions of Khuzestan province, southwest of Iran. However, more than an 80% probability of P. papatasi was observed in rainy and temperate bio-climatic zones with a high potential of CL transmission. Finding P. sergenti revealed the probability of transmission and distribution patterns of a non-native vector of CL in related zones. These findings could be used as models indicating climatic zones and environmental variables connected to sand fly presence and vector distribution. Furthermore, this information is appropriate for future research efforts into the ecology of Phlebotomine sand flies and for the prevention of CL vector transmission as a public health priority. © 2016 The Society for Vector Ecology.

[Using infrared thermal asymmetry analysis for objective assessment of the lesion of facial nerve function].

PubMed

Liu, Xu-long; Hong, Wen-xue; Song, Jia-lin; Wu, Zhen-ying

2012-03-01

The skin temperature distribution of a healthy human body exhibits a contralateral symmetry. Some lesions of facial nerve function are associated with an alteration of the thermal distribution of the human body. Since the dissipation of heat through the skin occurs for the most part in the form of infrared radiation, infrared thermography is the method of choice to capture the alteration of the infrared thermal distribution. This paper presents a new method of analysis of the thermal asymmetry named effective thermal area ratio, which is a product of two variables. The first variable is mean temperature difference between the specific facial region and its contralateral region. The second variable is a ratio, which is equal to the area of the abnormal region divided by the total area. Using this new method, we performed a controlled trial to assess the facial nerve function of the healthy subjects and the patients with Bell's palsy respectively. The results show: that the mean specificity and sensitivity of this method are 0.90 and 0.87 respectively, improved by 7% and 26% compared with conventional methods. Spearman correlation coefficient between effective thermal area ratio and the degree of facial nerve function is an average of 0.664. Hence, concerning the diagnosis and assessment of facial nerve function, infrared thermography is a powerful tool; while the effective ther mal area ratio is an efficient clinical indicator.

Influences of mechanical exposure biographies on physical capabilities of workers from automotive industry - a study on possible dose-response relationships and consequences for short and long term job rotation.

PubMed

Rademacher, Holger; Bruder, Ralph; Sinn-Behrendt, Andrea; Landau, Kurt

2012-01-01

This paper describes a field study in production areas of a vehicle manufacturing plant, where 106 male workers (aged from 20 to 63 years) were examined and interviewed by the authors. Aim of study was to identify relationships between specific physical worker capabilities and doses of mechanical exposures using self-developed standardized questionnaires as well as a battery of work-specific tests. The dependent variables are different "physical capabilities", classified using a five-point rating scale with regard to the grade of limitation of the respective capability. Independent variables are "age" and specific "mechanical exposures". Several exposures were combined and multiplied with their respective durations in order to determine doses on three different body regions - back, shoulder-neck and upper limbs. There are significant positive correlations between "age" and "dose of mechanical exposure on back/shoulder-neck/upper limbs region". The analysis of the relationship between dose of exposure and different capabilities to lift or reposition loads (with variable weight) shows weak significant correlations for all three body regions. Data analysis shows no significant correlations between any dose of mechanical exposure and capabilities to work in awkward body postures.These results should be considered in age management programs when scheduling future employee assignments to workplaces, especially for production systems where manual handling tasks are dominant.

Spatio-temporal variability of aerosols in the tropics relationship with atmospheric and oceanic environments

NASA Astrophysics Data System (ADS)

Zuluaga-Arias, Manuel D.

2011-12-01

Earth's radiation budget is directly influenced by aerosols through the absorption of solar radiation and subsequent heating of the atmosphere. Aerosols modulate the hydrological cycle indirectly by modifying cloud properties, precipitation and ocean heat storage. In addition, polluting aerosols impose health risks in local, regional and global scales. In spite of recent advances in the study of aerosols variability, uncertainty in their spatio-temporal distributions still presents a challenge in the understanding of climate variability. For example, aerosol loading varies not only from year to year but also on higher frequency intraseasonal time scales producing strong variability on local and regional scales. An assessment of the impact of aerosol variability requires long period measurements of aerosols at both regional and global scales. The present dissertation compiles a large database of remotely sensed aerosol loading in order to analyze its spatio-temporal variability, and how this load interacts with different variables that characterize the dynamic and thermodynamic states of the environment. Aerosol Index (AI) and Aerosol Optical Depth (AOD) were used as measures of the atmospheric aerosol load. In addition, atmospheric and oceanic satellite observations, and reanalysis datasets is used in the analysis to investigate aerosol-environment interactions. A diagnostic study is conducted to produce global and regional aerosol satellite climatologies, and to analyze and compare the validity of aerosol retrievals. We find similarities and differences between the aerosol distributions over various regions of the globe when comparing the different satellite retrievals. A nonparametric approach is also used to examine the spatial distribution of the recent trends in aerosol concentration. A significant positive trend was found over the Middle East, Arabian Sea and South Asian regions strongly influenced by increases in dust events. Spectral and composite analyses of surface temperature, atmospheric wind, geopotential height, outgoing longwave radiation, water vapor and precipitation together with the climatology of aerosols provide insight on how the variables interact. Different modes of variability, especially in intraseasonal time scales appear as strong modulators of the aerosol distribution. In particular, we investigate how two modes of variability related to the westward propagating synoptic African Easterly Waves of the Tropical Atlantic Ocean affect the horizontal and vertical structure of the environment. The statistical significance of these two modes is tested with the use of two different spectral techniques. The pattern of propagation of aerosol load shows good correspondence with the progression of the atmospheric and oceanic conditions suitable for dust mobilization over the Atlantic Ocean. We present extensions to previous studies related with dust variability over the Atlantic region by evaluating the performance of the long period satellite aerosol retrievals in determining modes of aerosol variability. Results of the covariability between aerosols-environment motivate the use of statistical regression models to test the significance of the forecasting skill of daily AOD time series. The regression models are calibrated using atmospheric variables as predictors from the reanalysis variables. The results show poor forecasting skill with significant error growing after the 3 rd day of the prediction. It is hypothesized that the simplicity of linear models results in an inability to provide a useful forecast.

Quantifying the effects of climate variability and human activities on runoff for Kaidu River Basin in arid region of northwest China

NASA Astrophysics Data System (ADS)

Chen, Zhongsheng; Chen, Yaning; Li, Baofu

2013-02-01

Much attention has recently been focused on the effects that climate variability and human activities have had on runoff. In this study, data from the Kaidu River Basin in the arid region of northwest China were analyzed to investigate changes in annual runoff during the period of 1960-2009. The nonparametric Mann-Kendall test and the Mann-Kendall-Sneyers test were used to identify trend and step change point in the annual runoff. It was found that the basin had a significant increasing trend in annual runoff. Step change point in annual runoff was identified in the basin, which occurred in the year around 1993 dividing the long-term runoff series into a natural period (1960-1993) and a human-induced period (1994-2009). Then, the hydrologic sensitivity analysis method was employed to evaluate the effects of climate variability and human activities on mean annual runoff for the human-induced period based on precipitation and potential evapotranspiration. In 1994-2009, climate variability was the main factor that increased runoff with contribution of 90.5 %, while the increasing percentage due to human activities only accounted for 9.5 %, showing that runoff in the Kaidu River Basin is more sensitive to climate variability than human activities. This study quantitatively distinguishes the effects between climate variability and human activities on runoff, which can do duty for a reference for regional water resources assessment and management.

Predicted Responses of Vegetation to Climate Change: A Global Analysis of Changes in Primary Productivity and Water Use Efficiency in the 21st Century

NASA Astrophysics Data System (ADS)

Bernardes, S.

2016-12-01

Global coupled carbon-climate simulations show considerable variability in outputs for atmospheric and land fields over the 21st century. This variability includes changes in temperature and in the quantity and spatiotemporal distribution of precipitation for large regions on the planet. Studies have considered that reductions in water availability due to decreased precipitation and increased water demand by the atmosphere may negatively affect plant metabolism and reduce carbon uptake. Future increases in carbon dioxide concentrations are expected to affect those interactions and potentially offset reductions in productivity. It is uncertain how plants will adjust their water use efficiency (WUE, plant production per water loss by evapotranspiration) in response to changing environmental conditions. This work investigates predicted changes in WUE in the 21st century by analyzing an ensemble of Earth System Models from the Coupled Model Intercomparison Project 5 (CMIP5), together with flux tower data and products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Two representative concentration pathways were selected to describe possible climate futures (RCP4.5 and RCP8.5). Periods of analysis included 2006-2099 (predicted) and 1850-2005 (reference). Comparisons between modeled, flux and satellite data for IPCC SREX regions were used to address the significant intermodel variability observed for the CMIP5 ensemble (larger variability for RCP8.5, higher intermodel agreement in Southeast Asia, lower intermodel agreement in arid areas). Model skill was evaluated in support of model selection and the spatiotemporal analysis of changes in WUE. Global, regional and latitudinal distributions of departures of projected conditions in relation to historical values are presented for both concentration pathways. Results showed high model sensitivity to different concentration pathways and increase in GPP and WUE for most of the planet (increases consistently higher for RCP8.5). Higher increases in GPP and WUE are predicted to occur over higher latitudes in the northern hemisphere (boreal region), with WUE usually following GPP in changes. Decreases in productivity and WUE occur mostly in the tropics, affecting tropical forests in Central America and in the Amazon.

World Voice Day in news: analysis of reports on the Voice Campaign in Brazil.

PubMed

Dornelas, Rodrigo; Giannini, Susana Pimentel Pinto; Ferreira, Léslie Piccolotto

2015-01-01

To analyze the television reports on the World Voice Day transmitted by Globo(r) TV. We researched television reports broadcasted by Globo(r) Network in regional television news programs from March 15 to April 20, 2013. For the data analysis, the Document Analysis technique was used. The analyzed variables were the following: location, broadcasting period, duration, interviewed professional, mention of multiprofessional work, orientation to the population, and the interview approach (health promotion or disease prevention). Through statistical analysis, the interview approach was considered the outcome and associated with the other variables. On the regions where there are news programs for the researched TV station, the majority made reports about the Voice Campaign. Among these, we discovered that the five regions of Brazil were contemplated, in the morning/afternoon periods, with medium duration of 5.3 minutes. The presence of the speech-language pathologist was observed in greater numbers of the interviews, as also the emphasis on the importance of a multiprofessional work. Regarding the content presented, the interviewees focused on diseases caused by habits that impair the voice, with orientation to the public about what negatively interferes in the vocal well-being. The approach of the interviews was not, in the majority of times, of the same nature (promoting the vocal well-being or preventing voice disorder), and the interprofessional practice is still seen less frequently as a possible work strategy.

Quantitative and qualitative analysis of naphthenic acids in natural waters surrounding the Canadian oil sands industry.

PubMed

Ross, Matthew S; Pereira, Alberto dos Santos; Fennell, Jon; Davies, Martin; Johnson, James; Sliva, Lucie; Martin, Jonathan W

2012-12-04

The Canadian oil sands industry stores toxic oil sands process-affected water (OSPW) in large tailings ponds adjacent to the Athabasca River or its tributaries, raising concerns over potential seepage. Naphthenic acids (NAs; C(n)H(2n-Z)O(2)) are toxic components of OSPW, but are also natural components of bitumen and regional groundwaters, and may enter surface waters through anthropogenic or natural sources. This study used a selective high-resolution mass spectrometry method to examine total NA concentrations and NA profiles in OSPW (n = 2), Athabasca River pore water (n = 6, representing groundwater contributions) and surface waters (n = 58) from the Lower Athabasca Region. NA concentrations in surface water (< 2-80.8 μg/L) were 100-fold lower than previously estimated. Principal components analysis (PCA) distinguished sample types based on NA profile, and correlations to water quality variables identified two sources of NAs: natural fatty acids, and bitumen-derived NAs. Analysis of NA data with water quality variables highlighted two tributaries to the Athabasca River-Beaver River and McLean Creek-as possibly receiving OSPW seepage. This study is the first comprehensive analysis of NA profiles in surface waters of the region, and demonstrates the need for highly selective analytical methods for source identification and in monitoring for potential effects of development on ambient water quality.

Analysis of the effect of local heat island in Seoul using LANDSAT image

NASA Astrophysics Data System (ADS)

Lee, K. I.; Ryu, J.; Jeon, S. W.

2017-12-01

The increase in the rate of industrialization due to urbanization has caused the Urban Heat Island phenomenon which means that the temperature of the city is higher than the surrounding area, and its intensity is increasing with climate change. Among the cities where heat island phenomenon occur, Seoul city has different degree of urbanization, green area ratio, energy consumption, and population density by each district unit. As a result, the strength of heat island phenomenon is also different. The average maximum temperature in each region may differ by more than 3 °, which is bigger than the suburbs in Seoul and it means that analysis of UHI effect by regional unit is needed. Therefore, this study is to extract the UHI Intensity of the regional unit of the Seoul Metropolitan City using the satellite image, analyzed the difference of intensity according to the regional unit. And do linear regression analysis with variables included in three categories(regional meteorological conditions, anthropogenic heat generation, land use factors). As a result, The UHI Intensity value of the Gu unit is significantly different from the UHI Intensity distribution of the Dong unit. The variable having the greatest positive correlation with UHI Intensity was NDBI(Normalized Difference Built-up Index) which shows the distribution of urban area, and Urban area ratio also has high correlation. There was a negative correlation between mean wind speed but there was no significant correlation between population density and power consumption. The result of this study is to identify the regional difference of UHI Intensity and to identify the factors inducing heat island phenomenon. so It is expected that it will provide direction in urban thermal environment design and policy development in the future.

Comparative analysis of meteorological and hydrological drought in the Pearl River basin during the period 1960-2012

NASA Astrophysics Data System (ADS)

Xu, K.; Wu, C.; Hu, B.; Niu, J.

2017-12-01

Drought is one of the major natural hazards that can have devastating impacts on the regional environment, agriculture, and water resources. Previous studies have conducted the assessment of historic changes in meteorological drought over various regional scales but rarely considered hydrological drought due to limited hydrological observations. Here, we use a long-term (1960-2012) gridded hydro-meteorological data to present a comparative analysis of meteorological and hydrological drought in the Pearl River basin in southern China using the standardized precipitation index (SPI) and the standardized runoff index (SRI). The variation in SPI and SRI at four different timescales (1-, 3-, 6-, and 12-month) is investigated using the Mann-Kendall (M-K) method and continuous wavelet transform (CWT). The results indicate that the correlation between SPI and SRI is strong over the Pearl River basin and tends to be stronger at the longer timescale. Meanwhile, the periodic oscillation pattern of SPI becomes more consistent with that of SRI with the increased timescale. The SPI can be used as a substitute for SRI to represent the hydrological drought at the long-term scale. Overall there is a noticeably wetting trend mainly in the eastern parts and a significant drying trend mainly in the western regions and the downstream area of the Pearl River basin. The variability of meteorological drought is significant mainly in the eastern and western regions, while the variability of hydrological drought tends to be larger mainly in the western region. CWT analysis indicates a period of 0.75-7 years in both meteorological and hydrological droughts during the period 1960-2012 in the study region.

Assessment of climate change impacts on climate variables using probabilistic ensemble modeling and trend analysis

NASA Astrophysics Data System (ADS)

Safavi, Hamid R.; Sajjadi, Sayed Mahdi; Raghibi, Vahid

2017-10-01

Water resources in snow-dependent regions have undergone significant changes due to climate change. Snow measurements in these regions have revealed alarming declines in snowfall over the past few years. The Zayandeh-Rud River in central Iran chiefly depends on winter falls as snow for supplying water from wet regions in high Zagrous Mountains to the downstream, (semi-)arid, low-lying lands. In this study, the historical records (baseline: 1971-2000) of climate variables (temperature and precipitation) in the wet region were chosen to construct a probabilistic ensemble model using 15 GCMs in order to forecast future trends and changes while the Long Ashton Research Station Weather Generator (LARS-WG) was utilized to project climate variables under two A2 and B1 scenarios to a future period (2015-2044). Since future snow water equivalent (SWE) forecasts by GCMs were not available for the study area, an artificial neural network (ANN) was implemented to build a relationship between climate variables and snow water equivalent for the baseline period to estimate future snowfall amounts. As a last step, homogeneity and trend tests were performed to evaluate the robustness of the data series and changes were examined to detect past and future variations. Results indicate different characteristics of the climate variables at upstream stations. A shift is observed in the type of precipitation from snow to rain as well as in its quantities across the subregions. The key role in these shifts and the subsequent side effects such as water losses is played by temperature.

Advances in the regionalization approach: geostatistical techniques for estimating flood quantiles

NASA Astrophysics Data System (ADS)

Chiarello, Valentina; Caporali, Enrica; Matthies, Hermann G.

2015-04-01

The knowledge of peak flow discharges and associated floods is of primary importance in engineering practice for planning of water resources and risk assessment. Streamflow characteristics are usually estimated starting from measurements of river discharges at stream gauging stations. However, the lack of observations at site of interest as well as the measurement inaccuracies, bring inevitably to the necessity of developing predictive models. Regional analysis is a classical approach to estimate river flow characteristics at sites where little or no data exists. Specific techniques are needed to regionalize the hydrological variables over the considered area. Top-kriging or topological kriging, is a kriging interpolation procedure that takes into account the geometric organization and structure of hydrographic network, the catchment area and the nested nature of catchments. The continuous processes in space defined for the point variables are represented by a variogram. In Top-kriging, the measurements are not point values but are defined over a non-zero catchment area. Top-kriging is applied here over the geographical space of Tuscany Region, in Central Italy. The analysis is carried out on the discharge data of 57 consistent runoff gauges, recorded from 1923 to 2014. Top-kriging give also an estimation of the prediction uncertainty in addition to the prediction itself. The results are validated using a cross-validation procedure implemented in the package rtop of the open source statistical environment R The results are compared through different error measurement methods. Top-kriging seems to perform better in nested catchments and larger scale catchments but no for headwater or where there is a high variability for neighbouring catchments.

An observational and modeling study of the regional impacts of climate variability

NASA Astrophysics Data System (ADS)

Horton, Radley M.

Climate variability has large impacts on humans and their agricultural systems. Farmers are at the center of this agricultural network, but it is often agricultural planners---regional planners, extension agents, commodity groups and cooperatives---that translate climate information for users. Global climate models (GCMs) are a leading tool for understanding and predicting climate and climate change. Armed with climate projections and forecasts, agricultural planners adapt their decision-making to optimize outcomes. This thesis explores what GCMs can, and cannot, tell us about climate variability and change at regional scales. The question is important, since high-quality regional climate projections could assist farmers and regional planners in key management decisions, contributing to better agricultural outcomes. To answer these questions, climate variability and its regional impacts are explored in observations and models for the current and future climate. The goals are to identify impacts of observed variability, assess model simulation of variability, and explore how climate variability and its impacts may change under enhanced greenhouse warming. Chapter One explores how well Goddard Institute for Space Studies (GISS) atmospheric models, forced by historical sea surface temperatures (SST), simulate climatology and large-scale features during the exceptionally strong 1997--1999 El Nino Southern Oscillation (ENSO) cycle. Reasonable performance in this 'proof of concept' test is considered a minimum requirement for further study of variability in models. All model versions produce appropriate local changes with ENSO, indicating that with correct ocean temperatures these versions are capable of simulating the large-scale effects of ENSO around the globe. A high vertical resolution model (VHR) provides the best simulation. Evidence is also presented that SST anomalies outside the tropical Pacific may play a key role in generating remote teleconnections even during El Nino events. Based on the results from Chapter One, the analysis is expanded in several ways in Chapter Two. To gain a more complete and statistically meaningful understanding of ENSO, a 25 year time period is used instead of a single event. To gain a fuller understanding of climate variability, additional patterns are analyzed. Finally analysis is conducted at the regional scales that are of interest to farmers and agricultural planners. Key findings are that GISS ModelE can reproduce: (1) the spatial pattern associated with two additional related modes, the Arctic Oscillation (AO) and the North Atlantic Oscillation (NAO); (2) rainfall patterns in Indonesia; and (3) dynamical features such as sea level pressure (SLP) gradients and wind in the study regions. When run in coupled mode, the same model reproduces similar modes spatially but with reduced variance and weak teleconnections. Since Chapter Two identified Western Indonesia as the region where GCMs hold the most promise for agricultural applications, in Chapter Three a finer spatial and temporal scale analysis of ENSO's effects is presented. Agricultural decision-making is also linked to ENSO's climate effects. Early rainy season precipitation and circulation, and same-season planting and harvesting dates, are shown to be sensitive to ENSO. The locus of ENSO convergence and rainfall anomalies is shown to be near the axis of rainy season establishment, defined as the 6--8 mm/day isohyet, an approximate threshold for irrigated rice cultivation. As the axis tracks south and east between October and January, so do ENSO anomalies. Circulation anomalies associated with ENSO are shown to be similar to those associated with rainfall anomalies, suggesting that long lead-time ENSO forecasts may allow more adaptation than 'wait and see' methods, with little loss of forecast skill. Additional findings include: (1) rice and corn yields are lower (higher) during dry (wet) trimesters and El Nino (La Nina) years; and (2) a statistically significant negative relationship exists between malaria cases and ENSO. The final chapter adds climate change to the climate variability story. Under high CO2, the model able to capture ENSO dynamics---an atmospheric model coupled to the Cane-Zebiak ocean model ('C4' here)---generates more El Nino-like mean conditions in the tropical Pacific. These changes produce a 4x larger increase in maximum precipitation with warming in C4 than an atmospheric model with a slab ocean (Q4), dramatically enhancing the Pacific Hadley and Walker circulations, and through positive feedbacks, increasing the global temperature. Near Nordeste warming alone (Q4) produces added rainfall, which in C4 is partially cancelled out by El Nino-like changes in the Walker Cell. Both Q4 and C4 produce small changes in Indonesia, although C4 generates large circulation and precipitation anomalies over the Western Indian Ocean. C4 changes in the midlatitudes produce a very strong Pacific North American pattern (PNA) response that dominates a small positive AO change associated with Q4. These PNA changes produce increased rainfall over the Southeastern United States (SEUS) in C4. AO and NAO-like variability are also found to increase with enhanced CO2. This thesis highlights how climate variability influences regional climate variability, with an emphasis on four regions: Nordeste, Brazil, Western Indonesia, the Southeastern United States (SEUS), and the Mediterranean. It links El Nino-driven delay in the onset of rainy season drivers in Western Indonesia to decision-making about when to plant the year's largest crop. In a coupled configuration, the GISS GCM produces strong El Nino-like changes with global warming. This result suggests that the impacts---climatological and agricultural---of climate change may ultimately exceed the impacts of current variability. Somewhat paradoxically, these results indicate that one of the central manifestations of climate change is likely to be changes in patterns of climate variability and their regional impacts.

Predictors of emotional problems and physical aggression among children of Hong Kong Chinese, Mainland Chinese and Filipino immigrants to Canada.

PubMed

Beiser, Morton; Hamilton, Hayley; Rummens, Joanna Anneke; Oxman-Martinez, Jacqueline; Ogilvie, Linda; Humphrey, Chuck; Armstrong, Robert

2010-10-01

Data from the New Canadian Children and Youth Study (NCCYS), a national study of immigrant children and youth in Canada, are used to examine the mental health salience of putatively universal determinants, as well as of immigration-specific factors. Universal factors (UF) include age, gender, family and neighbourhood characteristics. Migration-specific (MS) factors include ethnic background, acculturative stress, prejudice, and the impact of region of resettlement within Canada. In a sample of children from Hong Kong, the Philippines and Mainland China, the study examined the determinants of emotional problems (EP), and physical aggression (PA). A two-step regression analysis entered UF on step 1, and MS variables on step 2. Universal factors accounted for 12.1% of EP variance. Addition of MS variables increased explained variance to 15.6%. Significant UF predictors: parental depression, family dysfunction, and parent's education. Significant MS variables: country of origin, region of resettlement, resettlement stress, prejudice, and limited linguistic fluency. UF accounted for 6.3% of variance in PA scores. Adding migration-specific variables increased variance explained to 9.1%. UF: age, gender, parent's depression, family dysfunction. MS: country of origin, region of resettlement, resettlement stress, and parent's perception of prejudice. Net of the effect of factors affecting the mental health of most, if not all children, migration-specific variables contribute to understanding immigrant children's mental health.

Placing Local Aggregations in a Larger-Scale Context: Hierarchical Modeling of Black-Footed Albatross Dispersion.

PubMed

Michael, P E; Jahncke, J; Hyrenbach, K D

2016-01-01

At-sea surveys facilitate the study of the distribution and abundance of marine birds along standardized transects, in relation to changes in the local environmental conditions and large-scale oceanographic forcing. We analyzed the form and the intensity of black-footed albatross (Phoebastria nigripes: BFAL) spatial dispersion off central California, using five years (2004-2008) of vessel-based surveys of seven replicated survey lines. We related BFAL patchiness to local, regional and basin-wide oceanographic variability using two complementary approaches: a hypothesis-based model and an exploratory analysis. The former tested the strength and sign of hypothesized BFAL responses to environmental variability, within a hierarchical atmosphere-ocean context. The latter explored BFAL cross-correlations with atmospheric / oceanographic variables. While albatross dispersion was not significantly explained by the hierarchical model, the exploratory analysis revealed that aggregations were influenced by static (latitude, depth) and dynamic (wind speed, upwelling) environmental variables. Moreover, the largest BFAL patches occurred along the survey lines with the highest densities, and in association with shallow banks. In turn, the highest BFAL densities occurred during periods of negative Pacific Decadal Oscillation index values and low atmospheric pressure. The exploratory analyses suggest that BFAL dispersion is influenced by basin-wide, regional-scale and local environmental variability. Furthermore, the hypothesis-based model highlights that BFAL do not respond to oceanographic variability in a hierarchical fashion. Instead, their distributions shift more strongly in response to large-scale ocean-atmosphere forcing. Thus, interpreting local changes in BFAL abundance and dispersion requires considering diverse environmental forcing operating at multiple scales.

Inter-annual variability of carbon fluxes in temperate forest ecosystems: effects of biotic and abiotic factors

NASA Astrophysics Data System (ADS)

Chen, M.; Keenan, T. F.; Hufkens, K.; Munger, J. W.; Bohrer, G.; Brzostek, E. R.; Richardson, A. D.

2014-12-01

Carbon dynamics in terrestrial ecosystems are influenced by both abiotic and biotic factors. Abiotic factors, such as variation in meteorological conditions, directly drive biophysical and biogeochemical processes; biotic factors, referring to the inherent properties of the ecosystem components, reflect the internal regulating effects including temporal dynamics and memory. The magnitude of the effect of abiotic and biotic factors on forest ecosystem carbon exchange has been suggested to vary at different time scales. In this study, we design and conduct a model-data fusion experiment to investigate the role and relative importance of the biotic and abiotic factors for inter-annual variability of the net ecosystem CO2 exchange (NEE) of temperate deciduous forest ecosystems in the Northeastern US. A process-based model (FöBAAR) is parameterized at four eddy-covariance sites using all available flux and biometric measurements. We conducted a "transplant" modeling experiment, that is, cross- site and parameter simulations with different combinations of site meteorology and parameters. Using wavelet analysis and variance partitioning techniques, analysis of model predictions identifies both spatial variant and spatially invariant parameters. Variability of NEE was primarily modulated by gross primary productivity (GPP), with relative contributions varying from hourly to yearly time scales. The inter-annual variability of GPP and NEE is more regulated by meteorological forcing, but spatial variability in certain model parameters (biotic response) has more substantial effects on the inter-annual variability of ecosystem respiration (Reco) through the effects on carbon pools. Both the biotic and abiotic factors play significant roles in modulating the spatial and temporal variability in terrestrial carbon cycling in the region. Together, our study quantifies the relative importance of both, and calls for better understanding of them to better predict regional CO2 exchanges.

Streamflow variability and classification using false nearest neighbor method

NASA Astrophysics Data System (ADS)

Vignesh, R.; Jothiprakash, V.; Sivakumar, B.

2015-12-01

Understanding regional streamflow dynamics and patterns continues to be a challenging problem. The present study introduces the false nearest neighbor (FNN) algorithm, a nonlinear dynamic-based method, to examine the spatial variability of streamflow over a region. The FNN method is a dimensionality-based approach, where the dimension of the time series represents its variability. The method uses phase space reconstruction and nearest neighbor concepts, and identifies false neighbors in the reconstructed phase space. The FNN method is applied to monthly streamflow data monitored over a period of 53 years (1950-2002) in an extensive network of 639 stations in the contiguous United States (US). Since selection of delay time in phase space reconstruction may influence the FNN outcomes, analysis is carried out for five different delay time values: monthly, seasonal, and annual separation of data as well as delay time values obtained using autocorrelation function (ACF) and average mutual information (AMI) methods. The FNN dimensions for the 639 streamflow series are generally identified to range from 4 to 12 (with very few exceptional cases), indicating a wide range of variability in the dynamics of streamflow across the contiguous US. However, the FNN dimensions for a majority of the streamflow series are found to be low (less than or equal to 6), suggesting low level of complexity in streamflow dynamics in most of the individual stations and over many sub-regions. The FNN dimension estimates also reveal that streamflow dynamics in the western parts of the US (including far west, northwestern, and southwestern parts) generally exhibit much greater variability compared to that in the eastern parts of the US (including far east, northeastern, and southeastern parts), although there are also differences among 'pockets' within these regions. These results are useful for identification of appropriate model complexity at individual stations, patterns across regions and sub-regions, interpolation and extrapolation of data, and catchment classification. An attempt is also made to relate the FNN dimensions with catchment characteristics and streamflow statistical properties.

Does objective cluster analysis serve as a useful precursor to seasonal precipitation prediction at local scale? Application to western Ethiopia

NASA Astrophysics Data System (ADS)

Zhang, Ying; Moges, Semu; Block, Paul

2018-01-01

Prediction of seasonal precipitation can provide actionable information to guide management of various sectoral activities. For instance, it is often translated into hydrological forecasts for better water resources management. However, many studies assume homogeneity in precipitation across an entire study region, which may prove ineffective for operational and local-level decisions, particularly for locations with high spatial variability. This study proposes advancing local-level seasonal precipitation predictions by first conditioning on regional-level predictions, as defined through objective cluster analysis, for western Ethiopia. To our knowledge, this is the first study predicting seasonal precipitation at high resolution in this region, where lives and livelihoods are vulnerable to precipitation variability given the high reliance on rain-fed agriculture and limited water resources infrastructure. The combination of objective cluster analysis, spatially high-resolution prediction of seasonal precipitation, and a modeling structure spanning statistical and dynamical approaches makes clear advances in prediction skill and resolution, as compared with previous studies. The statistical model improves versus the non-clustered case or dynamical models for a number of specific clusters in northwestern Ethiopia, with clusters having regional average correlation and ranked probability skill score (RPSS) values of up to 0.5 and 33 %, respectively. The general skill (after bias correction) of the two best-performing dynamical models over the entire study region is superior to that of the statistical models, although the dynamical models issue predictions at a lower resolution and the raw predictions require bias correction to guarantee comparable skills.

Relation of macroinvertebrate community impairment to catchment characteristics in New Jersey streams

USGS Publications Warehouse

Kennen, J.G.

1999-01-01

The level of macroinvertebrate community impairment was statistically related to selected basin and water-quality characteristics in New Jersey streams. More than 700 ambient biomonitoring stations were chosen to evaluate potential and known anthropogenic effects. Macroinvertebrate communities were assessed with a modified rapid-bioassessment approach using three impairment ratings (nonimpaired, moderately impaired, and severely impaired). Maximum-likelihood multiple logistic-regression analysis was used to develop equations defining the probability of community impairment above predetermined impairment levels. Seven of the original 140 explanatory variables were highly related to the level of community impairment. Explanatory variables found to be most useful for predicting severe macroinvertebrate community impairment were the amount of urban land and total flow of municipal effluent. Area underlain by the Reading Prong physiographic region and amount of forested land were inversely related to severe impairment. Nonparametric analysis of variance on rank-transformed bioassessment scores was used to evaluate differences in level of impairment among physiographic regions and major drainage areas simultaneously. Rejection of the null hypothesis indicated that the levels of impairment among all six physiographic regions and five major drainage areas were not equal. Physiographic regions located in the less urbanized northwest portion of New Jersey were not significantly different from each other and had the lowest occurrence of severely impaired macroinvertebrate communities. Physiographic regions containing urban centers had a higher probability of exhibiting a severely impaired macroinvertebrate community. Analysis of major drainage areas indicates that levels of impairment in the Atlantic Coastal Rivers drainage area differed significantly from those in the Lower Delaware River drainage area.

Regionalization of land-use impacts on streamflow using a network of paired catchments

NASA Astrophysics Data System (ADS)

Ochoa-Tocachi, Boris F.; Buytaert, Wouter; De Bièvre, Bert

2016-09-01

Quantifying the impact of land use and cover (LUC) change on catchment hydrological response is essential for land-use planning and management. Yet hydrologists are often not able to present consistent and reliable evidence to support such decision-making. The issue tends to be twofold: a scarcity of relevant observations, and the difficulty of regionalizing any existing observations. This study explores the potential of a paired catchment monitoring network to provide statistically robust, regionalized predictions of LUC change impact in an environment of high hydrological variability. We test the importance of LUC variables to explain hydrological responses and to improve regionalized predictions using 24 catchments distributed along the Tropical Andes. For this, we calculate first 50 physical catchment properties, and then select a subset based on correlation analysis. The reduced set is subsequently used to regionalize a selection of hydrological indices using multiple linear regression. Contrary to earlier studies, we find that incorporating LUC variables in the regional model structures increases significantly regression performance and predictive capacity for 66% of the indices. For the runoff ratio, baseflow index, and slope of the flow duration curve, the mean absolute error reduces by 53% and the variance of the residuals by 79%, on average. We attribute the explanatory capacity of LUC in the regional model to the pairwise monitoring setup, which increases the contrast of the land-use signal in the data set. As such, it may be a useful strategy to optimize data collection to support watershed management practices and improve decision-making in data-scarce regions.

Study for urbanization corresponding to socio-economic activities in Savannaket, Laos using satellite remote sensing

NASA Astrophysics Data System (ADS)

Kimijiama, S.; Nagai, M.

2014-06-01

In Greater Mekong Sub-region (GMS), economic liberalization and deregulation facilitated by GMS Regional Economic Corporation Program (GMS-ECP) has triggered urbanization in the region. However, the urbanization rate and its linkage to socio-economic activities are ambiguous. The objectives of this paper are to: (a) determine the changes in urban area from 1972 to 2013 using remote sensing data, and (b) analyse the relationships between urbanization with respect to socio-economic activities in central Laos. The study employed supervised classification and human visible interpretation to determine changes in urbanization rate. Regression analysis was used to analyze the correlation between the urbanization rate and socio-economic variables. The result shows that the urban area increased significantly from 1972 to 2013. The socio-economic variables such as school enrollment, labour force, mortality rate, water source and sanitation highly correlated with the rate of urbanization during the period. The study concluded that identifying the highly correlated socio-economic variables with urbanization rate could enable us to conduct a further urbanization simulation. The simulation helps in designing policies for sustainable development.

Geomorphic determinants of species composition of alpine tundra, Glacier National Park, U.S.A.

USGS Publications Warehouse

George P. Malanson,; Bengtson, Lindsey E.; Fagre, Daniel B.

2012-01-01

Because the distribution of alpine tundra is associated with spatially limited cold climates, global warming may threaten its local extent or existence. This notion has been challenged, however, based on observations of the diversity of alpine tundra in small areas primarily due to topographic variation. The importance of diversity in temperature or moisture conditions caused by topographic variation is an open question, and we extend this to geomorphology more generally. The extent to which geomorphic variation per se, based on relatively easily assessed indicators, can account for the variation in alpine tundra community composition is analyzed versus the inclusion of broad indicators of regional climate variation. Visual assessments of topography are quantified and reduced using principal components analysis (PCA). Observations of species cover are reduced using detrended correspondence analysis (DCA). A “best subsets” regression approach using the Akaike Information Criterion for selection of variables is compared to a simple stepwise regression with DCA scores as the dependent variable and scores on significant PCA axes plus more direct measures of topography as independent variables. Models with geographic coordinates (representing regional climate gradients) excluded explain almost as much variation in community composition as models with them included, although they are important contributors to the latter. The geomorphic variables in the model are those associated with local moisture differences such as snowbeds. The potential local variability of alpine tundra can be a buffer against climate change, but change in precipitation may be as important as change in temperature.

Seasonal and interannual cross-shelf transport over the Texas and Louisiana continental shelf

NASA Astrophysics Data System (ADS)

Thyng, Kristen M.; Hetland, Robert D.

2018-05-01

Numerical drifters are tracked in a hydrodynamic simulation of circulation over the Texas-Louisiana shelf to analyze patterns in cross-shelf transport of materials. While the important forcing mechanisms in the region (wind, river, and deep eddies) and associated flow patterns are known, the resultant material transport is less well understood. The primary metric used in the calculations is the percent of drifters released within a region that cross the 100 m isobath. Results of the analysis indicate that, averaged over the eleven years of the simulation, there are two regions on the shelf - over the Texas shelf during winter, and over the Louisiana shelf in summer - with increased seasonal probability for offshore transport. Among the two other distinct regions, the big bend region in Texas has increased probability for onshore transport, and the Mississippi Delta region has an increase in offshore transport, for both seasons. Some of these regions of offshore transport have marked interannual variability. This interannual variability is correlated to interannual changes in forcing conditions. Winter transport off of the Texas shelf is correlated with winter mean wind direction, with more northerly winds enhancing offshore transport; summer transport off the Louisiana shelf is correlated with Mississippi River discharge.

[Births prevalence of 27 selected congenital anomalies in 7 geographic regions of Argentina].

PubMed

Campaña, Hebe; Pawluk, Mariela S; López Camelo, Jorge S

2010-10-01

The aim of the present work was to estimate the frequency of 27 birth defects in 7 geographical regions of Argentina. Observational, cross-sectional, descriptive design. A sample of 21,844 new born with birth defects was selected, ascertained from 855,220 births, between 1994 and 2007, in 59 hospitals belonging to the ECLAMC network. In order to identify regions of high frequency a Poisson regression was used, adjusted by different hospitals from the same region. The model included a time variable to detect secular trends and 6 dummy variables for 7 predefined geographical regions: Metropolitana (MET); Pampa (PAM); Centro (CEN); Cuyo (CUY); Noroeste (NOA); Nordeste (NEA) and Patagonia (PAT). High frequencies regional analysis showed the following significant results: PAM: severe hypospadias; CEN: spina bifida, microtia, cleft lip with cleft palate, polycystic kidney, postaxial polydactyly and Down syndrome; CUY: postaxial polydactyly; NOA: omphalocele, gastroschisis, cleft lip without cleft palate, cleft lip with cleft palate, anorectal atresia/stenosis, indeterminate sex, preaxial polydactyly and pectoral agenesis; PAT: cleft lip without cleft palate. Out of the 27 congenital anomalies analyzed, fourteen showed a frequency significatively higher in one or more regions.

Wind, Circulation, and Topographic Effects on Alongshore Phytoplankton Variability in the California Current

NASA Astrophysics Data System (ADS)

Fiechter, Jerome; Edwards, Christopher A.; Moore, Andrew M.

2018-04-01

A physical-biogeochemical model is used to produce a retrospective analysis at 3-km resolution of alongshore phytoplankton variability in the California Current during 1988-2010. The simulation benefits from downscaling a regional circulation reanalysis, which provides improved physical ocean state estimates in the high-resolution domain. The emerging pattern is one of local upwelling intensification in response to increased alongshore wind stress in the lee of capes, modulated by alongshore meanders in the geostrophic circulation. While stronger upwelling occurs near most major topographic features, substantial increases in phytoplankton biomass only ensue where local circulation patterns are conducive to on-shelf retention of upwelled nutrients. Locations of peak nutrient delivery and chlorophyll accumulation also exhibit interannual variability and trends noticeably larger than the surrounding shelf regions, thereby suggesting that long-term planktonic ecosystem response in the California Current exhibits a significant local scale (O(100 km)) alongshore component.

Brightness Variations in the Solar Atmosphere as Seen by SOHO

NASA Astrophysics Data System (ADS)

Brkovic, A.; Rüedi, I.; Solanki, S. K.; Huber, M. C. E.; Stenflo, J. O.; Stucki, K.; Harrison, R.; Fludra, A.

We present preliminary results of a statistical analysis of the brightness variations of solar features at different levels in the solar atmosphere. We observed quiet Sun regions at disc centre using the Coronal Diagnostic Spectrometer (CDS) onboard the Solar and Heliospheric Observatory (SOHO). We find significant variability at all time scales in all parts of the quiet Sun, from darkest intranetwork to brightest network. Such variations are observed simultaneously in the chromospheric He I 584.33 Angstroms (2 \\cdot 10^4 K) line, the transition region O V 629.74 Angstroms (2.5 \\cdot 10^5 K) and coronal Mg IX 368.06 Angstroms (10^6 K) line. The relative variability is independent of brightness and most of the variability appears to take place on time scales longer than 5 minutes for all 3 spectral lines. No significant differences are observed between the different data sets.

Analysis of Biomass Feedstock Availability and Variability for the Peace River Region of Alberta, Canada

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stephen, Jamie; Sokhansanj, Shahabaddine; Bi, X.T.

2009-11-01

Biorefineries or other biomass-dependent facilities require a predictable, dependable feedstock supplied over many years to justify capital investments. Determining inter-year variability in biomass availability is essential to quantifying the feedstock supply risk. Using a geographic information system (GIS) and historic crop yield data, average production was estimated for 10 sites in the Peace River region of Alberta, Canada. Four high-yielding potential sites were investigated for variability over a 20 year time-frame (1980 2000). The range of availability was large, from double the average in maximum years to nothing in minimum years. Biomass availability is a function of grain yield, themore » biomass to grain ratio, the cropping frequency, and residue retention rate to ensure future crop productivity. Storage strategies must be implemented and alternate feedstock sources identified to supply biomass processing facilities in low-yield years.« less

An effective drift correction for dynamical downscaling of decadal global climate predictions

NASA Astrophysics Data System (ADS)

Paeth, Heiko; Li, Jingmin; Pollinger, Felix; Müller, Wolfgang A.; Pohlmann, Holger; Feldmann, Hendrik; Panitz, Hans-Jürgen

2018-04-01

Initialized decadal climate predictions with coupled climate models are often marked by substantial climate drifts that emanate from a mismatch between the climatology of the coupled model system and the data set used for initialization. While such drifts may be easily removed from the prediction system when analyzing individual variables, a major problem prevails for multivariate issues and, especially, when the output of the global prediction system shall be used for dynamical downscaling. In this study, we present a statistical approach to remove climate drifts in a multivariate context and demonstrate the effect of this drift correction on regional climate model simulations over the Euro-Atlantic sector. The statistical approach is based on an empirical orthogonal function (EOF) analysis adapted to a very large data matrix. The climate drift emerges as a dramatic cooling trend in North Atlantic sea surface temperatures (SSTs) and is captured by the leading EOF of the multivariate output from the global prediction system, accounting for 7.7% of total variability. The SST cooling pattern also imposes drifts in various atmospheric variables and levels. The removal of the first EOF effectuates the drift correction while retaining other components of intra-annual, inter-annual and decadal variability. In the regional climate model, the multivariate drift correction of the input data removes the cooling trends in most western European land regions and systematically reduces the discrepancy between the output of the regional climate model and observational data. In contrast, removing the drift only in the SST field from the global model has hardly any positive effect on the regional climate model.

A probabilistic method for streamflow projection and associated uncertainty analysis in a data sparse alpine region

NASA Astrophysics Data System (ADS)

Ren, Weiwei; Yang, Tao; Shi, Pengfei; Xu, Chong-yu; Zhang, Ke; Zhou, Xudong; Shao, Quanxi; Ciais, Philippe

2018-06-01

Climate change imposes profound influence on regional hydrological cycle and water security in many alpine regions worldwide. Investigating regional climate impacts using watershed scale hydrological models requires a large number of input data such as topography, meteorological and hydrological data. However, data scarcity in alpine regions seriously restricts evaluation of climate change impacts on water cycle using conventional approaches based on global or regional climate models, statistical downscaling methods and hydrological models. Therefore, this study is dedicated to development of a probabilistic model to replace the conventional approaches for streamflow projection. The probabilistic model was built upon an advanced Bayesian Neural Network (BNN) approach directly fed by the large-scale climate predictor variables and tested in a typical data sparse alpine region, the Kaidu River basin in Central Asia. Results show that BNN model performs better than the general methods across a number of statistical measures. The BNN method with flexible model structures by active indicator functions, which reduce the dependence on the initial specification for the input variables and the number of hidden units, can work well in a data limited region. Moreover, it can provide more reliable streamflow projections with a robust generalization ability. Forced by the latest bias-corrected GCM scenarios, streamflow projections for the 21st century under three RCP emission pathways were constructed and analyzed. Briefly, the proposed probabilistic projection approach could improve runoff predictive ability over conventional methods and provide better support to water resources planning and management under data limited conditions as well as enable a facilitated climate change impact analysis on runoff and water resources in alpine regions worldwide.

Modeling the influence of atmospheric leading modes on the variability of the Arctic freshwater cycle

NASA Astrophysics Data System (ADS)

Niederdrenk, L.; Sein, D.; Mikolajewicz, U.

2013-12-01

Global general circulation models show remarkable differences in modeling the Arctic freshwater cycle. While they agree on the general sinks and sources of the freshwater budget, they differ largely in the magnitude of the mean values as well as in the variability of the freshwater terms. Regional models can better resolve the complex topography and small scale processes, but they are often uncoupled, thus missing the air-sea interaction. Additionally, regional models mostly use some kind of salinity restoring or flux correction, thus disturbing the freshwater budget. Our approach to investigate the Arctic hydrologic cycle and its variability is a regional atmosphere-ocean model setup, consisting of the global ocean model MPIOM with high resolution in the Arctic coupled to the regional atmosphere model REMO. The domain of the atmosphere model covers all catchment areas of the rivers draining into the Arctic. To account for all sinks and sources of freshwater in the Arctic, we include a discharge model providing terrestrial lateral waterflows. We run the model without salinity restoring but with freshwater correction, which is set to zero in the Arctic. This allows for the analysis of a closed freshwater budget in the Artic region. We perform experiments for the second half of the 20th century and use data from the global model MPIOM/ECHAM5 performed with historical conditions, that was used within the 4th Assessment Report of the IPCC, as forcing for our regional model. With this setup, we investigate how the dominant modes of large-scale atmospheric variability impact the variability in the freshwater components. We focus on the two leading empirical orthogonal functions of winter mean sea level pressure, as well as on the North Atlantic Oscillation and the Siberian High. These modes have a large impact on the Arctic Ocean circulation as well as on the solid and liquid export through Fram Strait and through the Canadian archipelago. However, they cannot explain the variability in river runoff. We find that not only winter conditions are responsible for increased river runoff, but also an enhanced summer cyclone activity, especially over Eurasia.

Intra- and inter-population variability and evaluation of the physical development of a young generation.

PubMed

Yampolskaya, Yulia A

2005-07-01

This study is concerned with long-term anthropometric examinations of children and adolescents aged 3-17 years in Moscow (over 10,500 persons, longitudinal and cross-sectional). Population variability of physical development was analyzed by means of regional estimation tables, which were developed on the basis of a regression analysis (scale of the regression of body mass to body length within a range from M - 1sigmaR to M + 2 sigmaR) and used for individual and group diagnostics taking into account age and sex. Such an approach allowed for the determination of the dynamics of the variability of Moscow schoolchildren from decade to decade (inter-population variability) and variations due to social differences (intra-population variability).

Multi-criteria evaluation of CMIP5 GCMs for climate change impact analysis

NASA Astrophysics Data System (ADS)

Ahmadalipour, Ali; Rana, Arun; Moradkhani, Hamid; Sharma, Ashish

2017-04-01

Climate change is expected to have severe impacts on global hydrological cycle along with food-water-energy nexus. Currently, there are many climate models used in predicting important climatic variables. Though there have been advances in the field, there are still many problems to be resolved related to reliability, uncertainty, and computing needs, among many others. In the present work, we have analyzed performance of 20 different global climate models (GCMs) from Climate Model Intercomparison Project Phase 5 (CMIP5) dataset over the Columbia River Basin (CRB) in the Pacific Northwest USA. We demonstrate a statistical multicriteria approach, using univariate and multivariate techniques, for selecting suitable GCMs to be used for climate change impact analysis in the region. Univariate methods includes mean, standard deviation, coefficient of variation, relative change (variability), Mann-Kendall test, and Kolmogorov-Smirnov test (KS-test); whereas multivariate methods used were principal component analysis (PCA), singular value decomposition (SVD), canonical correlation analysis (CCA), and cluster analysis. The analysis is performed on raw GCM data, i.e., before bias correction, for precipitation and temperature climatic variables for all the 20 models to capture the reliability and nature of the particular model at regional scale. The analysis is based on spatially averaged datasets of GCMs and observation for the period of 1970 to 2000. Ranking is provided to each of the GCMs based on the performance evaluated against gridded observational data on various temporal scales (daily, monthly, and seasonal). Results have provided insight into each of the methods and various statistical properties addressed by them employed in ranking GCMs. Further; evaluation was also performed for raw GCM simulations against different sets of gridded observational dataset in the area.

Environmental and Regional Determinants of Anopheles (Diptera: Culicidae) Larval Distribution in Belize, Central America

DTIC Science & Technology

1993-01-01

hydrology , soils and, consequently, vege- tation cover (Hartshorn et al. 1984). The terms “regional” and “region” are used in this article for...and A. argyritar- sis Robineau-Desvoidy, were used for analysis of associations with environmental factors, habitat types, and regions. Using ...significantly contributing environmental variables, dis- criminant functions (DF) were constructed for the Anopheles species, except for A. argy

[Homicides involving firearms in Argentina between 1991 and 2006: a multilevel analysis].

PubMed

Zunino, Marina Gabriela; Diez Roux, Ana Victoria; de Souza, Edinilsa Ramos

2012-12-01

The influence of variables at different levels of organization and the effect of time on the occurrence of firearm-related homicides (FRH) in Argentina between 1991 and 2006 was analyzed using multilevel analysis. A three-level Poisson regression model was used. The first level corresponded to the distribution of the number of FRH by sex and age group for each administrative region and (four-year) period; the second corresponded to the variation over time in the interior of each administrative region; the third modeled the variation between administrative regions in accordance with the Level of Urbanization, Percentage of Homes with Unsatisfied Basic Needs and the Percentage of Working Adults. There were 15,067 FRH in persons aged 14 and over between 1991 and 2006 in the 493 administrative regions. The risk of death was higher in males and persons of 15 to 29 years of age; ages above that were associated with a lower risk. The influence of age was greater in central-urban zones and between 1999 and 2002 than during other periods. The level of urbanization was the socioeconomic variable most strongly associated with FRH risk. The risk of death from FRH was 1.6 times higher in central-urban zones compared with non-central zones. In both zones, the risk was highest between 1999 and 2002.

Tomato (Solanum lycopersicum) variety discrimination and hybridization analysis based on the 5S rRNA region.

PubMed

Sun, Yan-Lin; Kang, Ho-Min; Kim, Young-Sik; Baek, Jun-Pill; Zheng, Shi-Lin; Xiang, Jin-Jun; Hong, Soon-Kwan

2014-05-04

The tomato ( Solanum lycopersicum ) is a major vegetable crop worldwide. To satisfy popular demand, more than 500 tomato varieties have been bred. However, a clear variety identification has not been found. Thorough understanding of the phylogenetic relationship and hybridization information of tomato varieties is very important for further variety breeding. Thus, in this study, we collected 26 tomato varieties and attempted to distinguish them based on the 5S rRNA region, which is widely used in the determination of phylogenetic relations. Sequence analysis of the 5S rRNA region suggested that a large number of nucleotide variations exist among tomato varieties. These variable nucleotide sites were also informative regarding hybridization. Chromas sequencing of Yellow Mountain View and Seuwiteuking varieties indicated three and one variable nucleotide sites in the non-transcribed spacer (NTS) of the 5S rRNA region showing hybridization, respectively. Based on a phylogenetic tree constructed using the 5S rRNA sequences, we observed that 16 tomato varieties were divided into three groups at 95% similarity. Rubiking and Sseommeoking, Lang Selection Procedure and Seuwiteuking, and Acorn Gold and Yellow Mountain View exhibited very high identity with their partners. This work will aid variety authentication and provides a basis for further tomato variety breeding.

Spatial variability of total carbon and soil organic carbon in agricultural soils in Baranja region, Croatia

NASA Astrophysics Data System (ADS)

Bogunović, Igor; Trevisani, Sebastiano; Pereira, Paulo; Šeput, Miranda

2017-04-01

Climate change is expected to have an important influence on the crop production in agricultural regions. Soil carbon represents an important soil property that contributes to mitigate the negative influence of climate change on intensive cropped areas. Based on 5063 soil samples sampled from soil top layer (0-30 cm) we studied the spatial distribution of total carbon (TC) and soil organic carbon (SOC) content in various soil types (Anthrosols, Cambisols, Chernozems, Fluvisols, Gleysols, Luvisols) in Baranja region, Croatia. TC concentrations ranged from 2.10 to 66.15 mg/kg (with a mean of 16.31 mg/kg). SOC concentrations ranged from 1.86 to 58.00 mg/kg (with a mean of 13.35 mg/kg). TC and SOC showed moderate heterogeneity with coefficient of variation (CV) of 51.3% and 33.8%, respectively. Average concentrations of soil TC vary in function of soil types in the following decreasing order: Anthrosols (20.9 mg/kg) > Gleysols (19.3 mg/kg) > Fluvisols (15.6 mg/kg) > Chernozems (14.2 mg/kg) > Luvisols (12.6 mg/kg) > Cambisols (11.1 mg/kg), while SOC concentrations follow next order: Gleysols (15.4 mg/kg) > Fluvisols (13.2 mg/kg) = Anthrosols (13.2 mg/kg) > Chernozems (12.6 mg/kg) > Luvisols (11.4 mg/kg) > Cambisols (10.5 mg/kg). Performed geostatistical analysis of TC and SOC; both the experimental variograms as well as the interpolated maps reveal quite different spatial patterns of the two studied soil properties. The analysis of the spatial variability and of the spatial patterns of the produced maps show that SOC is likely influenced by antrophic processes. Spatial variability of SOC indicates soil health deterioration on an important significant portion of the studied area; this suggests the need for future adoption of environmentally friendly soil management in the Baranja region. Regional maps of TC and SOC provide quantitative information for regional planning and environmental monitoring and protection purposes.

Analysis of the regional MiKlip decadal prediction system over Europe: skill, added value of regionalization, and ensemble size dependeny

NASA Astrophysics Data System (ADS)

Reyers, Mark; Moemken, Julia; Pinto, Joaquim; Feldmann, Hendrik; Kottmeier, Christoph; MiKlip Module-C Team

2017-04-01

Decadal climate predictions can provide a useful basis for decision making support systems for the public and private sectors. Several generations of decadal hindcasts and predictions have been generated throughout the German research program MiKlip. Together with the global climate predictions computed with MPI-ESM, the regional climate model (RCM) COSMO-CLM is used for regional downscaling by MiKlip Module-C. The RCMs provide climate information on spatial and temporal scales closer to the needs of potential users. In this study, two downscaled hindcast generations are analysed (named b0 and b1). The respective global generations are both initialized by nudging them towards different reanalysis anomaly fields. An ensemble of five starting years (1961, 1971, 1981, 1991, and 2001), each comprising ten ensemble members, is used for both generations in order to quantify the regional decadal prediction skill for precipitation and near-surface temperature and wind speed over Europe. All datasets (including hindcasts, observations, reanalysis, and historical MPI-ESM runs) are pre-processed in an analogue manner by (i) removing the long-term trend and (ii) re-gridding to a common grid. Our analysis shows that there is potential for skillful decadal predictions over Europe in the regional MiKlip ensemble, but the skill is not systematic and depends on the PRUDENCE region and the variable. Further, the differences between the two hindcast generations are mostly small. As we used detrended time series, the predictive skill found in our study can probably attributed to reasonable predictions of anomalies which are associated with the natural climate variability. In a sensitivity study, it is shown that the results may strongly change when the long-term trend is kept in the datasets, as here the skill of predicting the long-term trend (e.g. for temperature) also plays a major role. The regionalization of the global ensemble provides an added value for decadal predictions for some complex regions like the Mediterranean and Iberian Peninsula, while for other regions no systematic improvement is found. A clear dependence of the performance of the regional MiKlip system on the ensemble size is detected. For all variables in both hindcast generations, the skill increases when the ensemble is enlarged. The results indicate that a number of ten members is an appropriate ensemble size for decadal predictions over Europe.

Southeast Pacific atmospheric composition and variability sampled along 20˚S during VOCALS-REx

DOE Office of Scientific and Technical Information (OSTI.GOV)

Allen, G.; Kleinman, L.; Coe, H.

2011-01-10

The VAMOS Ocean-Climate-Atmosphere-Land Regional Experiment (VOCALS-REx) was conducted from 15 October to 15 November 2008 in the South East Pacific region to investigate interactions between land, sea and atmosphere in this unique tropical eastern ocean environment and to improve the skill of global and regional models in representing the region. This study synthesises selected aircraft, ship and surface site observations from VOCALS-REx to statistically summarise and characterise the atmospheric composition and variability of the Marine Boundary Layer (MBL) and Free Troposphere (FT) along the 20{sup o} S parallel between 70{sup o} W and 85{sup o} W. Significant zonal gradients inmore » mean MBL sub-micron aerosol particle size and composition, carbon monoxide, ozone and sulphur dioxide were seen over the campaign, with a generally more variable and polluted coastal environment and a less variable, more pristine remote maritime regime. Gradients are observed to be associated with strong gradients in cloud droplet number. The FT is often more polluted in terms of trace gases than the MBL in the mean; however increased variability in the FT composition suggests an episodic nature to elevated concentrations. This is consistent with a complex vertical interleaving of airmasses with diverse sources and hence pollutant concentrations as seen by generalised back trajectory analysis, which suggests contributions from both local and long-range sources. Furthermore, back trajectory analysis demonstrates that the observed zonal gradients both in the boundary layer and the free troposphere are characteristic of marked changes in airmass history with distance offshore - coastal boundary layer airmasses having been in recent contact with the local land surface and remote maritime airmasses having resided over ocean for in excess of ten days. Boundary layer composition to the east of 75{sup o} W was observed to be dominated by coastal emissions from sources to the west of the Andes, with evidence for diurnal pumping of the Andean boundary layer above the height of the marine capping inversion. The climatology presented here aims to provide a valuable dataset to inform model simulation and future process studies, particularly in the context of aerosol-cloud interaction and further evaluation of dynamical processes in the SEP region for conditions analogous to those during VOCALS-REx.« less

River-discharge variability and trends in southeastern Central Andes since 1940

NASA Astrophysics Data System (ADS)

Castino, Fabiana; Bookhagen, Bodo; Strecker, Manfred R.

2017-04-01

The southern Central Andes in NW Argentina comprise small to medium drainage basins (102-104 km2) particularly sensitive to climate variability. In this area and in contrast to larger drainage basins such as the Amazon or La Plata rivers, floodplains or groundwater reservoirs either do not exist or are small. This reduces their dampening effect on discharge variability. Previous studies highlighted a rapid discharge increase up to 40% in seven years in the southern Central Andes during the 1970s, inferred to have been associated with the global 1976-77 climate shift. To better understand the processes that drive variations in river discharge in this region, we analyze discharge variability on different timescales, relying on four time series of monthly discharge between 1940 and 2015. Since river discharge in this complex mountain environment results in a pronounced non-stationary and non-linear character, we apply the Hilbert-Huang Transform (HHT) to evaluate non-stationary oscillatory modes of variability and trends. An Ensemble Empirical Mode Decomposition (EEMD) analysis revealed that discharge variability in this region can be decomposed in four quasi-periodic, statistically significant oscillatory modes, associated with timescales varying from 1 to ˜20y. In addition, statistically significant long-term trends show increasing discharge during the period between 1940 and 2015, documenting an intensification of the hydrological cycle during this period. Furthermore, time-dependent intrinsic correlation (TDIC) analysis shows that discharge variability is most likely linked to the phases of the Pacific Decadal Oscillation (PDO) at multi-decadal timescales (˜20y) and, to a lesser degree, to the Tropical South Atlantic SST anomaly (TSA) variability at shorter timescales (˜2-5y). Finally, our results suggest that the rapid discharge increased occurred during the 1970s coincides with the periodic enhancement of discharge mainly linked to the rise of the PDO oscillation from the negative to the positive phase in superposition with the long-term increasing trend, further modulated by TSA variability.

In Silico Prediction Analysis of Idiotope-Driven T–B Cell Collaboration in Multiple Sclerosis

PubMed Central

Høglund, Rune A.; Lossius, Andreas; Johansen, Jorunn N.; Homan, Jane; Benth, Jūratė Šaltytė; Robins, Harlan; Bogen, Bjarne; Bremel, Robert D.; Holmøy, Trygve

2017-01-01

Memory B cells acting as antigen-presenting cells are believed to be important in multiple sclerosis (MS), but the antigen they present remains unknown. We hypothesized that B cells may activate CD4+ T cells in the central nervous system of MS patients by presenting idiotopes from their own immunoglobulin variable regions on human leukocyte antigen (HLA) class II molecules. Here, we use bioinformatics prediction analysis of B cell immunoglobulin variable regions from 11 MS patients and 6 controls with other inflammatory neurological disorders (OINDs), to assess whether the prerequisites for such idiotope-driven T–B cell collaboration are present. Our findings indicate that idiotopes from the complementarity determining region (CDR) 3 of MS patients on average have high predicted affinities for disease associated HLA-DRB1*15:01 molecules and are predicted to be endosomally processed by cathepsin S and L in positions that allows such HLA binding to occur. Additionally, complementarity determining region 3 sequences from cerebrospinal fluid (CSF) B cells from MS patients contain on average more rare T cell-exposed motifs that could potentially escape tolerance and stimulate CD4+ T cells than CSF B cells from OIND patients. Many of these features were associated with preferential use of the IGHV4 gene family by CSF B cells from MS patients. This is the first study to combine high-throughput sequencing of patient immune repertoires with large-scale prediction analysis and provides key indicators for future in vitro and in vivo analyses. PMID:29038659

In Silico Prediction Analysis of Idiotope-Driven T-B Cell Collaboration in Multiple Sclerosis.

PubMed

Høglund, Rune A; Lossius, Andreas; Johansen, Jorunn N; Homan, Jane; Benth, Jūratė Šaltytė; Robins, Harlan; Bogen, Bjarne; Bremel, Robert D; Holmøy, Trygve

2017-01-01

Memory B cells acting as antigen-presenting cells are believed to be important in multiple sclerosis (MS), but the antigen they present remains unknown. We hypothesized that B cells may activate CD4 + T cells in the central nervous system of MS patients by presenting idiotopes from their own immunoglobulin variable regions on human leukocyte antigen (HLA) class II molecules. Here, we use bioinformatics prediction analysis of B cell immunoglobulin variable regions from 11 MS patients and 6 controls with other inflammatory neurological disorders (OINDs), to assess whether the prerequisites for such idiotope-driven T-B cell collaboration are present. Our findings indicate that idiotopes from the complementarity determining region (CDR) 3 of MS patients on average have high predicted affinities for disease associated HLA-DRB1*15:01 molecules and are predicted to be endosomally processed by cathepsin S and L in positions that allows such HLA binding to occur. Additionally, complementarity determining region 3 sequences from cerebrospinal fluid (CSF) B cells from MS patients contain on average more rare T cell-exposed motifs that could potentially escape tolerance and stimulate CD4 + T cells than CSF B cells from OIND patients. Many of these features were associated with preferential use of the IGHV4 gene family by CSF B cells from MS patients. This is the first study to combine high-throughput sequencing of patient immune repertoires with large-scale prediction analysis and provides key indicators for future in vitro and in vivo analyses.

Techniques for estimating flood-depth frequency relations for streams in West Virginia

USGS Publications Warehouse

Wiley, J.B.

1987-01-01

Multiple regression analyses are applied to data from 119 U.S. Geological Survey streamflow stations to develop equations that estimate baseline depth (depth of 50% flow duration) and 100-yr flood depth on unregulated streams in West Virginia. Drainage basin characteristics determined from the 100-yr flood depth analysis were used to develop 2-, 10-, 25-, 50-, and 500-yr regional flood depth equations. Two regions with distinct baseline depth equations and three regions with distinct flood depth equations are delineated. Drainage area is the most significant independent variable found in the central and northern areas of the state where mean basin elevation also is significant. The equations are applicable to any unregulated site in West Virginia where values of independent variables are within the range evaluated for the region. Examples of inapplicable sites include those in reaches below dams, within and directly upstream from bridge or culvert constrictions, within encroached reaches, in karst areas, and where streams flow through lakes or swamps. (Author 's abstract)

An analysis of wildfire frequency and burned area relationships with human pressure and climate gradients in the context of fire regime

NASA Astrophysics Data System (ADS)

Jiménez-Ruano, Adrián; Rodrigues Mimbrero, Marcos; de la Riva Fernández, Juan

2017-04-01

Understanding fire regime is a crucial step towards achieving a better knowledge of the wildfire phenomenon. This study proposes a method for the analysis of fire regime based on multidimensional scatterplots (MDS). MDS are a visual approach that allows direct comparison among several variables and fire regime features so that we are able to unravel spatial patterns and relationships within the region of analysis. Our analysis is conducted in Spain, one of the most fire-affected areas within the Mediterranean region. Specifically, the Spanish territory has been split into three regions - Northwest, Hinterland and Mediterranean - considered as representative fire regime zones according to MAGRAMA (Spanish Ministry of Agriculture, Environment and Food). The main goal is to identify key relationships between fire frequency and burnt area, two of the most common fire regime features, with socioeconomic activity and climate. In this way we will be able to better characterize fire activity within each fire region. Fire data along the period 1974-2010 was retrieved from the General Statistics Forest Fires database (EGIF). Specifically, fire frequency and burnt area size was examined for each region and fire season (summer and winter). Socioeconomic activity was defined in terms of human pressure on wildlands, i.e. the presence and intensity of anthropogenic activity near wildland or forest areas. Human pressure was built from GIS spatial information about land use (wildland-agriculture and wildland-urban interface) and demographic potential. Climate variables (average maximum temperature and annual precipitation) were extracted from MOTEDAS (Monthly Temperature Dataset of Spain) and MOPREDAS (Monthly Precipitation Dataset of Spain) datasets and later reclassified into ten categories. All these data were resampled to fit the 10x10 Km grid used as spatial reference for fire data. Climate and socioeconomic variables were then explored by means of MDS to find the extent to which fire frequency and burnt areas are controlled by either environmental, human, or both factors. Results reveal a noticeable link between fire frequency and human activity, especially in the Northwest area during winter. On the other hand, in the Hinterland and Mediterranean regions, human and climate factors 'work' together in terms of their relationship with fire activity, being the concurrence of high human pressure and favourable climate conditions the main driver. In turn, burned area shows a similar behaviour except in the Hinterland region, were fire-affected area depends mostly on climate factors. Overall, we can conclude that the visual analysis of multidimensional scatterplots has proved to be a powerful tool that facilitates characterization and investigation of fire regimes.

Summer U.S. Surface Air Temperature Variability: Controlling Factors and AMIP Simulation Biases

NASA Astrophysics Data System (ADS)

Merrifield, A.; Xie, S. P.

2016-02-01

This study documents and investigates biases in simulating summer surface air temperature (SAT) variability over the continental U.S. in the Coupled Model Intercomparison Project (CMIP5) Atmospheric Model Intercomparison Project (AMIP). Empirical orthogonal function (EOF) and multivariate regression analyses are used to assess the relative importance of circulation and the land surface feedback at setting summer SAT over a 30-year period (1979-2008). In observations, regions of high SAT variability are closely associated with midtropospheric highs and subsidence, consistent with adiabatic theory (Meehl and Tebaldi 2004, Lau and Nath 2012). Preliminary analysis shows the majority of the AMIP models feature high SAT variability over the central U.S., displaced south and/or west of observed centers of action (COAs). SAT COAs in models tend to be concomitant with regions of high sensible heat flux variability, suggesting an excessive land surface feedback in these models modulate U.S. summer SAT. Additionally, tropical sea surface temperatures (SSTs) play a role in forcing the leading EOF mode for summer SAT, in concert with internal atmospheric variability. There is evidence that models respond to different SST patterns than observed. Addressing issues with the bulk land surface feedback and the SST-forced component of atmospheric variability may be key to improving model skill in simulating summer SAT variability over the U.S.

Production cost analysis of Euphorbia lathyris. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mendel, D.A.; Schooley, F.A.; Dickenson, R.L.

1979-08-01

The purpose of SRI's study was to estimate the costs of producing Euphorbia in commercial quantities in five regions of the United States, which include both irrigated and nonirrigated areas. The study assumed that a uniform crop yield could be achieved in the five regions by varying the quantities of production inputs. Therefore, the production costs estimates, which are based on fourth quarter 1978 dollars, include both fixed and variable costs for each region. Doane's Machinery Custom Rates for 1978 were used to estimate all variable costs except materials, which were estimated separately. Custom rates are determined by members ofmore » the Doane Countywide Farm Panel, a group of farmers specifically selected to represent the various sizes and types of commercial farms found throughout the country. The rates reported are the most recent rates the panel members had either paid, charged, or known for certain a second party had paid or charged. Custom rates for any particular operation include equipment operating costs (fuel, lubrication, and repairs), equipment ownership costs (depreciation, taxes, interest), as well as a labor charge for the operator. Custom rates are regionally specific and thereby assist the accuracy of this analysis. Fixed costs include land, management, and transportation of the plant material to a conversion facility. When appropriate, fixed costs were regionally specific. Changes in total production costs over future time periods were not addressed. The total estimated production costs of Euphorbia in each region were compared with production costs for corn and alfalfa in the same regions. Finally, the effects on yield and costs of changes in the production inputs were estimated.« less

Selecting global climate models for regional climate change studies

PubMed Central

Pierce, David W.; Barnett, Tim P.; Santer, Benjamin D.; Gleckler, Peter J.

2009-01-01

Regional or local climate change modeling studies currently require starting with a global climate model, then downscaling to the region of interest. How should global models be chosen for such studies, and what effect do such choices have? This question is addressed in the context of a regional climate detection and attribution (D&A) study of January-February-March (JFM) temperature over the western U.S. Models are often selected for a regional D&A analysis based on the quality of the simulated regional climate. Accordingly, 42 performance metrics based on seasonal temperature and precipitation, the El Nino/Southern Oscillation (ENSO), and the Pacific Decadal Oscillation are constructed and applied to 21 global models. However, no strong relationship is found between the score of the models on the metrics and results of the D&A analysis. Instead, the importance of having ensembles of runs with enough realizations to reduce the effects of natural internal climate variability is emphasized. Also, the superiority of the multimodel ensemble average (MM) to any 1 individual model, already found in global studies examining the mean climate, is true in this regional study that includes measures of variability as well. Evidence is shown that this superiority is largely caused by the cancellation of offsetting errors in the individual global models. Results with both the MM and models picked randomly confirm the original D&A results of anthropogenically forced JFM temperature changes in the western U.S. Future projections of temperature do not depend on model performance until the 2080s, after which the better performing models show warmer temperatures. PMID:19439652

Quantifying Spatial and Seasonal Variability in Atmospheric Ammonia with In Situ and Space-Based Observations

NASA Technical Reports Server (NTRS)

Pinder, Robert W.; Walker, John T.; Bash, Jesse O.; Cady-Pereira, Karen E.; Henze, Daven K.; Luo, Mingzhao; Osterman, Gregory B.; Shepard, Mark W.

2011-01-01

Ammonia plays an important role in many biogeochemical processes, yet atmospheric mixing ratios are not well known. Recently, methods have been developed for retrieving NH3 from space-based observations, but they have not been compared to in situ measurements. We have conducted a field campaign combining co-located surface measurements and satellite special observations from the Tropospheric Emission Spectrometer (TES). Our study includes 25 surface monitoring sites spanning 350 km across eastern North Carolina, a region with large seasonal and spatial variability in NH3. From the TES spectra, we retrieve a NH3 representative volume mixing ratio (RVMR), and we restrict our analysis to times when the region of the atmosphere observed by TES is representative of the surface measurement. We find that the TES NH3 RVMR qualitatively captures the seasonal and spatial variability found in eastern North Carolina. Both surface measurements and TES NH3 show a strong correspondence with the number of livestock facilities within 10 km of the observation. Furthermore, we find that TES H3 RVMR captures the month-to-month variability present in the surface observations. The high correspondence with in situ measurements and vast spatial coverage make TES NH3 RVMR a valuable tool for understanding regional and global NH3 fluxes.

Developmental craniofacial anthropometry: Assessment of Race effects

PubMed Central

Durtschi, Reid B.; Chung, Dongjun; Gentry, Lindell R.; Chung, Moo K.; Vorperian, Houri K.

2010-01-01

Differences in craniofacial anatomy among racial groups have been documented in a variety of structures but the oral and maxillofacial regions have been shown to be a particularly defining region of variability between different racial/ethnic groups. Such comparisons are informative, but they neither address developmental changes of the craniofacial anatomy, nor do they assess or take into account the natural variability within individual races that may account for similar reported, across-group variations. The purpose of this report was to compare – using medical imaging studies – the growth trend of select race sensitive craniofacial variables in the oral and pharyngeal regions when all races: White, Asian, Black, and Hispanic (AR) are included versus only a single race category: White (WR). Race effect was tested by comparing sex specific growth fits (4th degree polynomial model) for AR versus WR data. Findings indicate that the inclusion of all races versus a single race did not significantly alter the growth model fits. Thus, the inclusion of all races permits the advancement of general growth models; however, methodologically it is best to treat the race variable as a covariate in all future analysis to test for both potential all race effects or individual race effects, on general growth models. PMID:19753647

Identification of quantitative trait loci for fibrin clot phenotypes: The EuroCLOT study

PubMed Central

Williams, Frances MK; Carter, Angela M; Kato, Bernet; Falchi, Mario; Bathum, Lise; Surdulescu, Gabriela; Kyvik, Kirsten Ohm; Palotie, Aarno; Spector, Tim D; Grant, Peter J

2012-01-01

Objectives Fibrin makes up the structural basis of an occlusive arterial thrombus and variability in fibrin phenotype relates to cardiovascular risk. The aims of the current study from the EU consortium EuroCLOT were to 1) determine the heritability of fibrin phenotypes and 2) identify QTLs associated with fibrin phenotypes. Methods 447 dizygotic (DZ) and 460 monozygotic (MZ) pairs of healthy UK Caucasian female twins and 199 DZ twin pairs from Denmark were studied. D-dimer, an indicator of fibrin turnover, was measured by ELISA and measures of clot formation, morphology and lysis were determined by turbidimetric assays. Heritability estimates and genome-wide linkage analysis were performed. Results Estimates of heritability for d-dimer and turbidometric variables were in the range 17 - 46%, with highest levels for maximal absorbance which provides an estimate of clot density. Genome-wide linkage analysis revealed 6 significant regions with LOD>3 on 5 chromosomes (5, 6, 9, 16 and 17). Conclusions The results indicate a significant genetic contribution to variability in fibrin phenotypes and highlight regions in the human genome which warrant further investigation in relation to ischaemic cardiovascular disorders and their therapy. PMID:19150881

MULTIPLE-LOCUS VARIABLE-NUMBER TANDEM REPEAT ANALYSIS OF BRUCELLA ISOLATES FROM THAILAND.

PubMed

Kumkrong, Khurawan; Chankate, Phanita; Tonyoung, Wittawat; Intarapuk, Apiradee; Kerdsin, Anusak; Kalambaheti, Thareerat

2017-01-01

Brucellosis-induced abortion can result in significant economic loss to farm animals. Brucellosis can be transmitted to humans during slaughter of infected animals or via consumption of contaminated food products. Strain identification of Brucella isolates can reveal the route of transmission. Brucella strains were isolated from vaginal swabs of farm animal, cow milk and from human blood cultures. Multiplex PCR was used to identify Brucella species, and owing to high DNA homology among Brucella isolates, multiple-locus variable-number tandem repeat analysis (MLVA) based on the number of tandem repeats at 16 different genomic loci was used for strain identification. Multiplex PCR categorized the isolates into B. abortus (n = 7), B. melitensis (n = 37), B. suis (n = 3), and 5 of unknown Brucella spp. MLVA-16 clustering analysis differentiated the strains into various genotypes, with Brucella isolates from the same geographic region being closely related, and revealed that the Thai isolates were phylogenetically distinct from those in other countries, including within the Southeast Asian region. Thus, MLVA-16 typing has utility in epidemiological studies.

Variability in the performance of preventive services and in the degree of control of identified health problems: A primary care study protocol

PubMed Central

Bolíbar, Bonaventura; Pareja, Clara; Astier-Peña, M Pilar; Morán, Julio; Rodríguez-Blanco, Teresa; Rosell-Murphy, Magdalena; Iglesias, Manuel; Juncosa, Sebastián; Mascort, Juanjo; Violan, Concepció; Magallón, Rosa; Apezteguia, Javier

2008-01-01

Background Preventive activities carried out in primary care have important variability that makes necessary to know which factors have an impact in order to establish future strategies for improvement. The present study has three objectives: 1) To describe the variability in the implementation of 7 preventive services (screening for smoking status, alcohol abuse, hypertension, hypercholesterolemia, obesity, influenza and tetanus immunization) and to determine their related factors; 2) To describe the degree of control of 5 identified health problems (smoking, alcohol abuse, hypertension, hypercholesterolemia and obesity); 3) To calculate intraclass correlation coefficients. Design Multi-centered cross-sectional study of a randomised sample of primary health care teams from 3 regions of Spain designed to analyse variability and related factors of 7 selected preventive services in years 2006 and 2007. At the end of 2008, we will perform a cross-sectional study of a cohort of patients attended in 2006 or 2007 to asses the degree of control of 5 identified health problems. All subjects older than16 years assigned to a randomised sample of 22 computerized primary health care teams and attended during the study period are included in each region providing a sample with more than 850.000 subjects. The main outcome measures will be implementation of 7 preventive services and control of 5 identified health problems. Furthermore, there will be 3 levels of data collection: 1) Patient level (age, gender, morbidity, preventive services, attendance); 2) Health-care professional level (professional characteristics, years working at the team, workload); 3) Team level (characteristics, electronic clinical record system). Data will be transferred from electronic clinical records to a central database with prior encryption and dissociation of subject, professional and team identity. Global and regional analysis will be performed including standard analysis for primary health care teams and health-care professional level. Linear and logistic regression multilevel analysis adjusted for individual and cluster variables will also be performed. Variability in the number of preventive services implemented will be calculated with Poisson multilevel models. Team and health-care professional will be considered random effects. Intraclass correlation coefficients, standard error and variance components for the different outcome measures will be calculated. PMID:18691407

Interannual variability and predictability over the Arabian Penuinsula Winter monsoon region

NASA Astrophysics Data System (ADS)

Adnan Abid, Muhammad; Kucharski, Fred; Almazroui, Mansour; Kang, In-Sik

2016-04-01

Interannual winter rainfall variability and its predictability are analysed over the Arabian Peninsula region by using observed and hindcast datasets from the state-of-the-art European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal prediction System 4 for the period 1981-2010. An Arabian winter monsoon index (AWMI) is defined to highlight the Arabian Peninsula as the most representative region for the Northern Hemispheric winter dominating the summer rainfall. The observations show that the rainfall variability is relatively large over the northeast of the Arabian Peninsula. The correlation coefficient between the Nino3.4 index and rainfall in this region is 0.33, suggesting potentially some modest predictability, and indicating that El Nino increases and La Nina decreases the rainfall. Regression analysis shows that upper-level cyclonic circulation anomalies that are forced by El Nino Southern Oscillation (ENSO) are responsible for the winter rainfall anomalies over the Arabian region. The stronger (weaker) mean transient-eddy activity related to the upper-level trough induced by the warm (cold) sea-surface temperatures during El Nino (La Nina) tends to increase (decrease) the rainfall in the region. The model hindcast dataset reproduces the ENSO-rainfall connection. The seasonal mean predictability of the northeast Arabian rainfall index is 0.35. It is shown that the noise variance is larger than the signal over the Arabian Peninsula region, which tends to limit the prediction skill. The potential predictability is generally increased in ENSO years and is, in particular, larger during La Nina compared to El Nino years in the region. Furthermore, central Pacific ENSO events and ENSO events with weak signals in the Indian Ocean tend to increase predictability over the Arabian region.

Influence of winter NAO pattern on variable renewable energies potential in Europe over the 20th century

NASA Astrophysics Data System (ADS)

François, Baptiste; Raynaud, Damien; Hingray, Benoit; Creutin, Jean-Dominique

2017-04-01

Integration of Variable Renewable Energy (VRE) sources in the electricity system is a challenge because of temporal and spatial fluctuations of their power generation resulting from their driving weather variables (i.e. solar radiation wind speed, precipitation, and temperature). Very few attention was paid to low frequency variability (i.e. from annual to decades) even though it may have significant impact on energy system and energy market Following the current increase in electricity supplied by VRE generation, one could ask the question about the risk of ending up in a situation in which the level of production of one or more VRE is exceptionally low or exceptionally high for a long period of time and/or over a large area. What would be the risk for an investor if the return on investment has been calculated on a high energy production period? What would be the cost in term of carbon emission whether the system manager needs to turn on coal power plant to satisfy the demand? Such dramatic events would definitely impact future stakeholder decision to invest in a particular energy source or another. Weather low frequency variability is mainly governed by large-scale teleconnection patterns impacting the climate at global scale such as El Niño - Southern Oscillation (ENSO) in the tropics and in North America or the North Atlantic Oscillation (hereafter, NAO) in North America and Europe. Teleconnection pattern's influence on weather variability cascades to VRE variability and ends up by impacting electricity system. The aim of this study is to analysis the impact of the NAO on VRE generation in Europe during the winter season. The analysis is carried out over the twentieth century (i.e. from 1900 to 2010), in order to take into account climate low frequency variability, and for a set of 12 regions covering a large range of climates in Europe. Weather variable time series are obtained by using the ERA20C reanalysis and the SCAMP model (Sequential Constructive Atmospheric Analogues for Multivariate weather Predictions, Raynaud et al. 2016). The analysis is performed for solar, wind and run-of-the river energy sources taken individually. For NAO sensitive regions, results shown important deviations between power generation distributions obtained either for strongly positive or strongly negative NAO events. We also used the optimal VRE combination provided by the 100 % solution project (http://thesolutionsproject.org/). We then discuss over the 12 considered regions the vulnerability to NAO events for the energy mix suggested by the 100 % solution project. Reference: Raynaud, D., Hingray, B., Zin, I., Anquetin, S., Debionne, S., Vautard, R., 2016. Atmospheric analogues for physically consistent scenarios of surface weather in Europe and Maghreb. Int. J. Climatol. doi:10.1002/joc.4844

Use of USDA forest inventory and analysis data to assess oak tree health in Minnesota

Treesearch

Kathryn W. Kromroy; Jennifer Juzwik; Paul D. Castillo

2003-01-01

As a precursor to a regional assessment for the Upper Midwest, three variables were examined as measures of oak health in Minnesota between 1974 and 1990 using USDA Forest Service Inventory and Analysis data. Mortality was 6 percent in the 1986-1990 inventory based on numbers of dead oaks per total oaks on plots with...

Southern Hemisphere rainfall variability over the past 200 years

NASA Astrophysics Data System (ADS)

Gergis, Joëlle; Henley, Benjamin J.

2017-04-01

This study presents an analysis of three palaeoclimate rainfall reconstructions from the Southern Hemisphere regions of south-eastern Australia (SEA), southern South Africa (SAF) and southern South America (SSA). We provide a first comparison of rainfall variations in these three regions over the past two centuries, with a focus on identifying synchronous wet and dry periods. Despite the uncertainties associated with the spatial and temporal limitations of the rainfall reconstructions, we find evidence of dynamically-forced climate influences. An investigation of the twentieth century relationship between regional rainfall and the large-scale climate circulation features of the Pacific, Indian and Southern Ocean regions revealed that Indo-Pacific variations of the El Niño-Southern Oscillation (ENSO) and the Indian Ocean dipole dominate rainfall variability in SEA and SAF, while the higher latitude Southern Annular Mode (SAM) exerts a greater influence in SSA. An assessment of the stability of the regional rainfall-climate circulation modes over the past two centuries revealed a number of non-stationarities, the most notable of which occurs during the early nineteenth century around 1820. This corresponds to a time when the influence of ENSO on SEA, SAF and SSA rainfall weakens and there is a strengthening of the influence of SAM. We conclude by advocating the use of long-term palaeoclimate data to estimate decadal rainfall variability for future water resource management.

Spectrum of phenotypic anomalies in four families with deletion of the SHOX enhancer region.

PubMed

Gatta, Valentina; Palka, Chiara; Chiavaroli, Valentina; Franchi, Sara; Cannataro, Giovanni; Savastano, Massimo; Cotroneo, Antonio Raffaele; Chiarelli, Francesco; Mohn, Angelika; Stuppia, Liborio

2014-07-23

SHOX alterations have been reported in 67% of patients affected by Léri-Weill dyschondrosteosis (LWD), with a larger prevalence of gene deletions than point mutations. It has been recently demonstrated that these deletions can involve the SHOX enhancer region, rather that the coding region, with variable phenotype of the affected patients.Here, we report a SHOX gene analysis carried out by MLPA in 14 LWD patients from 4 families with variable phenotype. All patients presented a SHOX enhancer deletion. In particular, a patient with a severe bilateral Madelung deformity without short stature showed a homozygous alteration identical to the recently described 47.5 kb PAR1 deletion. Moreover, we identified, for the first time, in three related patients with a severe bilateral Madelung deformity, a smaller deletion than the 47.5 kb PAR1 deletion encompassing the same enhancer region (ECR1/CNE7). Data reported in this study provide new information about the spectrum of phenotypic alterations showed by LWD patients with different deletions of the SHOX enhancer region.

Spectrum of phenotypic anomalies in four families with deletion of the SHOX enhancer region

PubMed Central

2014-01-01

Background SHOX alterations have been reported in 67% of patients affected by Léri-Weill dyschondrosteosis (LWD), with a larger prevalence of gene deletions than point mutations. It has been recently demonstrated that these deletions can involve the SHOX enhancer region, rather that the coding region, with variable phenotype of the affected patients. Here, we report a SHOX gene analysis carried out by MLPA in 14 LWD patients from 4 families with variable phenotype. Case presentation All patients presented a SHOX enhancer deletion. In particular, a patient with a severe bilateral Madelung deformity without short stature showed a homozygous alteration identical to the recently described 47.5 kb PAR1 deletion. Moreover, we identified, for the first time, in three related patients with a severe bilateral Madelung deformity, a smaller deletion than the 47.5 kb PAR1 deletion encompassing the same enhancer region (ECR1/CNE7). Conclusions Data reported in this study provide new information about the spectrum of phenotypic alterations showed by LWD patients with different deletions of the SHOX enhancer region. PMID:25056248

The 1985 central chile earthquake: a repeat of previous great earthquakes in the region?

PubMed

Comte, D; Eisenberg, A; Lorca, E; Pardo, M; Ponce, L; Saragoni, R; Singh, S K; Suárez, G

1986-07-25

A great earthquake (surface-wave magnitude, 7.8) occurred along the coast of central Chile on 3 March 1985, causing heavy damage to coastal towns. Intense foreshock activity near the epicenter of the main shock occurred for 11 days before the earthquake. The aftershocks of the 1985 earthquake define a rupture area of 170 by 110 square kilometers. The earthquake was forecast on the basis of the nearly constant repeat time (83 +/- 9 years) of great earthquakes in this region. An analysis of previous earthquakes suggests that the rupture lengths of great shocks in the region vary by a factor of about 3. The nearly constant repeat time and variable rupture lengths cannot be reconciled with time- or slip-predictable models of earthquake recurrence. The great earthquakes in the region seem to involve a variable rupture mode and yet, for unknown reasons, remain periodic. Historical data suggest that the region south of the 1985 rupture zone should now be considered a gap of high seismic potential that may rupture in a great earthquake in the next few tens of years.

Geometric morphometric analysis of Colombian Anopheles albimanus (Diptera: Culicidae) reveals significant effect of environmental factors on wing traits and presence of a metapopulation

PubMed Central

Gómez, Giovan F.; Márquez, Edna J.; Gutiérrez, Lina A.; Conn, Jan E.; Correa, Margarita M.

2015-01-01

Anopheles albimanus is a major malaria mosquito vector in Colombia. In the present study, wing variability (size and shape) in An. albimanus populations from Colombian Maracaibo and Chocó bio-geographical eco-regions and the relationship of these phenotypic traits with environmental factors were evaluated. Microsatellite and morphometric data facilitated a comparison of the genetic and phenetic structure of this species. Wing size was influenced by elevation and relative humidity, whereas wing shape was affected by these two variables and also by rainfall, latitude, temperature and eco-region. Significant differences in mean shape between populations and eco-regions were detected, but they were smaller than those at the intra-population level. Correct assignment based on wing shape was low at the population level (<58%) and only slightly higher (>70%) at the eco-regional level, supporting the low population structure inferred from microsatellite data. Wing size was similar among populations with no significant differences between eco-regions. Population relationships in the genetic tree did not agree with those from the morphometric data; however, both datasets consistently reinforced a panmictic population of An. albimanus. Overall, site-specific population differentiation is not strongly supported by wing traits or genotypic data. We hypothesize that the metapopulation structure of An. albimanus throughout these Colombian eco-regions is favoring plasticity in wing traits, a relevant characteristic of species living under variable environmental conditions and colonizing new habitats. PMID:24704285

Characterization of the variable-number tandem repeats in vrrA from different Bacillus anthracis isolates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jackson, P.J.; Walthers, E.A.; Richmond, K.L.

1997-04-01

PCR analysis of 198 Bacillus anthracis isolates revealed a variable region of DNA sequence differing in length among the isolates. Five Polymorphisms differed by the presence Of two to six copies of the 12-bp tandem repeat 5{prime}-CAATATCAACAA-3{prime}. This variable-number tandem repeat (VNTR) region is located within a larger sequence containing one complete open reading frame that encodes a putative 30-kDa protein. Length variation did not change the reading frame of the encoded protein and only changed the copy number of a 4-amino-acid sequence (QYQQ) from 2 to 6. The structure of the VNTR region suggests that these multiple repeats aremore » generated by recombination or polymerase slippage. Protein structures predicted from the reverse-translated DNA sequence suggest that any structural changes in the encoded protein are confined to the region encoded by the VNTR sequence. Copy number differences in the VNTR region were used to define five different B. anthracis alleles. Characterization of 198 isolates revealed allele frequencies of 6.1, 17.7, 59.6, 5.6, and 11.1% sequentially from shorter to longer alleles. The high degree of polymorphism in the VNTR region provides a criterion for assigning isolates to five allelic categories. There is a correlation between categories and geographic distribution. Such molecular markers can be used to monitor the epidemiology of anthrax outbreaks in domestic and native herbivore populations. 22 refs., 4 figs., 3 tabs.« less

Heart rate variability to monitor performance in elite athletes: Criticalities and avoidable pitfalls.

PubMed

Lucini, Daniela; Marchetti, Ilaria; Spataro, Antonio; Malacarne, Mara; Benzi, Manuela; Tamorri, Stefano; Sala, Roberto; Pagani, Massimo

2017-08-01

Spectral analysis of Heart Rate Variability (HRV) is a simple, non-invasive technique that is widely used in sport to assess sympatho-vagal regulation of the heart. Its employment is increasing partly due to the rising usage of wearable devices. However data acquisition using these devices may be suboptimal because they cannot discriminate between sinus and non-sinus beats and do not record any data regarding respiratory frequency. This information is mandatory for a correct clinical interpretation. This study involved 974 elite athletes, all of them underwent a complete autonomic assessment, by way of Autoregressive HRV analysis. In 91 subjects (9% of the total population) we observed criticalities of either cardiac rhythm or respiration. Through perusal of one-lead ECG analysis we observed that 77 subjects had atrial or ventricular ectopy, i.e. conditions which impair stationarity and sinus rhythm. Running anyway autonomic nervous system analysis in this population, we observed that RR variance and raw values of LF and HF regions are significantly higher in arrhythmic subjects. In addition 14 subjects had slow (about 6 breath/min, 0.1Hz) respiration. This condition clouds the separation between LF from HF spectral regions of RR interval variability, respectively markers of the prevalent sympathetic and vagal modulation of SA node and of their synergistic interaction. Caution must be payed when assessing HRV with non-ECG wearable devices. Recording ECG signal and ensuring that respiratory rate is higher than 10 breath/min are both prerequisites for a more reliable analysis of HRV particularly in athletes. Copyright © 2017 Elsevier B.V. All rights reserved.

Geographically weighted regression and geostatistical techniques to construct the geogenic radon potential map of the Lazio region: A methodological proposal for the European Atlas of Natural Radiation.

PubMed

Ciotoli, G; Voltaggio, M; Tuccimei, P; Soligo, M; Pasculli, A; Beaubien, S E; Bigi, S

2017-01-01

In many countries, assessment programmes are carried out to identify areas where people may be exposed to high radon levels. These programmes often involve detailed mapping, followed by spatial interpolation and extrapolation of the results based on the correlation of indoor radon values with other parameters (e.g., lithology, permeability and airborne total gamma radiation) to optimise the radon hazard maps at the municipal and/or regional scale. In the present work, Geographical Weighted Regression and geostatistics are used to estimate the Geogenic Radon Potential (GRP) of the Lazio Region, assuming that the radon risk only depends on the geological and environmental characteristics of the study area. A wide geodatabase has been organised including about 8000 samples of soil-gas radon, as well as other proxy variables, such as radium and uranium content of homogeneous geological units, rock permeability, and faults and topography often associated with radon production/migration in the shallow environment. All these data have been processed in a Geographic Information System (GIS) using geospatial analysis and geostatistics to produce base thematic maps in a 1000 m × 1000 m grid format. Global Ordinary Least Squared (OLS) regression and local Geographical Weighted Regression (GWR) have been applied and compared assuming that the relationships between radon activities and the environmental variables are not spatially stationary, but vary locally according to the GRP. The spatial regression model has been elaborated considering soil-gas radon concentrations as the response variable and developing proxy variables as predictors through the use of a training dataset. Then a validation procedure was used to predict soil-gas radon values using a test dataset. Finally, the predicted values were interpolated using the kriging algorithm to obtain the GRP map of the Lazio region. The map shows some high GRP areas corresponding to the volcanic terrains (central-northern sector of Lazio region) and to faulted and fractured carbonate rocks (central-southern and eastern sectors of the Lazio region). This typical local variability of autocorrelated phenomena can only be taken into account by using local methods for spatial data analysis. The constructed GRP map can be a useful tool to implement radon policies at both the national and local levels, providing critical data for land use and planning purposes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Relationships between income inequality and health: a study on rural and urban regions of Canada.

PubMed

Vafaei, Afshin; Rosenberg, Mark W; Pickett, William

2010-01-01

Many studies have demonstrated that health is a function of relative and not absolute income within populations. Canadian studies are not conclusive; most indicate that there is no relationship between income inequality and health within Canada. There is a need for further investigation into the validity of the 'relative income' hypothesis in the Canadian population. The primary objective of this research was to test the 'relative income' hypothesis across Canadian health regions. The second objective was to extend the hypothesis to consider rural versus urban populations. This research involved ecological analyses. The source of the data was the Canadian Community Health Survey, Cycle 3.1. The units of analysis were Canadian health regions. Health of a region was estimated as the percentage of people who rated their health as good or excellent. The primary exposure variable was the ratio of people whose personal income was less than $15,000 relative to those reporting more than $80,000 in the year preceding the survey. This ratio provided a measure of the distribution of income. The main covariates were ecological measures of socio-demographic variables, social capital, substance use behaviours (smoking and alcohol consumption), rural/urban status of the region, and absolute income in the region. Correlation analyses and multiple linear regressions were performed to ascertain the relationship between income inequality and population health, adjusting for important covariates. The measure of income inequality alone appeared to explain 18% of the variability in the measure of population health. However, after adding the measure of absolute income to the model, although 29% of the variability was explained, the independent contribution of the inequality measure became non-significant. Linear regression models suggested that the absolute income variable alone could explain 30% of the variance in the health status of populations. Other variables with a statistically significant contribution to the final model were education and alcohol consumption. The effect of rural/urban geographic status on the relationship of interest was similar to other covariates. This variable did not change the individual relationship between income inequality or absolute income and the measure of population health status. In both rural and urban regions, absolute income and education had positive effects on population health. In urban regions alcohol consumption was a significant negative contributor to population health status; whereas, in rural regions, smoking status had a significant negative effect on population health status. Across Canadian health regions, health status in populations was a function of absolute income but not relative income. Regions with higher levels of education had better levels of self-rated health. A larger percentage of heavy drinkers was also correlated with lower population health status. Findings were consistently observed in rural and urban populations. The study findings have implications for public health, economic, and social policies.

Impacts analysis of car following models considering variable vehicular gap policies

NASA Astrophysics Data System (ADS)

Xin, Qi; Yang, Nan; Fu, Rui; Yu, Shaowei; Shi, Zhongke

2018-07-01

Due to the important roles playing in the vehicles' adaptive cruise control system, variable vehicular gap polices were employed to full velocity difference model (FVDM) to investigate the traffic flow properties. In this paper, two new car following models were put forward by taking constant time headway(CTH) policy and variable time headway(VTH) policy into optimal velocity function, separately. By steady state analysis of the new models, an equivalent optimal velocity function was defined. To determine the linear stable conditions of the new models, we introduce equivalent expressions of safe vehicular gap, and then apply small amplitude perturbation analysis and long terms of wave expansion techniques to obtain the new models' linear stable conditions. Additionally, the first order approximate solutions of the new models were drawn at the stable region, by transforming the models into typical Burger's partial differential equations with reductive perturbation method. The FVDM based numerical simulations indicate that the variable vehicular gap polices with proper parameters directly contribute to the improvement of the traffic flows' stability and the avoidance of the unstable traffic phenomena.

On the Origin and Spread of the Scab Disease of Apple: Out of Central Asia

PubMed Central

Gladieux, Pierre; Zhang, Xiu-Guo; Afoufa-Bastien, Damien; Valdebenito Sanhueza, Rosa-Maria; Sbaghi, Mohamed; Le Cam, Bruno

2008-01-01

Background Venturia inaequalis is an ascomycete fungus responsible for apple scab, a disease that has invaded almost all apple growing regions worldwide, with the corresponding adverse effects on apple production. Monitoring and predicting the effectiveness of intervention strategies require knowledge of the origin, introduction pathways, and population biology of pathogen populations. Analysis of the variation of genetic markers using the inferential framework of population genetics offers the potential to retrieve this information. Methodology/Principal Findings Here, we present a population genetic analysis of microsatellite variation in 1,273 strains of V. inaequalis representing 28 orchard samples from seven regions in five continents. Analysis of molecular variance revealed that most of the variation (88%) was distributed within localities, which is consistent with extensive historical migrations of the fungus among and within regions. Despite this shallow population structure, clustering analyses partitioned the data set into separate groups corresponding roughly to geography, indicating that each region hosts a distinct population of the fungus. Comparison of the levels of variability among populations, along with coalescent analyses of migration models and estimates of genetic distances, was consistent with a scenario in which the fungus emerged in Central Asia, where apple was domesticated, before its introduction into Europe and, more recently, into other continents with the expansion of apple growing. Across the novel range, levels of variability pointed to multiple introductions and all populations displayed signatures of significant post-introduction increases in population size. Most populations exhibited high genotypic diversity and random association of alleles across loci, indicating recombination both in native and introduced areas. Conclusions/Significance Venturia inaequalis is a model of invasive phytopathogenic fungus that has now reached the ultimate stage of the invasion process with a broad geographic distribution and well-established populations displaying high genetic variability, regular sexual reproduction, and demographic expansion. PMID:18197265

Modeling photovoltaic diffusion: an analysis of geospatial datasets

NASA Astrophysics Data System (ADS)

Davidson, Carolyn; Drury, Easan; Lopez, Anthony; Elmore, Ryan; Margolis, Robert

2014-07-01

This study combines address-level residential photovoltaic (PV) adoption trends in California with several types of geospatial information—population demographics, housing characteristics, foreclosure rates, solar irradiance, vehicle ownership preferences, and others—to identify which subsets of geospatial information are the best predictors of historical PV adoption. Number of rooms, heating source and house age were key variables that had not been previously explored in the literature, but are consistent with the expected profile of a PV adopter. The strong relationship provided by foreclosure indicators and mortgage status have less of an intuitive connection to PV adoption, but may be highly correlated with characteristics inherent in PV adopters. Next, we explore how these predictive factors and model performance varies between different Investor Owned Utility (IOU) regions in California, and at different spatial scales. Results suggest that models trained with small subsets of geospatial information (five to eight variables) may provide similar explanatory power as models using hundreds of geospatial variables. Further, the predictive performance of models generally decreases at higher resolution, i.e., below ZIP code level since several geospatial variables with coarse native resolution become less useful for representing high resolution variations in PV adoption trends. However, for California we find that model performance improves if parameters are trained at the regional IOU level rather than the state-wide level. We also find that models trained within one IOU region are generally representative for other IOU regions in CA, suggesting that a model trained with data from one state may be applicable in another state.

Cloning and sequence analysis of complementary DNA encoding an aberrantly rearranged human T-cell gamma chain.

PubMed Central

Dialynas, D P; Murre, C; Quertermous, T; Boss, J M; Leiden, J M; Seidman, J G; Strominger, J L

1986-01-01

Complementary DNA (cDNA) encoding a human T-cell gamma chain has been cloned and sequenced. At the junction of the variable and joining regions, there is an apparent deletion of two nucleotides in the human cDNA sequence relative to the murine gamma-chain cDNA sequence, resulting simultaneously in the generation of an in-frame stop codon and in a translational frameshift. For this reason, the sequence presented here encodes an aberrantly rearranged human T-cell gamma chain. There are several surprising differences between the deduced human and murine gamma-chain amino acid sequences. These include poor homology in the variable region, poor homology in a discrete segment of the constant region precisely bounded by the expected junctions of exon CII, and the presence in the human sequence of five potential sites for N-linked glycosylation. Images PMID:3458221

Estimating annual suspended-sediment loads in the northern and central Appalachian Coal region

USGS Publications Warehouse

Koltun, G.F.

1985-01-01

Multiple-regression equations were developed for estimating the annual suspended-sediment load, for a given year, from small to medium-sized basins in the northern and central parts of the Appalachian coal region. The regression analysis was performed with data for land use, basin characteristics, streamflow, rainfall, and suspended-sediment load for 15 sites in the region. Two variables, the maximum mean-daily discharge occurring within the year and the annual peak discharge, explained much of the variation in the annual suspended-sediment load. Separate equations were developed employing each of these discharge variables. Standard errors for both equations are relatively large, which suggests that future predictions will probably have a low level of precision. This level of precision, however, may be acceptable for certain purposes. It is therefore left to the user to asses whether the level of precision provided by these equations is acceptable for the intended application.

Multinational corporate penetration, industrialism, region, and social security expenditures: a cross-national analysis.

PubMed

Clark, R; Filinson, R

1991-01-01

This study examines the determinants of spending on social security programs. We draw predictions from industrialism and dependency theories for the explanation of social security programs. The explanations are tested with data on seventy-five nations, representative of core, semipheripheral and peripheral nations. Industrialization variables such as the percentage of older adults and economic productivity have strong effects in models involving all nations, as does multinational corporate (MNC) penetration in extraction, particularly when region is controlled; such penetration is negatively associated with spending on social security. We then look at industrialism and dependency effects for peripheral and non-core nations alone. The effects of all industrialization variables, except economic productivity, appear insignificant for peripheral nations, while the effects of region and multinational corporate penetration in extractive and agricultural industries appears significant. Models involving all non-core nations (peripheral and semi-peripheral) look more like models for all nations than for peripheral nations alone.

Desmoglein 4 diversity and correlation analysis with coat color in goat.

PubMed

E, G X; Zhao, Y J; Ma, Y H; Cao, G L; He, J N; Na, R S; Zhao, Z Q; Jiang, C D; Zhang, J H; Arlvd, S; Chen, L P; Qiu, X Y; Hu, W; Huang, Y F

2016-03-04

Desmoglein 4 (DSG4) has an important role in the development of wool traits in domestic animals. The full-length DSG4 gene, which contains 3918 bp, a complete open-reading-frame, and encodes a 1040-amino acid protein, was amplified from Liaoning cashmere goat. The sequence was compared with that of DSG4 from other animals and the results show that the DSG4 coding region is consistent with interspecies conservation. Thirteen single-nucleotide polymorphisms (SNPs) were identified in a highly variable region of DSG4, and one SNP (M-1, G>T) was significantly correlated with white and black coat color in goat. Haplotype distribution of the highly variable region of DSG4 was assessed in 179 individuals from seven goat breeds to investigate its association with coat color and its differentiation among populations. However, the lack of a signature result indicates DGS4 haplotypes related with the color of goat coat.

Investigation Hydrometeorological Regime of the White Sea Based on Satellite Altimetry Data

NASA Astrophysics Data System (ADS)

Lebedev, Sergey A.

2016-08-01

The White Sea are the seas of the Arctic Ocean. Today complicated hydrodynamic, tidal, ice, and meteorological regimes of these seas may be investigated on the basis of remote sensing data, specifically of satellite altimetry data. Results of calibration and validation of satellite altimetry measurements (sea surface height and sea surface wind speed) and comparison with regional tidal model show that this type of data may be successfully used in scientific research and in monitoring of the environment. Complex analysis of the tidal regime of the White Sea and comparison between global and regional tidal models show advantages of regional tidal model for use in tidal correction of satellite altimetry data. Examples of using the sea level data in studying long-term variability of the Barents and White Seas are presented. Interannual variability of sea ice edge position is estimated on the basis of altimetry data.

Conserved Structural Elements in the V3 Crown of HIV-1 gp120

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, X.; Burke, V; Totrov, M

2010-01-01

Binding of the third variable region (V3) of the HIV-1 envelope glycoprotein gp120 to the cell-surface coreceptors CCR5 or CXCR4 during viral entry suggests that there are conserved structural elements in this sequence-variable region. These conserved elements could serve as epitopes to be targeted by a vaccine against HIV-1. Here we perform a systematic structural analysis of representative human anti-V3 monoclonal antibodies in complex with V3 peptides, revealing that the crown of V3 has four conserved structural elements: an arch, a band, a hydrophobic core and the peptide backbone. These are either unaffected by or are subject to minimal sequencemore » variation. As these regions are targeted by cross-clade neutralizing human antibodies, they provide a blueprint for the design of vaccine immunogens that could elicit broadly cross-reactive protective antibodies.« less

Phenotypic variability of the cat eye syndrome. Case report and review of the literature.

PubMed

Rosias, P R; Sijstermans, J M; Theunissen, P M; Pulles-Heintzberger, C F; De Die-Smulders, C E; Engelen, J J; Van Der Meer, S B

2001-01-01

We present a male infant with preauricular skin tags and pits, downslanting palpebral fissures, hypertelorism, ectopic anus, hypospadias, and hypoplastic left heart syndrome. The clinical features in our patient show phenotypic overlap with the cat eye syndrome, as illustrated by the review of 105 reported cases. Cytogenetic analysis revealed a supernumerary marker chromosome, which was identified by microdissection and fluorescence in situ hybridization as an isodicentric chromosome 22(pter --> q11.2::q11.2 --> pter). It was proved with probes specific for the cat eye syndrome critical region that this region was present in quadruplicate in the propositus. We conclude that CES is characterized by large phenotypic variability, ranging from near normal to severe malformations, as reflected in the neurodevelopmental outcome. Preauricular skin tags and/or pits are the most consistent features, and suggest the presence of a supernumerary bisatellited marker chromosome 22 derived from duplication of the CES critical region.

Constraints on the Genetic and Antigenic Variability of Measles Virus.

PubMed

Beaty, Shannon M; Lee, Benhur

2016-04-21

Antigenic drift and genetic variation are significantly constrained in measles virus (MeV). Genetic stability of MeV is exceptionally high, both in the lab and in the field, and few regions of the genome allow for rapid genetic change. The regions of the genome that are more tolerant of mutations (i.e., the untranslated regions and certain domains within the N, C, V, P, and M proteins) indicate genetic plasticity or structural flexibility in the encoded proteins. Our analysis reveals that strong constraints in the envelope proteins (F and H) allow for a single serotype despite known antigenic differences among its 24 genotypes. This review describes some of the many variables that limit the evolutionary rate of MeV. The high genomic stability of MeV appears to be a shared property of the Paramyxovirinae, suggesting a common mechanism that biologically restricts the rate of mutation.

Constraints on the Genetic and Antigenic Variability of Measles Virus

PubMed Central

Beaty, Shannon M.; Lee, Benhur

2016-01-01

Antigenic drift and genetic variation are significantly constrained in measles virus (MeV). Genetic stability of MeV is exceptionally high, both in the lab and in the field, and few regions of the genome allow for rapid genetic change. The regions of the genome that are more tolerant of mutations (i.e., the untranslated regions and certain domains within the N, C, V, P, and M proteins) indicate genetic plasticity or structural flexibility in the encoded proteins. Our analysis reveals that strong constraints in the envelope proteins (F and H) allow for a single serotype despite known antigenic differences among its 24 genotypes. This review describes some of the many variables that limit the evolutionary rate of MeV. The high genomic stability of MeV appears to be a shared property of the Paramyxovirinae, suggesting a common mechanism that biologically restricts the rate of mutation. PMID:27110809

ENSO Related Inter-Annual Lightning Variability from the Full TRMM LIS Lightning Climatology

NASA Technical Reports Server (NTRS)

Clark, Austin; Cecil, Daniel

2018-01-01

The El Nino/Southern Oscillation (ENSO) contributes to inter-annual variability of lightning production more than any other atmospheric oscillation. This study further investigated how ENSO phase affects lightning production in the tropics and subtropics using the Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS). Lightning data were averaged into mean annual warm, cold, and neutral 'years' for analysis of the different phases and compared to model reanalysis data. An examination of the regional sensitivities and preliminary analysis of three locations was conducted using model reanalysis data to determine the leading convective mechanisms in these areas and how they might respond to the ENSO phases

Unveiling the physics of AGN through X-ray variability

NASA Astrophysics Data System (ADS)

Hernández-García, L.; González-Martín, O.; Masegosa, J.; Márquez, I.

2017-03-01

Although variability is a general property characterizing active galactic nuclei (AGN), it is not well established whether the changes occur in the same way in every nuclei. The main purpose of this work is to study the X-ray variability pattern(s) in AGN selected at optical wavelengths in a large sample, including low ionization nuclear emission line regions (LINERs) and type 1.8, 1.9, and 2 Seyferts, using the public archives in Chandra and/or XMM-Newton. Spectra of the same source gathered at different epochs were simultaneously fitted to study long term variations; the variability patterns were studied allowing different parameters to vary during the spectral fit. Whenever possible, short term variations from the analysis of the light curves and long term UV flux variability were studied. Variations at X-rays in timescales of months/years are very common in all AGN families but short term variations are only found in type 1.8 and 1.9 Seyferts. The main driver of the long term X-ray variations seems to be related to changes in the nuclear power. Other variability patterns cannot be discarded in a few cases. We discuss the geometry and physics of AGN through the X-ray variability analysis.

Genetic variability in isolates of Chromobacterium violaceum from pulmonary secretion, water, and soil.

PubMed

Santini, A C; Magalhães, J T; Cascardo, J C M; Corrêa, R X

2016-04-28

Chromobacterium violaceum is a free-living Gram-negative bacillus usually found in the water and soil in tropical regions, which causes infections in humans. Chromobacteriosis is characterized by rapid dissemination and high mortality. The aim of this study was to detect the genetic variability among C. violaceum type strain ATCC 12472, and seven isolates from the environment and one from a pulmonary secretion from a chromobacteriosis patient from Ilhéus, Bahia. The molecular characterization of all samples was performed by polymerase chain reaction (PCR) sequencing and 16S rDNA analysis. Primers specific for two ATCC 12472 pathogenicity genes, hilA and yscD, as well as random amplified polymorphic DNA (RAPD), were used for PCR amplification and comparative sequencing of the products. For a more specific approach, the PCR products of 16S rDNA were digested with restriction enzymes. Seven of the samples, including type-strain ATCC 12472, were amplified by the hilA primers; these were subsequently sequenced. Gene yscD was amplified only in type-strain ATCC 12472. MspI and AluI digestion revealed 16S rDNA polymorphisms. This data allowed the generation of a dendogram for each analysis. The isolates of C. violaceum have variability in random genomic regions demonstrated by RAPD. Also, these isolates have variability in pathogenicity genes, as demonstrated by sequencing and restriction enzyme digestion.

Disentangling environmental correlates of vascular plant biodiversity in a Mediterranean hotspot.

PubMed

Molina-Venegas, Rafael; Aparicio, Abelardo; Pina, Francisco José; Valdés, Benito; Arroyo, Juan

2013-10-01

We determined the environmental correlates of vascular plant biodiversity in the Baetic-Rifan region, a plant biodiversity hotspot in the western Mediterranean. A catalog of the whole flora of Andalusia and northern Morocco, the region that includes most of the Baetic-Rifan complex, was compiled using recent comprehensive floristic catalogs. Hierarchical cluster analysis (HCA) and detrended correspondence analysis (DCA) of the different ecoregions of Andalusia and northern Morocco were conducted to determine their floristic affinities. Diversity patterns were studied further by focusing on regional endemic taxa. Endemic and nonendemic alpha diversities were regressed to several environmental variables. Finally, semi-partial regressions on distance matrices were conducted to extract the respective contributions of climatic, altitudinal, lithological, and geographical distance matrices to beta diversity in endemic and nonendemic taxa. We found that West Rifan plant assemblages had more similarities with Andalusian ecoregions than with other nearby northern Morocco ecoregions. The endemic alpha diversity was explained relatively well by the environmental variables related to summer drought and extreme temperature values. Of all the variables, geographical distance contributed by far the most to spatial turnover in species diversity in the Baetic-Rifan hotspot. In the Baetic range, elevation was the most significant driver of nonendemic species beta diversity, while lithology and elevation were the main drivers of endemic beta diversity. Despite the fact that Andalusia and northern Morocco are presently separated by the Atlantic Ocean and the Mediterranean Sea, the Baetic and Rifan mountain ranges have many floristic similarities - especially in their western ranges - due to past migration of species across the Strait of Gibraltar. Climatic variables could be shaping the spatial distribution of endemic species richness throughout the Baetic-Rifan hotspot. Determinants of spatial turnover in biodiversity in the Baetic-Rifan hotspot vary in importance between endemic and nonendemic species.

Reduced error signalling in medication-naive children with ADHD: associations with behavioural variability and post-error adaptations

PubMed Central

Plessen, Kerstin J.; Allen, Elena A.; Eichele, Heike; van Wageningen, Heidi; Høvik, Marie Farstad; Sørensen, Lin; Worren, Marius Kalsås; Hugdahl, Kenneth; Eichele, Tom

2016-01-01

Background We examined the blood-oxygen level–dependent (BOLD) activation in brain regions that signal errors and their association with intraindividual behavioural variability and adaptation to errors in children with attention-deficit/hyperactivity disorder (ADHD). Methods We acquired functional MRI data during a Flanker task in medication-naive children with ADHD and healthy controls aged 8–12 years and analyzed the data using independent component analysis. For components corresponding to performance monitoring networks, we compared activations across groups and conditions and correlated them with reaction times (RT). Additionally, we analyzed post-error adaptations in behaviour and motor component activations. Results We included 25 children with ADHD and 29 controls in our analysis. Children with ADHD displayed reduced activation to errors in cingulo-opercular regions and higher RT variability, but no differences of interference control. Larger BOLD amplitude to error trials significantly predicted reduced RT variability across all participants. Neither group showed evidence of post-error response slowing; however, post-error adaptation in motor networks was significantly reduced in children with ADHD. This adaptation was inversely related to activation of the right-lateralized ventral attention network (VAN) on error trials and to task-driven connectivity between the cingulo-opercular system and the VAN. Limitations Our study was limited by the modest sample size and imperfect matching across groups. Conclusion Our findings show a deficit in cingulo-opercular activation in children with ADHD that could relate to reduced signalling for errors. Moreover, the reduced orienting of the VAN signal may mediate deficient post-error motor adaptions. Pinpointing general performance monitoring problems to specific brain regions and operations in error processing may help to guide the targets of future treatments for ADHD. PMID:26441332

Regional and social differences concerning overweight, participation in health check-ups and vaccination. Analysis of data from a whole birth cohort of 6-year old children in a prosperous German city

PubMed Central

Koller, Daniela; Mielck, Andreas

2009-01-01

Background Studies on health inequalities still focus mostly on adults. Research about social disparities and health in children is slowly increasing, also in Germany, but these studies are mostly restricted to individual social variables derived from the parents to determine social class. This paper analyses the data of the medical check-up prior to school enrolment to determine differences concerning overweight, participation in health check-ups and immunization; it includes individual social variables but also regional variables describing the social environment of the children. Methods The dataset includes 9,353 children who started school in 2004 in Munich, Germany. Three dependent variables are included (i.e. overweight, health check-ups, vaccinations). The individual level social variables are: children's sex, mother tongue of the parents, Kindergarten visit. On the small scale school district level, two regional social variables could be included as well, i.e. percentage of single-parent households, percentage of households with low educational level. Associations are assessed by cross tables and regression analyses. The regional level variables are included by multilevel analyses. Results The analyses indicate that there is a large variation between the school districts concerning the three dependent variables, and that there is no district with very 'problematic values' for all three of them (i.e. high percentage of overweight, low levels of health check-ups and vaccinations). Throughout the bivariate and multivariate analyses, the mother tongue of the children's parents shows the most pronounced association with these dependent variables; i.e. children growing up in non-German-speaking families tend to be more overweight and don't visit preventive check-ups as often as children of German-speaking parents. An opposite association can be seen concerning vaccinations. Regional level influences are present as well, but they are rather small when the individual level social variables are controlled for. Conclusion The dataset of the medical check-up prior to school enrolment offers a great opportunity for public health research, as it comprises a whole age cohort. The number and scope of variables is quite limited, though. On one hand, it includes only few variables on health or health related risks. On the other, it would be important to have more information from the region where the children live, e.g. the availability of community and health care services for parents and children, social networks of families with children, areas where children can play outside, traffic noise and air pollution. Despite these shortcomings, the need for specific interventions can already be derived from the data analyzed here, e.g. programs to reduce overweight in children should focus on parents with a mother tongue other than German. PMID:19183444

Spatial and temporal variability of fine particle composition and source types in five cities of Connecticut and Massachusetts

PubMed Central

Lee, Hyung Joo; Gent, Janneane F.; Leaderer, Brian P.; Koutrakis, Petros

2011-01-01

To protect public health from PM2.5 air pollution, it is critical to identify the source types of PM2.5 mass and chemical components associated with higher risks of adverse health outcomes. Source apportionment modeling using Positive Matrix Factorization (PMF), was used to identify PM2.5 source types and quantify the source contributions to PM2.5 in five cities of Connecticut and Massachusetts. Spatial and temporal variability of PM2.5 mass, components and source contributions were investigated. PMF analysis identified five source types: regional pollution as traced by sulfur, motor vehicle, road dust, oil combustion and sea salt. The sulfur-related regional pollution and traffic source type were major contributors to PM2.5. Due to sparse ground-level PM2.5 monitoring sites, current epidemiological studies are susceptible to exposure measurement errors. The higher correlations in concentrations and source contributions between different locations suggest less spatial variability, resulting in less exposure measurement errors. When concentrations and/or contributions were compared to regional averages, correlations were generally higher than between-site correlations. This suggests that for assigning exposures for health effects studies, using regional average concentrations or contributions from several PM2.5 monitors is more reliable than using data from the nearest central monitor. PMID:21429560

Spatiotemporal drought variability of the eastern Tibetan Plateau during the last millennium

NASA Astrophysics Data System (ADS)

Deng, Yang; Gou, Xiaohua; Gao, Linlin; Yang, Meixue; Zhang, Fen

2017-09-01

Tibetan Plateau is the headwater region of many major Asian rivers and very susceptive to climate change. Therefore, knowledge about climate and its spatiotemporal variability in this area is very important for ecological conservation, water resource management and social development. The aim of this study was to reconstruct and analyze the hydroclimate variation on eastern Tibetan Plateau (ETP) over many centuries and explore possible forcing factors on regional hydroclimate variability. We used 118 tree-ring chronologies from ETP to reconstruct the gridded May-July Standardized Precipitation Evapotranspiration Index for the ETP over the last millennium. The reconstruction was developed using an ensemble point-by-point reconstruction method, and a searching region method was used to locate the candidate tree-ring chronologies. The reconstructions have nicely captured the spatial and temporal features of the regional drought variation. The drought variations in south and north of 32.5°N are notably different, which may be related to the divergence influence of North Atlantic Oscillation on the climate systems in the south and north, as well as differences in local climate. Spectral analysis and series comparison suggest that the drought variation in the northeastern Tibetan Plateau has been possibly influenced by solar activity on centurial and longer time scale.

Nonstationarity of daily rainfall annual maxima in Puglia (Southern Italy)

NASA Astrophysics Data System (ADS)

Totaro, Vincenzo; Gioia, Andrea; Iacobellis, Vito

2017-04-01

Extreme flood events occurring in the last decades, due to climatic conditions in rapid evolution and/or changes in land cover, has lead the scientific community to develop and improve probabilistic techniques in order to take into account these effects, as also requested by the EU Floods Directive 2007/60. In the recent literature are becoming more popular studies that investigate the nonstationarity of the variables usually treated in hydrology through the analysis of their trend behavior. In this context it is also useful to assess the impact that the climate and /or land cover modifications have on the performances of the probabilistic stationary models used to predict hydrological variables such as rainfall and flood peaks. Among several proposed approaches, we use the redefined concept of return period and risk by considering the variability over time of the position parameter of the GEV distribution, with the subsequent discussion about the implications of analytical and technical characters. The analysis was carried out on the time series of annual maximum of daily precipitation available for a broad number of rainfall gauged stations in Puglia (Southern Italy). The investigation, conducted at the regional scale, leads to the identification of areas with different significativity of the statistical tests usually performed in order to assess nonstationarity. The evaluated change of return period leads to considerations useful to redesign methods for regional analysis of flood frequency.

Manipulation of length and lexicality localizes the functional neuroanatomy of phonological processing in adult readers.

PubMed

Church, Jessica A; Balota, David A; Petersen, Steven E; Schlaggar, Bradley L

2011-06-01

In a previous study of single word reading, regions in the left supramarginal gyrus and left angular gyrus showed positive BOLD activity in children but significantly less activity in adults for high-frequency words [Church, J. A., Coalson, R. S., Lugar, H. M., Petersen, S. E., & Schlaggar, B. L. A developmental fMRI study of reading and repetition reveals changes in phonological and visual mechanisms over age. Cerebral Cortex, 18, 2054-2065, 2008]. This developmental decrease may reflect decreased reliance on phonological processing for familiar stimuli in adults. Therefore, in the present study, variables thought to influence phonological demand (string length and lexicality) were manipulated. Length and lexicality effects in the brain were explored using both ROI and whole-brain approaches. In the ROI analysis, the supramarginal and angular regions from the previous study were applied to this study. The supramarginal region showed a significant positive effect of length, consistent with a role in phonological processing, whereas the angular region showed only negative deflections from baseline with a strong effect of lexicality and other weaker effects. At the whole-brain level, varying effects of length and lexicality and their interactions were observed in 85 regions throughout the brain. The application of hierarchical clustering analysis to the BOLD time course data derived from these regions revealed seven clusters, with potentially revealing anatomical locations. Of note, a left angular gyrus region was the sole constituent of one cluster. Taken together, these findings in adult readers (1) provide support for a widespread set of brain regions affected by lexical variables, (2) corroborate a role for phonological processing in the left supramarginal gyrus, and (3) do not support a strong role for phonological processing in the left angular gyrus.

Spatiotemporal investigation of long-term seasonal temperature variability in Libya

NASA Astrophysics Data System (ADS)

Elsharkawy, S. G.; Elmallah, E. S.

2016-09-01

Throughout this work, spatial and temporal variations of seasonal surface air temperature have been investigated. Moreover, the effects of relative internal (teleconnection) and external (solar) forcing on surface air temperature variability have been examined. Seasonal temperature time series covering 30 different meteorological locations and lasting over the last century are considered. These locations are classified into two groups based on their spatial distribution. One represents Coast Libya Surface Air Temperature (CLSAT), contains 19 locations, and the other represents Desert Libya Surface Air Temperature (DLSAT), contains 11 locations. Average temperature departure test is applied to investigate the nature of temperature variations. Temperature trends are analyzed using the nonparametric Mann-Kendall test and their coefficients are calculated using Sen's slope estimate. Cross-correlation and spectral analysis techniques are also applied. Our results showed temperature deviation from average within a band of ± 2°C at coast region, while ± 4°C at desert region. Extreme behavior intensions between summer and winter temperatures at coast region are noticed. Segmentation process declared reversal cooling/warming behavior within temperature records for all seasons. Desert region shows warming trend for all seasons with higher coefficients than obtained at coast region. Results obtained for spectral analysis show different short and medium signals and concluded that not only the spectral properties are different for different geographical regions but also different for different climatic seasons on regional scale as well. Cross-correlation results showed that highest influence for Rz upon coastal temperature is always in conjunction with highest influence of NAO upon coastal temperature during the period 1981-2010. Desert region does not obey this phenomenon, where highest temperature-NAO correlations at desert during autumn and winter seasons are not accompanied with highest correlations for temperature-Rz.

Copula Multivariate analysis of Gross primary production and its hydro-environmental driver; A BIOME-BGC model applied to the Antisana páramos

NASA Astrophysics Data System (ADS)

Minaya, Veronica; Corzo, Gerald; van der Kwast, Johannes; Galarraga, Remigio; Mynett, Arthur

2014-05-01

Simulations of carbon cycling are prone to uncertainties from different sources, which in general are related to input data, parameters and the model representation capacities itself. The gross carbon uptake in the cycle is represented by the gross primary production (GPP), which deals with the spatio-temporal variability of the precipitation and the soil moisture dynamics. This variability associated with uncertainty of the parameters can be modelled by multivariate probabilistic distributions. Our study presents a novel methodology that uses multivariate Copulas analysis to assess the GPP. Multi-species and elevations variables are included in a first scenario of the analysis. Hydro-meteorological conditions that might generate a change in the next 50 or more years are included in a second scenario of this analysis. The biogeochemical model BIOME-BGC was applied in the Ecuadorian Andean region in elevations greater than 4000 masl with the presence of typical vegetation of páramo. The change of GPP over time is crucial for climate scenarios of the carbon cycling in this type of ecosystem. The results help to improve our understanding of the ecosystem function and clarify the dynamics and the relationship with the change of climate variables. Keywords: multivariate analysis, Copula, BIOME-BGC, NPP, páramos

Local SPTHA through tsunami inundation simulations: a test case for two coastal critical infrastructures in the Mediterranean

NASA Astrophysics Data System (ADS)

Volpe, M.; Selva, J.; Tonini, R.; Romano, F.; Lorito, S.; Brizuela, B.; Argyroudis, S.; Salzano, E.; Piatanesi, A.

2016-12-01

Seismic Probabilistic Tsunami Hazard Analysis (SPTHA) is a methodology to assess the exceedance probability for different thresholds of tsunami hazard intensity, at a specific site or region in a given time period, due to a seismic source. A large amount of high-resolution inundation simulations is typically required for taking into account the full variability of potential seismic sources and their slip distributions. Starting from regional SPTHA offshore results, the computational cost can be reduced by considering for inundation calculations only a subset of `important' scenarios. We here use a method based on an event tree for the treatment of the seismic source aleatory variability; a cluster analysis on the offshore results to define the important sources; epistemic uncertainty treatment through an ensemble modeling approach. We consider two target sites in the Mediterranean (Milazzo, Italy, and Thessaloniki, Greece) where coastal (non nuclear) critical infrastructures (CIs) are located. After performing a regional SPTHA covering the whole Mediterranean, for each target site, few hundreds of representative scenarios are filtered out of all the potential seismic sources and the tsunami inundation is explicitly modeled, obtaining a site-specific SPTHA, with a complete characterization of the tsunami hazard in terms of flow depth and velocity time histories. Moreover, we also explore the variability of SPTHA at the target site accounting for coseismic deformation (i.e. uplift or subsidence) due to near field sources located in very shallow water. The results are suitable and will be applied for subsequent multi-hazard risk analysis for the CIs. These applications have been developed in the framework of the Italian Flagship Project RITMARE, EC FP7 ASTARTE (Grant agreement 603839) and STREST (Grant agreement 603389) projects, and of the INGV-DPC Agreement.

Assessing Variability in Brain Tumor Segmentation to Improve Volumetric Accuracy and Characterization of Change.

PubMed

Rios Piedra, Edgar A; Taira, Ricky K; El-Saden, Suzie; Ellingson, Benjamin M; Bui, Alex A T; Hsu, William

2016-02-01

Brain tumor analysis is moving towards volumetric assessment of magnetic resonance imaging (MRI), providing a more precise description of disease progression to better inform clinical decision-making and treatment planning. While a multitude of segmentation approaches exist, inherent variability in the results of these algorithms may incorrectly indicate changes in tumor volume. In this work, we present a systematic approach to characterize variability in tumor boundaries that utilizes equivalence tests as a means to determine whether a tumor volume has significantly changed over time. To demonstrate these concepts, 32 MRI studies from 8 patients were segmented using four different approaches (statistical classifier, region-based, edge-based, knowledge-based) to generate different regions of interest representing tumor extent. We showed that across all studies, the average Dice coefficient for the superset of the different methods was 0.754 (95% confidence interval 0.701-0.808) when compared to a reference standard. We illustrate how variability obtained by different segmentations can be used to identify significant changes in tumor volume between sequential time points. Our study demonstrates that variability is an inherent part of interpreting tumor segmentation results and should be considered as part of the interpretation process.

Stereophysicochemical variability plots highlight conserved antigenic areas in Flaviviruses

PubMed Central

Schein, Catherine H; Zhou, Bin; Braun, Werner

2005-01-01

Background Flaviviruses, which include Dengue (DV) and West Nile (WN), mutate in response to immune system pressure. Identifying escape mutants, variant progeny that replicate in the presence of neutralizing antibodies, is a common way to identify functionally important residues of viral proteins. However, the mutations typically occur at variable positions on the viral surface that are not essential for viral replication. Methods are needed to determine the true targets of the neutralizing antibodies. Results Stereophysicochemical variability plots (SVPs), 3-D images of protein structures colored according to variability, as determined by our PCPMer program, were used to visualize residues conserved in their physical chemical properties (PCPs) near escape mutant positions. The analysis showed 1) that escape mutations in the flavivirus envelope protein are variable residues by our criteria and 2) two escape mutants found at the same position in many flaviviruses sit above clusters of conserved residues from different regions of the linear sequence. Conservation patterns in T-cell epitopes in the NS3- protease suggest a similar mechanism of immune system evasion. Conclusion The SVPs add another dimension to structurally defining the binding sites of neutralizing antibodies. They provide a useful aid for determining antigenically important regions and designing vaccines. PMID:15845145

Intraseasonal variability of sea level and circulation in the Gulf of Thailand: the role of the Madden-Julian Oscillation

NASA Astrophysics Data System (ADS)

Oliver, Eric C. J.

2014-01-01

Intraseasonal variability of the tropical Indo-Pacific ocean is strongly related to the Madden-Julian Oscillation (MJO). Shallow seas in this region, such as the Gulf of Thailand, act as amplifiers of the direct ocean response to surface wind forcing by efficient setup of sea level. Intraseasonal ocean variability in the Gulf of Thailand region is examined using statistical analysis of local tide gauge observations and surface winds. The tide gauges detect variability on intraseasonal time scales that is related to the MJO through its effect on local wind. The relationship between the MJO and the surface wind is strongly seasonal, being most vigorous during the monsoon, and direction-dependent. The observations are then supplemented with simulations of sea level and circulation from a fully nonlinear barotropic numerical ocean model (Princeton Ocean Model). The numerical model reproduces well the intraseasonal sea level variability in the Gulf of Thailand and its seasonal modulations. The model is then used to map the wind-driven response of sea level and circulation in the entire Gulf of Thailand. Finally, the predictability of the setup and setdown signal is discussed by relating it to the, potentially predictable, MJO index.

Insights into hydroclimatic variability of Southern California since 125 ka, from multi-proxy analyses of alpine lakes

NASA Astrophysics Data System (ADS)

Glover, K. C.; MacDonald, G. M.; Kirby, M.

2016-12-01

Hydroclimatic variability is especially important in California, a water-stressed and increasingly populous region. We assess the range of past hydroclimatic sensitivity and variability in the San Bernardino Mountains of Southern California based on 125 ka of lacustrine sediment records. Geochemistry, charcoal and pollen highlight periods of sustained moisture, aridity and sudden variability driven by orbital and oceanic variations. Marine Isotope Stage 3 (MIS 3) is one such period of greater moisture availability that lasted c. 30 kyr, with smaller-scale perturbations likely reflect North Atlantic Dansgaard-Oeschgar events. Past glacial periods, MIS 4 and MIS 2, display high-amplitude changes. These include periods of reduced forest cover that span millennia, indicating long-lasting aridity. Rapid forest expansion also occurs, marking sudden shifts towards wet conditions. Fire regimes have also changed in tandem with hydroclimate and vegetation. Higher-resolution analysis of the past 10 ka shows that Southern California hydroclimate was broadly similar to other regions of the Southwest and Great Basin, including an orbital and oceanic-driven wet Early Holocene, dry Mid-Holocene, and highly variable Late Holocene. Shorter-term pluvial conditions occur throughout the Holocene, with episodic moisture likely derived from a Pacific source.

Investigation of the marked and long-standing spatial inhomogeneity of the Hungarian suicide rate: a spatial regression approach.

PubMed

Balint, Lajos; Dome, Peter; Daroczi, Gergely; Gonda, Xenia; Rihmer, Zoltan

2014-02-01

In the last century Hungary had astonishingly high suicide rates characterized by marked regional within-country inequalities, a spatial pattern which has been quite stable over time. To explain the above phenomenon at the level of micro-regions (n=175) in the period between 2005 and 2011. Our dependent variable was the age and gender standardized mortality ratio (SMR) for suicide while explanatory variables were factors which are supposed to influence suicide risk, such as measures of religious and political integration, travel time accessibility of psychiatric services, alcohol consumption, unemployment and disability pensionery. When applying the ordinary least squared regression model, the residuals were found to be spatially autocorrelated, which indicates the violation of the assumption on the independence of error terms and - accordingly - the necessity of application of a spatial autoregressive (SAR) model to handle this problem. According to our calculations the SARlag model was a better way (versus the SARerr model) of addressing the problem of spatial autocorrelation, furthermore its substantive meaning is more convenient. SMR was significantly associated with the "political integration" variable in a negative and with "lack of religious integration" and "disability pensionery" variables in a positive manner. Associations were not significant for the remaining explanatory variables. Several important psychiatric variables were not available at the level of micro-regions. We conducted our analysis on aggregate data. Our results may draw attention to the relevance and abiding validity of the classic Durkheimian suicide risk factors - such as lack of social integration - apropos of the spatial pattern of Hungarian suicides. © 2013 Published by Elsevier B.V.

Interannual variability of temperature in the UTLS region over Ganges-Brahmaputra-Meghna river basin based on COSMIC GNSS RO data

NASA Astrophysics Data System (ADS)

Khandu; Awange, Joseph L.; Forootan, Ehsan

2016-04-01

Poor reliability of radiosonde records across South Asia imposes serious challenges in understanding the structure of upper-tropospheric and lower-stratospheric (UTLS) region. The Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission launched in April 2006 has overcome many observational limitations inherent in conventional atmospheric sounding instruments. This study examines the interannual variability of UTLS temperature over the Ganges-Brahmaputra-Meghna (GBM) river basin in South Asia using monthly averaged COSMIC radio occultation (RO) data, together with two global reanalyses. Comparisons between August 2006 and December 2013 indicate that MERRA (Modern-Era Retrospective Analysis for Research Application) and ERA-Interim (European Centre for Medium-Range Weather Forecasts reanalysis) are warmer than COSMIC RO data by 2 °C between 200 and 50 hPa levels. These warm biases with respect to COSMIC RO data are found to be consistent over time. The UTLS temperature show considerable interannual variability from 2006 to 2013 in addition to warming (cooling) trends in the troposphere (stratosphere). The cold (warm) anomalies in the upper troposphere (tropopause region) are found to be associated with warm ENSO (El Niño-Southern Oscillation) phase, while quasi-biennial oscillation (QBO) is negatively (positively) correlated with temperature anomalies at 70 hPa (50 hPa) level. PCA (principal component analysis) decomposition of tropopause temperatures and heights over the basin indicate that ENSO accounts for 73 % of the interannual (non-seasonal) variability with a correlation of 0.77 with Niño3.4 index whereas the QBO explains about 10 % of the variability. The largest tropopause anomaly associated with ENSO occurs during the winter, when ENSO reaches its peak. The tropopause temperature (height) increased (decreased) by about 1.5 °C (300 m) during the last major El Niño event of 2009/2010. In general, we find decreasing (increasing) trend in tropopause temperature (height) between 2006 and 2013.

Simulating the Snow Water Equivalent and its changing pattern over Nepal

NASA Astrophysics Data System (ADS)

Niroula, S.; Joseph, J.; Ghosh, S.

2016-12-01

Snow fall in the Himalayan region is one of the primary sources of fresh water, which accounts around 10% of total precipitation of Nepal. Snow water is an intricate variable in terms of its global and regional estimates whose complexity is favored by spatial variability linked with rugged topography. The study is primarily focused on simulation of Snow Water Equivalent (SWE) by the use of a macroscale hydrologic model, Variable Infiltration Capacity (VIC). As whole Nepal including its Himalayas lies under the catchment of Ganga River in India, contributing at least 40% of annual discharge of Ganges, this model was run in the entire watershed that covers part of Tibet and Bangladesh as well. Meteorological inputs for 29 years (1979-2007) are drawn from ERA-INTERIM and APHRODITE dataset for horizontal resolution of 0.25 degrees. The analysis was performed to study temporal variability of SWE in the Himalayan region of Nepal. The model was calibrated by observed stream flows of the tributaries of the Gandaki River in Nepal which ultimately feeds river Ganga. Further, the simulated SWE is used to estimate stream flow in this river basin. Since Nepal has a greater snow cover accumulation in monsoon season than in winter at high altitudes, seasonality fluctuations in SWE affecting the stream flows are known. The model provided fair estimates of SWE and stream flow as per statistical analysis. Stream flows are known to be sensitive to the changes in snow water that can bring a negative impact on power generation in a country which has huge hydroelectric potential. In addition, our results on simulated SWE in second largest snow-fed catchment of the country will be helpful for reservoir management, flood forecasting and other water resource management issues. Keywords: Hydrology, Snow Water Equivalent, Variable Infiltration Capacity, Gandaki River Basin, Stream Flow

Application of correspondence analysis in the assessment of mine tailings dam breakage risk in the Mediterranean region.

PubMed

Salgueiro, Ana Rita; Pereira, Henrique Garcia; Rico, Maria-Teresa; Benito, Gerado; Díez-Herreo, Andrés

2008-02-01

A new statistical approach for preliminary risk evaluation of breakage in tailings dam is presented and illustrated by a case study regarding the Mediterranean region. The objective of the proposed method is to establish an empirical scale of risk, from which guidelines for prioritizing the collection of further specific information can be derived. The method relies on a historical database containing, in essence, two sets of qualitative data: the first set concerns the variables that are observable before the disaster (e.g., type and size of the dam, its location, and state of activity), and the second refers to the consequences of the disaster (e.g., failure type, sludge characteristics, fatalities categorization, and downstream range of damage). Based on a modified form of correspondence analysis, where the second set of attributes are projected as "supplementary variables" onto the axes provided by the eigenvalue decomposition of the matrix referring to the first set, a "qualitative regression" is performed, relating the variables to be predicted (contained in the second set) with the "predictors" (the observable variables). On the grounds of the previously derived relationship, the risk of breakage in a new case can be evaluated, given observable variables. The method was applied in a case study regarding a set of 13 test sites where the ranking of risk obtained was validated by expert knowledge. Once validated, the procedure was included in the final output of the e-EcoRisk UE project (A Regional Enterprise Network Decision-Support System for Environmental Risk and Disaster Management of Large-Scale Industrial Spills), allowing for a dynamic historical database updating and providing a prompt rough risk evaluation for a new case. The aim of this section of the global project is to provide a quantified context where failure cases occurred in the past for supporting analogue reasoning in preventing similar situations.

The impact of inter-annual rainfall variability on food production in the Ganges basin

NASA Astrophysics Data System (ADS)

Siderius, Christian; Biemans, Hester; van Walsum, Paul; hellegers, Petra; van Ierland, Ekko; Kabat, Pavel

2014-05-01

Rainfall variability is expected to increase in the coming decades as the world warms. Especially in regions already water stressed, a higher rainfall variability will jeopardize food security. Recently, the impact of inter-annual rainfall variability has received increasing attention in regional to global analysis on water availability and food security. But the description of the dynamics behind it is still incomplete in most models. Contemporary land surface and hydrological models used for such analyses describe variability in production primarily as a function of yield, a process driven by biophysical parameters, thereby neglecting yearly variations in cropped area, a process driven largely by management decisions. Agricultural statistics for northern India show that the latter process could explain up to 40% of the observed inter-annual variation in food production in various states. We added a simple dynamic land use decision module to a land surface model (LPJmL) and analyzed to what extent this improved the estimation of variability in food production. Using this improved modelling framework we then assessed if and at which scale rainfall variability affects meeting the food self-sufficiency threshold. Early results for the Ganges Basin indicate that, while on basin level variability in crop production is still relatively low, several districts and states are highly affected (RSTD > 50%). Such insight can contribute to better recommendations on the most effective measures, at the most appropriate scale, to buffer variability in food production.

Using the Landsat Archive to Monitor Gully Erosion Development, in SE Nigeria, as a Response to Land-use Classification and Environmental Variability.

NASA Astrophysics Data System (ADS)

Brolly, M.; Iro, S.

2016-12-01

This study presents novel low budget methodologies for mapping and monitoring gully erosion development in South-East Nigeria. The unabated way gullies develop, and the lack of control measures in the SE Nigeria study area, motivates this work. The Landsat archive is used to determine change in land-use/cover classification over a 30-year period (1986-2015) in a region measuring 70km x 70km. Multi-resolution segmentation is enabled through Object Based Image Analysis (OBIA) and Pixel based classification techniques (supervised/unsupervised) using an initial dataset including 40 ground validated gully sites within the region. Detected increases in gully area are positively correlated with land clearance, manifested by associated vegetation reduction and anthropogenic encroachment with r values reported of -0.94 (p<0.05) and -0.97 (p<0.05) for the Pixel and OBIA classification approaches respectively. Within the study region 14 specific gullies are further vectorised and quantified in terms of extent and rates of change. Local and regional results are then examined in regard to land-use and environmental variables, such as meteorology, soil and rock geology, and topographical/landscape parameters. Of the 14 specific sites, the maximum reported erosion rates are 232010m2 per year for the largest gully (4123765m2) and -501m2 per year for the smallest (2749m2), representing year on year % increases of 9% and -0.15% respectively. These erosion rates were exhibited in 1988 and 2007. Analysis of topography across the region at 30m resolution reveals 90% of the 40 observed gullies develop on concave slopes with high values of 4 plan curvatures and greater than 15° inclines with highest erosion rates exhibited on ferralsols soil type. Principal Component Analysis reveals inter-variable similarities, via component 1, between Slope (58%), Elevation (50%) and Gully Area (62%), while, Vegetation loss (14%), Soil structure (8%) and Rate of gully change (3%) are better defined by the second component, showing their similarities.

Regional Deprivation Index and Socioeconomic Inequalities Related to Infant Deaths in Korea.

PubMed

Yun, Jae-Won; Kim, Young-Ju; Son, Mia

2016-04-01

Deprivation indices have been widely used to evaluate neighborhood socioeconomic status and therefore examine individuals within their regional context. Although some studies on the development of deprivation indices were conducted in Korea, additional research is needed to construct a more valid and reliable deprivation index. Therefore, a new deprivation index, named the K index, was constructed using principal component analysis. This index was compared with the Carstairs, Townsend and Choi indices. A possible association between infant death and deprivation was explored using the K index. The K index had a higher correlation with the infant mortality rate than did the other three indices. The regional deprivation quintiles were unequally distributed throughout the country. Despite the overall trend of gradually decreasing infant mortality rates, inequalities in infant deaths according to the deprivation quintiles persisted and widened. Despite its significance, the regional deprivation variable had a smaller effect on infant deaths than did individual variables. The K index functions as a deprivation index, and we may use this index to estimate the regional socioeconomic status in Korea. We found that inequalities in infant deaths according to the time trend persisted. To reduce the health inequalities among infants in Korea, regional deprivation should be considered.

The tropospheric biennial oscillation defined by a biennial mode of sea surface temperature and its impact on the atmospheric circulation and precipitation in the tropical eastern Indo-western Pacific region

NASA Astrophysics Data System (ADS)

Kim, Jinju; Kim, Kwang-Yul

2016-10-01

Temporal and spatial patterns of anomalous atmospheric circulation and precipitation over the Indo-Pacific region are analyzed in conjunction with the Tropospheric Biennial Oscillation as represented by the biennial mode of sea surface temperature anomalies (SSTA). The biennial components of key variables are identified independently of other variability via CSEOF analysis. Then, its impact on the Asian-Australian monsoon is examined. The biennial mode exhibits a seasonally distinctive atmospheric response over the tropical eastern Indo-western Pacific (EIWP) region (90°-150°E, 20°S-20°N). In boreal summer, local meridional circulation is a distinguishing characteristic over the tropical EIWP region, whereas a meridionally expanded branch of intensified zonal circulation develops in austral summer. Temporally varying evolution and distinct timing of SSTA phase transition in the Indian and Pacific Oceans is considered a main factor for this variation of circulation in the tropical EIWP region. The impact of the biennial mode is not the same between the two seasons, with different impacts over ocean areas in Asian monsoon and Australian monsoon regions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Balaguru, Karthik; Leung, Lai-Yung R.; Yoon, Jin-Ho

Despite the strong dependence of the Power Dissipation Index (PDI), which is a measure of the intensity of Tropical Cyclone (TC) activity, on tropical sea-surface temperatures (SSTs), the variations in PDI are not completely explained by SST. Here we show, using an analysis of a string of observational data sets, that the variability of the thermocline depth (TD) in the east Pacific exerts a significant degree of control on the variability of PDI in that region. On average, a deep thermocline with a larger reservoir of heat favors TC intensification by reducing SST cooling while a shallow thermocline with amore » smaller heat reservoir promotes enhanced SST cooling that contributes to TC decay. At interannual time scales, the variability of basin-mean TD accounts for nearly 30% of the variability in the PDI during the TC season. Also, about 20% of the interannual variability in the east Pacific basin-mean TD is due to the El Niño and the Southern Oscillation (ENSO), a dominant climate signal in this region. This study suggests that a better understanding of the factors governing the interannual variability of the TD conditions in the east Pacific and how they may change over time, may lead to an improved projection of future east Pacific TC activity.« less

Analysis of variable sites between two complete South China tiger (Panthera tigris amoyensis) mitochondrial genomes.

PubMed

Zhang, Wenping; Yue, Bisong; Wang, Xiaofang; Zhang, Xiuyue; Xie, Zhong; Liu, Nonglin; Fu, Wenyuan; Yuan, Yaohua; Chen, Daqing; Fu, Danghua; Zhao, Bo; Yin, Yuzhong; Yan, Xiahui; Wang, Xinjing; Zhang, Rongying; Liu, Jie; Li, Maoping; Tang, Yao; Hou, Rong; Zhang, Zhihe

2011-10-01

In order to investigate the mitochondrial genome of Panthera tigris amoyensis, two South China tigers (P25 and P27) were analyzed following 15 cymt-specific primer sets. The entire mtDNA sequence was found to be 16,957 bp and 17,001 bp long for P25 and P27 respectively, and this difference in length between P25 and P27 occurred in the number of tandem repeats in the RS-3 segment of the control region. The structural characteristics of complete P. t. amoyensis mitochondrial genomes were also highly similar to those of P. uncia. Additionally, the rate of point mutation was only 0.3% and a total of 59 variable sites between P25 and P27 were found. Out of the 59 variable sites, 6 were located in 6 different tRNA genes, 6 in the 2 rRNA genes, 7 in non-coding regions (one located between tRNA-Asn and tRNA-Tyr and six in the D-loop), and 40 in 10 protein-coding genes. COI held the largest amount of variable sites (9 sites) and Cytb contained the highest variable rate (0.7%) in the complete sequences. Moreover, out of the 40 variable sites located in 10 protein-coding genes, 12 sites were nonsynonymous.

Modelling space of spread Dengue Hemorrhagic Fever (DHF) in Central Java use spatial durbin model

NASA Astrophysics Data System (ADS)

Ispriyanti, Dwi; Prahutama, Alan; Taryono, Arkadina PN

2018-05-01

Dengue Hemorrhagic Fever is one of the major public health problems in Indonesia. From year to year, DHF causes Extraordinary Event in most parts of Indonesia, especially Central Java. Central Java consists of 35 districts or cities where each region is close to each other. Spatial regression is an analysis that suspects the influence of independent variables on the dependent variables with the influences of the region inside. In spatial regression modeling, there are spatial autoregressive model (SAR), spatial error model (SEM) and spatial autoregressive moving average (SARMA). Spatial Durbin model is the development of SAR where the dependent and independent variable have spatial influence. In this research dependent variable used is number of DHF sufferers. The independent variables observed are population density, number of hospitals, residents and health centers, and mean years of schooling. From the multiple regression model test, the variables that significantly affect the spread of DHF disease are the population and mean years of schooling. By using queen contiguity and rook contiguity, the best model produced is the SDM model with queen contiguity because it has the smallest AIC value of 494,12. Factors that generally affect the spread of DHF in Central Java Province are the number of population and the average length of school.

Why inputs matter: Selection of climatic variables for species distribution modelling in the Himalayan region

NASA Astrophysics Data System (ADS)

Bobrowski, Maria; Schickhoff, Udo

2017-04-01

Betula utilis is a major constituent of alpine treeline ecotones in the western and central Himalayan region. The objective of this study is to provide first time analysis of the potential distribution of Betula utilis in the subalpine and alpine belts of the Himalayan region using species distribution modelling. Using Generalized Linear Models (GLM) we aim at examining climatic factors controlling the species distribution under current climate conditions. Furthermore we evaluate the prediction ability of climate data derived from different statistical methods. GLMs were created using least correlated bioclimatic variables derived from two different climate models: 1) interpolated climate data (i.e. Worldclim, Hijmans et al., 2005) and 2) quasi-mechanistical statistical downscaling (i.e. Chelsa; Karger et al., 2016). Model accuracy was evaluated by the ability to predict the potential species distribution range. We found that models based on variables of Chelsa climate data had higher predictive power, whereas models using Worldclim climate data consistently overpredicted the potential suitable habitat for Betula utilis. Although climatic variables of Worldclim are widely used in modelling species distribution, our results suggest to treat them with caution when remote regions like the Himalayan mountains are in focus. Unmindful usage of climatic variables for species distribution models potentially cause misleading projections and may lead to wrong implications and recommendations for nature conservation. References: Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G. & Jarvis, A. (2005) Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25, 1965-1978. Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N., Linder, H.P. & Kessler, M. (2016) Climatologies at high resolution for the earth land surface areas. arXiv:1607.00217 [physics].

Changing precipitation in western Europe, climate change or natural variability?

NASA Astrophysics Data System (ADS)

Aalbers, Emma; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart

2017-04-01

Multi-model RCM-GCM ensembles provide high resolution climate projections, valuable for among others climate impact assessment studies. While the application of multiple models (both GCMs and RCMs) provides a certain robustness with respect to model uncertainty, the interpretation of differences between ensemble members - the combined result of model uncertainty and natural variability of the climate system - is not straightforward. Natural variability is intrinsic to the climate system, and a potentially large source of uncertainty in climate change projections, especially for projections on the local to regional scale. To quantify the natural variability and get a robust estimate of the forced climate change response (given a certain model and forcing scenario), large ensembles of climate model simulations of the same model provide essential information. While for global climate models (GCMs) a number of such large single model ensembles exists and have been analyzed, for regional climate models (RCMs) the number and size of single model ensembles is limited, and the predictability of the forced climate response at the local to regional scale is still rather uncertain. We present a regional downscaling of a 16-member single model ensemble over western Europe and the Alps at a resolution of 0.11 degrees (˜12km), similar to the highest resolution EURO-CORDEX simulations. This 16-member ensemble was generated by the GCM EC-EARTH, which was downscaled with the RCM RACMO for the period 1951-2100. This single model ensemble has been investigated in terms of the ensemble mean response (our estimate of the forced climate response), as well as the difference between the ensemble members, which measures natural variability. We focus on the response in seasonal mean and extreme precipitation (seasonal maxima and extremes with a return period up to 20 years) for the near to far future. For most precipitation indices we can reliably determine the climate change signal, given the applied model chain and forcing scenario. However, the analysis also shows how limited the information in single ensemble members is on the local scale forced climate response, even for high levels of global warming when the forced response has emerged from natural variability. Analysis and application of multi-model ensembles like EURO-CORDEX should go hand-in-hand with single model ensembles, like the one presented here, to be able to correctly interpret the fine-scale information in terms of a forced signal and random noise due to natural variability.

For whom is income inequality most harmful? A multi-level analysis of income inequality and mortality in Norway.

PubMed

Dahl, Espen; Ivar Elstad, Jon; Hofoss, Dag; Martin-Mollard, Melissa

2006-11-01

This study investigates the degree to which contextual income inequality in economic regions in Norway affected mortality during the 1990s, above the effects of mean regional income and individual-level confounders. A further objective is to explore whether income inequality effects on mortality differed between socioeconomic groups. Data were constructed by linkages of administrative registers encompassing all Norwegian inhabitants. The outcome variable was all-cause mortality during 6 years (i.e., died 1994-1999 or alive end of 1999). Men and women aged 25-66 in 1993 were analysed. Regions' mean income and income inequality (in terms of gini coefficients) were calculated from consumption-units-adjusted family disposable income. Individual-level variables included sex, age, marital status, individual income, education, and being a recipient of health-related welfare benefits. Multilevel logistic regression models were fitted for 2,197,231 individuals nested within 88 regions. After adjusting for regional mean income and individual-level variables, the odds ratio (OR) for mortality 1994-1999 was 1.028 (95% CI 1.023-1.033) on the gini variable multiplied by 100. Analyses of cross-level interactions indicated some, albeit modest, income inequality effects on mortality in the upper income and educational categories. Among those with low individual income, low education, and among recipients of health-related welfare benefits, mortality effects of higher regional income inequality were significantly stronger than among those more advantageously placed in the social structure. The results of this study differ from previous studies which have suggested that contextual income inequality has a minor impact on population health in egalitarian countries. The results indicate that in Norway, neither a comparatively egalitarian income distribution nor generous and comprehensive welfare institutions hindered the emergence of regional-level income inequality effects on mortality, and these effects were particularly marked among socioeconomically disadvantaged groups. Explanations for the results are discussed.

Assessing the Impact of Climatic Variability and Change on Maize Production in the Midwestern USA

NASA Astrophysics Data System (ADS)

Andresen, J.; Jain, A. K.; Niyogi, D. S.; Alagarswamy, G.; Biehl, L.; Delamater, P.; Doering, O.; Elias, A.; Elmore, R.; Gramig, B.; Hart, C.; Kellner, O.; Liu, X.; Mohankumar, E.; Prokopy, L. S.; Song, C.; Todey, D.; Widhalm, M.

2013-12-01

Weather and climate remain among the most important uncontrollable factors in agricultural production systems. In this study, three process-based crop simulation models were used to identify the impacts of climate on the production of maize in the Midwestern U.S.A. during the past century. The 12-state region is a key global production area, responsible for more than 80% of U.S. domestic and 25% of total global production. The study is a part of the Useful to Useable (U2U) Project, a USDA NIFA-sponsored project seeking to improve the resilience and profitability of farming operations in the region amid climate variability and change. Three process-based crop simulation models were used in the study: CERES-Maize (DSSAT, Hoogenboom et al., 2012), the Hybrid-Maize model (Yang et al., 2004), and the Integrated Science Assessment Model (ISAM, Song et al., 2013). Model validation was carried out with individual plot and county observations. The models were run with 4 to 50 km spatial resolution gridded weather data for representative soils and cultivars, 1981-2012, to examine spatial and temporal yield variability within the region. We also examined the influence of different crop models and spatial scales on regional scale yield estimation, as well as a yield gap analysis between observed and attainable yields. An additional study was carried out with the CERES-Maize model at 18 individual site locations 1901-2012 to examine longer term historical trends. For all simulations, all input variables were held constant in order to isolate the impacts of climate. In general, the model estimates were in good agreement with observed yields, especially in central sections of the region. Regionally, low precipitation and soil moisture stress were chief limitations to simulated crop yields. The study suggests that at least part of the observed yield increases in the region during recent decades have occurred as the result of wetter, less stressful growing season weather conditions.

Regional variation in the biogeochemical and physical characteristics of natural peatland pools.

PubMed

Turner, T Edward; Billett, Michael F; Baird, Andy J; Chapman, Pippa J; Dinsmore, Kerry J; Holden, Joseph

2016-03-01

Natural open-water pools are a common feature of northern peatlands and are known to be an important source of atmospheric methane (CH4). Pool environmental variables, particularly water chemistry, vegetation community and physical characteristics, have the potential to exert strong controls on carbon cycling in pools. A total of 66 peatland pools were studied across three regions of the UK (northern Scotland, south-west Scotland, and Northern Ireland). We found that within-region variability of pool water chemistry was low; however, for many pool variables measured there were significant differences between regions. PCA analysis showed that pools in SW Scotland were strongly associated with greater vegetative cover and shallower water depth which is likely to increase dissolved organic carbon (DOC) mineralisation rates, whereas pools in N Scotland were more open and deeper. Pool water DOC, particulate organic carbon and dissolved CH4 concentrations were significantly different between regions. Pools in Northern Ireland had the highest concentrations of DOC (mean=14.5 mg L(-1)) and CH4 (mean=20.6 μg C L(-1)). Chloride and sulphate concentrations were significantly higher in the pools in N Scotland (mean values 26.3 and 2.40 mg L(-1), respectively) than elsewhere, due to a stronger marine influence. The ratio of UV absorbance at 465 nm to absorbance at 665 nm for pools in Northern Ireland indicated that DOC was sourced from poorly humified peat, potentially increasing the bioavailability and mineralisation of organic carbon in pools compared to the pools elsewhere. This study, which specifically aims to address a lack of basic biogeochemical knowledge about pool water chemistry, clearly shows that peatland pools are highly regionally variable. This is likely to be a reflection of significant regional-scale differences in peatland C cycling. Copyright © 2015 Elsevier B.V. All rights reserved.

Genetic variation of the riparian pioneer tree species populus nigra. II. Variation In susceptibility to the foliar rust melampsora larici-populina

PubMed

Legionnet; Muranty; Lefevre

1999-04-01

Partial resistance of Populus nigra L. to three races of the foliar rust Melampsora larici-populina Kleb. was studied in a field trial and in laboratory tests, using a collection of P. nigra originating from different places throughout France. No total resistance was found. The partial resistance was split into epidemiological components, which proved to be under genetic control. Various patterns of association of epidemiological components values were found. Principal components analysis revealed their relationships. Only 24% of the variance of the field susceptibility could be explained by the variation of the epidemiological components of susceptibility. This variable was significantly correlated with susceptibility to the most ancient and widespread race of the pathogen, and with the variables related to the size of the lesions of the different races. Analysis of variance showed significant differences in susceptibility between regions and between stands within one region. Up to 20% of variation was between regions, and up to 22% between stands, so that these genetic factors appeared to be more differentiated than the neutral diversity (up to 3.5% Legionnet & Lefevre, 1996). However, no clear pattern of geographical distribution of diversity was detected.

Phylogenetic analysis of feline immunodeficiency virus strains from naturally infected cats in Belgium and The Netherlands.

PubMed

Roukaerts, Inge D M; Theuns, Sebastiaan; Taffin, Elien R L; Daminet, Sylvie; Nauwynck, Hans J

2015-01-22

Feline immunodeficiency virus (FIV) is a major pathogen in feline populations worldwide, with seroprevalences up to 26%. Virus strains circulating in domestic cats are subdivided into different phylogenetic clades (A-E), based on the genetic diversity of the V3-V4 region of the env gene. In this report, a phylogenetic analysis of the V3-V4 env region, and a variable region in the gag gene was made for 36 FIV strains isolated in Belgium and The Netherlands. All newly generated gag sequences clustered together with previously known clade A FIV viruses, confirming the dominance of clade A viruses in Northern Europe. The same was true for the obtained env sequences, with only one sample of an unknown env subtype. Overall, the genetic diversity of FIV strains sequenced in this report was low. This indicates a relatively recent introduction of FIV in Belgium and The Netherlands. However, the sample with an unknown env subtype indicates that new introductions of FIV from unknown origin do occur and this will likely increase genetic variability in time. Copyright © 2014 Elsevier B.V. All rights reserved.

A statistical model for predicting the inter-annual variability of birch pollen abundance in Northern and North-Eastern Europe.

PubMed

Ritenberga, Olga; Sofiev, Mikhail; Siljamo, Pilvi; Saarto, Annika; Dahl, Aslog; Ekebom, Agneta; Sauliene, Ingrida; Shalaboda, Valentina; Severova, Elena; Hoebeke, Lucie; Ramfjord, Hallvard

2018-02-15

The paper suggests a methodology for predicting next-year seasonal pollen index (SPI, a sum of daily-mean pollen concentrations) over large regions and demonstrates its performance for birch in Northern and North-Eastern Europe. A statistical model is constructed using meteorological, geophysical and biological characteristics of the previous year). A cluster analysis of multi-annual data of European Aeroallergen Network (EAN) revealed several large regions in Europe, where the observed SPI exhibits similar patterns of the multi-annual variability. We built the model for the northern cluster of stations, which covers Finland, Sweden, Baltic States, part of Belarus, and, probably, Russia and Norway, where the lack of data did not allow for conclusive analysis. The constructed model was capable of predicting the SPI with correlation coefficient reaching up to 0.9 for some stations, odds ratio is infinitely high for 50% of sites inside the region and the fraction of prediction falling within factor of 2 from observations, stays within 40-70%. In particular, model successfully reproduced both the bi-annual cycle of the SPI and years when this cycle breaks down. Copyright © 2017 Elsevier B.V. All rights reserved.

Prevalence and predictors of postoperative pain after ear, nose, and throat surgery.

PubMed

Sommer, Michael; Geurts, José W J M; Stessel, Bjorn; Kessels, Alfons G H; Peters, Madelon L; Patijn, Jacob; van Kleef, Maarten; Kremer, Bernd; Marcus, Marco A E

2009-02-01

To determine postoperative pain in different types of ear, nose, and throat (ENT) surgery and their psychological preoperative predictors. Prospective cohort study. Academic hospital. A total of 217 patients undergoing ENT surgery. All ENT, neck, and salivary gland surgery. Postoperative pain and predictors for postoperative pain. Fifty percent of the patients undergoing surgery on the oral, pharyngeal, and laryngeal region and on the neck and salivary gland region had a visual analog scale score higher than 40 mm on day 1. In the patients who underwent oropharyngeal region operations the VAS score remained high on all 4 days. A VAS pain score higher than 40 mm was found in less than 30% of patients after endoscopic procedures and less than 20% after ear and nose surgery. After bivariate analysis, 6 variables--age, sex, preoperative pain, expected pain, short-term fear, and pain catastrophizing--had a predictive value. Multivariate analysis showed only preoperative pain, pain catastrophizing, and anatomical site of operation as independent predictors. Differences exist in the prevalence of unacceptable postoperative pain between ENT operations performed on different anatomical sites. A limited set of variables can be used to predict the occurrence of unacceptable postoperative pain after ENT surgery.

Redescription and molecular characterization of Anoplocephala manubriata, Railliet et al., 1914 (Cestoda: Anoplocephalidae) from a Sri Lankan wild elephant (Elephas maximus).

PubMed

Perera, K U E; Wickramasinghe, Susiji; Perera, B V P; Bandara, K B A T; Rajapakse, R P V J

2017-06-01

The present work provides a detailed morphological and molecular description of Anoplocephala manubriata in elephants. Adult worms were recovered during an autopsy of a wild elephant in Elephant Transit Home, Udawalawe, Sri Lanka. Necropsy findings revealed a severe cestode infection in the small intestine. These tapeworms were tightly attached to the intestinal mucosae, resulted in hyperemic thickened intestinal mucosae, variable size irregular well-demarcated multifocal ulcerative regions sometimes covered with necrotic membranes and variable size, diffuse, well-demarcated raised nodular masses were evident in the small intestine. The article provides an account of the biology of A. manubriata and a comparative analysis of the morphology and morphometrics of Anoplocephala species that occur in different hosts. Phylogenetic analysis of the second internal transcribed spacer region (ITS-2), a portion of the 28S region and cytochrome oxidase subunit 1 (COX1) genes revealed that A. manubriata is closely associated with Anoplocephala species in horse in comparison to other Anoplocephalines. This study will enhance the current knowledge in taxonomy of elephant tapeworms and contribute to future phylogenetic studies. Copyright © 2017 Elsevier B.V. All rights reserved.

Effect of meteorological variables on Plasmodium vivax and Plasmodium falciparum malaria in outbreak prone districts of Rajasthan, India.

PubMed

Lingala, Mercy A L

Malaria is a public health problem caused by Plasmodium parasite and transmitted by anopheline mosquitoes. Arid and semi-arid regions of western India are prone to malaria outbreaks. Malaria outbreak prone districts viz. Bikaner, Barmer and Jodhpur were selected to study the effect of meteorological variables on Plasmodium vivax and Plasmodium falciparum malaria outbreaks for the period of 2009-2012. The data of monthly malaria cases and meteorological variables was analysed using SPSS 20v. Spearman correlation analysis was conducted to examine the strength of the relationship between meteorological variables, P. vivax and P. falciparum malaria cases. Pearson's correlation analysis was carried out among the meteorological variables to observe the independent effect of each independent variable on the outcome. Results indicate that malaria outbreaks have occurred in Bikaner and Barmer due to continuous rains for more than two months. Rainfall has shown to be an important predictor of malaria outbreaks in Rajasthan. P. vivax is more significantly correlated with rainfall, minimum temperature (P<0.01) and less significantly with relative humidity (P<0.05); whereas P. falciparum is significantly correlated with rainfall, relative humidity (P<0.01) and less significantly with temperature (P<0.05). The determination of the lag period for P. vivax is relative humidity and for P. falciparum is temperature. The lag period between malaria cases and rainfall is shorter for P. vivax than P. falciparum. In conclusion, the knowledge generated is not only useful to take prompt malaria control interventions but also helpful to develop better forecasting model in outbreak prone regions. Copyright © 2017 The Author. Published by Elsevier Ltd.. All rights reserved.

Coupled Modes over Indian Ocean at Sub-seasonal time Scales and its Prediction

NASA Astrophysics Data System (ADS)

Jung, E.; Kirtman, B. P.

2014-12-01

Sub-seasonal variability over the Indian Ocean, such as Madden-Julian Oscillation impacts weather and climate globally. However, the prediction of tropical sub-seasonal variability (TSV) remains a challenge, and understanding air-sea interactions on TSV time-scales is likely to be an important part of the prediction problem. The purpose of this paper is to examine the predictability of sub-seasonal variability in the tropical Indo-Pacific region. The analysis emphasizes on variability associated with coupled air-sea interactions in observational estimates, and how well these coupled modes are simulated and predicted within the context of a 30-year retrospective forecast experiment with a state-of-the-art atmosphere-ocean coupled model. The analysis shows that Sea Surface Temperature anomalies (SSTA) over the Indian Ocean tend to precede precipitation anomalies by 7-11 days with maximum amplitude over the Arabian Sea and the Bay of Bengal for summer and along the Seychelles-Chagos Thermocline Ridge (SCTR) region for winter. Though these coupled modes are captured by the models, the forecasts fail to predict its evolution. Based on the diagnosis of these coupled modes, we introduce a SCTR-SST index and an index that measures the modulation of the low-frequency amplitude (LFAM) of sub-seasonal SSTA variability over SCTR as a way to predict the coupled modes. Based on correlation with the observed variability, SCTR-SST has forecast skill of about 45 days over the Indian Ocean. However the sub-seasonal SSTAs in the predictions and the observational estimates do not have any direct ENSO tele-connection. In contrast, the LFAM of the sub-seasonal SSTA variance over SCTR is strongly correlated with ENSO, suggesting enhanced sub-seasonal variance on seasonal time-scales is potentially predictable.

Genomic Characterization of Variable Surface Antigens Reveals a Telomere Position Effect as a Prerequisite for RNA Interference-Mediated Silencing in Paramecium tetraurelia

PubMed Central

Baranasic, Damir; Oppermann, Timo; Cheaib, Miriam; Cullum, John; Schmidt, Helmut

2014-01-01

ABSTRACT Antigenic or phenotypic variation is a widespread phenomenon of expression of variable surface protein coats on eukaryotic microbes. To clarify the mechanism behind mutually exclusive gene expression, we characterized the genetic properties of the surface antigen multigene family in the ciliate Paramecium tetraurelia and the epigenetic factors controlling expression and silencing. Genome analysis indicated that the multigene family consists of intrachromosomal and subtelomeric genes; both classes apparently derive from different gene duplication events: whole-genome and intrachromosomal duplication. Expression analysis provides evidence for telomere position effects, because only subtelomeric genes follow mutually exclusive transcription. Microarray analysis of cultures deficient in Rdr3, an RNA-dependent RNA polymerase, in comparison to serotype-pure wild-type cultures, shows cotranscription of a subset of subtelomeric genes, indicating that the telomere position effect is due to a selective occurrence of Rdr3-mediated silencing in subtelomeric regions. We present a model of surface antigen evolution by intrachromosomal gene duplication involving the maintenance of positive selection of structurally relevant regions. Further analysis of chromosome heterogeneity shows that alternative telomere addition regions clearly affect transcription of closely related genes. Consequently, chromosome fragmentation appears to be of crucial importance for surface antigen expression and evolution. Our data suggest that RNAi-mediated control of this genetic network by trans-acting RNAs allows rapid epigenetic adaptation by phenotypic variation in combination with long-term genetic adaptation by Darwinian evolution of antigen genes. PMID:25389173

Harmonic analysis of the precipitation in Greece

NASA Astrophysics Data System (ADS)

Nastos, P. T.; Zerefos, C. S.

2009-04-01

Greece is a country with a big variety of climates due to its geographical position, to the many mountain ranges and also to the multifarious and long coastline. The mountainous volumes are of such orientation that influences the distribution of the precipitation, having as a result, Western Greece to present great differentiations from Central and Eastern Greece. The application of harmonic analysis to the annual variability of precipitation is the goal of this study, so that the components, which compose the annual variability, be elicited. For this purpose, the mean monthly precipitation data from 30 meteorological stations of National Meteorological Service were used for the time period 1950-2000. The initial target is to reduce the number of variables and to detect structure in the relationships between variables. The most commonly used technique for this purpose is the application of Factor Analysis to a table having as columns the meteorological stations-variables and rows the monthly mean precipitation, so that 2 main factors were calculated, which explain the 98% of total variability of precipitation in Greece. Factor 1, representing the so-called uniform field and interpreting the most of the total variance, refers in fact to the Mediterranean depressions, affecting mainly the West of Greece and also the East Aegean and the Asia Minor coasts. In the process, the Fourier Analysis was applied to the factor scores extracted from the Factor Analysis, so that 2 harmonic components are resulted, which explain above the 98% of the total variability of each main factor, and are due to different synoptic and thermodynamic processes associated with Greece's precipitation construction. Finally, the calculation of the time of occurrence of the maximum precipitation, for each harmonic component of each one of the two main factors, gives the spatial distribution of appearance of the maximum precipitation in the Hellenic region.

Co-variability of smoke and fire in the Amazon basin

NASA Astrophysics Data System (ADS)

Mishra, Amit Kumar; Lehahn, Yoav; Rudich, Yinon; Koren, Ilan

2015-05-01

The Amazon basin is a hot spot of anthropogenically-driven biomass burning, accounting for approximately 15% of total global fire emissions. It is essential to accurately measure these fires for robust regional and global modeling of key environmental processes. Here we have explored the link between spatio-temporal variability patterns in the Amazon basin's fires and the resulting smoke loading using 11 years (2002-2012) of data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Aerosol Robotic Network (AERONET) observations. Focusing on the peak burning season (July-October), our analysis shows strong inter-annual correlation between aerosol optical depth (AOD) and two MODIS fire products: fire radiative power (FRP) and fire pixel counts (FC). Among these two fire products, the FC better indicates the amount of smoke in the basin, as represented in remotely sensed AOD data. This fire product is significantly correlated both with regional AOD retrievals from MODIS and with point AOD measurements from the AERONET stations, pointing to spatial homogenization of the smoke over the basin on a seasonal time scale. However, MODIS AODs are found better than AERONET AODs observation for linking between smoke and fire. Furthermore, MODIS AOD measurements are strongly correlated with number of fires ∼10-20 to the east, most likely due to westward advection of smoke by the wind. These results can be rationalized by the regional topography and the wind regimes. Our analysis can improve data assimilation of satellite and ground-based observations into regional and global model studies, thus improving the assessment of the environmental and climatic impacts of frequency and distribution variability of the Amazon basin's fires. We also provide the optimal spatial and temporal scales for ground-based observations, which could be used for such applications.

The phosphotransferase system-dependent sucrose utilization regulon in enteropathogenic Escherichia coli strains is located in a variable chromosomal region containing iap sequences.

PubMed

Treviño-Quintanilla, Luis Gerardo; Escalante, Adelfo; Caro, Alma Delia; Martínez, Alfredo; González, Ricardo; Puente, José Luis; Bolívar, Francisco; Gosset, Guillermo

2007-01-01

The capacity to utilize sucrose as a carbon and energy source (Scr(+) phenotype) is a highly variable trait among Escherichia coli strains. In this study, seven enteropathogenic E. coli (EPEC) strains from different sources were studied for their capacity to grow using sucrose. Liquid media cultures showed that all analyzed strains have the Scr(+) phenotype and two distinct groups were defined: one of five and another of two strains displaying doubling times of 67 and 125 min, respectively. The genes conferring the Scr(+) phenotype in one of the fast-growing strains (T19) were cloned and sequenced. Comparative sequence analysis revealed that this strain possesses the scr regulon genes scrKYABR, encoding phosphoenolpyruvate:phosphotransferase system-dependent sucrose transport and utilization activities. Transcript level quantification revealed sucrose-dependent induction of scrK and scrR genes in fast-growing strains, whereas no transcripts were detected in slow-growing strains. Sequence comparison analysis revealed that the scr genes in strain T19 are almost identical to those present in the scr regulon of prototype EPEC E2348/69 and in both strains, the scr genes are inserted in the chromosomal intergenic region of hypothetical genes ygcE and ygcF. Comparison of the ygcE-ygcF intergenic region sequence of strains MG1655, enterohemorrhagic EDL933, uropathogenic ECFT073 and EPEC T19-E2348/69 revealed that the number of extragenic highly repeated iap sequences corresponded to nine, four, two and none, respectively. These results show that the iap sequence-containing chromosomal ygcE-ygcF intergenic region is highly variable in E. coli. Copyright (c) 2007 S. Karger AG, Basel.

Estimating Bacterial Diversity for Ecological Studies: Methods, Metrics, and Assumptions

PubMed Central

Birtel, Julia; Walser, Jean-Claude; Pichon, Samuel; Bürgmann, Helmut; Matthews, Blake

2015-01-01

Methods to estimate microbial diversity have developed rapidly in an effort to understand the distribution and diversity of microorganisms in natural environments. For bacterial communities, the 16S rRNA gene is the phylogenetic marker gene of choice, but most studies select only a specific region of the 16S rRNA to estimate bacterial diversity. Whereas biases derived from from DNA extraction, primer choice and PCR amplification are well documented, we here address how the choice of variable region can influence a wide range of standard ecological metrics, such as species richness, phylogenetic diversity, β-diversity and rank-abundance distributions. We have used Illumina paired-end sequencing to estimate the bacterial diversity of 20 natural lakes across Switzerland derived from three trimmed variable 16S rRNA regions (V3, V4, V5). Species richness, phylogenetic diversity, community composition, β-diversity, and rank-abundance distributions differed significantly between 16S rRNA regions. Overall, patterns of diversity quantified by the V3 and V5 regions were more similar to one another than those assessed by the V4 region. Similar results were obtained when analyzing the datasets with different sequence similarity thresholds used during sequences clustering and when the same analysis was used on a reference dataset of sequences from the Greengenes database. In addition we also measured species richness from the same lake samples using ARISA Fingerprinting, but did not find a strong relationship between species richness estimated by Illumina and ARISA. We conclude that the selection of 16S rRNA region significantly influences the estimation of bacterial diversity and species distributions and that caution is warranted when comparing data from different variable regions as well as when using different sequencing techniques. PMID:25915756

Genetic Characterization of Circulating African Swine Fever Viruses in Nigeria (2007-2015).

PubMed

Luka, P D; Achenbach, J E; Mwiine, F N; Lamien, C E; Shamaki, D; Unger, H; Erume, J

2017-10-01

Sequencing and analysis of three discrete genome regions of African swine fever viruses (ASFV) from archival samples collected in 2007-2011 and active and passive surveillance between 2012 and 2015 in Nigeria were carried out. Analysis was conducted by genotyping of three single-copy African swine fever (ASF) genes. The E183L and B646L genes that encode structural proteins p54 and p72, respectively, were utilized to delineate genotypes before intragenotypic resolution by characterization of the tetrameric amino acid repeat region within the hypervariable central variable region of the B602L gene. The results showed no variation in the p72 and p54 gene regions sequenced. Phylogeny of p72 sequences revealed that all the Nigerian isolates belonged to genotype I, while that of the p54 recovered the Ia genotype. Analysis of B602L gene revealed the differences in the number of tetrameric repeats. Four new variants (Tet-15, Tet-17a, Tet-17b and Tet-48) were recovered, while a fifth variant (Tet-20) was the most widely distributed in the country displacing Tet-36 reported previously in 2003-2006. The viruses responsible for ASF outbreaks in Nigeria are from very closely related but mutated variants of the virus that have been circulating since 1997. A practical implication of the genetic variability of the Nigerian viral isolates in this study is the need for continuous sampling and analysis of circulating viruses, which will provide epidemiological information on the evolution of ASFV in the field versus new incursion for informed strategic control of the disease in the country. © 2016 Blackwell Verlag GmbH.

Remote Sensing-Driven Climatic/Environmental Variables for Modelling Malaria Transmission in Sub-Saharan Africa.

PubMed

Ebhuoma, Osadolor; Gebreslasie, Michael

2016-06-14

Malaria is a serious public health threat in Sub-Saharan Africa (SSA), and its transmission risk varies geographically. Modelling its geographic characteristics is essential for identifying the spatial and temporal risk of malaria transmission. Remote sensing (RS) has been serving as an important tool in providing and assessing a variety of potential climatic/environmental malaria transmission variables in diverse areas. This review focuses on the utilization of RS-driven climatic/environmental variables in determining malaria transmission in SSA. A systematic search on Google Scholar and the Institute for Scientific Information (ISI) Web of Knowledge(SM) databases (PubMed, Web of Science and ScienceDirect) was carried out. We identified thirty-five peer-reviewed articles that studied the relationship between remotely-sensed climatic variable(s) and malaria epidemiological data in the SSA sub-regions. The relationship between malaria disease and different climatic/environmental proxies was examined using different statistical methods. Across the SSA sub-region, the normalized difference vegetation index (NDVI) derived from either the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) or Moderate-resolution Imaging Spectrometer (MODIS) satellite sensors was most frequently returned as a statistically-significant variable to model both spatial and temporal malaria transmission. Furthermore, generalized linear models (linear regression, logistic regression and Poisson regression) were the most frequently-employed methods of statistical analysis in determining malaria transmission predictors in East, Southern and West Africa. By contrast, multivariate analysis was used in Central Africa. We stress that the utilization of RS in determining reliable malaria transmission predictors and climatic/environmental monitoring variables would require a tailored approach that will have cognizance of the geographical/climatic setting, the stage of malaria elimination continuum, the characteristics of the RS variables and the analytical approach, which in turn, would support the channeling of intervention resources sustainably.

Remote Sensing-Driven Climatic/Environmental Variables for Modelling Malaria Transmission in Sub-Saharan Africa

PubMed Central

Ebhuoma, Osadolor; Gebreslasie, Michael

2016-01-01

Malaria is a serious public health threat in Sub-Saharan Africa (SSA), and its transmission risk varies geographically. Modelling its geographic characteristics is essential for identifying the spatial and temporal risk of malaria transmission. Remote sensing (RS) has been serving as an important tool in providing and assessing a variety of potential climatic/environmental malaria transmission variables in diverse areas. This review focuses on the utilization of RS-driven climatic/environmental variables in determining malaria transmission in SSA. A systematic search on Google Scholar and the Institute for Scientific Information (ISI) Web of KnowledgeSM databases (PubMed, Web of Science and ScienceDirect) was carried out. We identified thirty-five peer-reviewed articles that studied the relationship between remotely-sensed climatic variable(s) and malaria epidemiological data in the SSA sub-regions. The relationship between malaria disease and different climatic/environmental proxies was examined using different statistical methods. Across the SSA sub-region, the normalized difference vegetation index (NDVI) derived from either the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) or Moderate-resolution Imaging Spectrometer (MODIS) satellite sensors was most frequently returned as a statistically-significant variable to model both spatial and temporal malaria transmission. Furthermore, generalized linear models (linear regression, logistic regression and Poisson regression) were the most frequently-employed methods of statistical analysis in determining malaria transmission predictors in East, Southern and West Africa. By contrast, multivariate analysis was used in Central Africa. We stress that the utilization of RS in determining reliable malaria transmission predictors and climatic/environmental monitoring variables would require a tailored approach that will have cognizance of the geographical/climatic setting, the stage of malaria elimination continuum, the characteristics of the RS variables and the analytical approach, which in turn, would support the channeling of intervention resources sustainably. PMID:27314369

Trend analysis of evapotranspiration over India: Observed from long-term satellite measurements

NASA Astrophysics Data System (ADS)

Goroshi, Sheshakumar; Pradhan, Rohit; Singh, Raghavendra P.; Singh, K. K.; Parihar, Jai Singh

2017-12-01

Owing to the lack of consistent spatial time series data on actual evapotranspiration ( ET), very few studies have been conducted on the long-term trend and variability in ET at a national scale over the Indian subcontinent. The present study uses biome specific ET data derived from NOAA satellite's advanced very high resolution radiometer to investigate the trends and variability in ET over India from 1983 to 2006. Trend analysis using the non-parametric Mann-Kendall test showed that the domain average ET decreased during the period at a rate of 0.22 mm year^{-1}. A strong decreasing trend (m = -1.75 mm year^{-1}, F = 17.41, P 0.01) was observed in forest regions. Seasonal analyses indicated a decreasing trend during southwest summer monsoon (m= -0.320 mm season^{-1} year^{-1}) and post-monsoon period (m= -0.188 mm season^{-1 } year^{-1}). In contrast, an increasing trend was observed during northeast winter monsoon (m = 0.156 mm season^{-1 } year^{-1}) and pre-monsoon (m = 0.068 mm season^{-1 } year^{-1}) periods. Despite an overall net decline in the country, a considerable increase ( 4 mm year^{-1}) was observed over arid and semi-arid regions. Grid level correlation with various climatic parameters exhibited a strong positive correlation (r >0.5) of ET with soil moisture and precipitation over semi-arid and arid regions, whereas a negative correlation (r -0.5) occurred with temperature and insolation in dry regions of western India. The results of this analysis are useful for understanding regional ET dynamics and its relationship with various climatic parameters over India. Future studies on the effects of ET changes on the hydrological cycle, carbon cycle, and energy partitioning are needed to account for the feedbacks to the climate.

On the relationship between ecosystem-scale hyperspectral reflectance and CO2 exchange in European mountain grasslands

NASA Astrophysics Data System (ADS)

Balzarolo, M.; Vescovo, L.; Hammerle, A.; Gianelle, D.; Papale, D.; Tomelleri, E.; Wohlfahrt, G.

2015-05-01

In this paper we explore the skill of hyperspectral reflectance measurements and vegetation indices (VIs) derived from these in estimating carbon dioxide (CO2) fluxes of grasslands. Hyperspectral reflectance data, CO2 fluxes and biophysical parameters were measured at three grassland sites located in European mountain regions using standardized protocols. The relationships between CO2 fluxes, ecophysiological variables, traditional VIs and VIs derived using all two-band combinations of wavelengths available from the whole hyperspectral data space were analysed. We found that VIs derived from hyperspectral data generally explained a large fraction of the variability in the investigated dependent variables but differed in their ability to estimate midday and daily average CO2 fluxes and various derived ecophysiological parameters. Relationships between VIs and CO2 fluxes and ecophysiological parameters were site-specific, likely due to differences in soils, vegetation parameters and environmental conditions. Chlorophyll and water-content-related VIs explained the largest fraction of variability in most of the dependent variables. Band selection based on a combination of a genetic algorithm with random forests (GA-rF) confirmed that it is difficult to select a universal band region suitable across the investigated ecosystems. Our findings have major implications for upscaling terrestrial CO2 fluxes to larger regions and for remote- and proximal-sensing sampling and analysis strategies and call for more cross-site synthesis studies linking ground-based spectral reflectance with ecosystem-scale CO2 fluxes.

Characterizing CDOM Spectral Variability Across Diverse Regions and Spectral Ranges

NASA Astrophysics Data System (ADS)

Grunert, Brice K.; Mouw, Colleen B.; Ciochetto, Audrey B.

2018-01-01

Satellite remote sensing of colored dissolved organic matter (CDOM) has focused on CDOM absorption (aCDOM) at a reference wavelength, as its magnitude provides insight into the underwater light field and large-scale biogeochemical processes. CDOM spectral slope, SCDOM, has been treated as a constant or semiconstant parameter in satellite retrievals of aCDOM despite significant regional and temporal variabilities. SCDOM and other optical metrics provide insights into CDOM composition, processing, food web dynamics, and carbon cycling. To date, much of this work relies on fluorescence techniques or aCDOM in spectral ranges unavailable to current and planned satellite sensors (e.g., <300 nm). In preparation for anticipated future hyperspectral satellite missions, we take the first step here of exploring global variability in SCDOM and fit deviations in the aCDOM spectra using the recently proposed Gaussian decomposition method. From this, we investigate if global variability in retrieved SCDOM and Gaussian components is significant and regionally distinct. We iteratively decreased the spectral range considered and analyzed the number, location, and magnitude of fitted Gaussian components to understand if a reduced spectral range impacts information obtained within a common spectral window. We compared the fitted slope from the Gaussian decomposition method to absorption-based indices that indicate CDOM composition to determine the ability of satellite-derived slope to inform the analysis and modeling of large-scale biogeochemical processes. Finally, we present implications of the observed variability for remote sensing of CDOM characteristics via SCDOM.

Seasonal and Regional Variability in North Pacific Upper-Ocean Turbulence

NASA Astrophysics Data System (ADS)

Najjar, R.; Creedon, R.; Cronin, M. F.

2016-02-01

Turbulent diffusion at marine mixed layer base (MLB) plays a fundamental role in the transport of energy between the upper and abyssal ocean. Recent investigations of North Pacific mooring data at Ocean Climate Stations (OCS) Papa (50.1N,144.9W) and KEO (32.3N,144.6E) suggest seasonal and regional variability in thermal diffusivity (κT). In this investigation, it is hypothesized that these observed differences in κT are directly associated with synoptic variability in net surface heat flux (Q0), surface wind stress (τ), mixed layer depth (h), and density stratification at MLB (∂zσ|-h). To test this hypothesis, daily-averaged time series of κT are regressed against those of Q0, τ, h, and ∂zσ|-h at both Papa and KEO over a six year time period (2007-2013). Seasonality of each time series is removed before regression to capture synoptic variability of each variable. Preliminary results of the regression analysis suggest statistically significant correlations between κT and all forcing parameters at both mooring sites. These correlations have well-determined orders of magnitude and signs consistent with the hypothesis. As a result, differences in κT between Papa and KEO may be recast in terms of differences in their correlation coefficients. In order to continue investigation of these parameters and their effects on mean seasonal differences between the two regions, these results will be compared with turbulence predicted by the K-Profile Parameterization ocean turbulence model.

Regulation of eutrophication susceptibility in oligohaline zones of a northern Gulf of Mexico estuary, Mobile Bay, Alabama

EPA Science Inventory

Variability in estuarine eutrophication susceptibility to nutrinets was examined in a comparative empirical analysis of 7 oligohaline tidal river regions. Eutrophication response, in terms of phytoplankton biomass (chlorophylla), was related to estuarine mixing times scales and ...

Microbial, physical and chemical properties of irrigation water in rice fields of Southern Brazil.

PubMed

Reche, Maria Helena L R; Machado, Vilmar; Saul, Danilo A; Macedo, Vera R M; Marcolin, Elio; Knaak, Neiva; Fiuza, Lidia M

2016-03-01

This paper presents the results of the statistical analysis of microbiological, physical and chemical parameters related to the quality of the water used in rice fields in Southern Brazil. Data were collected during three consecutive crop years, within structure of a comprehensive monitoring program. The indicators used were: potential hydrogen, electrical conductivity, turbidity, nitrogen, phosphorus, potassium, calcium, total and fecal coliforms. Principal Component and Discriminant Analysis showed consistent differences between the water irrigation and drainage, as the temporal variation demonstrated a clear reduction in the concentration of most of the variables analyzed. The pattern of this reduction is not the same in the two regions - that is, the importance of each of the different variables in the observed differentiation is modified in two locations. These results suggested that the variations in the water quality utilized for rice irrigation was influenced by certain specific aspects of each rice region in South Brazilian - such as anthropic action or soil/climate conditions in each hydrographic basin.

Southern Arizona hydroclimate over the last 3000 years: a comparison of speleothem elemental data and climate model simulations

NASA Astrophysics Data System (ADS)

King, J.; Harrington, M. D.; Cole, J. E.; Drysdale, R.; Woodhead, J. D.; Fasullo, J.; Stevenson, S.; Otto-Bliesner, B. L.; Overpeck, J. T.; Edwards, R. L.; Henderson, G. M.

2017-12-01

Understanding long-term hydroclimate is particularly important in semiarid regions where prolonged droughts may be exacerbated by a warming climate. In many regions, speleothem trace elements correlate with regional wet and dry climate signals. In the drought-prone Southwestern US (SW), wet and dry episodes are strongly influenced by seasonal changes in atmospheric circulation and teleconnections to remote forcing. Here, we address the need for seasonal moisture reconstructions using paleoclimate and climate model approaches. First, we present a high-resolution (sub-annual) record of speleothem trace elements spanning the last 3000 years from Fort Huachuca Cave, AZ, to investigate the variability of regional seasonal precipitation and sustained regional droughts. In a principal component (PC) analysis of the speleothem, trace elements associated with wet (Sr, Ba) and dry (P, Y, Zn) episodes load strongly and inversely, and the associated PC signals correlate with local gridded precipitation data over the last 50 years (R > 0.6, p < 0.1). These results suggest that the elemental signals provide a seasonal moisture record for Southern Arizona. We use the record to examine the frequency and timing of extreme droughts in the region and compare the speleothem record's frequency domain characteristics with other regional moisture records and with climate model output. The speleothem record demonstrates strong low-frequency variability with pronounced multi-decadal dry periods, a feature notably lacking in drought metrics from simulations of the last millennium. We also examine the seasonal SW precipitation response to modes of climate variability and external forcings, including volcanic eruptions, in both the speleothem record and the Community Earth System Model's Last Millennium Ensemble (CESM-LME). Notably, ENSO and volcanic forcing have a discernable effect on SW seasonal precipitation in model simulations, particularly when the two processes combine to shift the position of the ITCZ. This integrated analysis of paleodata with climate model results will help us identify and explain discrepancies between these information sources and improve stakeholders' ability to anticipate and prepare for future drought.

The impact of Southern Atlantic moisture source in the precipitation regime of Sahel and Brazilian Nordeste using lagrangian models

NASA Astrophysics Data System (ADS)

Drumond, A.; Nieto, R.; Gimeno, L.; Ambrizzi, T.; Trigo, R.

2009-04-01

The socio-economical problems related to the severe droughts observed over Brazilian "Nordeste" and Sahel are well known nowadays. Several studies have showed that the precipitation regimes over these regions are influenced by the Inter Tropical Convergence Zone (ITCZ) variability, which can be related with the climatic variations observed in the South and North Tropical Atlantic basins. However, a climatological detailed assessment of the annual cycle of the oceanic moisture contribution to both these regions is still needed in order to get a better understanding of their precipitation regimes and variability. To answer this question, a climatological seasonal analysis of the moisture supply from the South Atlantic to the precipitation in the "Nordeste" and Sahel was performed using a new Lagrangian method of diagnosis which identifies the humidity contributions to the moisture budget over a region. The applied methodology computes budgets of evaporation minus precipitation by calculating changes in the specific humidity along forward-trajectories for the following 10 days. In order to take into account distinct regional contributions we have divided the South Atlantic basin in several latitudinal bands (with a 5° width), and all air-masses residing over each region were tracked forward using the available 5-year dataset (2000-2004). For the Sahel, the preliminary results suggest that the oceanic band northwards 10 degrees south acts as a moisture source for the precipitation along the year and its contribution reaches the maximum during the austral winter, probably related to the ITCZ annual migration over the region. On the other hand, the precipitation over "Nordeste" can be better related to air masses emanating from the oceanic bands between 10 and 20 degrees south. However the response over the region is very heterogeneous spatially and temporally probably due to the high variability of the local climate characteristics. In order to clarify dynamically the origin of the moisture that reaches the semi-arid "Nordeste", a backward-trajectories analysis is being conducted and the results will be presented elsewhere.

New insights into the use of stable water isotopes at the northern Antarctic Peninsula as a tool for regional climate studies

NASA Astrophysics Data System (ADS)

Fernandoy, Francisco; Tetzner, Dieter; Meyer, Hanno; Gacitúa, Guisella; Hoffmann, Kirstin; Falk, Ulrike; Lambert, Fabrice; MacDonell, Shelley

2018-03-01

Due to recent atmospheric and oceanic warming, the Antarctic Peninsula is one of the most challenging regions of Antarctica to understand in terms of both local- and regional-scale climate signals. Steep topography and a lack of long-term and in situ meteorological observations complicate the extrapolation of existing climate models to the sub-regional scale. Therefore, new techniques must be developed to better understand processes operating in the region. Isotope signals are traditionally related mainly to atmospheric conditions, but a detailed analysis of individual components can give new insight into oceanic and atmospheric processes. This paper aims to use new isotopic records collected from snow and firn cores in conjunction with existing meteorological and oceanic datasets to determine changes at the climatic scale in the northern extent of the Antarctic Peninsula. In particular, a discernible effect of sea ice cover on local temperatures and the expression of climatic modes, especially the Southern Annular Mode (SAM), is demonstrated. In years with a large sea ice extension in winter (negative SAM anomaly), an inversion layer in the lower troposphere develops at the coastal zone. Therefore, an isotope-temperature relationship (δ-T) valid for all periods cannot be obtained, and instead the δ-T depends on the seasonal variability of oceanic conditions. Comparatively, transitional seasons (autumn and spring) have a consistent isotope-temperature gradient of +0.69 ‰ °C-1. As shown by firn core analysis, the near-surface temperature in the northern-most portion of the Antarctic Peninsula shows a decreasing trend (-0.33 °C year-1) between 2008 and 2014. In addition, the deuterium excess (dexcess) is demonstrated to be a reliable indicator of seasonal oceanic conditions, and therefore suitable to improve a firn age model based on seasonal dexcess variability. The annual accumulation rate in this region is highly variable, ranging between 1060 and 2470 kg m-2 year-1 from 2008 to 2014. The combination of isotopic and meteorological data in areas where data exist is key to reconstruct climatic conditions with a high temporal resolution in polar regions where no direct observations exist.

Regional co-variability of spatial and temporal soil moisture-precipitation coupling in North Africa: an observational perspective

NASA Astrophysics Data System (ADS)

Petrova, Irina Y.; van Heerwaarden, Chiel C.; Hohenegger, Cathy; Guichard, Françoise

2018-06-01

The magnitude and sign of soil moisture-precipitation coupling (SMPC) is investigated using a probability-based approach and 10 years of daily microwave satellite data across North Africa at a 1° horizontal scale. Specifically, the co-existence and co-variability of spatial (i.e. using soil moisture gradients) and temporal (i.e. using soil moisture anomaly) soil moisture effects on afternoon rainfall is explored. The analysis shows that in the semi-arid environment of the Sahel, the negative spatial and the negative temporal coupling relationships do not only co-exist, but are also dependent on one another. Hence, if afternoon rain falls over temporally drier soils, it is likely to be surrounded by a wetter environment. Two regions are identified as SMPC hot spots. These are the south-western part of the domain (7-15° N, 10° W-7° E), with the most robust negative SMPC signal, and the South Sudanese region (5-13° N, 24-34° E). The sign and significance of the coupling in the latter region is found to be largely modulated by the presence of wetlands and is susceptible to the number of long-lived propagating convective systems. The presence of wetlands and an irrigated land area is found to account for about 30 % of strong and significant spatial SMPC in the North African domain. This study provides the first insight into regional variability of SMPC in North Africa, and supports the potential relevance of mechanisms associated with enhanced sensible heat flux and mesoscale variability in surface soil moisture for deep convection development.

Multi-scale linkages of winter drought variability to ENSO and the Arctic Oscillation: A case study in Shaanxi, North China

NASA Astrophysics Data System (ADS)

Liu, Zhiyong; Zhang, Xin; Fang, Ruihong

2018-02-01

Understanding the potential connections between climate indices such as the El Niño-Southern Oscillation (ENSO) and Arctic Oscillation (AO) and drought variability will be beneficial for making reasonable predictions or assumptions about future regional droughts, and provide valuable information to improve water resources planning and design for specific regions of interest. This study is to examine the multi-scale relationships between winter drought variability over Shaanxi (North China) and both ENSO and AO during the period 1960-2009. To accomplish this, we first estimated winter dryness/wetness conditions over Shaanxi based on the self-calibrating Palmer drought severity index (PDSI). Then, we identified the spatiotemporal variability of winter dryness/wetness conditions in the study area by using the empirical orthogonal function (EOF). Two primary sub-regions of winter dryness/wetness conditions across Shaanxi were identified. We further examined the periodical oscillations of dryness/wetness conditions and the multi-scale relationships between dryness/wetness conditions and both ENSO and AO in winter using wavelet analysis. The results indicate that there are inverse multi-scale relations between winter dryness/wetness conditions and ENSO (according to the wavelet coherence) for most of the study area. Moreover, positive multi-scale relations between winter dryness/wetness conditions and AO are mainly observed. The results could be beneficial for making reasonable predictions or assumptions about future regional droughts and provide valuable information to improve water resources planning and design within this study area. In addition to the current study area, this study may also offer a useful reference for other regions worldwide with similar climate conditions.

THESEUS: maximum likelihood superpositioning and analysis of macromolecular structures.

PubMed

Theobald, Douglas L; Wuttke, Deborah S

2006-09-01

THESEUS is a command line program for performing maximum likelihood (ML) superpositions and analysis of macromolecular structures. While conventional superpositioning methods use ordinary least-squares (LS) as the optimization criterion, ML superpositions provide substantially improved accuracy by down-weighting variable structural regions and by correcting for correlations among atoms. ML superpositioning is robust and insensitive to the specific atoms included in the analysis, and thus it does not require subjective pruning of selected variable atomic coordinates. Output includes both likelihood-based and frequentist statistics for accurate evaluation of the adequacy of a superposition and for reliable analysis of structural similarities and differences. THESEUS performs principal components analysis for analyzing the complex correlations found among atoms within a structural ensemble. ANSI C source code and selected binaries for various computing platforms are available under the GNU open source license from http://monkshood.colorado.edu/theseus/ or http://www.theseus3d.org.

Climatic Redistribution of Canada's Water Resources (CROCWR): An analysis of spatial and temporal hydrological trends and patterns in western Canada

NASA Astrophysics Data System (ADS)

Bawden, A. J.; Burn, D. H.; Prowse, T. D.

2012-12-01

Climate variability and change can have profound impacts on the hydrologic regime of a watershed. These effects are likely to be especially severe in regions particularly sensitive to changes in climate, such as the Canadian north, or when there are other stresses on the hydrologic regime, such as may occur when there are large withdrawals from, or land-use changes within, a watershed. A recent report of the Intergovernmental Panel on Climate Change (IPCC) stressed that future climate is likely to accelerate the hydrologic cycle and hence may affect water security in certain locations. For some regions, this will mean enhanced access to water resources, but because the effects will not be spatially uniform, other regions will experience reduced access. Understanding these patterns is critical for water managers and government agencies in western Canada - an area of highly contrasting hydroclimatic regimes and overlapping water-use and jurisdictional borders - as adapting to climate change may require reconsideration of inter-regional transfers and revised allocation of water resources to competing industrial sectors, including agriculture, hydroelectric production, and oil and gas. This research involves the detection and examination of spatial and temporal streamflow trends in western Canadian rivers as a response to changing climatic factors, including temperature, precipitation, snowmelt, and the synoptic patterns controlling these drivers. The study area, known as the CROCWR region, extends from the Pacific coast of British Columbia as far east as the Saskatchewan-Manitoba border and from the Canada-United States international border through a large portion of the Northwest Territories. This analysis examines hydrologic trends in monthly and annual streamflow for a collection of 34 hydrometric gauging stations believed to adequately represent the overall effects of climate variability and change on flows in western Canada by means of the Mann-Kendall non-parametric trend test. Large-scale spatial patterns are determined through examination of trends and contrasts between upper and lower reaches of individual sub-basins, as well as via analysis of streamflow redistributions within the CROCWR region as an entirety (i.e. north, south, east and/or west-moving patterns). Results are used to predict future implications of hydroclimatic variability and change on western Canada's water resources and recommend measures to be taken by water managers in response to these changes. This research is part of a larger hydroclimatic study that includes an analysis of the climatic drivers contributing to shifting flow regimes in western Canada as well as a study of the controlling synoptic patterns and teleconnections associated with changes in these driving forces.

Spatio-temporal analysis of annual rainfall in Crete, Greece

NASA Astrophysics Data System (ADS)

Varouchakis, Emmanouil A.; Corzo, Gerald A.; Karatzas, George P.; Kotsopoulou, Anastasia

2018-03-01

Analysis of rainfall data from the island of Crete, Greece was performed to identify key hydrological years and return periods as well as to analyze the inter-annual behavior of the rainfall variability during the period 1981-2014. The rainfall spatial distribution was also examined in detail to identify vulnerable areas of the island. Data analysis using statistical tools and spectral analysis were applied to investigate and interpret the temporal course of the available rainfall data set. In addition, spatial analysis techniques were applied and compared to determine the rainfall spatial distribution on the island of Crete. The analysis presented that in contrast to Regional Climate Model estimations, rainfall rates have not decreased, while return periods vary depending on seasonality and geographic location. A small but statistical significant increasing trend was detected in the inter-annual rainfall variations as well as a significant rainfall cycle almost every 8 years. In addition, statistically significant correlation of the island's rainfall variability with the North Atlantic Oscillation is identified for the examined period. On the other hand, regression kriging method combining surface elevation as secondary information improved the estimation of the annual rainfall spatial variability on the island of Crete by 70% compared to ordinary kriging. The rainfall spatial and temporal trends on the island of Crete have variable characteristics that depend on the geographical area and on the hydrological period.

Focused maternity care in Ghana: results of a cluster analysis.

PubMed

Ayanore, Martin Amogre; Pavlova, Milena; Groot, Wim

2016-08-17

Ghana missed out in attaining Millennium Development Goal 5 in 2015. The provision of adequate prenatal and postnatal care remains problematic, with poor evidence on women's views on met and unmet maternity care needs across all regions in Ghana. This paper examines maternal care utilization in Ghana by applying WHO indicators for focused maternal care utilization. Two-step cluster analysis segregated women into groups based on the components of the maternity care used. Using cluster membership variables as dependent variables, we applied multinomial and binary regression to examine associations of care use with individual, household and regional characteristics. We identified three patterns of care use: adequate, less and least adquate care. The presence of a female and skilled provider is an indicator of adequate care. Women in Volta, Upper West, Northern and Western regions received less adequate care compared with other regions. Supply-related factors (drugs availability, distance/transport, health insurance ownership, rural residence) were associated with adequacy of care. The lack of female autonomy, widowed/divorced women, age and parity were associated with less adequate care. Care patterns were distinctively associated with the quality of health care support (skilled and female attendant) instead of with the number of visits made to the facility. Across regions and within rural settings, disparities exist, often compounded by supply-related factors. Efforts to address skilled workforce shortages, greater accountability for quality and equity, improving women motivation for care seeking and active participation are important for maternity care in Ghana.

Measuring phenological variability from satellite imagery

USGS Publications Warehouse

Reed, Bradley C.; Brown, Jesslyn F.; Vanderzee, D.; Loveland, Thomas R.; Merchant, James W.; Ohlen, Donald O.

1994-01-01

Vegetation phenological phenomena are closely related to seasonal dynamics of the lower atmosphere and are therefore important elements in global models and vegetation monitoring. Normalized difference vegetation index (NDVI) data derived from the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer (AVHRR) satellite sensor offer a means of efficiently and objectively evaluating phenological characteristics over large areas. Twelve metrics linked to key phenological events were computed based on time-series NDVI data collected from 1989 to 1992 over the conterminous United States. These measures include the onset of greenness, time of peak NDVI, maximum NDVI, rate of greenup, rate of senescence, and integrated NDVI. Measures of central tendency and variability of the measures were computed and analyzed for various land cover types. Results from the analysis showed strong coincidence between the satellite-derived metrics and predicted phenological characteristics. In particular, the metrics identified interannual variability of spring wheat in North Dakota, characterized the phenology of four types of grasslands, and established the phenological consistency of deciduous and coniferous forests. These results have implications for large- area land cover mapping and monitoring. The utility of re- motely sensed data as input to vegetation mapping is demonstrated by showing the distinct phenology of several land cover types. More stable information contained in ancillary data should be incorporated into the mapping process, particularly in areas with high phenological variability. In a regional or global monitoring system, an increase in variability in a region may serve as a signal to perform more detailed land cover analysis with higher resolution imagery.

Seasonal Variability in European Radon Measurements

NASA Astrophysics Data System (ADS)

Groves-Kirkby, C. J.; Denman, A. R.; Phillips, P. S.; Crockett, R. G. M.; Sinclair, J. M.

2009-04-01

In temperate climates, domestic radon concentration levels are generally seasonally dependent, the level in the home reflecting the convolution of two time-dependent functions. These are the source soil-gas radon concentration itself, and the principal force driving radon into the building from the soil, namely the pressure-difference between interior and exterior environment. While the meteorological influence can be regarded as relatively uniform on a European scale, its variability being defined largely by the influence of North-Atlantic weather systems, soil-gas radon is generally more variable as it is essentially geologically dependent. Seasonal variability of domestic radon concentration can therefore be expected to exhibit geographical variability, as is indeed the case. To compensate for the variability of domestic radon levels when assessing the long term radon health risks, the results of individual short-term measurements are generally converted to equivalent mean annual levels by application of a Seasonal Correction Factor (SCF). This is a multiplying factor, typically derived from measurements of a large number of homes, applied to the measured short-term radon concentration to provide a meaningful annual mean concentration for dose-estimation purposes. Following concern as to the universal applicability of a single SCF set, detailed studies in both the UK and France have reported location-specific SCF sets for different regions of each country. Further results indicate that SCFs applicable to the UK differ significantly from those applicable elsewhere in Europe and North America in both amplitude and phase, supporting the thesis that seasonal variability in indoor radon concentration cannot realistically be compensated for by a single national or international SCF scheme. Published data characterising the seasonal variability of European national domestic radon concentrations, has been collated and analysed, with the objective of identifying correlations between published datasets and local geographic/geological conditions. Available data included regional SCF figures from the United Kingdom and from France, together with nationally-consolidated results from a number of other European countries. Analysis of this data shows significant variability between different countries and from region to region within those countries where regional data is available. Overall, radon-rich sedimentary geologies, particularly high porosity limestones etc., exhibit high seasonal variation, while radon-rich igneous geologies demonstrate relatively constant, albeit somewhat higher, radon concentration levels. Examples of the former can be found in the Pennines and South Downs in England, Languedoc and Brittany in France. Greatest variability is found in Switzerland, still subject to the ongoing Alpine orogeny, where the inhabited part of the country is largely overlain with recently-deposited light, porous sediments. Low-variability high-radon regions include the granite-rich Cornwall/Devon peninsular in England, and Auvergne and the Ardennes in France, all components of the Devonian-Carboniferous Hercynian belt, which extends from the Iberian peninsular through South-West Ireland and South-West England to France and Germany.

Towards the Rational Design of a Candidate Vaccine against Pregnancy Associated Malaria: Conserved Sequences of the DBL6ε Domain of VAR2CSA

PubMed Central

Badaut, Cyril; Bertin, Gwladys; Rustico, Tatiana; Fievet, Nadine; Massougbodji, Achille; Gaye, Alioune; Deloron, Philippe

2010-01-01

Background Placental malaria is a disease linked to the sequestration of Plasmodium falciparum infected red blood cells (IRBC) in the placenta, leading to reduced materno-fetal exchanges and to local inflammation. One of the virulence factors of P. falciparum involved in cytoadherence to chondroitin sulfate A, its placental receptor, is the adhesive protein VAR2CSA. Its localisation on the surface of IRBC makes it accessible to the immune system. VAR2CSA contains six DBL domains. The DBL6ε domain is the most variable. High variability constitutes a means for the parasite to evade the host immune response. The DBL6ε domain could constitute a very attractive basis for a vaccine candidate but its reported variability necessitates, for antigenic characterisations, identifying and classifying commonalities across isolates. Methodology/Principal Findings Local alignment analysis of the DBL6ε domain had revealed that it is not as variable as previously described. Variability is concentrated in seven regions present on the surface of the DBL6ε domain. The main goal of our work is to classify and group variable sequences that will simplify further research to determine dominant epitopes. Firstly, variable sequences were grouped following their average percent pairwise identity (APPI). Groups comprising many variable sequences sharing low variability were found. Secondly, ELISA experiments following the IgG recognition of a recombinant DBL6ε domain, and of peptides mimicking its seven variable blocks, allowed to determine an APPI cut-off and to isolate groups represented by a single consensus sequence. Conclusions/Significance A new sequence approach is used to compare variable regions in sequences that have extensive segmental gene relationship. Using this approach, the VAR2CSA DBL6 domain is composed of 7 variable blocks with limited polymorphism. Each variable block is composed of a limited number of consensus types. Based on peptide based ELISA, variable blocks with 85% or greater sequence identity are expected to be recognized equally well by antibody and can be considered the same consensus type. Therefore, the analysis of the antibody response against the classified small number of sequences should be helpful to determine epitopes. PMID:20585655

Sub-Seasonal Variability of Tropical Rainfall Observed by TRMM and Ground-based Polarimetric Radar

NASA Astrophysics Data System (ADS)

Dolan, Brenda; Rutledge, Steven; Lang, Timothy; Cifelli, Robert; Nesbitt, Stephen

2010-05-01

Studies of tropical precipitation characteristics from the TRMM-LBA and NAME field campaigns using ground-based polarimetric S-band data have revealed significant differences in microphysical processes occurring in the various meteorological regimes sampled in those projects. In TRMM-LMA (January-February 1999 in Brazil; a TRMM ground validation experiment), variability is driven by prevailing low-level winds. During periods of low-level easterlies, deeper and more intense convection is observed, while during periods of low-level westerlies, weaker convection embedded in widespread stratiform precipitation is common. In the NAME region (North American Monsoon Experiment, summer 2004 along the west coast of Mexico), strong terrain variability drives differences in precipitation, with larger drops and larger ice mass aloft associated with convection occurring over the coastal plain compared to convection over the higher terrain of the Sierra Madre Occidental, or adjacent coastal waters. Comparisons with the TRMM precipitation radar (PR) indicate that such sub-seasonal variability in these two regions are not well characterized by the TRMM PR reflectivity and rainfall statistics. TRMM PR reflectivity profiles in the LBA region are somewhat lower than S-Pol values, particularly in the more intense easterly regime convection. In NAME, mean reflectivities are even more divergent, with TRMM profiles below those of S-Pol. In both regions, the TRMM PR does not capture rain rates above 80 mm hr-1 despite much higher rain rates estimated from the S-Pol polarimetric data, and rain rates are generally lower for a given reflectivity from TRMM PR compared to S-Pol. These differences between TRMM PR and S-Pol may arise from the inability of Z-R relationships to capture the full variability of microphysical conditions or may highlight problems with TRMM retrievals over land. In addition to the TRMM-LBA and NAME regions, analysis of sub-seasonal precipitation variability and comparison of TRMM PR statistics with ground-based radar has been extended to other regions of the globe. The Australian Bureau of Meteorology C-band polarimetric radar C-Pol has been collecting data in Darwin, Australia for over a decade. The Darwin region affords the opportunity to look at precipitation characteristics over land and ocean, as well as variability associated with monsoon and break periods over long periods of time. The polarimetric X-band radar XPort was stationed in West Africa at a field site in Benin during the 2006 and 2007 African monsoon periods, where differences in rainfall associated with African Easterly Wave (AEW) passages and non-AEW periods can be examined. Similar comparisons between TRMM PR and ground based polarimetric radars will also be reported for these regions.

Analysis of Atmospheric Composition and Tropospheric Variability With Integrated Open- Path and Ground-Based Solar Infrared Absorption Spectroscopy

NASA Astrophysics Data System (ADS)

Steill, J. D.; Compton, R. N.; Hager, J. S.

2006-12-01

Ground-based solar infrared absorption spectroscopy coupled with open-path spectroscopy provides a means for analysis of the highly variable contribution of the boundary layer to problems of radiative transfer and atmospheric chemistry. This is of particular importance in geographic regions of significant local anthropogenic influence and large tropospheric fluctuations in general. A Bomem DA8 FT-IR integrated with a sun-tracking and open-path system (~0.5 km) is located at The University of Tennessee, in downtown Knoxville and near The Great Smoky Mountains National Park, an area known for problematic air quality. From atmospheric absorption spectra, boundary layer concentrations as well as total column abundances and vertical concentration profiles are derived. A record of more than 1000 solar-sourced atmospheric spectra covering a period greater than three years in duration is under analysis to characterize the limit of precision in total column abundance determinations for many gases such as O3, CO, CH4, N2O, HF and CO2. Initial efforts using atmospheric O2 as a calibration indicate the solar-sourced spectra may not meet the precision required for the highly accurate atmospheric CO2 quantification by such global efforts as the OCO and NDSC. However, the determined variability of CO2 and other gas concentrations is statistically significant and is indicative of local concentration fluxes pertinent to the regional atmospheric chemistry. This is therefore an important data record in the southeastern United States, a somewhat under- sampled geographic region. In addition to providing a means to improve the analysis of solar spectra, the open-path data is useful for elucidation of seasonal and diurnal trends in the trace gas concentrations. This provides an urban air quality monitor in addition to improving the description of the total atmospheric composition, as the open-path system is stable and permanent.

Heat wave phenomenon in southern Slovakia: long-term changes and variability of daily maximum air temperature in Hurbanovo within the 1901-2009 period

NASA Astrophysics Data System (ADS)

Pecho, J.; Výberči, D.; Jarošová, M.; Å¥Astný, P. Å.

2010-09-01

Analysis of long-term changes and temporal variability of heat waves incidence in the region of southern Slovakia within the 1901-2009 periods is a goal of the presented contribution. It is expected that climate change in terms of global warming would amplify temporal frequency and spatial extension of extreme heat wave incidence in region of central Europe in the next few decades. The frequency of occurrence and amplitude of heat waves may be impacted by changes in the temperature regime. Heat waves can cause severe thermal environmental stress leading to higher hospital admission rates, health complications, and increased mortality. These effects arise because of one or more meteorology-related factors such as higher effective temperatures, sunshine, more consecutive hot days and nights, stagnation, increased humidity, increased pollutant emissions, and accelerated photochemical smog and particulate formation. Heat waves bring about higher temperatures, increased solar heating of buildings, inhibited ventilation, and a larger number of consecutive warm days and nights. All of these effects increase the thermal loads on buildings, reduce their ability to cool down, and increase indoor temperatures. The paper is focused to analysis of long-term and inter-decadal temporal variability of heat waves occurrence at meteorological station Hurbanovo (time-series of daily maximum air temperature available from at least 1901). We can characterize the heat waves by its magnitude and duration, hence both of these characteristics need to be investigated together using sophisticated statistical methods developed particularly for the analysis of extreme hydrological events. We investigated particular heat wave periods either from the severity point of view using HWI index. In the paper we also present the results of statistical analysis of daily maximum air temperature within 1901-2009 period. Apart from these investigation efforts we also focused on synoptic causes of heat wave incidence in connection with macro scale circulation patterns in central European region.

GANP regulates recruitment of AID to immunoglobulin variable regions by modulating transcription and nucleosome occupancy

PubMed Central

Singh, Shailendra Kumar; Maeda, Kazuhiko; Eid, Mohammed Mansour Abbas; Almofty, Sarah Ameen; Ono, Masaya; Pham, Phuong; Goodman, Myron F.; Sakaguchi, Nobuo

2013-01-01

Somatic hypermutation in B cells is initiated by activation-induced cytidine deaminase-catalyzed C→U deamination at immunoglobulin variable regions. Here we investigate the role of the germinal centre-associated nuclear protein (GANP) in enhancing the access of activation-induced cytidine deaminase (AID) to immunoglobulin variable regions. We show that the nuclear export factor GANP is involved in chromatin modification at rearranged immunoglobulin variable loci, and its activity requires a histone acetyltransferase domain. GANP interacts with the transcription stalling protein Spt5 and facilitates RNA Pol-II recruitment to immunoglobulin variable regions. Germinal centre B cells from ganp-transgenic mice showed a higher AID occupancy at the immunoglobulin variable region, whereas B cells from conditional ganp-knockout mice exhibit a lower AID accessibility. These findings suggest that GANP-mediated chromatin modification promotes transcription complex recruitment and positioning at immunoglobulin variable loci to favour AID targeting. PMID:23652018

Hierarchical analysis of cardiovascular risk factors in relation to the development of acute coronary syndromes, in different parts of Greece: the CARDIO2000 study.

PubMed

Panagiotakos, Demosthenes B; Pitsavos, Christos; Chrysohoou, Christine; Stefanadis, Christodoulos

2008-01-01

During 2000 to 2002, 700 men (59 +/- 10 years) and 148 women (65 +/- 9 years) patients with first event of an ACS were randomly selected from cardiology clinics of Greek regions. Afterwards, 1078 population-based, age-matched and sex-matched controls were randomly selected from the same hospitals. The frequency ratio between men and women in the case series of patients was about 4:1, in both south and north Greek areas. Hierarchical classification analysis showed that for north Greek areas family history of coronary heart disease, hypercholesterolemia, hypertension, diabetes (explained variability 35%), and less significantly, dietary habits, smoking, body mass index, and physical activity status (explained variability 4%) were associated with the development of ACS, whereas for south Greek areas hypercholesterolemia, family history of coronary heart disease, diabetes, smoking, hypertension, dietary habits, physical activity (explained variability 34%), and less significantly body mass index (explained variability <1%), were associated with the development of the disease.

Analysis of variance in investigations on anisotropy of Cu ore deposits

NASA Astrophysics Data System (ADS)

Namysłowska-Wilczyńska, B.

1986-10-01

The problem of variability of copper grades and ore thickness in the Lubin copper ore deposit in southwestern Poland is presented. Results of statistical analysis of variations of ledge parameters carried out for three exploited regions of the mine, representing different types of lithological profile show considerable differences. Variability of copper grades occurs in vertical profiles, as well as on extension of field (the copper-bearing series). Against the background of a complex, well-substantiated description of the spatial variability in the Lubin deposit, a methodology is presented that has been applied for the determination of homogeneous ore blocks. The method is a two-factorial (cross) analysis of variance with the special tests of Tukey, Scheffe and Duncan. Blocks of homogeneous sandstone ore have dimensions of up to 160,000 m2 and 60,000 m2 in the case of the Cu content parameter and 200,000 m2 and 10,000 m2 for the thickness parameter.

Local-scale models reveal ecological niche variability in amphibian and reptile communities from two contrasting biogeographic regions

PubMed Central

Santos, Xavier; Felicísimo, Ángel M.

2016-01-01

Ecological Niche Models (ENMs) are widely used to describe how environmental factors influence species distribution. Modelling at a local scale, compared to a large scale within a high environmental gradient, can improve our understanding of ecological species niches. The main goal of this study is to assess and compare the contribution of environmental variables to amphibian and reptile ENMs in two Spanish national parks located in contrasting biogeographic regions, i.e., the Mediterranean and the Atlantic area. The ENMs were built with maximum entropy modelling using 11 environmental variables in each territory. The contributions of these variables to the models were analysed and classified using various statistical procedures (Mann–Whitney U tests, Principal Components Analysis and General Linear Models). Distance to the hydrological network was consistently the most relevant variable for both parks and taxonomic classes. Topographic variables (i.e., slope and altitude) were the second most predictive variables, followed by climatic variables. Differences in variable contribution were observed between parks and taxonomic classes. Variables related to water availability had the larger contribution to the models in the Mediterranean park, while topography variables were decisive in the Atlantic park. Specific response curves to environmental variables were in accordance with the biogeographic affinity of species (Mediterranean and non-Mediterranean species) and taxonomy (amphibians and reptiles). Interestingly, these results were observed for species located in both parks, particularly those situated at their range limits. Our findings show that ecological niche models built at local scale reveal differences in habitat preferences within a wide environmental gradient. Therefore, modelling at local scales rather than assuming large-scale models could be preferable for the establishment of conservation strategies for herptile species in natural parks. PMID:27761304

Mapping CO2 emission in highly urbanized region using standardized microbial respiration approach

NASA Astrophysics Data System (ADS)

Vasenev, V. I.; Stoorvogel, J. J.; Ananyeva, N. D.

2012-12-01

Urbanization is a major recent land-use change pathway. Land conversion to urban has a tremendous and still unclear effect on soil cover and functions. Urban soil can act as a carbon source, although its potential for CO2 emission is also very high. The main challenge in analysis and mapping soil organic carbon (SOC) in urban environment is its high spatial heterogeneity and temporal dynamics. The urban environment provides a number of specific features and processes that influence soil formation and functioning and results in a unique spatial variability of carbon stocks and fluxes at short distance. Soil sealing, functional zoning, settlement age and size are the predominant factors, distinguishing heterogeneity of urban soil carbon. The combination of these factors creates a great amount of contrast clusters with abrupt borders, which is very difficult to consider in regional assessment and mapping of SOC stocks and soil CO2 emission. Most of the existing approaches to measure CO2 emission in field conditions (eddy-covariance, soil chambers) are very sensitive to soil moisture and temperature conditions. They require long-term sampling set during the season in order to obtain relevant results. This makes them inapplicable for the analysis of CO2 emission spatial variability at the regional scale. Soil respiration (SR) measurement in standardized lab conditions enables to overcome this difficulty. SR is predominant outgoing carbon flux, including autotrophic respiration of plant roots and heterotrophic respiration of soil microorganisms. Microbiota is responsible for 50-80% of total soil carbon outflow. Microbial respiration (MR) approach provides an integral CO2 emission results, characterizing microbe CO2 production in optimal conditions and thus independent from initial difference in soil temperature and moisture. The current study aimed to combine digital soil mapping (DSM) techniques with standardized microbial respiration approach in order to analyse and map CO2 emission and its spatial variability in highly urbanized Moscow region. Moscow region with its variability of bioclimatic conditions and high urbanization level (10 % from the total area) was chosen as an interesting case study. Random soil sampling in different soil zones (4) and land-use types (3 non-urban and 3 urban) was organized in Moscow region in 2010-2011 (n=242). Both topsoil (0-10 cm) and subsoil (10-150 cm) were included. MR for each point was analysed using standardized microbial (basal) respiration approach, including the following stages: 1) air dried soil samples were moisturised up to 55% water content and preincubated (7 days, 22° C) in a plastic bag with air exchange; 2) soil MR (in μg CO2-C g-1) was measured as the rate of CO2 production (22° C, 24 h) after incubating 2g soil with 0.2 μl distilled water; 3) the MR results were used to estimate CO2 emission (kg C m-2 yr-1). Point MR and CO2 emission results obtained were extrapolated for the Moscow region area using regression model. As a result, two separate CO2 maps for topsoil and subsoil were created. High spatial variability was demonstrated especially for the urban areas. Thus standardized MR approach combined with DSM techniques provided a unique opportunity for spatial analysis of soil carbon temporal dynamics at the regional scale.

Did Child Restraint Laws Globally Converge? Examining 40 Years of Policy Diffusion.

PubMed

Nazif-Muñoz, José Ignacio

2015-01-01

The objective of the current study is to determine what factors have been associated with the global adoption of mandatory child restraint laws (ChRLs) since 1975. In order to determine what factors explained the global adoption of mandatory ChRLs, Weibull models were analyzed. To carry out this analysis, 170 countries were considered and the time risk corresponded to 5,146 observations for the period 1957-2013. The dependent variable was first time to adopt a ChRL. Independent variables representing global factors were the World Health Organization (WHO) and World Bank's (WB) road safety global campaign; the Geneva Convention on Road Traffic; and the United Nation's (UN) 1958 Vehicle Agreement. Independent variables representing regional factors were the creation of the European Transport Safety Council and being a Commonwealth country. Independent variables representing national factors were population; gross domestic product (GDP) per capita; political violence; existence of road safety nongovernmental organizations (NGOs); and existence of road safety agencies. Urbanization served as a control variable. To examine regional dynamics, Weibull models for Africa, Asia, Europe, North America, Latin America, the Caribbean, and the Commonwealth were also carried out. Empirical estimates from full Weibull models suggest that 2 global factors and 2 national factors are significantly associated with the adoption of this measure. The global factors explaining adoption are the WHO and WB's road safety global campaign implemented after 2004 (P <.01), and the UN's 1958 Vehicle Agreement (P <.001). National factors were GDP (P <.01) and existence of road safety agencies (P <.05). The time parameter ρ for the full Weibull model was 1.425 (P <.001), suggesting that the likelihood of ChRL adoption increased over the observed period of time, confirming that the diffusion of this policy was global. Regional analysis showed that the UN's Convention on Road Traffic was significant in Asia, the creation of the European Transport Safety Council was significant in Europe and North America, and the global campaign was in Africa. In Commonwealth and European and North American countries, the existence of road safety agencies was also positively associated with ChRL adoption. Results of the world models suggest that the WHO and WB's global road safety campaign was effective in disseminating ChRLs after 2004. Furthermore, regions such as Asia and Europe and North America were early adopters since specific regional and national characteristics anticipated the introduction of this policy before 2004. In this particular case, the creation of the European Transport Safety Council was fundamental in promoting ChRLs. Thus, in order to introduce conditions to more rapidly diffuse road safety measures across lagging regions, the maintenance of global efforts and the creation of road safety regional organizations should be encouraged. Lastly, the case of ChRL convergence illustrates how mechanisms of global and regional diffusion need to be analytically differentiated in order better to assess the process of policy diffusion.

IMPACT OF TRMM PRECIPITATION ON CPTEC’S RPSAS ANALYSIS

NASA Astrophysics Data System (ADS)

Herdies, D. L.; Bastarz, C. F.; Fernandez, J. P.

2009-12-01

In this work a data assimilation study was performed to assess the impact of estimated precipitation from TRMM (Tropical Rainfall Measuring Mission) on the CPTEC (Centro de Previsão de Tempo e Estudos Climáticos at Brasil) RPSAS (Regional Physical-space Statistical Analysis System) analyses and the Eta model forecast over the region of La Plata Basin, during a case o MCC (Mesoscale Convective Complex) occurred between 22th and 23th January 2003. The data assimilation system RPSAS and the mesoscale regional Eta model (both with 20km of spatial resolution) were run together with and without the TRMM precipitation. Is this study the assimilation of precipitation is basically a nudging process and is performed during the first guess stage by the Eta model, like in the NCEP (National Centers for Environmental Predictions) EDAS (Eta Data Assimilation System) precipitation data assimilation. During this process the model adjusts the precipitation by comparing, at which grid point and at which time step, the model precipitation against the TRMM precipitation. Doing this some adjustments are made on the latent heat vertical profile, water vapor mixing ratio and relative humidity, by considering the Betts-Miller-Janjic convective parameterization. On the next step, the RPSAS produces an analysis which covers most of the South America and the adjacent oceans. From this analysis the Eta model produces 6h, 12h, 18h and 24h forecast. Data collected from the SALLJEX (South America Low Level Jet EXperiment) was used to compare the forecasts of the model and the CPTEC 40km Regional Reanalysis was used to compare with the RPSAS analyses. Some preliminary results show that the precipitation assimilation improves the first hours of the forecast (typically 6h). The variables verified were the zonal and meridional wind, geopotential height and the precipitation. The convective precipitation fields were improved, mainly over the 6h forecast. This is an important improvement because the first guess field will serve as an analysis of the next forecast window. Also were noticed that the mean error for those variables was reduced (principally for the zonal wind). This reveals that with an improved first guess field, the model was able to detect the MCC occurred in the north of Argentina, due to the improved representation of the winds fields (direction and intensity), pressure and the surface variables.

Patterns in the Physical, Chemical, and Biological Composition of Icelandic Lakes and the Dominant Factors Controlling Variability Across Watersheds

NASA Astrophysics Data System (ADS)

Greco, A.; Strock, K.; Edwards, B. R.

2017-12-01

Fourteen lakes were sampled in the southern and western area of Iceland in June of 2017. The southern systems, within the Eastern Volcanic Zone, have minimal soil development and active volcanoes that produce ash input to lakes. Lakes in the Western Volcanic Zone were more diverse and located in older bedrock with more extensively weathered soil. Physical variables (temperature, oxygen concentration, and water clarity), chemical variables (pH, conductivity, dissolved and total nitrogen and phosphorus concentrations, and dissolved organic carbon concentration), and biological variables (algal biomass) were compared across the lakes sampled in these geographic regions. There was a large range in lake characteristics, including five to eighteen times higher algal biomass in the southern systems that experience active ash input to lakes. The lakes located in the Eastern Volcanic Zone also had higher conductivity and lower pH, especially in systems receiving substantial geothermal input. These results were analyzed in the context of more extensive lake sampling efforts across Iceland (46 lakes) to determine defining characteristics of lakes in each region and to identify variables that drive heterogeneous patterns in physical, chemical, and biological lake features within each region. Coastal systems, characterized by high conductivity, and glacially-fed systems, characterized by high iron concentrations, were unique from lakes in all other regions. Clustering and principal component analyses revealed that lake type (plateau, valley, spring-fed, and direct-runoff) was not the primary factor explaining variability in lake chemistry outside of the coastal and glacial lake types. Instead, lakes differentiated along a gradient of iron concentration and total nitrogen concentration. The physical and chemical properties of subarctic lakes are especially susceptible to both natural and human-induced environmental impacts. However, relatively little is known about the contemporary physical and chemical properties of Icelandic lakes, despite their abundance and importance as freshwater resources. Here we report an analysis of the physical, chemical, and biological characteristics of a set of subarctic lakes and use spatial Information to infer controls on lake heterogeneity within and across regions.

Regional agricultural susceptibility to climate variability: A district level analysis of Maharashtra, India

NASA Astrophysics Data System (ADS)

Swami, D.; Parthasarathy, D.; Dave, P.

2016-12-01

Climate variability (CV) has adverse impact on crop production and inadequate research carried out to assess the impact of CV on crop production has aggravated the ability of farmers to adapt (Jones et al., 2000). A better understanding of CV is required to reduce the vulnerability of farmers towards existing and future CV. Further, a wide variation in policies related to climate change exists at global level and considering the state/nation as a single unit for policy formulations may lead to under-representation of regional problems. Hence, the present work chooses to focus on CVassessment at the regional/district level of Maharashtra state in India. Here, interannual variability of wet and dry spells from year 1951-2013, are used as a measure of CV. Statistical declining trend of wet spells for (12/34) districts was observed across all the districts of Maharashtra. Districts showing highest change in wet spell pre and post 1976/77 are Beed, Latur and Osmanabad belong to Central Maharashtra Plateau zone and Western Maharashtra scarcity zone. Dry spells for (8/34) districts were found to statistically increase across all the districts of Maharashtra. Washim, Yavatmal of Vidarbha zone; and Latur, Parbhani of Amravati division belonging to Central Maharashtra Plateau zone and Central Vidarbha zone are found to reflect the large variation in their behavior pre and post 1976/77. Findings reveal that districts from the same agro-climate zones respond differently to CV, indicating significant spatial heterogeneity within the region. Trend in monsoon variability was found to be prominent after 1976/77, suggesting an enhanced role of climate change on climate variability after 1977. It necessitates separate policy formulation related to CV and agriculture for each district to bring out the solution for regional issues (socio-political, farmers, agriculturalists, economical) more clearly. Further we have attempted to link agriculture vulnerability and crop sensitivity to CV. Results signify spatial and temporal variability of different agro-ecological and climate parameters; suitable adaptation measures to famers and policy makers need to address this change. The findings can be utilized by farmers and policy makers while formulating agricultural policies and adaptation measures related to climate change.

Variability of particulate organic carbon concentration in the north polar Atlantic based on ocean color observations with Sea-viewing Wide Field-of-view Sensor (SeaWiFS)

NASA Technical Reports Server (NTRS)

Stramska, Malgorzata; Stramski, Dariusz

2005-01-01

We use satellite data from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) to investigate distributions of particulate organic carbon (POC) concentration in surface waters of the north polar Atlantic Ocean during the spring summer season (April through August) over a 6-year period from 1998 through 2003. By use of field data collected at sea, we developed regional relationships for the purpose of estimating POC from remote-sensing observations of ocean color. Analysis of several approaches used in the POC algorithm development and match-up analysis of coincident in situ derived and satellite-derived estimates of POC resulted in selection of an algorithm that is based on the blue-to-green ratio of remote-sensing reflectance R(sub rs) (or normalized water-leaving radiance L(sub wn)). The application of the selected algorithm to a 6-year record of SeaWiFS monthly composite data of L(sub wn) revealed patterns of seasonal and interannual variability of POC in the study region. For example, the results show a clear increase of POC throughout the season. The lowest values, generally less than 200 mg per cubic meters, and at some locations often less than 50 mg per cubic meters, were observed in April. In May and June, POC can exceed 300 or even 400 mg per cubic meters in some parts of the study region. Patterns of interannual variability are intricate, as they depend on the geographic location within the study region and particular time of year (month) considered. By comparing the results averaged over the entire study region and the entire season (April through August) for each year separately, we found that the lowest POC occurred in 2001 and the highest POC occurred in 2002 and 1999.

Using regional freight traffic assignment modeling to quantify the variability of pavement damage for highway cost allocation and revenue analysis.

DOT National Transportation Integrated Search

2014-12-01

While indicative of a vibrant economy, large volumes of freight traffic have been associated with : accelerated wear of pavements particularly. In seeking to adopt operational policies that reduce : undue deterioration of their infrastructure, state ...

Bacterial and Archaeal Communities Variability Associated with Upwelling and Anthropogenic Pressures in the Protection Area of Arraial do Cabo (Cabo Frio region - RJ).

PubMed

Coelho-Souza, Sergio A; Araújo, Fábio V; Cury, Juliano C; Jesus, Hugo E; Pereira, Gilberto C; Guimarães, Jean R D; Peixoto, Raquel S; Dávila, Alberto M R; Rosado, Alexandre S

2015-09-01

Upwelling systems contain a high diversity of pelagic microorganisms and their composition and activity are defined by factors like temperature and nutrient concentration. Denaturing gradient gel electrophoresis (DGGE) technique was used to verify the spatial and temporal genetic variability of Bacteria and Archaea in two stations of the Arraial do Cabo coastal region, one under upwelling pressure and another under anthropogenic pressure. In addition, biotic and abiotic variables were measured in surface and deep waters from three other stations between these stations. Six samplings were done during a year and adequately represented the degrees of upwelling and anthropogenic pressures to the system. Principal Component Analysis (PCA) showed negative correlations between the concentrations of ammonia and phosphorous with prokaryotic secondary production and the total heterotrophic bacteria. PCA also showed negative correlation between temperature and the abundance of prokaryotic cells. Bacterial and archaeal compositions were changeable as were the oceanographic conditions, and upwelling had a regional pressure while anthropogenic pressure was punctual. We suggest that the measurement of prokaryotic secondary production was associated with both Bacteria and Archaea activities, and that substrate availability and temperature determine nutrients cycling.

Is the Oceanography of the New Zealand Subantarctic Region Responding to the Tropics?

NASA Astrophysics Data System (ADS)

Forcen-Vazquez, A. N.

2016-02-01

The Campbell Plateau, south of New Zealand plays an important role in New Zealand's regional climate and its oceanography may have a significant impact on fluctuations in fish stocks and marine mammal populations. It is located between the Subtropical and Subantarctic Fronts and exhibits marked variability over long time scales. It has been previously assumed, because of its location, that the Campbell Plateau oceanography is driven by Subantarctic and polar processes. Recent analysis, presented here, suggests this in not the case, and instead forcing comes from the tropics and subtropics. This is supported by positive correlations of Sea Level Anomalies (SLA) and Sea Surface Temperature (SST) with the Southern Oscillation Index (SOI) with SOI leading changes on the Campbell Plateau by two months for SLA and seven months for SST. Here we will present evidence of the similarity between the Campbell Plateau and the Tasman Sea SLA trends which suggests a closer relationship with the subtropical region. Satellite collected SLA data and SST from the last two decades are investigated to understand trends and long-term variability over the Campbell Plateau and its relationship with the surrounding open ocean, and other potential remote drivers of variability.

Geostatistical analysis and isoscape of ice core derived water stable isotope records in an Antarctic macro region

NASA Astrophysics Data System (ADS)

Hatvani, István Gábor; Leuenberger, Markus; Kohán, Balázs; Kern, Zoltán

2017-09-01

Water stable isotopes preserved in ice cores provide essential information about polar precipitation. In the present study, multivariate regression and variogram analyses were conducted on 22 δ2H and 53 δ18O records from 60 ice cores covering the second half of the 20th century. Taking the multicollinearity of the explanatory variables into account, as also the model's adjusted R2 and its mean absolute error, longitude, elevation and distance from the coast were found to be the main independent geographical driving factors governing the spatial δ18O variability of firn/ice in the chosen Antarctic macro region. After diminishing the effects of these factors, using variography, the weights for interpolation with kriging were obtained and the spatial autocorrelation structure of the dataset was revealed. This indicates an average area of influence with a radius of 350 km. This allows the determination of the areas which are as yet not covered by the spatial variability of the existing network of ice cores. Finally, the regional isoscape was obtained for the study area, and this may be considered the first step towards a geostatistically improved isoscape for Antarctica.

Natural climate variability and teleconnections to precipitation over the Pacific-North American region in CMIP3 and CMIP5 models

NASA Astrophysics Data System (ADS)

Polade, Suraj D.; Gershunov, Alexander; Cayan, Daniel R.; Dettinger, Michael D.; Pierce, David W.

2013-05-01

climate variability will continue to be an important aspect of future regional climate even in the midst of long-term secular changes. Consequently, the ability of climate models to simulate major natural modes of variability and their teleconnections provides important context for the interpretation and use of climate change projections. Comparisons reported here indicate that the CMIP5 generation of global climate models shows significant improvements in simulations of key Pacific climate mode and their teleconnections to North America compared to earlier CMIP3 simulations. The performance of 14 models with simulations in both the CMIP3 and CMIP5 archives are assessed using singular value decomposition analysis of simulated and observed winter Pacific sea surface temperatures (SSTs) and concurrent precipitation over the contiguous United States and northwestern Mexico. Most of the models reproduce basic features of the key natural mode and their teleconnections, albeit with notable regional deviations from observations in both SST and precipitation. Increasing horizontal resolution in the CMIP5 simulations is an important, but not a necessary, factor in the improvement from CMIP3 to CMIP5.

Natural climate variability and teleconnections to precipitation over the Pacific-North American region in CMIP3 and CMIP5 models

USGS Publications Warehouse

Polade, Suraj D.; Gershunov, Alexander; Cayan, Daniel R.; Dettinger, Michael D.; Pierce, David W.

2013-01-01

Natural climate variability will continue to be an important aspect of future regional climate even in the midst of long-term secular changes. Consequently, the ability of climate models to simulate major natural modes of variability and their teleconnections provides important context for the interpretation and use of climate change projections. Comparisons reported here indicate that the CMIP5 generation of global climate models shows significant improvements in simulations of key Pacific climate mode and their teleconnections to North America compared to earlier CMIP3 simulations. The performance of 14 models with simulations in both the CMIP3 and CMIP5 archives are assessed using singular value decomposition analysis of simulated and observed winter Pacific sea surface temperatures (SSTs) and concurrent precipitation over the contiguous United States and northwestern Mexico. Most of the models reproduce basic features of the key natural mode and their teleconnections, albeit with notable regional deviations from observations in both SST and precipitation. Increasing horizontal resolution in the CMIP5 simulations is an important, but not a necessary, factor in the improvement from CMIP3 to CMIP5.

Synchronization of a Josephson junction array in terms of global variables

NASA Astrophysics Data System (ADS)

Vlasov, Vladimir; Pikovsky, Arkady

2013-08-01

We consider an array of Josephson junctions with a common LCR load. Application of the Watanabe-Strogatz approach [Physica DPDNPDT0167-278910.1016/0167-2789(94)90196-1 74, 197 (1994)] allows us to formulate the dynamics of the array via the global variables only. For identical junctions this is a finite set of equations, analysis of which reveals the regions of bistability of the synchronous and asynchronous states. For disordered arrays with distributed parameters of the junctions, the problem is formulated as an integro-differential equation for the global variables; here stability of the asynchronous states and the properties of the transition synchrony-asynchrony are established numerically.

Self-organizing map network-based precipitation regionalization for the Tibetan Plateau and regional precipitation variability

NASA Astrophysics Data System (ADS)

Wang, Nini; Yin, Jianchuan

2017-12-01

A precipitation-based regionalization for the Tibetan Plateau (TP) was investigated for regional precipitation trend analysis and frequency analysis using data from 1113 grid points covering the period 1900-2014. The results utilizing self-organizing map (SOM) network suggest that four clusters of precipitation coherent zones can be identified, including the southwestern edge, the southern edge, the southeastern region, and the north central region. Regionalization results of the SOM network satisfactorily represent the influences of the atmospheric circulation systems such as the East Asian summer monsoon, the south Asian summer monsoon, and the mid-latitude westerlies. Regionalization results also well display the direct impacts of physical geographical features of the TP such as orography, topography, and land-sea distribution. Regional-scale annual precipitation trend as well as regional differences of annual and seasonal total precipitation were investigated by precipitation index such as precipitation concentration index (PCI) and Standardized Anomaly Index (SAI). Results demonstrate significant negative long-term linear trends in southeastern TP and the north central part of the TP, indicating arid and semi-arid regions in the TP are getting drier. The empirical mode decomposition (EMD) method shows an evolution of the main cycle with 4 and 12 months for all the representative grids of four sub-regions. The cross-wavelet analysis suggests that predominant and effective period of Indian Ocean Dipole (IOD) on monthly precipitation is around ˜12 months, except for the representative grid of the northwestern region.

Egg prices, feed costs, and the decision to molt.

PubMed

McDaniel, B A; Aske, D R

2000-09-01

On April 7, 1998, the United Poultry Concerns filed a petition with the Department of Health and Human Services of the Food and Drug Administration calling for the elimination of the practice of forced molting of laying hens in the US. In reaction to this petition, this study investigated the economic importance of forced molting as a short-term production management tool for egg producers. The relationship between shell egg prices and feed costs and the occurrence of forced molting in the five shell egg-pricing regions in the US was addressed. The purpose of this analysis was to determine whether forced molting is used to slow egg production during periods of falling or low egg prices or periods of high or rising feed costs. Ordinary least squares was used to test the relationship between the independent variables (egg, corn, and meal prices) and the dependent variable (percentage of layers in molt). In four of the five regions, there was a significant inverse relationship (P < 0.05) between egg prices and the percentage of layers in molt. This analysis suggests that producers were influenced by current egg prices when making the decision to molt. However, the relationship between the percentage of layers in molt and corn and meal prices was less clear. Although a positive relationship between feed prices and molt was found in each region, in only one region was the relationship statistically significant (P < 0.05).

Analysis of new isolates reveals new genome organization and a hypervariable region in infectious myonecrosis virus (IMNV).

PubMed

Dantas, Márcia Danielle A; Chavante, Suely F; Teixeira, Dárlio Inácio A; Lima, João Paulo M S; Lanza, Daniel C F

2015-05-04

Infectious myonecrosis virus (IMNV) has been the cause of many losses in shrimp farming since 2002, when the first myonecrosis outbreak was reported at Brazilian's northeast coast. Two additional genomes of Brazilian IMNV isolates collected in 2009 and 2013 were sequenced and analyzed in the present study. The sequencing revealed extra 643 bp and 22 bp, at 5' and 3' ends of IMNV genome respectively, confirming that its actual size is at least 8226 bp long. Considering these additional sequences in genome extremities, ORF1 can starts at nt 470, encoding a 1708 aa polyprotein. Computational predictions reveal two stem loops and two pseudoknots in the 5' end and a putative stem loop and a slippery motif located at 3' end, indicating that these regions can be involved in the start and termination of translation. Through a careful phylogenetic analysis, a higher genetic variability among Brazilian isolates could be observed, comparing with Indonesian IMNV isolates. It was also observed that the most variable region of IMNV genome is located in the first half of ORF1, coinciding with a region which probably encodes the capsid protrusions. The results presented here are a starting point to elucidate the viral's translational regulation and the mechanisms involved in virulence. Copyright © 2015 Elsevier B.V. All rights reserved.

[Differentiation of geographic biovariants of smallpox virus by PCR].

PubMed

Babkin, I V; Babkina, I N

2010-01-01

Comparative analysis of amino acid and nucleotides sequences of ORFs located in extended segments of the terminal variable regions in variola virus genome detected a promising locus for viral genotyping according to the geographic origin. This is ORF O1L of VARV. The primers were calculated for synthesis of this ORF fragment by PCR, which makes it possible to distinguish South America-Western Africa genotype from other VARV strains. Subsequent RFLP analysis reliably differentiated Asian strains from African strains (except Western Africa isolates). This method has been tested using 16 VARV strains from various geographic regions. The developed approach is simple, fast and reliable.

Gravity-driven soap film dynamics in subcritical regimes

NASA Astrophysics Data System (ADS)

Auliel, M. I.; Castro, F.; Sosa, R.; Artana, G.

2015-10-01

We undertake the analysis of soap-film dynamics with the classical approach of asymptotic expansions. We focus our analysis in vertical soap film tunnels operating in subcritical regimes with elastic Mach numbers Me=O(10-1) . Considering the associated set of nondimensional numbers that characterize this flow, we show that the flow behaves as a two-dimensional (2D) divergence free flow with variable mass density. When the soap film dynamics agrees with that of a 2D and almost constant mass density flow, the regions where the second invariant of the velocity gradient is non-null correspond to regions where the rate of change of film thickness is non-negligible.

Temporal analysis of the frequency and duration of low and high streamflow: Years of record needed to characterize streamflow variability

USGS Publications Warehouse

Huh, S.; Dickey, D.A.; Meador, M.R.; Ruhl, K.E.

2005-01-01

A temporal analysis of the number and duration of exceedences of high- and low-flow thresholds was conducted to determine the number of years required to detect a level shift using data from Virginia, North Carolina, and South Carolina. Two methods were used - ordinary least squares assuming a known error variance and generalized least squares without a known error variance. Using ordinary least squares, the mean number of years required to detect a one standard deviation level shift in measures of low-flow variability was 57.2 (28.6 on either side of the break), compared to 40.0 years for measures of high-flow variability. These means become 57.6 and 41.6 when generalized least squares is used. No significant relations between years and elevation or drainage area were detected (P>0.05). Cluster analysis did not suggest geographic patterns in years related to physiography or major hydrologic regions. Referring to the number of observations required to detect a one standard deviation shift as 'characterizing' the variability, it appears that at least 20 years of record on either side of a shift may be necessary to adequately characterize high-flow variability. A longer streamflow record (about 30 years on either side) may be required to characterize low-flow variability. ?? 2005 Elsevier B.V. All rights reserved.

[The commercially cultivated edible oyster mushrooms Pleurotus sajor-caju and P. pulmonarius are two separate species, similar in morphology but reproductively isolated].

PubMed

Shnyreva, A A; Sivolapova, A B; Shnyreva, A V

2012-11-01

Two closely related commercially cultivated oyster mushroom species, Pleurotus pulmonarius and P. sajor-caju have been differentiated by traditional mating experiments as well as analysis of the variable ITS and IGS sequences of the ribosomal gene cluster. Molecular analysis of the variable ITS and IGS regions has allowed neither reliable differentiation between the morphologically similar species P. pulmonarius and P. sajor-caju nor confirmation of species identity of the P. sajor-caju strains CS-32, H-1, and H-2. Analysis of the sexual (mating) compatibility between haploid tester strains of these two species in monokaryon-monokaryon mating experiments has demonstrated complete reproductive isolation between P. pulmonarius and P. sajor-caju, thereby confirming that these are separate species.

Validation of newly designed regional earth system model (RegESM) for Mediterranean Basin

NASA Astrophysics Data System (ADS)

Turuncoglu, Ufuk Utku; Sannino, Gianmaria

2017-05-01

We present a validation analysis of a regional earth system model system (RegESM) for the Mediterranean Basin. The used configuration of the modeling system includes two active components: a regional climate model (RegCM4) and an ocean modeling system (ROMS). To assess the performance of the coupled modeling system in representing the climate of the basin, the results of the coupled simulation (C50E) are compared to the results obtained by a standalone atmospheric simulation (R50E) as well as several observation datasets. Although there is persistent cold bias in fall and winter, which is also seen in previous studies, the model reproduces the inter-annual variability and the seasonal cycles of sea surface temperature (SST) in a general good agreement with the available observations. The analysis of the near-surface wind distribution and the main circulation of the sea indicates that the coupled model can reproduce the main characteristics of the Mediterranean Sea surface and intermediate layer circulation as well as the seasonal variability of wind speed and direction when it is compared with the available observational datasets. The results also reveal that the simulated near-surface wind speed and direction have poor performance in the Gulf of Lion and surrounding regions that also affects the large positive SST bias in the region due to the insufficient horizontal resolution of the atmospheric component of the coupled modeling system. The simulated seasonal climatologies of the surface heat flux components are also consistent with the CORE.2 and NOCS datasets along with the overestimation in net long-wave radiation and latent heat flux (or evaporation, E), although a large observational uncertainty is found in these variables. Also, the coupled model tends to improve the latent heat flux by providing a better representation of the air-sea interaction as well as total heat flux budget over the sea. Both models are also able to reproduce the temporal evolution of the inter-annual anomaly of surface air temperature and precipitation (P) over defined sub-regions. The Mediterranean water budget (E, P and E-P) estimates also show that the coupled model has high skill in the representation of water budget of the Mediterranean Sea. To conclude, the coupled model reproduces climatological land surface fields and the sea surface variables in the range of observation uncertainty and allow studying air-sea interaction and main regional climate characteristics of the basin.

Mapping Regional Impervious Surface Distribution from Night Time Light: The Variability across Global Cities

NASA Astrophysics Data System (ADS)

Lin, M.; Yang, Z.; Park, H.; Qian, S.; Chen, J.; Fan, P.

2017-12-01

Impervious surface area (ISA) has become an important indicator for studying urban environments, but mapping ISA at the regional or global scale is still challenging due to the complexity of impervious surface features. The Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) nighttime light data is (NTL) and Resolution Imaging Spectroradiometer (MODIS) are the major remote sensing data source for regional ISA mapping. A single regression relationship between fractional ISA and NTL or various index derived based on NTL and MODIS vegetation index (NDVI) data was established in many previous studies for regional ISA mapping. However, due to the varying geographical, climatic, and socio-economic characteristics of different cities, the same regression relationship may vary significantly across different cities in the same region in terms of both fitting performance (i.e. R2) and the rate of change (Slope). In this study, we examined the regression relationship between fractional ISA and Vegetation Adjusted Nighttime light Urban Index (VANUI) for 120 randomly selected cities around the world with a multilevel regression model. We found that indeed there is substantial variability of both the R2 (0.68±0.29) and slopes (0.64±0.40) among individual regressions, which suggests that multilevel/hierarchical models are needed for accuracy improvement of future regional ISA mapping .Further analysis also let us find the this substantial variability are affected by climate conditions, socio-economic status, and urban spatial structures. However, all these effects are nonlinear rather than linear, thus could not modeled explicitly in multilevel linear regression models.

Variations in data collection can influence outcome measures of BMI measuring programmes.

PubMed

Townsend, Nick; Rutter, Harry; Foster, Charlie

2011-10-01

The World Health Organization (WHO) promotes the surveillance of obesity prevalence through standardized and harmonized surveillance systems. However, variations in data collection between countries, or between coordinating regions in countries can affect outcome measures. Multilevel analysis of 2007/08 National Child Measurement Programme (NCMP) data estimating the relationship between BMI z-score and data collection variations within coordinating regions whilst adjusting for individual-level and school-level variables. The 2007/08 NCMP collected height and weight measurements for 478,381 Reception year pupils (4-5-year-olds) and 496,297 year 6 pupils (10-11-year-olds) from 17,279 primary schools in 152 data collection coordinating regions in England. Data collection variables accounted for 29.7% of the regional variation in BMI z-score for Reception year pupils but only 5.3% for the older Year 6 pupils. Digit preference in the rounding of weight measurements had the greatest impact of all the data collection variables, explaining 26.4% of the regional variation in BMI z-score for Reception year pupils and 4.0% for Year 6 pupils. Although variations in data collection may have a small effect on individual measurements their impact can be magnified when scaled up to regional or national figures. All measurement programmes must regularly identify and minimize variations in data collection to improve accuracy of outcome measures. These factors include those identified within this study: participation and opt out rates, the time in the year the measurements are taken and the recording of measurements to the correct decimal place.

The USH2A c.2299delG mutation: dating its common origin in a Southern European population

PubMed Central

Aller, Elena; Larrieu, Lise; Jaijo, Teresa; Baux, David; Espinós, Carmen; González-Candelas, Fernando; Nájera, Carmen; Palau, Francesc; Claustres, Mireille; Roux, Anne-Françoise; Millán, José M

2010-01-01

Usher syndrome type II is the most common form of Usher syndrome. USH2A is the main responsible gene of the three known to be disease causing. It encodes two isoforms of the protein usherin. This protein is part of an interactome that has an essential role in the development and function of inner ear hair cells and photoreceptors. The gene contains 72 exons spanning over a region of 800 kb. Although numerous mutations have been described, the c.2299delG mutation is the most prevalent in several populations. Its ancestral origin was previously suggested after the identification of a common core haplotype restricted to 250 kb in the 5′ region that encodes the short usherin isoform. By extending the haplotype analysis over the 800 kb region of the USH2A gene with a total of 14 intragenic single nucleotide polymorphisms, we have been able to define 10 different c.2299delG haplotypes, showing high variability but preserving the previously described core haplotype. An exhaustive c.2299delG/control haplotype study suggests that the major source of variability in the USH2A gene is recombination. Furthermore, we have evidenced twice the amount of recombination hotspots located in the 500 kb region that covers the 3′ end of the gene, explaining the higher variability observed in this region when compared with the 250 kb of the 5′ region. Our data confirm the common ancestral origin of the c.2299delG mutation. PMID:20145675

Classification of California streams using combined deductive and inductive approaches: Setting the foundation for analysis of hydrologic alteration

USGS Publications Warehouse

Pyne, Matthew I.; Carlisle, Daren M.; Konrad, Christopher P.; Stein, Eric D.

2017-01-01

Regional classification of streams is an early step in the Ecological Limits of Hydrologic Alteration framework. Many stream classifications are based on an inductive approach using hydrologic data from minimally disturbed basins, but this approach may underrepresent streams from heavily disturbed basins or sparsely gaged arid regions. An alternative is a deductive approach, using watershed climate, land use, and geomorphology to classify streams, but this approach may miss important hydrological characteristics of streams. We classified all stream reaches in California using both approaches. First, we used Bayesian and hierarchical clustering to classify reaches according to watershed characteristics. Streams were clustered into seven classes according to elevation, sedimentary rock, and winter precipitation. Permutation-based analysis of variance and random forest analyses were used to determine which hydrologic variables best separate streams into their respective classes. Stream typology (i.e., the class that a stream reach is assigned to) is shaped mainly by patterns of high and mean flow behavior within the stream's landscape context. Additionally, random forest was used to determine which hydrologic variables best separate minimally disturbed reference streams from non-reference streams in each of the seven classes. In contrast to stream typology, deviation from reference conditions is more difficult to detect and is largely defined by changes in low-flow variables, average daily flow, and duration of flow. Our combined deductive/inductive approach allows us to estimate flow under minimally disturbed conditions based on the deductive analysis and compare to measured flow based on the inductive analysis in order to estimate hydrologic change.

Quantifying Individual Brain Connectivity with Functional Principal Component Analysis for Networks.

PubMed

Petersen, Alexander; Zhao, Jianyang; Carmichael, Owen; Müller, Hans-Georg

2016-09-01

In typical functional connectivity studies, connections between voxels or regions in the brain are represented as edges in a network. Networks for different subjects are constructed at a given graph density and are summarized by some network measure such as path length. Examining these summary measures for many density values yields samples of connectivity curves, one for each individual. This has led to the adoption of basic tools of functional data analysis, most commonly to compare control and disease groups through the average curves in each group. Such group differences, however, neglect the variability in the sample of connectivity curves. In this article, the use of functional principal component analysis (FPCA) is demonstrated to enrich functional connectivity studies by providing increased power and flexibility for statistical inference. Specifically, individual connectivity curves are related to individual characteristics such as age and measures of cognitive function, thus providing a tool to relate brain connectivity with these variables at the individual level. This individual level analysis opens a new perspective that goes beyond previous group level comparisons. Using a large data set of resting-state functional magnetic resonance imaging scans, relationships between connectivity and two measures of cognitive function-episodic memory and executive function-were investigated. The group-based approach was implemented by dichotomizing the continuous cognitive variable and testing for group differences, resulting in no statistically significant findings. To demonstrate the new approach, FPCA was implemented, followed by linear regression models with cognitive scores as responses, identifying significant associations of connectivity in the right middle temporal region with both cognitive scores.

Internal and forced eddy variability in the Labrador Sea

NASA Astrophysics Data System (ADS)

Bracco, A.; Luo, H.; Zhong, Y.; Lilly, J.

2009-04-01

Water mass transformation in the Labrador Sea, widely believed to be one of the key regions in the Atlantic Meridional Overturning Circulation (AMOC), now appears to be strongly impacted by vortex dynamics of the unstable boundary current. Large interannual variations in both eddy shedding and buoyancy transport from the boundary current have been observed but not explained, and are apparently sensitive to the state of the inflowing current. Heat and salinity fluxes associated with the eddies drive ventilation changes not accounted for by changes in local surface forcing, particularly during occasional years of extreme eddy activity, and constitute a predominant source of "internal" oceanic variability. The nature of this variable eddy-driven restratification is one of the outstanding questions along the northern transformation pathway. Here we investigate the eddy generation mechanism and the associated buoyancy fluxes by combining realistic and idealized numerical modeling, data analysis, and theory. Theory, supported by idealized experiments, provides criteria to test hypotheses as to the vortex formation process (by baroclinic instability linked to the bottom topography). Ensembles of numerical experiments with a high-resolution regional model (ROMS) allow for quantifying the sensitivity of eddy generation and property transport to variations in local and external forcing parameters. For the first time, we reproduce with a numerical simulation the observed interannual variability in the eddy kinetic energy in the convective region of the Labrador Basin and along the West Greenland Current.

The Climate Variability & Predictability (CVP) Program at NOAA - Observing and Understanding Processes Affecting the Propagation of Intraseasonal Oscillations in the Maritime Continent Region

NASA Astrophysics Data System (ADS)

Lucas, S. E.

2017-12-01

The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA's Climate Program Office (http://cpo.noaa.gov/CVP). In 2017, the CVP Program had a call for proposals focused on observing and understanding processes affecting the propagation of intraseasonal oscillations in the Maritime Continent region. This poster will present the recently funded CVP projects, the expected scientific outcomes, the geographic areas of their work in the Maritime Continent region, and the collaborations with the Office of Naval Research, Indonesian Agency for Meteorology, Climatology and Geophysics (BMKG), Japan Agency for Marine-Earth Science and Technology (JAMSTEC) and other partners.

Spatial correlation of shear-wave velocity in the San Francisco Bay Area sediments

USGS Publications Warehouse

Thompson, E.M.; Baise, L.G.; Kayen, R.E.

2007-01-01

Ground motions recorded within sedimentary basins are variable over short distances. One important cause of the variability is that local soil properties are variable at all scales. Regional hazard maps developed for predicting site effects are generally derived from maps of surficial geology; however, recent studies have shown that mapped geologic units do not correlate well with the average shear-wave velocity of the upper 30 m, Vs(30). We model the horizontal variability of near-surface soil shear-wave velocity in the San Francisco Bay Area to estimate values in unsampled locations in order to account for site effects in a continuous manner. Previous geostatistical studies of soil properties have shown horizontal correlations at the scale of meters to tens of meters while the vertical correlations are on the order of centimeters. In this paper we analyze shear-wave velocity data over regional distances and find that surface shear-wave velocity is correlated at horizontal distances up to 4 km based on data from seismic cone penetration tests and the spectral analysis of surface waves. We propose a method to map site effects by using geostatistical methods based on the shear-wave velocity correlation structure within a sedimentary basin. If used in conjunction with densely spaced shear-wave velocity profiles in regions of high seismic risk, geostatistical methods can produce reliable continuous maps of site effects. ?? 2006 Elsevier Ltd. All rights reserved.

MOSAIC: an online database dedicated to the comparative genomics of bacterial strains at the intra-species level.

PubMed

Chiapello, Hélène; Gendrault, Annie; Caron, Christophe; Blum, Jérome; Petit, Marie-Agnès; El Karoui, Meriem

2008-11-27

The recent availability of complete sequences for numerous closely related bacterial genomes opens up new challenges in comparative genomics. Several methods have been developed to align complete genomes at the nucleotide level but their use and the biological interpretation of results are not straightforward. It is therefore necessary to develop new resources to access, analyze, and visualize genome comparisons. Here we present recent developments on MOSAIC, a generalist comparative bacterial genome database. This database provides the bacteriologist community with easy access to comparisons of complete bacterial genomes at the intra-species level. The strategy we developed for comparison allows us to define two types of regions in bacterial genomes: backbone segments (i.e., regions conserved in all compared strains) and variable segments (i.e., regions that are either specific to or variable in one of the aligned genomes). Definition of these segments at the nucleotide level allows precise comparative and evolutionary analyses of both coding and non-coding regions of bacterial genomes. Such work is easily performed using the MOSAIC Web interface, which allows browsing and graphical visualization of genome comparisons. The MOSAIC database now includes 493 pairwise comparisons and 35 multiple maximal comparisons representing 78 bacterial species. Genome conserved regions (backbones) and variable segments are presented in various formats for further analysis. A graphical interface allows visualization of aligned genomes and functional annotations. The MOSAIC database is available online at http://genome.jouy.inra.fr/mosaic.

A south equatorial African precipitation dipole and the associated atmospheric circulation

NASA Astrophysics Data System (ADS)

Dezfuli, A. K.; Zaitchik, B.; Gnanadesikan, A.

2013-12-01

South Equatorial Africa (SEA) is a climatically diverse region that includes a dramatic topographic and vegetation contrast between the lowland, humid Congo basin to the west and the East African Plateau to the east. Due to lack of conventional weather data and a tendency for researchers to treat East and western Africa as separate regions, dynamics of the atmospheric water cycle across SEA have received relatively little attention, particularly at subseasonal timescales. Both western and eastern sectors of SEA are affected by large-scale drivers of the water cycle associated with Atlantic variability (western sector), Indian Ocean variability (eastern sector) and Pacific variability (both sectors). However, a specific characteristic of SEA is strong heterogeneity in interannual rainfall variability that cannot be explained by large-scale climatic phenomena. For this reason, this study examines regional climate dynamics on daily time-scale with a focus on the role that the abrupt topographic contrast between the lowland Congo and the East African highlands plays in driving rainfall behavior on short timescales. Analysis of daily precipitation data during November-March reveals a zonally-oriented dipole mode over SEA that explains the leading pattern of weather-scale precipitation variability in the region. The separating longitude of the two poles is coincident with the zonal variation of topography. An anomalous counter-clockwise atmospheric circulation associated with the dipole mode appears over the entire SEA. The circulation is triggered by its low-level westerly component, which is in turn generated by an interhemispheric pressure gradient. These enhanced westerlies hit the East African highlands and produce topographically-driven low-level convergence and convection that further intensifies the circulation. Recent studies have shown that under climate change the position and intensity of subtropical highs in both hemispheres and the intensity of precipitation over equatorial Africa are projected to change. Both of these trends have implications for the manner in which large-scale dynamics will interact with regional topography, affecting the intensity and frequency of the dipole mode characterized in this study and the occurrence of extreme wet and dry spells in the region.

The broad-band X-ray spectral variability of Mrk 841

NASA Technical Reports Server (NTRS)

George, I. M.; Nandra, K.; Fabian, A. C.; Turner, T. J.; Done, C.; Day, C. S. R.

1993-01-01

A detailed spectral analysis of five X-ray observations of Mrk 841 with the EXOSAT, Ginga, and ROSAT satellites is reported. Variability is apparent in both the soft (0.1-1.0 keV) and medium (1-20 keV) energy bands. Above, 1 keV, the spectra are adequately modeled by a power law with a strong emission line of equivalent width 450 eV. The large equivalent width of the emission line indicates a strongly enhanced reflection component of the source compared with other Seyferts observed with Ginga. The implications of the results of the analysis for physical models of the emission regions in this and other X-ray bright Seyferts are briefly examined.

Application of fuzzy logic in multicomponent analysis by optodes.

PubMed

Wollenweber, M; Polster, J; Becker, T; Schmidt, H L

1997-01-01

Fuzzy logic can be a useful tool for the determination of substrate concentrations applying optode arrays in combination with flow injection analysis, UV-VIS spectroscopy and kinetics. The transient diffuse reflectance spectra in the visible wavelength region from four optodes were evaluated to carry out the simultaneous determination of artificial mixtures of ampicillin and penicillin. The discrimination of the samples was achieved by changing the composition of the receptor gel and working pH. Different algorithms of pre-processing were applied on the data to reduce the spectral information to a few analytic-specific variables. These variables were used to develop the fuzzy model. After calibration the model was validated by an independent test data set.

Scales of variability of black carbon plumes and their dependence on resolution of ECHAM6-HAM

NASA Astrophysics Data System (ADS)

Weigum, Natalie; Stier, Philip; Schutgens, Nick; Kipling, Zak

2015-04-01

Prediction of the aerosol effect on climate depends on the ability of three-dimensional numerical models to accurately estimate aerosol properties. However, a limitation of traditional grid-based models is their inability to resolve variability on scales smaller than a grid box. Past research has shown that significant aerosol variability exists on scales smaller than these grid-boxes, which can lead to discrepancies between observations and aerosol models. The aim of this study is to understand how a global climate model's (GCM) inability to resolve sub-grid scale variability affects simulations of important aerosol features. This problem is addressed by comparing observed black carbon (BC) plume scales from the HIPPO aircraft campaign to those simulated by ECHAM-HAM GCM, and testing how model resolution affects these scales. This study additionally investigates how model resolution affects BC variability in remote and near-source regions. These issues are examined using three different approaches: comparison of observed and simulated along-flight-track plume scales, two-dimensional autocorrelation analysis, and 3-dimensional plume analysis. We find that the degree to which GCMs resolve variability can have a significant impact on the scales of BC plumes, and it is important for models to capture the scales of aerosol plume structures, which account for a large degree of aerosol variability. In this presentation, we will provide further results from the three analysis techniques along with a summary of the implication of these results on future aerosol model development.

Variability of African Farming Systems from Phenological Analysis of NDVI Time Series

NASA Technical Reports Server (NTRS)

Vrieling, Anton; deBeurs, K. M.; Brown, Molly E.

2011-01-01

Food security exists when people have access to sufficient, safe and nutritious food at all times to meet their dietary needs. The natural resource base is one of the many factors affecting food security. Its variability and decline creates problems for local food production. In this study we characterize for sub-Saharan Africa vegetation phenology and assess variability and trends of phenological indicators based on NDVI time series from 1982 to 2006. We focus on cumulated NDVI over the season (cumNDVI) which is a proxy for net primary productivity. Results are aggregated at the level of major farming systems, while determining also spatial variability within farming systems. High temporal variability of cumNDVI occurs in semiarid and subhumid regions. The results show a large area of positive cumNDVI trends between Senegal and South Sudan. These correspond to positive CRU rainfall trends found and relate to recovery after the 1980's droughts. We find significant negative cumNDVI trends near the south-coast of West Africa (Guinea coast) and in Tanzania. For each farming system, causes of change and variability are discussed based on available literature (Appendix A). Although food security comprises more than the local natural resource base, our results can perform an input for food security analysis by identifying zones of high variability or downward trends. Farming systems are found to be a useful level of analysis. Diversity and trends found within farming system boundaries underline that farming systems are dynamic.

Factors affecting the geographic distribution of West Nile virus in Georgia, USA: 2002-2004.

PubMed

Gibbs, Samantha E J; Wimberly, Michael C; Madden, Marguerite; Masour, Janna; Yabsley, Michael J; Stallknecht, David E

2006-01-01

The distribution of West Nile virus (WNV) is dependent on the occurrence of both susceptible avian reservoir hosts and competent mosquito vectors. Both factors can be influenced by geographic variables such as land use/landcover, elevation, human population density, physiographic region, and temperature. The current study uses geographic information systems (GIS) and logistic regression analyses to model the distribution of WNV in the state of Georgia based on a wild bird indicator system, and to identify human and environmental predictor variables that are important in the determination of WNV distribution. A database for Georgia was constructed that included (1) location points of all the avian samples tested for WNV, (2) local land use classifications, including temperature, physiographic divisions, land use/landcover, and elevation, (3) human demographic data from the U.S. Census, and (4) statistics summarizing land cover, elevation, and climate within a 1-km-radius landscape around each sample point. Logistic regression analysis was carried out using the serostatus of avian collection sites as the dependent variable. Temperature, housing density, urban/suburban land use, and mountain physiographic region were important variables in predicting the distribution of WNV in the state of Georgia. While weak, the positive correlation between WNV-antibody positive sites and the urban/suburban environment was consistent throughout the study period. The risks associated with WNV endemicity appear to be increased in urban/ suburban areas and decreased in the mountainous region of the state. This information may be used in addressing regional public health needs and mosquito control programs.

The intraannual variability of land-atmosphere coupling over North America in the Canadian Regional Climate Model (CRCM5)

NASA Astrophysics Data System (ADS)

Yang Kam Wing, G.; Sushama, L.; Diro, G. T.

2016-12-01

This study investigates the intraannual variability of soil moisture-temperature coupling over North America. To this effect, coupled and uncoupled simulations are performed with the fifth-generation Canadian Regional Climate Model (CRCM5), driven by ERA-Interim. In coupled simulations, land and atmosphere interact freely; in uncoupled simulations, the interannual variability of soil moisture is suppressed by prescribing climatological values for soil liquid and frozen water contents. The study also explores projected changes to coupling by comparing coupled and uncoupled CRCM5 simulations for current (1981-2010) and future (2071-2100) periods, driven by the Canadian Earth System Model. Coupling differs for the northern and southern parts of North America. Over the southern half, it is persistent throughout the year while for the northern half, strongly coupled regions generally follow the freezing line during the cold months. Detailed analysis of the southern Canadian Prairies reveals seasonal differences in the underlying coupling mechanism. During spring and fall, as opposed to summer, the interactive soil moisture phase impacts the snow depth and surface albedo, which further impacts the surface energy budget and thus the surface air temperature; the air temperature then influences the snow depth in a feedback loop. Projected changes to coupling are also season specific: relatively drier soil conditions strengthen coupling during summer, while changes in soil moisture phase, snow depth, and cloud cover impact coupling during colder months. Furthermore, results demonstrate that soil moisture variability amplifies the frequency of temperature extremes over regions of strong coupling in current and future climates.

Hydrological signals in height and gravity in northeastern Italy inferred from principal components analysis

NASA Astrophysics Data System (ADS)

Zerbini, S.; Raicich, F.; Richter, B.; Gorini, V.; Errico, M.

2010-04-01

This work describes a study of GPS heights, gravity and hydrological time series collected by stations located in northeastern Italy. During the last 12 years, changes in the long-term behaviors of the GPS heights and gravity time series are observed. In particular, starting in 2004-2005, a height increase is observed over the whole area. The temporal and spatial variability of these parameters has been studied as well as those of key hydrological variables, namely precipitation, hydrological balance and water table by using the Empirical Orthogonal Functions (EOF) analysis. The coupled variability between the GPS heights and the hydrological balance and precipitation data has been investigated by means of the Singular Value Decomposition (SVD) approach. Significant common patterns in the spatial and temporal variability of these parameters have been recognized. In particular, hydrology-induced variations are clearly observable starting in 2002-2003 in the southern part of the Po Plain for the longest time series, and from 2004-2005 over the whole area. These findings, obtained by means of purely mathematical approaches, are supported by sound physical interpretation suggesting that the climate-related fluctuations in the regional/local hydrological regime are one of the main contributors to the observed variations. A regional scale signal has been identified in the GPS station heights; it is characterized by the opposite behavior of the southern and northern stations in response to the hydrological forcing. At Medicina, in the southern Po Plain, the EOF analysis has shown a marked common signal between the GPS heights and the Superconducting Gravimeter (SG) data both over the long and the short period.

E-waste collection in Italy: Results from an exploratory analysis.

PubMed

Favot, Marinella; Grassetti, Luca

2017-09-01

This study looks at the performance of household electrical and electronic waste (WEEE) collection in 20 Italian regions from 2008 to 2015. The impact of several explicative variables on the results of e-waste collection is evaluated. The independent variables are socio-economic and demographic ones (age, gender, household size, education level, migration and income) along with technical-organisational variables (population density, presence of metropoles, macro regions, characteristics of the territory, percentage of household waste collected separately and number of e-waste collection points). The results show that the presence of collection points, the percentage of household waste collected separately and the percentage of females are positively correlated with the kg collected per inhabitant per year. For example, a variation of 1% of input (presence of collection points) corresponds to a 0.25% variation in the output (collection results) while 1% difference in the percentage of females in the population corresponds to a 7.549% difference in the collection rate. Population density, instead, is negatively correlated. It is interesting to note that there is a discrepancy between the Southern regions and the Centre regions (the former have an outcome 0.66 times lower than the latter) while the Northern regions perform similarly to the Centre ones. Moreover, the first year (2008) had a very low performance compared to the following years when the scheme constantly improved, mainly due to the additional collection points available. The Stochastic Frontier Model allows for the identification of the optimal production function among the 20 Italian regions. The best performing region is Tuscany (in the Centre), followed by Sardinia and Sicily (in the South). Copyright © 2017. Published by Elsevier Ltd.

Length and sequence variability in mitochondrial control region of the milkfish, Chanos chanos.

PubMed

Ravago, Rachel G; Monje, Virginia D; Juinio-Meñez, Marie Antonette

2002-01-01

Extensive length variability was observed in the mitochondrial control region of the milkfish, Chanos chanos. The nucleotide sequence of the control region and flanking regions was determined. Length variability and heteroplasmy was due to the presence of varying numbers of a 41-bp tandemly repeated sequence and a 48-bp insertion/deletion (indel). The structure and organization of the milkfish control region is similar to that of other teleost fish and vertebrates. However, extensive variation in the copy number of tandem repeats (4-20 copies) and the presence of a relatively large (48-bp) indel, are apparently uncommon in teleost fish control region sequences reported to date. High sequence variability of control region peripheral domains indicates the potential utility of selected regions as markers for population-level studies.

NGA-West 2 Equations for predicting PGA, PGV, and 5%-Damped PSA for shallow crustal earthquakes

USGS Publications Warehouse

Boore, David M.; Stewart, Jon P.; Seyhan, Emel; Atkinson, Gail M.

2013-01-01

We provide ground-motion prediction equations for computing medians and standard deviations of average horizontal component intensity measures (IMs) for shallow crustal earthquakes in active tectonic regions. The equations were derived from a global database with M 3.0–7.9 events. We derived equations for the primary M- and distance-dependence of the IMs after fixing the VS30-based nonlinear site term from a parallel NGA-West 2 study. We then evaluated additional effects using mixed effects residuals analysis, which revealed no trends with source depth over the M range of interest, indistinct Class 1 and 2 event IMs, and basin depth effects that increase and decrease long-period IMs for depths larger and smaller, respectively, than means from regional VS30-depth relations. Our aleatory variability model captures decreasing between-event variability with M, as well as within-event variability that increases or decreases with M depending on period, increases with distance, and decreases for soft sites.

The rDNA ITS region in the lessepsian marine angiosperm Halophila stipulacea (Forssk.) Aschers. (Hydrocharitaceae): intragenomic variability and putative pseudogenic sequences.

PubMed

Ruggiero, Maria Valeria; Procaccini, Gabriele

2004-01-01

Halophila stipulacea is a dioecious marine angiosperm, widely distributed along the western coasts of the Indian Ocean and the Red Sea. This species is thought to be a Lessepsian immigrant that entered the Mediterranean Sea from the Red Sea after the opening of the Suez Canal (1869). Previous studies have revealed both high phenotypic and genetic variability in Halophila stipulacea populations from the western Mediterranean basin. In order to test the hypothesis of a Lessepsian introduction, we compare genetic polymorphism between putative native (Red Sea) and introduced (Mediterranean) populations through rDNA ITS region (ITS1-5.8S-ITS2) sequence analysis. A high degree of intraindividual variability of ITS sequences was found. Most of the intragenomic polymorphism was due to pseudogenic sequences, present in almost all individuals. Features of ITS functional sequences and pseudogenes are described. Possible causes for the lack of homogenization of ITS paralogues within individuals are discussed.

Spatio-temporal variations of nitric acid total columns from 9 years of IASI measurements - a driver study

NASA Astrophysics Data System (ADS)

Ronsmans, Gaétane; Wespes, Catherine; Hurtmans, Daniel; Clerbaux, Cathy; Coheur, Pierre-François

2018-04-01

This study aims to understand the spatial and temporal variability of HNO3 total columns in terms of explanatory variables. To achieve this, multiple linear regressions are used to fit satellite-derived time series of HNO3 daily averaged total columns. First, an analysis of the IASI 9-year time series (2008-2016) is conducted based on various equivalent latitude bands. The strong and systematic denitrification of the southern polar stratosphere is observed very clearly. It is also possible to distinguish, within the polar vortex, three regions which are differently affected by the denitrification. Three exceptional denitrification episodes in 2011, 2014 and 2016 are also observed in the Northern Hemisphere, due to unusually low arctic temperatures. The time series are then fitted by multivariate regressions to identify what variables are responsible for HNO3 variability in global distributions and time series, and to quantify their respective influence. Out of an ensemble of proxies (annual cycle, solar flux, quasi-biennial oscillation, multivariate ENSO index, Arctic and Antarctic oscillations and volume of polar stratospheric clouds), only the those defined as significant (p value < 0.05) by a selection algorithm are retained for each equivalent latitude band. Overall, the regression gives a good representation of HNO3 variability, with especially good results at high latitudes (60-80 % of the observed variability explained by the model). The regressions show the dominance of annual variability in all latitudinal bands, which is related to specific chemistry and dynamics depending on the latitudes. We find that the polar stratospheric clouds (PSCs) also have a major influence in the polar regions, and that their inclusion in the model improves the correlation coefficients and the residuals. However, there is still a relatively large portion of HNO3 variability that remains unexplained by the model, especially in the intertropical regions, where factors not included in the regression model (such as vegetation fires or lightning) may be at play.

Characteristic analysis-1981: Final program and a possible discovery

USGS Publications Warehouse

McCammon, R.B.; Botbol, J.M.; Sinding-Larsen, R.; Bowen, R.W.

1983-01-01

The latest ornewest version of thecharacteristicanalysis (NCHARAN)computer program offers the exploration geologist a wide variety of options for integrating regionalized multivariate data. The options include the selection of regional cells for characterizing deposit models, the selection of variables that constitute the models, and the choice of logical combinations of variables that best represent these models. Moreover, the program provides for the display of results which, in turn, makes possible review, reselection, and refinement of a model. Most important, the performance of the above-mentioned steps in an interactive computing mode can result in a timely and meaningful interpretation of the data available to the exploration geologist. The most recent application of characteristic analysis has resulted in the possible discovery of economic sulfide mineralization in the Grong area in central Norway. Exploration data for 27 geophysical, geological, and geochemical variables were used to construct a mineralized and a lithogeochemical model for an area that contained a known massive sulfide deposit. The models were applied to exploration data collected from the Gjersvik area in the Grong mining district and resulted in the identification of two localities of possible mineralization. Detailed field examination revealed the presence of a sulfide vein system and a partially inverted stratigraphic sequence indicating the possible presence of a massive sulfide deposit at depth. ?? 1983 Plenum Publishing Corporation.

Chromosomal Mapping of Repetitive DNA Sequences in the Genus Bryconamericus (Characidae) and DNA Barcoding to Differentiate Populations.

PubMed

Santos, Angélica Rossotti Dos; Usso, Mariana Campaner; Gouveia, Juceli Gonzalez; Araya-Jaime, Cristian; Frantine-Silva, Wilson; Giuliano-Caetano, Lucia; Foresti, Fausto; Dias, Ana Lúcia

2017-06-01

The mapping of repetitive DNA sites by fluorescence in situ hybridization has been widely used for karyotype studies in different species of fish, especially when dealing with related species or even genera presenting high chromosome variability. This study analyzed three populations of Bryconamericus, with diploid number preserved, but with different karyotype formulae. Bryconamericus ecai, from the Forquetinha river/RS, presented three new cytotypes, increasing the number of karyotype forms to seven in this population. Other two populations of Bryconamericus sp. from the Vermelho stream/PR and Cambuta river/PR exhibited interpopulation variation. The chromosome mapping of rDNA sites revealed unique markings among the three populations, showing inter- and intrapopulation variability located in the terminal region. The molecular analysis using DNA barcoding complementing the cytogenetic analysis also showed differentiation among the three populations. The U2 small nuclear DNA repetitive sequence exhibited conserved features, being located in the interstitial region of a single chromosome pair. This is the first report on its occurrence in the genus Bryconamericus. Data obtained revealed a karyotype variability already assigned to the genus, along with polymorphism of ribosomal sites, demonstrating that this group of fish can be undergoing a divergent evolutionary process, constituting a substantive model for studies of chromosomal evolution.

Large variability of bathypelagic microbial eukaryotic communities across the world's oceans.

PubMed

Pernice, Massimo C; Giner, Caterina R; Logares, Ramiro; Perera-Bel, Júlia; Acinas, Silvia G; Duarte, Carlos M; Gasol, Josep M; Massana, Ramon

2016-04-01

In this work, we study the diversity of bathypelagic microbial eukaryotes (0.8-20 μm) in the global ocean. Seawater samples from 3000 to 4000 m depth from 27 stations in the Atlantic, Pacific and Indian Oceans were analyzed by pyrosequencing the V4 region of the 18S ribosomal DNA. The relative abundance of the most abundant operational taxonomic units agreed with the results of a parallel metagenomic analysis, suggesting limited PCR biases in the tag approach. Although rarefaction curves for single stations were seldom saturated, the global analysis of all sequences together suggested an adequate recovery of bathypelagic diversity. Community composition presented a large variability among samples, which was poorly explained by linear geographic distance. In fact, the similarity between communities was better explained by water mass composition (26% of the variability) and the ratio in cell abundance between prokaryotes and microbial eukaryotes (21%). Deep diversity appeared dominated by four taxonomic groups (Collodaria, Chrysophytes, Basidiomycota and MALV-II) appearing in different proportions in each sample. Novel diversity amounted to 1% of the pyrotags and was lower than expected. Our study represents an essential step in the investigation of bathypelagic microbial eukaryotes, indicating dominating taxonomic groups and suggesting idiosyncratic assemblages in distinct oceanic regions.

A Comparative Analysis of Machine Learning with WorldView-2 Pan-Sharpened Imagery for Tea Crop Mapping

PubMed Central

Chuang, Yung-Chung Matt; Shiu, Yi-Shiang

2016-01-01

Tea is an important but vulnerable economic crop in East Asia, highly impacted by climate change. This study attempts to interpret tea land use/land cover (LULC) using very high resolution WorldView-2 imagery of central Taiwan with both pixel and object-based approaches. A total of 80 variables derived from each WorldView-2 band with pan-sharpening, standardization, principal components and gray level co-occurrence matrix (GLCM) texture indices transformation, were set as the input variables. For pixel-based image analysis (PBIA), 34 variables were selected, including seven principal components, 21 GLCM texture indices and six original WorldView-2 bands. Results showed that support vector machine (SVM) had the highest tea crop classification accuracy (OA = 84.70% and KIA = 0.690), followed by random forest (RF), maximum likelihood algorithm (ML), and logistic regression analysis (LR). However, the ML classifier achieved the highest classification accuracy (OA = 96.04% and KIA = 0.887) in object-based image analysis (OBIA) using only six variables. The contribution of this study is to create a new framework for accurately identifying tea crops in a subtropical region with real-time high-resolution WorldView-2 imagery without field survey, which could further aid agriculture land management and a sustainable agricultural product supply. PMID:27128915

A Comparative Analysis of Machine Learning with WorldView-2 Pan-Sharpened Imagery for Tea Crop Mapping.

PubMed

Chuang, Yung-Chung Matt; Shiu, Yi-Shiang

2016-04-26

Tea is an important but vulnerable economic crop in East Asia, highly impacted by climate change. This study attempts to interpret tea land use/land cover (LULC) using very high resolution WorldView-2 imagery of central Taiwan with both pixel and object-based approaches. A total of 80 variables derived from each WorldView-2 band with pan-sharpening, standardization, principal components and gray level co-occurrence matrix (GLCM) texture indices transformation, were set as the input variables. For pixel-based image analysis (PBIA), 34 variables were selected, including seven principal components, 21 GLCM texture indices and six original WorldView-2 bands. Results showed that support vector machine (SVM) had the highest tea crop classification accuracy (OA = 84.70% and KIA = 0.690), followed by random forest (RF), maximum likelihood algorithm (ML), and logistic regression analysis (LR). However, the ML classifier achieved the highest classification accuracy (OA = 96.04% and KIA = 0.887) in object-based image analysis (OBIA) using only six variables. The contribution of this study is to create a new framework for accurately identifying tea crops in a subtropical region with real-time high-resolution WorldView-2 imagery without field survey, which could further aid agriculture land management and a sustainable agricultural product supply.

Factors Controlling Sediment Load in The Central Anatolia Region of Turkey: Ankara River Basin.

PubMed

Duru, Umit; Wohl, Ellen; Ahmadi, Mehdi

2017-05-01

Better understanding of the factors controlling sediment load at a catchment scale can facilitate estimation of soil erosion and sediment transport rates. The research summarized here enhances understanding of correlations between potential control variables on suspended sediment loads. The Soil and Water Assessment Tool was used to simulate flow and sediment at the Ankara River basin. Multivariable regression analysis and principal component analysis were then performed between sediment load and controlling variables. The physical variables were either directly derived from a Digital Elevation Model or from field maps or computed using established equations. Mean observed sediment rate is 6697 ton/year and mean sediment yield is 21 ton/y/km² from the gage. Soil and Water Assessment Tool satisfactorily simulated observed sediment load with Nash-Sutcliffe efficiency, relative error, and coefficient of determination (R²) values of 0.81, -1.55, and 0.93, respectively in the catchment. Therefore, parameter values from the physically based model were applied to the multivariable regression analysis as well as principal component analysis. The results indicate that stream flow, drainage area, and channel width explain most of the variability in sediment load among the catchments. The implications of the results, efficient siltation management practices in the catchment should be performed to stream flow, drainage area, and channel width.

Factors Controlling Sediment Load in The Central Anatolia Region of Turkey: Ankara River Basin

NASA Astrophysics Data System (ADS)

Duru, Umit; Wohl, Ellen; Ahmadi, Mehdi

2017-05-01

Better understanding of the factors controlling sediment load at a catchment scale can facilitate estimation of soil erosion and sediment transport rates. The research summarized here enhances understanding of correlations between potential control variables on suspended sediment loads. The Soil and Water Assessment Tool was used to simulate flow and sediment at the Ankara River basin. Multivariable regression analysis and principal component analysis were then performed between sediment load and controlling variables. The physical variables were either directly derived from a Digital Elevation Model or from field maps or computed using established equations. Mean observed sediment rate is 6697 ton/year and mean sediment yield is 21 ton/y/km² from the gage. Soil and Water Assessment Tool satisfactorily simulated observed sediment load with Nash-Sutcliffe efficiency, relative error, and coefficient of determination ( R²) values of 0.81, -1.55, and 0.93, respectively in the catchment. Therefore, parameter values from the physically based model were applied to the multivariable regression analysis as well as principal component analysis. The results indicate that stream flow, drainage area, and channel width explain most of the variability in sediment load among the catchments. The implications of the results, efficient siltation management practices in the catchment should be performed to stream flow, drainage area, and channel width.

Transport induced by mean-eddy interaction: II. Analysis of transport processes

NASA Astrophysics Data System (ADS)

Ide, Kayo; Wiggins, Stephen

2015-03-01

We present a framework for the analysis of transport processes resulting from the mean-eddy interaction in a flow. The framework is based on the Transport Induced by the Mean-Eddy Interaction (TIME) method presented in a companion paper (Ide and Wiggins, 2014) [1]. The TIME method estimates the (Lagrangian) transport across stationary (Eulerian) boundaries defined by chosen streamlines of the mean flow. Our framework proceeds after first carrying out a sequence of preparatory steps that link the flow dynamics to the transport processes. This includes the construction of the so-called "instantaneous flux" as the Hovmöller diagram. Transport processes are studied by linking the signals of the instantaneous flux field to the dynamical variability of the flow. This linkage also reveals how the variability of the flow contributes to the transport. The spatio-temporal analysis of the flux diagram can be used to assess the efficiency of the variability in transport processes. We apply the method to the double-gyre ocean circulation model in the situation where the Rossby-wave mode dominates the dynamic variability. The spatio-temporal analysis shows that the inter-gyre transport is controlled by the circulating eddy vortices in the fast eastward jet region, whereas the basin-scale Rossby waves have very little impact.

Brown dwarf photospheres are patchy: A Hubble space telescope near-infrared spectroscopic survey finds frequent low-level variability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buenzli, Esther; Apai, Dániel; Radigan, Jacqueline

2014-02-20

Condensate clouds strongly impact the spectra of brown dwarfs and exoplanets. Recent discoveries of variable L/T transition dwarfs argued for patchy clouds in at least some ultracool atmospheres. This study aims to measure the frequency and level of spectral variability in brown dwarfs and to search for correlations with spectral type. We used Hubble Space Telescope/Wide Field Camera 3 to obtain spectroscopic time series for 22 brown dwarfs of spectral types ranging from L5 to T6 at 1.1-1.7 μm for ≈40 minutes per object. Using Bayesian analysis, we find six brown dwarfs with confident (p > 95%) variability in themore » relative flux in at least one wavelength region at sub-percent precision, and five brown dwarfs with tentative (p > 68%) variability. We derive a minimum variability fraction f{sub min}=27{sub −7}{sup +11}% over all covered spectral types. The fraction of variables is equal within errors for mid-L, late-L, and mid-T spectral types; for early-T dwarfs we do not find any confident variable but the sample is too small to derive meaningful limits. For some objects, the variability occurs primarily in the flux peak in the J or H band, others are variable throughout the spectrum or only in specific absorption regions. Four sources may have broadband peak-to-peak amplitudes exceeding 1%. Our measurements are not sensitive to very long periods, inclinations near pole-on and rotationally symmetric heterogeneity. The detection statistics are consistent with most brown dwarf photospheres being patchy. While multiple-percent near-infrared variability may be rare and confined to the L/T transition, low-level heterogeneities are a frequent characteristic of brown dwarf atmospheres.« less

Regional and local species richness in an insular environment: Serpentine plants in California

USGS Publications Warehouse

Harrison, S.; Safford, H.D.; Grace, J.B.; Viers, J.H.; Davies, K.F.

2006-01-01

We asked how the richness of the specialized (endemic) flora of serpentine rock outcrops in California varies at both the regional and local scales. Our study had two goals: first, to test whether endemic richness is affected by spatial habitat structure (e.g., regional serpentine area, local serpentine outcrop area, regional and local measures of outcrop isolation), and second, to conduct this test in the context of a broader assessment of environmental influences (e.g., climate, soils, vegetation, disturbance) and historical influences (e.g., geologic age, geographic province) on local and regional species richness. We measured endemic and total richness and environmental variables in 109 serpentine sites (1000-m2 paired plots) in 78 serpentine-containing regions of the state. We used structural equation modeling (SEM) to simultaneously relate regional richness to regionalscale predictors, and local richness to both local-scale and regional-scale predictors. Our model for serpentine endemics explained 66% of the variation in local endemic richness based on local environment (vegetation, soils, rock cover) and on regional endemic richness. It explained 73% of the variation in regional endemic richness based on regional environment (climate and productivity), historical factors (geologic age and geographic province), and spatial structure (regional total area of serpentine, the only significant spatial variable in our analysis). We did not find a strong influence of spatial structure on species richness. However, we were able to distinguish local vs. regional influences on species richness to a novel extent, despite the existence of correlations between local and regional conditions. ?? 2006 by the Ecological Society of America.

Sub-seasonal temperature variability in the tropical upper troposphere and lower stratosphere observed with GPS radio occultation

NASA Astrophysics Data System (ADS)

Scherllin-Pirscher, Barbara; Randel, William J.; Kim, Joowan

2017-04-01

We investigate sub-seasonal temperature variability in the tropical upper troposphere and lower stratosphere (UTLS) region using daily gridded fields of GPS radio occultation measurements. The unprecedented vertical resolution (from about 100 m in the troposphere to about 1.5 km in the stratosphere) and high accuracy and precision (0.7 K to 1 K between 8 km and 25 km) make these data ideal for characterizing temperature oscillations with short vertical wavelengths. Long-term behavior of sub-seasonal temperature variability is investigated using the entire RO record from January 2002 to December 2014 (13 years of data). Transient sub-seasonal waves including eastward-propagating Kelvin waves (isolated with space-time spectral analysis) dominate large-scale zonal temperature variability in the tropical tropopause region and in the lower stratosphere. Above 20 km, Kelvin waves are strongly modulated by the quasi-biennial oscillation (QBO). Enhanced wave activity can be found during the westerly shear phase of the QBO. In the tropical tropopause region, however, sub-seasonal waves are highly transient in time. Several peaks of Kelvin-wave activity coincide with short-term fluctuations in tropospheric deep convection, but other episodes are not evidently related. Also, there are no obvious relationships with zonal winds or stability fields near the tropical tropopause. Further investigations of convective forcing and atmospheric background conditions along the waves' trajectories are needed to better understand sub-seasonal temperature variability near the tropopause. For more details, see Scherllin-Pirscher, B., Randel, W. J., and Kim, J.: Tropical temperature variability and Kelvin-wave activity in the UTLS from GPS RO measurements, Atmos. Chem. Phys., 17, 793-806, doi:10.5194/acp-17-793-2017, 2017. http://www.atmos-chem-phys.net/17/793/2017/acp-17-793-2017.html

A discussion of the links between solar variability and high-storm-surge events in Venice

NASA Astrophysics Data System (ADS)

Barriopedro, David; GarcíA-Herrera, Ricardo; Lionello, Piero; Pino, Cosimo

2010-07-01

This study explores the long-term frequency variability of high-surge events (HSEs) in the North Adriatic, the so-called acqua alta, which, particularly during autumn, cause flooding of the historical city center of Venice. The period 1948-2008, when hourly observations of sea level are available, is considered. The frequency of HSEs is correlated with the 11 year solar cycle, solar maxima being associated with a significant increase in the October-November-December HSE frequency. The seasonal geopotential height pattern at 1000 hPa (storm surge pattern; SSP) associated with the increased frequency of HSEs is identified for the whole time period and found to be similar to the positive phase of the main variability mode of the regional atmospheric circulation (empirical orthogonal function 1; EOF1). However, further analysis indicates that solar activity modulates the spatial patterns of the atmospheric circulation (EOF) and the favorable conditions for HSE occurrence (SSP). Under solar maxima, the occurrence of HSEs is enhanced by the main mode of regional atmospheric variability, namely, a large-scale wave train pattern that is symptomatic of storm track paths over northern Europe. Solar minima reveal a substantially different and less robust SSP, consisting of a meridionally oriented dipole with a preferred southward path of storm track activity, which is not associated with any dominant mode of atmospheric variability during low-solar periods. It is concluded that solar activity plays an indirect role in the frequency of HSEs by modulating the spatial patterns of the main modes of atmospheric regional variability, the favorable patterns for HSE occurrence, and their mutual relationships, so that constructive interaction between them is enhanced during solar maxima and inhibited in solar minima.

Image-Subtraction Photometry of Variable Stars in the Globular Clusters NGC 6388 and NGC 6441

NASA Technical Reports Server (NTRS)

Corwin, Michael T.; Sumerel, Andrew N.; Pritzl, Barton J.; Smith, Horace A.; Catelan, M.; Sweigart, Allen V.; Stetson, Peter B.

2006-01-01

We have applied Alard's image subtraction method (ISIS v2.1) to the observations of the globular clusters NGC 6388 and NGC 6441 previously analyzed using standard photometric techniques (DAOPHOT, ALLFRAME). In this reanalysis of observations obtained at CTIO, besides recovering the variables previously detected on the basis of our ground-based images, we have also been able to recover most of the RR Lyrae variables previously detected only in the analysis of Hubble Space Telescope WFPC2 observations of the inner region of NGC 6441. In addition, we report five possible new variables not found in the analysis of the EST observations of NGC 6441. This dramatically illustrates the capabilities of image subtraction techniques applied to ground-based data to recover variables in extremely crowded fields. We have also detected twelve new variables and six possible variables in NGC 6388 not found in our previous groundbased studies. Revised mean periods for RRab stars in NGC 6388 and NGC 6441 are 0.676 day and 0.756 day, respectively. These values are among the largest known for any galactic globular cluster. Additional probable type II Cepheids were identified in NGC 6388, confirming its status as a metal-rich globular cluster rich in Cepheids.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Horowitz, Kelsey A; Bench Reese, Samantha R; Remo, Timothy W

This brochure, published as an annual research highlight of the Clean Energy Manufacturing Analysis Center (CEMAC), summarizes CEMAC analysis of silicon carbide (SiC) power electronics for variable frequency motor drives. The key finding presented is that variations in manufacturing expertise, yields, and access to existing facilities impact regional costs and manufacturing location decisions for SiC ingots, wafers, chips, and power modules more than do core country-specific factors such as labor and electricity costs.

Drought assessment using a TRMM-derived standardized precipitation index for the upper São Francisco River basin, Brazil.

PubMed

Santos, Celso Augusto Guimarães; Brasil Neto, Reginaldo Moura; Passos, Jacqueline Sobral de Araújo; da Silva, Richarde Marques

2017-06-01

In this work, the use of Tropical Rainfall Measuring Mission (TRMM) rainfall data and the Standardized Precipitation Index (SPI) for monitoring spatial and temporal drought variabilities in the Upper São Francisco River basin is investigated. Thus, the spatiotemporal behavior of droughts and cluster regions with similar behaviors is identified. As a result, the joint analysis of clusters, dendrograms, and the spatial distribution of SPI values proved to be a powerful tool in identifying homogeneous regions. The results showed that the northeast region of the basin has the lowest rainfall indices and the southwest region has the highest rainfall depths, and that the region has well-defined dry and rainy seasons from June to August and November to January, respectively. An analysis of the drought and rain conditions showed that the studied region was homogeneous and well-distributed; however, the quantity of extreme and severe drought events in short-, medium- and long-term analysis was higher than that expected in regions with high rainfall depths, particularly in the south/southwest and southeast areas. Thus, an alternative classification is proposed to characterize the drought, which spatially categorizes the drought type (short-, medium-, and long-term) according to the analyzed drought event type (extreme, severe, moderate, and mild).

Solar Spectral Irradiance Variability of Some Chromospheric Emission Lines Through the Solar Activity Cycles 21-23

NASA Astrophysics Data System (ADS)

Göker, Ü. D.; Gigolashvili, M. Sh.; Kapanadze, N.

2017-06-01

A study of variations of solar spectral irradiance (SSI) in the wavelength ranges 121.5 nm-300.5 nm for the period 1981-2009 is presented. We used various data for ultraviolet (UV) spectral lines and international sunspot number (ISSN) from interactive data centers such as SME (NSSDC), UARS (GDAAC), SORCE (LISIRD) and SIDC, respectively. We reduced these data by using the MATLAB software package. In this respect, we revealed negative correlations of intensities of UV (289.5 nm-300.5 nm) spectral lines originating in the solar chromosphere with the ISSN index during the unusually prolonged minimum between the solar activity cycles (SACs) 23 and 24. We also compared our results with the variations of solar activity indices obtained by the ground-based telescopes. Therefore, we found that plage regions decrease while facular areas are increasing in SAC 23. However, the decrease in plage regions is seen in small sunspot groups (SGs), contrary to this, these regions in large SGs are comparable to previous SACs or even larger as is also seen in facular areas. Nevertheless, negative correlations between ISSN and SSI data indicate that these variations are in close connection with the classes of sunspots/SGs, faculae and plage regions. Finally, we applied the time series analysis of spectral lines corresponding to the wavelengths 121.5 nm-300.5 nm and made comparisons with the ISSN data. We found an unexpected increase in the 298.5 nm line for the Fe II ion. The variability of Fe II ion 298.5 nm line is in close connection with the facular areas and plage regions, and the sizes of these solar surface indices play an important role for the SSI variability, as well. So, we compared the connection between the sizes of faculae and plage regions, sunspots/SGs, chemical elements and SSI variability. Our future work will be the theoretical study of this connection and developing of a corresponding model.

Seasonal forecasts in the Sahel region: the use of rainfall-based predictive variables

NASA Astrophysics Data System (ADS)

Lodoun, Tiganadaba; Sanon, Moussa; Giannini, Alessandra; Traoré, Pierre Sibiry; Somé, Léopold; Rasolodimby, Jeanne Millogo

2014-08-01

In the Sahel region, seasonal predictions are crucial to alleviate the impacts of climate variability on populations' livelihoods. Agricultural planning (e.g., decisions about sowing date, fertilizer application date, and choice of crop or cultivar) is based on empirical predictive indices whose accuracy to date has not been scientifically proven. This paper attempts to statistically test whether the pattern of rainfall distribution over the May-July period contributes to predicting the real onset date and the nature (wet or dry) of the rainy season, as farmers believe. To that end, we considered historical records of daily rainfall from 51 stations spanning the period 1920-2008 and the different agro-climatic zones in Burkina Faso. We performed (1) principal component analysis to identify climatic zones, based on the patterns of intra-seasonal rainfall, (2) and linear discriminant analysis to find the best rainfall-based variables to distinguish between real and false onset dates of the rainy season, and between wet and dry seasons in each climatic zone. A total of nine climatic zones were identified in each of which, based on rainfall records from May to July, we derived linear discriminant functions to correctly predict the nature of a potential onset date of the rainy season (real or false) and that of the rainy season (dry or wet) in at least three cases out of five. These functions should contribute to alleviating the negative impacts of climate variability in the different climatic zones of Burkina Faso.

Global assessment of surfing conditions: seasonal, interannual and long-term variability

NASA Astrophysics Data System (ADS)

Espejo, A.; Losada, I.; Mendez, F.

2012-12-01

International surfing destinations owe a great debt to specific combinations of wind-wave, thermal conditions and local bathymetry. As surf quality depends on a vast number of geophysical variables, a multivariable standardized index on the basis of expert judgment is proposed to analyze surf resource in a worldwide domain. Data needed is obtained by combining several datasets (reanalyses): 60-year satellite-calibrated spectral wave hindcast (GOW, WaveWatchIII), wind fields from NCEP/NCAR, global sea surface temperature from ERSST.v3b, and global tides from TPXO7.1. A summary of the global surf resource is presented, which highlights the high degree of variability in surfable events. According to general atmospheric circulation, results show that west facing low to middle latitude coasts are more suitable for surfing, especially those in Southern Hemisphere. Month to month analysis reveals strong seasonal changes in the occurrence of surfable events, enhancing those in North Atlantic or North Pacific. Interannual variability is investigated by comparing occurrence values with global and regional climate patterns showing a great influence at both, global and regional scales. Analysis of long term trends shows an increase in the probability of surfable events over the west facing coasts on the planet (i.e. + 30 hours/year in California). The resulting maps provide useful information for surfers and surf related stakeholders, coastal planning, education, and basic research.; Figure 1. Global distribution of medium quality (a) and high quality surf conditions probability (b).