Predicting Local Dengue Transmission in Guangzhou, China, through the Influence of Imported Cases, Mosquito Density and Climate Variability

PubMed Central

Sang, Shaowei; Yin, Wenwu; Bi, Peng; Zhang, Honglong; Wang, Chenggang; Liu, Xiaobo; Chen, Bin; Yang, Weizhong; Liu, Qiyong

2014-01-01

Introduction Each year there are approximately 390 million dengue infections worldwide. Weather variables have a significant impact on the transmission of Dengue Fever (DF), a mosquito borne viral disease. DF in mainland China is characterized as an imported disease. Hence it is necessary to explore the roles of imported cases, mosquito density and climate variability in dengue transmission in China. The study was to identify the relationship between dengue occurrence and possible risk factors and to develop a predicting model for dengue’s control and prevention purpose. Methodology and Principal Findings Three traditional suburbs and one district with an international airport in Guangzhou city were selected as the study areas. Autocorrelation and cross-correlation analysis were used to perform univariate analysis to identify possible risk factors, with relevant lagged effects, associated with local dengue cases. Principal component analysis (PCA) was applied to extract principal components and PCA score was used to represent the original variables to reduce multi-collinearity. Combining the univariate analysis and prior knowledge, time-series Poisson regression analysis was conducted to quantify the relationship between weather variables, Breteau Index, imported DF cases and the local dengue transmission in Guangzhou, China. The goodness-of-fit of the constructed model was determined by pseudo-R2, Akaike information criterion (AIC) and residual test. There were a total of 707 notified local DF cases from March 2006 to December 2012, with a seasonal distribution from August to November. There were a total of 65 notified imported DF cases from 20 countries, with forty-six cases (70.8%) imported from Southeast Asia. The model showed that local DF cases were positively associated with mosquito density, imported cases, temperature, precipitation, vapour pressure and minimum relative humidity, whilst being negatively associated with air pressure, with different time

Predicting local dengue transmission in Guangzhou, China, through the influence of imported cases, mosquito density and climate variability.

PubMed

Sang, Shaowei; Yin, Wenwu; Bi, Peng; Zhang, Honglong; Wang, Chenggang; Liu, Xiaobo; Chen, Bin; Yang, Weizhong; Liu, Qiyong

2014-01-01

Each year there are approximately 390 million dengue infections worldwide. Weather variables have a significant impact on the transmission of Dengue Fever (DF), a mosquito borne viral disease. DF in mainland China is characterized as an imported disease. Hence it is necessary to explore the roles of imported cases, mosquito density and climate variability in dengue transmission in China. The study was to identify the relationship between dengue occurrence and possible risk factors and to develop a predicting model for dengue's control and prevention purpose. Three traditional suburbs and one district with an international airport in Guangzhou city were selected as the study areas. Autocorrelation and cross-correlation analysis were used to perform univariate analysis to identify possible risk factors, with relevant lagged effects, associated with local dengue cases. Principal component analysis (PCA) was applied to extract principal components and PCA score was used to represent the original variables to reduce multi-collinearity. Combining the univariate analysis and prior knowledge, time-series Poisson regression analysis was conducted to quantify the relationship between weather variables, Breteau Index, imported DF cases and the local dengue transmission in Guangzhou, China. The goodness-of-fit of the constructed model was determined by pseudo-R2, Akaike information criterion (AIC) and residual test. There were a total of 707 notified local DF cases from March 2006 to December 2012, with a seasonal distribution from August to November. There were a total of 65 notified imported DF cases from 20 countries, with forty-six cases (70.8%) imported from Southeast Asia. The model showed that local DF cases were positively associated with mosquito density, imported cases, temperature, precipitation, vapour pressure and minimum relative humidity, whilst being negatively associated with air pressure, with different time lags. Imported DF cases and mosquito density play a

What variables are important in predicting bovine viral diarrhea virus? A random forest approach.

PubMed

Machado, Gustavo; Mendoza, Mariana Recamonde; Corbellini, Luis Gustavo

2015-07-24

Bovine viral diarrhea virus (BVDV) causes one of the most economically important diseases in cattle, and the virus is found worldwide. A better understanding of the disease associated factors is a crucial step towards the definition of strategies for control and eradication. In this study we trained a random forest (RF) prediction model and performed variable importance analysis to identify factors associated with BVDV occurrence. In addition, we assessed the influence of features selection on RF performance and evaluated its predictive power relative to other popular classifiers and to logistic regression. We found that RF classification model resulted in an average error rate of 32.03% for the negative class (negative for BVDV) and 36.78% for the positive class (positive for BVDV).The RF model presented area under the ROC curve equal to 0.702. Variable importance analysis revealed that important predictors of BVDV occurrence were: a) who inseminates the animals, b) number of neighboring farms that have cattle and c) rectal palpation performed routinely. Our results suggest that the use of machine learning algorithms, especially RF, is a promising methodology for the analysis of cross-sectional studies, presenting a satisfactory predictive power and the ability to identify predictors that represent potential risk factors for BVDV investigation. We examined classical predictors and found some new and hard to control practices that may lead to the spread of this disease within and among farms, mainly regarding poor or neglected reproduction management, which should be considered for disease control and eradication.

Identifying important motivational factors for professionals in Greek hospitals

PubMed Central

Kontodimopoulos, Nick; Paleologou, Victoria; Niakas, Dimitris

2009-01-01

Background The purpose of this study was to identify important motivational factors according to the views of health-care professionals in Greek hospitals and particularly to determine if these might differ in the public and private sectors. Methods A previously developed -and validated- instrument addressing four work-related motivators (job attributes, remuneration, co-workers and achievements) was used. Three categories of health care professionals, doctors (N = 354), nurses (N = 581) and office workers (N = 418), working in public and private hospitals, participated and motivation was compared across socio-demographic and occupational variables. Results The range of reported motivational factors was mixed and Maslow's conclusions that lower level motivational factors must be met before ascending to the next level were not confirmed. The highest ranked motivator for the entire sample, and by professional subgroup, was achievements (P < 0.001). Within subgroups, motivators were similar, and only one significant difference was observed, namely between doctors and nurses in respect to co-workers (P < 0.05). Remuneration (and salary in particular) was reported as a significant incentive only for professionals in managerial positions. Health professionals in private hospitals were motivated by all factors significantly more than their public-hospital counterparts. Conclusion The results are in agreement with the literature which focuses attention to management approaches employing both monetary and non-monetary incentives to motivate health care workers. This study showed that intrinsic factors are particularly important and should become a target for effective employee motivation. PMID:19754968

What Variables Appear Important in Changing Traditional Inservice Training Procedures.

ERIC Educational Resources Information Center

Sobol, Francis Thomas

Herein are discussed descriptive findings from the educational literature on the question of what variables appear important in changing traditional in-service training procedures. The question of the content versus the process of in-service training, important problems in in-service training programs, and implications of the important problems…

The importance of histopathological and clinical variables in predicting the evolution of colon cancer.

PubMed

Diculescu, Mircea; Iacob, Răzvan; Iacob, Speranţa; Croitoru, Adina; Becheanu, Gabriel; Popeneciu, Valentin

2002-09-01

It has been a consensus that prognostic factors should always be taken into account before planning treatment in colorectal cancer. A 5 year prospective study was conducted, in order to assess the importance of several histopathological and clinical prognostic variables in the prediction of evolution in colon cancer. Some of the factors included in the analysis are still subject to dispute by different authors. 46 of 53 screened patients qualified to enter the study and underwent a potentially curative resection of the tumor, followed, when necessary, by adjuvant chemotherapy. Univariate and multivariate analyses were carried out in order to identify independent prognostic indicators. The endpoint of the study was considered the recurrence of the tumor or the detection of metastases. 65.2% of the patients had a good evolution during the follow up period. Multivariate survival analysis performed by Cox proportional hazard model identified 3 independent prognostic factors: Dukes stage (p = 0.00002), the grade of differentiation (p = 0.0009) and the weight loss index, representing the weight loss of the patient divided by the number of months when it was actually lost (p = 0.02). Age under 40 years, sex, microscopic aspect of the tumor, tumor location, anemia degree were not identified by our analysis as having prognostic importance. Histopathological factors continue to be the most valuable source of information regarding the possible evolution of patients with colorectal cancer. Individual clinical symptoms or biological parameters such as erytrocyte sedimentation rate or hemoglobin level are of little or no prognostic value. More research is required relating to the impact of a performance status index (which could include also weight loss index) as another reliable prognostic variable.

Field potential soil variability index to identify precision agriculture opportunity

USDA-ARS?s Scientific Manuscript database

Precision agriculture (PA) technologies used for identifying and managing within-field variability are not widely used despite decades of advancement. Technological innovations in agronomic tools, such as canopy reflectance or electrical conductivity sensors, have created opportunities to achieve a ...

Optical Spectra of Four Objects Identified with Variable Radio Sources

NASA Astrophysics Data System (ADS)

Chavushyan, V.; Mujica, R.; Gorshkov, A. G.; Konnikova, V. K.; Mingaliev, M. G.

2000-06-01

We obtained optical spectra of four objects identified with variable radio sources. Three objects (0029+0554, 0400+0550, 2245+0500) were found to be quasars with redshifts of 1.314, 0.761, and 1.091. One object (2349+0534) has a continuum spectrum characteristic of BL Lac objects. We analyze spectra of the radio sources in the range 0.97-21.7 GHz for the epoch 1997 and in the range 3.9-11.1 GHz for the epoch 1990, as well as the pattern of variability of their flux densities on time scales of 1.5 and 7 years.

Variable importance in nonlinear kernels (VINK): classification of digitized histopathology.

PubMed

Ginsburg, Shoshana; Ali, Sahirzeeshan; Lee, George; Basavanhally, Ajay; Madabhushi, Anant

2013-01-01

Quantitative histomorphometry is the process of modeling appearance of disease morphology on digitized histopathology images via image-based features (e.g., texture, graphs). Due to the curse of dimensionality, building classifiers with large numbers of features requires feature selection (which may require a large training set) or dimensionality reduction (DR). DR methods map the original high-dimensional features in terms of eigenvectors and eigenvalues, which limits the potential for feature transparency or interpretability. Although methods exist for variable selection and ranking on embeddings obtained via linear DR schemes (e.g., principal components analysis (PCA)), similar methods do not yet exist for nonlinear DR (NLDR) methods. In this work we present a simple yet elegant method for approximating the mapping between the data in the original feature space and the transformed data in the kernel PCA (KPCA) embedding space; this mapping provides the basis for quantification of variable importance in nonlinear kernels (VINK). We show how VINK can be implemented in conjunction with the popular Isomap and Laplacian eigenmap algorithms. VINK is evaluated in the contexts of three different problems in digital pathology: (1) predicting five year PSA failure following radical prostatectomy, (2) predicting Oncotype DX recurrence risk scores for ER+ breast cancers, and (3) distinguishing good and poor outcome p16+ oropharyngeal tumors. We demonstrate that subsets of features identified by VINK provide similar or better classification or regression performance compared to the original high dimensional feature sets.

Identifying populations sensitive to environmental chemicals by simulating toxicokinetic variability.

PubMed

Ring, Caroline L; Pearce, Robert G; Setzer, R Woodrow; Wetmore, Barbara A; Wambaugh, John F

2017-09-01

The thousands of chemicals present in the environment (USGAO, 2013) must be triaged to identify priority chemicals for human health risk research. Most chemicals have little of the toxicokinetic (TK) data that are necessary for relating exposures to tissue concentrations that are believed to be toxic. Ongoing efforts have collected limited, in vitro TK data for a few hundred chemicals. These data have been combined with biomonitoring data to estimate an approximate margin between potential hazard and exposure. The most "at risk" 95th percentile of adults have been identified from simulated populations that are generated either using standard "average" adult human parameters or very specific cohorts such as Northern Europeans. To better reflect the modern U.S. population, we developed a population simulation using physiologies based on distributions of demographic and anthropometric quantities from the most recent U.S. Centers for Disease Control and Prevention National Health and Nutrition Examination Survey (NHANES) data. This allowed incorporation of inter-individual variability, including variability across relevant demographic subgroups. Variability was analyzed with a Monte Carlo approach that accounted for the correlation structure in physiological parameters. To identify portions of the U.S. population that are more at risk for specific chemicals, physiologic variability was incorporated within an open-source high-throughput (HT) TK modeling framework. We prioritized 50 chemicals based on estimates of both potential hazard and exposure. Potential hazard was estimated from in vitro HT screening assays (i.e., the Tox21 and ToxCast programs). Bioactive in vitro concentrations were extrapolated to doses that produce equivalent concentrations in body tissues using a reverse dosimetry approach in which generic TK models are parameterized with: 1) chemical-specific parameters derived from in vitro measurements and predicted from chemical structure; and 2) with

Barcode Identifiers as a Practical Tool for Reliable Species Assignment of Medically Important Black Yeast Species

PubMed Central

Heinrichs, Guido; de Hoog, G. Sybren

2012-01-01

Herpotrichiellaceous black yeasts and relatives comprise severe pathogens flanked by nonpathogenic environmental siblings. Reliable identification by conventional methods is notoriously difficult. Molecular identification is hampered by the sequence variability in the internal transcribed spacer (ITS) domain caused by difficult-to-sequence homopolymeric regions and by poor taxonomic attribution of sequences deposited in GenBank. Here, we present a potential solution using short barcode identifiers (27 to 50 bp) based on ITS2 ribosomal DNA (rDNA), which allows unambiguous definition of species-specific fragments. Starting from proven sequences of ex-type and authentic strains, we were able to describe 103 identifiers. Multiple BLAST searches of these proposed barcode identifiers in GenBank revealed uniqueness for 100 taxonomic entities, whereas the three remaining identifiers each matched with two entities, but the species of these identifiers could easily be discriminated by differences in the remaining ITS regions. Using the proposed barcode identifiers, a 4.1-fold increase of 100% matches in GenBank was achieved in comparison to the classical approach using the complete ITS sequences. The proposed barcode identifiers will be made accessible for the diagnostic laboratory in a permanently updated online database, thereby providing a highly practical, reliable, and cost-effective tool for identification of clinically important black yeasts and relatives. PMID:22785187

Identifying marine Important Bird Areas using at-sea survey data

USGS Publications Warehouse

Smith, Melanie A.; Walker, Nathan J.; Free, Christopher M.; Kirchhoff, Matthew J.; Drew, Gary S.; Warnock, Nils; Stenhouse, Iain J.

2014-01-01

Effective marine bird conservation requires identification of at-sea locations used by populations for foraging, staging, and migration. Using an extensive database of at-sea survey data spanning over 30 years, we developed a standardized and data-driven spatial method for identifying globally significant marine Important Bird Areas in Alaska. To delineate these areas we developed a six-step process: binning data and accounting for unequal survey effort, filtering input data for persistence of species use, using a moving window analysis to produce maps representing a gradient from low to high abundance, drawing core area boundaries around major concentrations based on abundance thresholds, validating the results, and combining overlapping boundaries into important areas for multiple species. We identified 126 bird core areas which were merged into 59 pelagic sites important to 45 out of 57 species assessed. The final areas included approximately 34–38% of all marine birds in Alaska waters, within just 6% of the total area. We identified globally significant Important Bird Areas spanning 20 degrees of latitude and 56 degrees of longitude, in two different oceans, with climates ranging from temperate to polar. Although our maps did suffer from some data gaps, these gaps did not preclude us from identifying sites that incorporated 13% of the assessed continental waterbird population and 9% of the assessed global seabird population. The application of this technique over a large and productive region worked well for a wide range of birds, exhibiting a variety of foraging strategies and occupying a variety of ecosystem types.

Examining Preservice Science Teachers' Skills of Formulating Hypotheses and Identifying Variables

ERIC Educational Resources Information Center

Aydogdu, Bülent

2015-01-01

The aim of this study is to examine preservice science teachers' skills of formulating hypotheses and identifying variables. The research has a phenomenological research design. The data was gathered qualitatively. In this study, preservice science teachers were first given two scenarios (Scenario-1 & Scenario-2) containing two different…

Analysis of individual cells identifies cell-to-cell variability following induction of cellular senescence.

PubMed

Wiley, Christopher D; Flynn, James M; Morrissey, Christapher; Lebofsky, Ronald; Shuga, Joe; Dong, Xiao; Unger, Marc A; Vijg, Jan; Melov, Simon; Campisi, Judith

2017-10-01

Senescent cells play important roles in both physiological and pathological processes, including cancer and aging. In all cases, however, senescent cells comprise only a small fraction of tissues. Senescent phenotypes have been studied largely in relatively homogeneous populations of cultured cells. In vivo, senescent cells are generally identified by a small number of markers, but whether and how these markers vary among individual cells is unknown. We therefore utilized a combination of single-cell isolation and a nanofluidic PCR platform to determine the contributions of individual cells to the overall gene expression profile of senescent human fibroblast populations. Individual senescent cells were surprisingly heterogeneous in their gene expression signatures. This cell-to-cell variability resulted in a loss of correlation among the expression of several senescence-associated genes. Many genes encoding senescence-associated secretory phenotype (SASP) factors, a major contributor to the effects of senescent cells in vivo, showed marked variability with a subset of highly induced genes accounting for the increases observed at the population level. Inflammatory genes in clustered genomic loci showed a greater correlation with senescence compared to nonclustered loci, suggesting that these genes are coregulated by genomic location. Together, these data offer new insights into how genes are regulated in senescent cells and suggest that single markers are inadequate to identify senescent cells in vivo. © 2017 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.

Temporal variability in the importance of hydrologic, biotic, and climatic descriptors of dissolved oxygen dynamics in a shallow tidal-marsh creek

NASA Astrophysics Data System (ADS)

Nelson, Natalie G.; Muñoz-Carpena, Rafael; Neale, Patrick J.; Tzortziou, Maria; Megonigal, J. Patrick

2017-08-01

Due to strong abiotic forcing, dissolved oxygen (DO) in shallow tidal creeks often disobeys the conventional explanation of general aquatic DO cycling as biologically regulated. In the present work, we seek to quantify the relative importance of abiotic (hydrologic and climatic), and biotic (primary productivity as represented by chlorophyll-a) descriptors of tidal creek DO. By fitting multiple linear regression models of DO to hourly chlorophyll-a, water quality, hydrology, and weather data collected in a tidal creek of a Chesapeake Bay marsh (Maryland, USA), temporal shifts (summer-early winter) in the relative importance of tidal creek DO descriptors were uncovered. Moreover, this analysis identified an alternative approach to evaluating tidal stage as a driver of DO by dividing stage into two DO-relevant variables: stage above and below bankfull depth. Within the hydrologic variable class, stage below bankfull depth dominated as an important descriptor, thus highlighting the role of pore water drainage and mixing as influential processes forcing tidal creek DO. Study findings suggest that tidal creek DO dynamics are explained by a balance of hydrologic, climatic, and biotic descriptors during warmer seasons due to many of these variables (i.e., chlorophyll-a, water temperature) acting as tracers of estuarine-marsh water mixing; conversely, in early winter months when estuarine and marsh waters differ less distinctly, hydrologic variables increase in relative importance as descriptors of tidal creek DO. These findings underline important distinctions in the underlying mechanisms dictating DO variability in shallow tidal marsh-creek environments relative to open water estuarine systems.

Temporal variability in the importance of hydrologic, biotic, and climatic descriptors of dissolved oxygen dynamics in a shallow tidal-marsh creek

NASA Astrophysics Data System (ADS)

Nelson, N.; Munoz-Carpena, R.; Neale, P.; Tzortziou, M.; Megonigal, P.

2017-12-01

Due to strong abiotic forcing, dissolved oxygen (DO) in shallow tidal creeks often disobeys the conventional explanation of general aquatic DO cycling as biologically-regulated. In the present work, we seek to quantify the relative importance of abiotic (hydrologic and climatic), and biotic (primary productivity as represented by chlorophyll-a) descriptors of tidal creek DO. By fitting multiple linear regression models of DO to hourly chlorophyll-a, water quality, hydrology, and weather data collected in a tidal creek of a Chesapeake Bay marsh (Maryland, USA), temporal shifts (summer - early winter) in the relative importance of tidal creek DO descriptors were uncovered. Moreover, this analysis identified an alternative approach to evaluating tidal stage as a driver of DO by dividing stage into two DO-relevant variables: stage above and below bankfull depth. Within the hydrologic variable class, stage below bankfull depth dominated as an important descriptor, thus highlighting the role of pore water drainage and mixing as influential processes forcing tidal creek DO. Study findings suggest that tidal creek DO dynamics are explained by a balance of hydrologic, climatic, and biotic descriptors during warmer seasons due to many of these variables (i.e., chlorophyll-a, water temperature) acting as tracers of estuarine-marsh water mixing; conversely, in early winter months when estuarine and marsh waters differ less distinctly, hydrologic variables increase in relative importance as descriptors of tidal creek DO. These findings underline important distinctions in the underlying mechanisms dictating DO variability in shallow tidal marsh-creek environments relative to open water estuarine systems.

Identifying Student Difficulties with Control of Variables Reasoning

NASA Astrophysics Data System (ADS)

Boudreaux, Andrew

2005-03-01

Emerging standards for the science learning of precollege students can be regarded as a statement of what constitutes science literacy.^1 These standards emphasize basic concepts such as mass, volume and density, and fundamental process skills such as proportional reasoning, the interpretation of graphs and other representations, and the control of variables in the design of experiments. At Western Washington University, the liberal arts physics course is a general university requirement and for many students one of the only physical science course taken between high school and college graduation. Thus the pre-course understandings of these students can be taken as a measure of the level of science literacy attained in precollege education. An effort is underway at Western Washington University to examine what students know and are able to do both before and after course instruction. Preliminary results indicate that in many cases students have serious conceptual and reasoning difficulties with the material. An example that involves the interpretation of experimental results in deciding whether a particular variable influences (i.e., affects) or determines (i.e., predicts) a given result will be discussed. Evidence from written questions will be presented to identify specific student difficulties.^1See, for example, Project 2061, American Association for the Advancement of Science. 1990. Science for All Americans.New York, NY: Oxford University Press.

Spatially-Resolved Influence of Temperature and Salinity on Stock and Recruitment Variability of Commercially Important Fishes in the North Sea

PubMed Central

Akimova, Anna; Núñez-Riboni, Ismael; Kempf, Alexander; Taylor, Marc H.

2016-01-01

Understanding of the processes affecting recruitment of commercially important fish species is one of the major challenges in fisheries science. Towards this aim, we investigated the relation between North Sea hydrography (temperature and salinity) and fish stock variables (recruitment, spawning stock biomass and pre-recruitment survival index) for 9 commercially important fishes using spatially-resolved cross-correlation analysis. We used high-resolution (0.2° × 0.2°) hydrographic data fields matching the maximal temporal extent of the fish population assessments (1948–2013). Our approach allowed for the identification of regions in the North Sea where environmental variables seem to be more influential on the fish stocks, as well as the regions of a lesser or nil influence. Our results confirmed previously demonstrated negative correlations between temperature and recruitment of cod and plaice and identified regions of the strongest correlations (German Bight for plaice and north-western North Sea for cod). We also revealed a positive correlation between herring spawning stock biomass and temperature in the Orkney-Shetland area, as well as a negative correlation between sole pre-recruitment survival index and temperature in the German Bight. A strong positive correlation between sprat stock variables and salinity in the central North Sea was also found. To our knowledge the results concerning correlations between North Sea hydrography and stocks’ dynamics of herring, sole and sprat are novel. The new information about spatial distribution of the correlation provides an additional help to identify mechanisms underlying these correlations. As an illustration of the utility of these results for fishery management, an example is provided that incorporates the identified environmental covariates in stock-recruitment models. PMID:27584155

Using abiotic variables to predict importance of sites for species representation.

PubMed

Albuquerque, Fabio; Beier, Paul

2015-10-01

In systematic conservation planning, species distribution data for all sites in a planning area are used to prioritize each site in terms of the site's importance toward meeting the goal of species representation. But comprehensive species data are not available in most planning areas and would be expensive to acquire. As a shortcut, ecologists use surrogates, such as occurrences of birds or another well-surveyed taxon, or land types defined from remotely sensed data, in the hope that sites that represent the surrogates also represent biodiversity. Unfortunately, surrogates have not performed reliably. We propose a new type of surrogate, predicted importance, that can be developed from species data for a q% subset of sites. With species data from this subset of sites, importance can be modeled as a function of abiotic variables available at no charge for all terrestrial areas on Earth. Predicted importance can then be used as a surrogate to prioritize all sites. We tested this surrogate with 8 sets of species data. For each data set, we used a q% subset of sites to model importance as a function of abiotic variables, used the resulting function to predict importance for all sites, and evaluated the number of species in the sites with highest predicted importance. Sites with the highest predicted importance represented species efficiently for all data sets when q = 25% and for 7 of 8 data sets when q = 20%. Predicted importance requires less survey effort than direct selection for species representation and meets representation goals well compared with other surrogates currently in use. This less expensive surrogate may be useful in those areas of the world that need it most, namely tropical regions with the highest biodiversity, greatest biodiversity loss, most severe lack of inventory data, and poorly developed protected area networks. © 2015 Society for Conservation Biology.

The Importance of Freshwater to Spatial Variability of Aragonite Saturation State in the Gulf of Alaska

NASA Astrophysics Data System (ADS)

Siedlecki, Samantha A.; Pilcher, Darren J.; Hermann, Albert J.; Coyle, Ken; Mathis, Jeremy

2017-11-01

High-latitude and subpolar regions like the Gulf of Alaska (GOA) are more vulnerable than equatorial regions to rising carbon dioxide (CO2) levels, in part due to local processes that amplify the global signal. Recent field observations have shown that the shelf of the GOA is currently experiencing seasonal corrosive events (carbonate mineral saturation states Ω, Ω < 1), including suppressed Ω in response to ocean acidification as well as local processes like increased low-alkalinity glacial meltwater discharge. While the glacial discharge mainly influences the inner shelf, on the outer shelf, upwelling brings corrosive waters from the deep GOA. In this work, we develop a high-resolution model for carbon dynamics in the GOA, identify regions of high variability of Ω, and test the sensitivity of those regions to changes in the chemistry of glacial meltwater discharge. Results indicate the importance of this climatically sensitive and relatively unconstrained regional freshwater forcing for Ω variability in the nearshore. The increase was nearly linear at 0.002 Ω per 100 µmol/kg increase in alkalinity in the freshwater runoff. We find that the local winds, biological processes, and freshwater forcing all contribute to the spatial distribution of Ω and identify which of these three is highly correlated to the variability in Ω. Given that the timing and magnitude of these processes will likely change during the next few decades, it is critical to elucidate the effect of local processes on the background ocean acidification signal using robust models, such as the one described here.

Identifying individuality and variability in team tactics by means of statistical shape analysis and multilayer perceptrons.

PubMed

Jäger, Jörg M; Schöllhorn, Wolfgang I

2012-04-01

Offensive and defensive systems of play represent important aspects of team sports. They include the players' positions at certain situations during a match, i.e., when players have to be on specific positions on the court. Patterns of play emerge based on the formations of the players on the court. Recognition of these patterns is important to react adequately and to adjust own strategies to the opponent. Furthermore, the ability to apply variable patterns of play seems to be promising since they make it harder for the opponent to adjust. The purpose of this study is to identify different team tactical patterns in volleyball and to analyze differences in variability. Overall 120 standard situations of six national teams in women's volleyball are analyzed during a world championship tournament. Twenty situations from each national team are chosen, including the base defence position (start configuration) and the two players block with middle back deep (end configuration). The shapes of the defence formations at the start and end configurations during the defence of each national team as well as the variability of these defence formations are statistically analyzed. Furthermore these shapes data are used to train multilayer perceptrons in order to test whether artificial neural networks can recognize the teams by their tactical patterns. Results show significant differences between the national teams in both the base defence position at the start and the two players block with middle back deep at the end of the standard defence situation. Furthermore, the national teams show significant differences in variability of the defence systems and start-positions are more variable than the end-positions. Multilayer perceptrons are able to recognize the teams at an average of 98.5%. It is concluded that defence systems in team sports are highly individual at a competitive level and variable even in standard situations. Artificial neural networks can be used to recognize

Authentic Early Experience in Medical Education: A Socio-Cultural Analysis Identifying Important Variables in Learning Interactions within Workplaces

ERIC Educational Resources Information Center

Yardley, Sarah; Brosnan, Caragh; Richardson, Jane; Hays, Richard

2013-01-01

This paper addresses the question "what are the variables influencing social interactions and learning during Authentic Early Experience (AEE)?" AEE is a complex educational intervention for new medical students. Following critique of the existing literature, multiple qualitative methods were used to create a study framework conceptually…

A Framework for Categorizing Important Project Variables

NASA Technical Reports Server (NTRS)

Parsons, Vickie S.

2003-01-01

While substantial research has led to theories concerning the variables that affect project success, no universal set of such variables has been acknowledged as the standard. The identification of a specific set of controllable variables is needed to minimize project failure. Much has been hypothesized about the need to match project controls and management processes to individual projects in order to increase the chance for success. However, an accepted taxonomy for facilitating this matching process does not exist. This paper surveyed existing literature on classification of project variables. After an analysis of those proposals, a simplified categorization is offered to encourage further research.

Identifying Useful Auxiliary Variables for Incomplete Data Analyses: A Note on a Group Difference Examination Approach

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.

2014-01-01

This research note contributes to the discussion of methods that can be used to identify useful auxiliary variables for analyses of incomplete data sets. A latent variable approach is discussed, which is helpful in finding auxiliary variables with the property that if included in subsequent maximum likelihood analyses they may enhance considerably…

Identifying Decadal to Multi-decadal Variability in the Pacific by Empirical Mode Decomposition

NASA Astrophysics Data System (ADS)

Sommers, L. A.; Hamlington, B.; Cheon, S. H.

2016-12-01

Large scale climate variability in the Pacific Ocean like that associated with ENSO and the Pacific Decadal Oscillation (PDO) has been shown to have a significant impact on climate and sea level across a range of timescales. The changes related to these climate signals have worldwide impacts on fisheries, weather, and precipitation patterns among others. Understanding these inter-annual to multi-decadal oscillations is imperative to longer term climate forecasts and understanding how climate will behave, and its effect on changes in sea level. With a 110-year reconstruction of sea level, we examine decadal to multi-decadal variability seen in the sea level fluctuations in the Pacific Ocean. Using empirical mode decomposition (EMD), we break down regional sea level into a series of intrinsic mode functions (IMFs) and attempt attribution of these IMFs to specific climate modes of variability. In particular, and not unexpectedly, we identify IMFs associated with the PDO, finding correlations between the PDO Index and IMFs in the Pacific Ocean upwards of 0.6-0.8 over the 110-year reconstructed record. Perhaps more significantly, we also find evidence of a longer multi-decadal signal ( 50-60 years) in the higher order IMFs. This lower frequency variability has been suggested in previous literature as influencing GMSL, but here we find a regional pattern associated with this multi-decadal signal. By identifying and separating these periodic climate signals, we can gain a better understanding of how the sea level variability associated with these modes can impact sea level on short timescales and serve to exacerbate the effects of long-term sea level change.

A new approach to hazardous materials transportation risk analysis: decision modeling to identify critical variables.

PubMed

Clark, Renee M; Besterfield-Sacre, Mary E

2009-03-01

We take a novel approach to analyzing hazardous materials transportation risk in this research. Previous studies analyzed this risk from an operations research (OR) or quantitative risk assessment (QRA) perspective by minimizing or calculating risk along a transport route. Further, even though the majority of incidents occur when containers are unloaded, the research has not focused on transportation-related activities, including container loading and unloading. In this work, we developed a decision model of a hazardous materials release during unloading using actual data and an exploratory data modeling approach. Previous studies have had a theoretical perspective in terms of identifying and advancing the key variables related to this risk, and there has not been a focus on probability and statistics-based approaches for doing this. Our decision model empirically identifies the critical variables using an exploratory methodology for a large, highly categorical database involving latent class analysis (LCA), loglinear modeling, and Bayesian networking. Our model identified the most influential variables and countermeasures for two consequences of a hazmat incident, dollar loss and release quantity, and is one of the first models to do this. The most influential variables were found to be related to the failure of the container. In addition to analyzing hazmat risk, our methodology can be used to develop data-driven models for strategic decision making in other domains involving risk.

Identifying important nodes by adaptive LeaderRank

NASA Astrophysics Data System (ADS)

Xu, Shuang; Wang, Pei

2017-03-01

Spreading process is a common phenomenon in complex networks. Identifying important nodes in complex networks is of great significance in real-world applications. Based on the spreading process on networks, a lot of measures have been proposed to evaluate the importance of nodes. However, most of the existing measures are appropriate to static networks, which are fragile to topological perturbations. Many real-world complex networks are dynamic rather than static, meaning that the nodes and edges of such networks may change with time, which challenge numerous existing centrality measures. Based on a new weighted mechanism and the newly proposed H-index and LeaderRank (LR), this paper introduces a variant of the LR measure, called adaptive LeaderRank (ALR), which is a new member of the LR-family. Simulations on six real-world networks reveal that the new measure can well balance between prediction accuracy and robustness. More interestingly, the new measure can better adapt to the adjustment or local perturbations of network topologies, as compared with the existing measures. By discussing the detailed properties of the measures from the LR-family, we illustrate that the ALR has its competitive advantages over the other measures. The proposed algorithm enriches the measures to understand complex networks, and may have potential applications in social networks and biological systems.

The importance of immune gene variability (MHC) in evolutionary ecology and conservation

PubMed Central

Sommer, Simone

2005-01-01

Genetic studies have typically inferred the effects of human impact by documenting patterns of genetic differentiation and levels of genetic diversity among potentially isolated populations using selective neutral markers such as mitochondrial control region sequences, microsatellites or single nucleotide polymorphism (SNPs). However, evolutionary relevant and adaptive processes within and between populations can only be reflected by coding genes. In vertebrates, growing evidence suggests that genetic diversity is particularly important at the level of the major histocompatibility complex (MHC). MHC variants influence many important biological traits, including immune recognition, susceptibility to infectious and autoimmune diseases, individual odours, mating preferences, kin recognition, cooperation and pregnancy outcome. These diverse functions and characteristics place genes of the MHC among the best candidates for studies of mechanisms and significance of molecular adaptation in vertebrates. MHC variability is believed to be maintained by pathogen-driven selection, mediated either through heterozygote advantage or frequency-dependent selection. Up to now, most of our knowledge has derived from studies in humans or from model organisms under experimental, laboratory conditions. Empirical support for selective mechanisms in free-ranging animal populations in their natural environment is rare. In this review, I first introduce general information about the structure and function of MHC genes, as well as current hypotheses and concepts concerning the role of selection in the maintenance of MHC polymorphism. The evolutionary forces acting on the genetic diversity in coding and non-coding markers are compared. Then, I summarise empirical support for the functional importance of MHC variability in parasite resistance with emphasis on the evidence derived from free-ranging animal populations investigated in their natural habitat. Finally, I discuss the importance of

Trophic characteristics of a mangrove fish community in Southwest Thailand: Important mangrove contribution and intraspecies feeding variability

NASA Astrophysics Data System (ADS)

Zagars, Matiss; Ikejima, Kou; Kasai, Akihide; Arai, Nobuaki; Tongnunui, Prasert

2013-03-01

Mangrove production has been found to make a major contribution to the nutrition of a fish community in the Sikao Creek mangrove estuary, Southwest Thailand. Gut content analysis and carbon and nitrogen stable isotope analysis were used to assess fish feeding behavior and trophic reliance on different primary producers (mangrove leaves, phytoplankton, microphytobenthos) focusing on 19 dominant fish species, and 4 potential fish food items. Cluster analysis identified 5 trophic groups and the IsoSource model indicated the importance of primary food sources in trophically supporting different fish species. Most analyzed fish species had carbon isotopic signatures that were more depleted than those reported in previous studies, and the IsoSource model indicated that mangrove leaves were an important primary food source. This may be a specific characteristic of our study site, which is not well connected to other productive coastal habitats that provide alternative primary food sources. Thus we suggest that food chains in trophically isolated mangrove estuaries of southwest Thailand are more dependent on mangrove tree production. We also assessed the relationship of individuality in fish feeding habits and variability of δ13C values and showed that several mangrove fish species have significant intraspecies variability in feeding habits, possibly due to high intraspecific competition.

Genes Important for Schizosaccharomyces pombe Meiosis Identified Through a Functional Genomics Screen

PubMed Central

Blyth, Julie; Makrantoni, Vasso; Barton, Rachael E.; Spanos, Christos; Rappsilber, Juri; Marston, Adele L.

2018-01-01

Meiosis is a specialized cell division that generates gametes, such as eggs and sperm. Errors in meiosis result in miscarriages and are the leading cause of birth defects; however, the molecular origins of these defects remain unknown. Studies in model organisms are beginning to identify the genes and pathways important for meiosis, but the parts list is still poorly defined. Here we present a comprehensive catalog of genes important for meiosis in the fission yeast, Schizosaccharomyces pombe. Our genome-wide functional screen surveyed all nonessential genes for roles in chromosome segregation and spore formation. Novel genes important at distinct stages of the meiotic chromosome segregation and differentiation program were identified. Preliminary characterization implicated three of these genes in centrosome/spindle pole body, centromere, and cohesion function. Our findings represent a near-complete parts list of genes important for meiosis in fission yeast, providing a valuable resource to advance our molecular understanding of meiosis. PMID:29259000

Identifying public water facilities with low spatial variability of disinfection by-products for epidemiological investigations

PubMed Central

Hinckley, A; Bachand, A; Nuckols, J; Reif, J

2005-01-01

Background and Aims: Epidemiological studies of disinfection by-products (DBPs) and reproductive outcomes have been hampered by misclassification of exposure. In most epidemiological studies conducted to date, all persons living within the boundaries of a water distribution system have been assigned a common exposure value based on facility-wide averages of trihalomethane (THM) concentrations. Since THMs do not develop uniformly throughout a distribution system, assignment of facility-wide averages may be inappropriate. One approach to mitigate this potential for misclassification is to select communities for epidemiological investigations that are served by distribution systems with consistently low spatial variability of THMs. Methods and Results: A feasibility study was conducted to develop methods for community selection using the Information Collection Rule (ICR) database, assembled by the US Environmental Protection Agency. The ICR database contains quarterly DBP concentrations collected between 1997 and 1998 from the distribution systems of 198 public water facilities with minimum service populations of 100 000 persons. Facilities with low spatial variation of THMs were identified using two methods; 33 facilities were found with low spatial variability based on one or both methods. Because brominated THMs may be important predictors of risk for adverse reproductive outcomes, sites were categorised into three exposure profiles according to proportion of brominated THM species and average TTHM concentration. The correlation between THMs and haloacetic acids (HAAs) in these facilities was evaluated to see whether selection by total trihalomethanes (TTHMs) corresponds to low spatial variability for HAAs. TTHMs were only moderately correlated with HAAs (r = 0.623). Conclusions: Results provide a simple method for a priori selection of sites with low spatial variability from state or national public water facility datasets as a means to reduce exposure

STUDY TO IDENTIFY IMPORTANT PARAMETERS FOR CHARACTERIZING PESTICIDE RESIDUE TRANSFER EFFICIENCIES

EPA Science Inventory

To reduce the uncertainty associated with current estimates of children's exposure to pesticides by dermal contact and non-dietary ingestion, residue transfer data are required. Prior to conducting exhaustive studies, a screening study to identify the important parameters for...

How Variables Uncorrelated with the Dependent Variable Can Actually Make Excellent Predictors: The Important Suppressor Variable Case.

ERIC Educational Resources Information Center

Woolley, Kristin K.

Many researchers are unfamiliar with suppressor variables and how they operate in multiple regression analyses. This paper describes the role suppressor variables play in a multiple regression model and provides practical examples that explain how they can change research results. A variable that when added as another predictor increases the total…

The importance of identifying and modifying unemployment predictor variables in the evolution of a novel model of care for low back pain in the general population.

PubMed

Harris, Simon A; Rampersaud, Y Raja

2016-01-01

=22.9%). However, 10.5% of Et0 became UEt1 (Et0/Et1=102, Et0/UEt1=12). Bivariate analysis identified elevated baseline ODI score as the only significant predictor variable for UEt1 in Et0 cohort (p=.0101). Conversely, ISAEC improved the employment status in 41% of UEt0 to Et1 (UEt0/Et1=16, UEt0/UEt1=23), and the absence of depression was significant for predicting RTW (p=.0001). From a societal perspective, employment status as an outcome measure is paramount in assessing the value of a new model of care for LBP. Mitigation strategies for the predictor variables identified will be included in ISAEC pathways to translate clinical improvement into societal added value. Copyright © 2015 Elsevier Inc. All rights reserved.

Functional Analysis of Problem Behavior: A Systematic Approach for Identifying Idiosyncratic Variables

PubMed Central

Roscoe, Eileen M.; Schlichenmeyer, Kevin J.; Dube, William V.

2015-01-01

When inconclusive functional analysis (FA) outcomes occur, a number of modifications have been made to enhance the putative establishing operation or consequence associated with behavioral maintenance. However, a systematic method for identifying relevant events to test during modified FAs has not been evaluated. The purpose of this study was to develop and evaluate a technology for systematically identifying events to test in a modified FA after an initial FA led to inconclusive outcomes. Six individuals whose initial FA showed little or no responding or high levels only in the control condition participated. An indirect assessment (IA) questionnaire developed for identifying idiosyncratic variables was administered, and a descriptive analysis (DA) was conducted. Results from the IA only or a combination of the IA and DA were used to inform modified FA test and control conditions. Conclusive FA outcomes were obtained with five of the six participants during the modified FA phase. PMID:25930176

Variable Neighborhood Search Heuristics for Selecting a Subset of Variables in Principal Component Analysis

ERIC Educational Resources Information Center

Brusco, Michael J.; Singh, Renu; Steinley, Douglas

2009-01-01

The selection of a subset of variables from a pool of candidates is an important problem in several areas of multivariate statistics. Within the context of principal component analysis (PCA), a number of authors have argued that subset selection is crucial for identifying those variables that are required for correct interpretation of the…

Coral Luminescence Identifies the Pacific Decadal Oscillation as a Primary Driver of River Runoff Variability Impacting the Southern Great Barrier Reef

PubMed Central

Rodriguez-Ramirez, Alberto; Grove, Craig A.; Zinke, Jens; Pandolfi, John M.; Zhao, Jian-xin

2014-01-01

The Pacific Decadal Oscillation (PDO) is a large-scale climatic phenomenon modulating ocean-atmosphere variability on decadal time scales. While precipitation and river flow variability in the Great Barrier Reef (GBR) catchments are sensitive to PDO phases, the extent to which the PDO influences coral reefs is poorly understood. Here, six Porites coral cores were used to produce a composite record of coral luminescence variability (runoff proxy) and identify drivers of terrestrial influence on the Keppel reefs, southern GBR. We found that coral skeletal luminescence effectively captured seasonal, inter-annual and decadal variability of river discharge and rainfall from the Fitzroy River catchment. Most importantly, although the influence of El Niño-Southern Oscillation (ENSO) events was evident in the luminescence records, the variability in the coral luminescence composite record was significantly explained by the PDO. Negative luminescence anomalies (reduced runoff) were associated with El Niño years during positive PDO phases while positive luminescence anomalies (increased runoff) coincided with strong/moderate La Niña years during negative PDO phases. This study provides clear evidence that not only ENSO but also the PDO have significantly affected runoff regimes at the Keppel reefs for at least a century, and suggests that upcoming hydrological disturbances and ecological responses in the southern GBR region will be mediated by the future evolution of these sources of climate variability. PMID:24416214

Coral luminescence identifies the Pacific Decadal Oscillation as a primary driver of river runoff variability impacting the southern Great Barrier Reef.

PubMed

Rodriguez-Ramirez, Alberto; Grove, Craig A; Zinke, Jens; Pandolfi, John M; Zhao, Jian-xin

2014-01-01

The Pacific Decadal Oscillation (PDO) is a large-scale climatic phenomenon modulating ocean-atmosphere variability on decadal time scales. While precipitation and river flow variability in the Great Barrier Reef (GBR) catchments are sensitive to PDO phases, the extent to which the PDO influences coral reefs is poorly understood. Here, six Porites coral cores were used to produce a composite record of coral luminescence variability (runoff proxy) and identify drivers of terrestrial influence on the Keppel reefs, southern GBR. We found that coral skeletal luminescence effectively captured seasonal, inter-annual and decadal variability of river discharge and rainfall from the Fitzroy River catchment. Most importantly, although the influence of El Niño-Southern Oscillation (ENSO) events was evident in the luminescence records, the variability in the coral luminescence composite record was significantly explained by the PDO. Negative luminescence anomalies (reduced runoff) were associated with El Niño years during positive PDO phases while positive luminescence anomalies (increased runoff) coincided with strong/moderate La Niña years during negative PDO phases. This study provides clear evidence that not only ENSO but also the PDO have significantly affected runoff regimes at the Keppel reefs for at least a century, and suggests that upcoming hydrological disturbances and ecological responses in the southern GBR region will be mediated by the future evolution of these sources of climate variability.

Identifying novel phenotypes of acute heart failure using cluster analysis of clinical variables.

PubMed

Horiuchi, Yu; Tanimoto, Shuzou; Latif, A H M Mahbub; Urayama, Kevin Y; Aoki, Jiro; Yahagi, Kazuyuki; Okuno, Taishi; Sato, Yu; Tanaka, Tetsu; Koseki, Keita; Komiyama, Kota; Nakajima, Hiroyoshi; Hara, Kazuhiro; Tanabe, Kengo

2018-07-01

Acute heart failure (AHF) is a heterogeneous disease caused by various cardiovascular (CV) pathophysiology and multiple non-CV comorbidities. We aimed to identify clinically important subgroups to improve our understanding of the pathophysiology of AHF and inform clinical decision-making. We evaluated detailed clinical data of 345 consecutive AHF patients using non-hierarchical cluster analysis of 77 variables, including age, sex, HF etiology, comorbidities, physical findings, laboratory data, electrocardiogram, echocardiogram and treatment during hospitalization. Cox proportional hazards regression analysis was performed to estimate the association between the clusters and clinical outcomes. Three clusters were identified. Cluster 1 (n=108) represented "vascular failure". This cluster had the highest average systolic blood pressure at admission and lung congestion with type 2 respiratory failure. Cluster 2 (n=89) represented "cardiac and renal failure". They had the lowest ejection fraction (EF) and worst renal function. Cluster 3 (n=148) comprised mostly older patients and had the highest prevalence of atrial fibrillation and preserved EF. Death or HF hospitalization within 12-month occurred in 23% of Cluster 1, 36% of Cluster 2 and 36% of Cluster 3 (p=0.034). Compared with Cluster 1, risk of death or HF hospitalization was 1.74 (95% CI, 1.03-2.95, p=0.037) for Cluster 2 and 1.82 (95% CI, 1.13-2.93, p=0.014) for Cluster 3. Cluster analysis may be effective in producing clinically relevant categories of AHF, and may suggest underlying pathophysiology and potential utility in predicting clinical outcomes. Copyright © 2018 Elsevier B.V. All rights reserved.

A Multi-sensor Approach to Identify Crop Sensitivity Related to Climate Variability in Central India

NASA Astrophysics Data System (ADS)

Mondal, P.; DeFries, R. S.; Jain, M.; Robertson, A. W.; Galford, G. L.; Small, C.

2012-12-01

Agriculture is a primary source of livelihood for over 70% of India's population, with staple crops (e.g. winter wheat) playing a pivotal role in satisfying an ever-increasing food-demand of a growing population. Agricultural yield in India has been reported to be highly correlated with the timing and total amount of monsoon rainfall and/or temperature depending on crop type. With expected change in future climate (temperature and precipitation), significant fluctuations in crop yields are projected for near future. To date, little work has identified the sensitivity of cropping intensity, or the number of crops planted in a given year, to climate variability. The objective of this study is to shed light on relative importance of different climate parameters through a statistical analysis of inter-annual variations in cropping intensity at a regional scale, which may help identify adaptive strategies in response to future climate anomalies. Our study focuses on a highly human-modified landscape in central India, and uses a multi-sensor approach to determine the sensitivity of agriculture to climate variability. First, we assembled the 16-day time-series of 250m Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI), and applied a spline function-based smoothing algorithm to develop maps of monsoon and winter crops in Central India for a decadal time-span. A hierarchical model involving moderate resolution Landsat (30m) data was used to estimate the heterogeneity of the spectral signature within the MODIS dataset (250m). We then compared the season-specific cropping patterns with spatio-temporal variability in climate parameters derived from the Tropical Rainfall Measuring Mission (TRMM) data. Initial data indicates that the existence of a monsoon crop has moderate to strong correlation with wet season end date (ρ = .522), wet season length (ρ = .522), and the number of rainy days during wet season (ρ = .829). Existence of a winter

Identifying Psychosocial Variables That Predict Safer Sex Intentions in Adolescents and Young Adults

PubMed Central

Brüll, Phil; Ruiter, Robert A. C.; Wiers, Reinout W.; Kok, Gerjo

2016-01-01

Young people are especially vulnerable to sexually transmitted infections (STIs). The triad of deliberate and effective safer sex behavior encompasses condom use, combined with additional information about a partner’s sexual health, and the kind of sex acts usually performed. To identify psychosocial predictors of young people’s intentions to have safer sex, as related to this triad, we conducted an online study with 211 sexually active participants aged between 18 and 24 years. Predictors [i.e., perceived behavioral control (PBC), subjective norms, and intention] taken from Fishbein and Ajzen’s Reasoned Action Approach (RAA), were combined with more distal variables (e.g., behavioral inhibition, sensation seeking, parental monitoring, and knowledge about STIs). Beyond the highly predictive power of RAA variables, additional variance was explained by the number of instances of unprotected sexual intercourse (SI) during the last 12 months and reasons for using barrier protection during first SI. In particular, past condom non-use behavior moderated PBC related to intended condom use. Further, various distal variables showed significant univariate associations with intentions related to the three behaviors of interest. It may, therefore, be helpful to include measures of past behavior as well as certain additional distal variables in future safer sex programs designed to promote health-sustaining sexual behavior. PMID:27148520

Identifying optimal remotely-sensed variables for ecosystem monitoring in Colorado Plateau drylands

USGS Publications Warehouse

Poitras, Travis; Villarreal, Miguel; Waller, Eric K.; Nauman, Travis; Miller, Mark E.; Duniway, Michael C.

2018-01-01

Water-limited ecosystems often recover slowly following anthropogenic or natural disturbance. Multitemporal remote sensing can be used to monitor ecosystem recovery after disturbance; however, dryland vegetation cover can be challenging to accurately measure due to sparse cover and spectral confusion between soils and non-photosynthetic vegetation. With the goal of optimizing a monitoring approach for identifying both abrupt and gradual vegetation changes, we evaluated the ability of Landsat-derived spectral variables to characterize surface variability of vegetation cover and bare ground across a range of vegetation community types. Using three year composites of Landsat data, we modeled relationships between spectral information and field data collected at monitoring sites near Canyonlands National Park, UT. We also developed multiple regression models to assess improvement over single variables. We found that for all vegetation types, percent cover bare ground could be accurately modeled with single indices that included a combination of red and shortwave infrared bands, while near infrared-based vegetation indices like NDVI worked best for quantifying tree cover and total live vegetation cover in woodlands. We applied four models to characterize the spatial distribution of putative grassland ecological states across our study area, illustrating how this approach can be implemented to guide dryland ecosystem management.

Identifying Outcomes that Are Important to Living Kidney Donors: A Nominal Group Technique Study.

PubMed

Hanson, Camilla S; Chapman, Jeremy R; Gill, John S; Kanellis, John; Wong, Germaine; Craig, Jonathan C; Teixeira-Pinto, Armando; Chadban, Steve J; Garg, Amit X; Ralph, Angelique F; Pinter, Jule; Lewis, Joshua R; Tong, Allison

2018-06-07

Living kidney donor candidates accept a range of risks and benefits when they decide to proceed with nephrectomy. Informed consent around this decision assumes they receive reliable data about outcomes they regard as critical to their decision making. We identified the outcomes most important to living kidney donors and described the reasons for their choices. Previous donors were purposively sampled from three transplant units in Australia (Sydney and Melbourne) and Canada (Vancouver). In focus groups using the nominal group technique, participants identified outcomes of donation, ranked them in order of importance, and discussed the reasons for their preferences. An importance score was calculated for each outcome. Qualitative data were analyzed thematically. Across 14 groups, 123 donors aged 27-78 years identified 35 outcomes. Across all participants, the ten highest ranked outcomes were kidney function (importance=0.40, scale 0-1), time to recovery (0.27), surgical complications (0.24), effect on family (0.22), donor-recipient relationship (0.21), life satisfaction (0.18), lifestyle restrictions (0.18), kidney failure (0.14), mortality (0.13), and acute pain/discomfort (0.12). Kidney function and kidney failure were more important to Canadian participants, compared with Australian donors. The themes identified included worthwhile sacrifice, insignificance of risks and harms, confidence and empowerment, unfulfilled expectations, and heightened susceptibility. Living kidney donors prioritized a range of outcomes, with the most important being kidney health and the surgical, lifestyle, functional, and psychosocial effects of donation. Donors also valued improvements to their family life and donor-recipient relationship. There were clear regional differences in the rankings. Copyright © 2018 by the American Society of Nephrology.

Identifying environmental variables explaining genotype-by-environment interaction for body weight of rainbow trout (Onchorynchus mykiss): reaction norm and factor analytic models.

PubMed

Sae-Lim, Panya; Komen, Hans; Kause, Antti; Mulder, Han A

2014-02-26

Identifying the relevant environmental variables that cause GxE interaction is often difficult when they cannot be experimentally manipulated. Two statistical approaches can be applied to address this question. When data on candidate environmental variables are available, GxE interaction can be quantified as a function of specific environmental variables using a reaction norm model. Alternatively, a factor analytic model can be used to identify the latent common factor that explains GxE interaction. This factor can be correlated with known environmental variables to identify those that are relevant. Previously, we reported a significant GxE interaction for body weight at harvest in rainbow trout reared on three continents. Here we explore their possible causes. Reaction norm and factor analytic models were used to identify which environmental variables (age at harvest, water temperature, oxygen, and photoperiod) may have caused the observed GxE interaction. Data on body weight at harvest was recorded on 8976 offspring reared in various locations: (1) a breeding environment in the USA (nucleus), (2) a recirculating aquaculture system in the Freshwater Institute in West Virginia, USA, (3) a high-altitude farm in Peru, and (4) a low-water temperature farm in Germany. Akaike and Bayesian information criteria were used to compare models. The combination of days to harvest multiplied with daily temperature (Day*Degree) and photoperiod were identified by the reaction norm model as the environmental variables responsible for the GxE interaction. The latent common factor that was identified by the factor analytic model showed the highest correlation with Day*Degree. Day*Degree and photoperiod were the environmental variables that differed most between Peru and other environments. Akaike and Bayesian information criteria indicated that the factor analytical model was more parsimonious than the reaction norm model. Day*Degree and photoperiod were identified as environmental

Identifying environmental variables explaining genotype-by-environment interaction for body weight of rainbow trout (Onchorynchus mykiss): reaction norm and factor analytic models

PubMed Central

2014-01-01

Background Identifying the relevant environmental variables that cause GxE interaction is often difficult when they cannot be experimentally manipulated. Two statistical approaches can be applied to address this question. When data on candidate environmental variables are available, GxE interaction can be quantified as a function of specific environmental variables using a reaction norm model. Alternatively, a factor analytic model can be used to identify the latent common factor that explains GxE interaction. This factor can be correlated with known environmental variables to identify those that are relevant. Previously, we reported a significant GxE interaction for body weight at harvest in rainbow trout reared on three continents. Here we explore their possible causes. Methods Reaction norm and factor analytic models were used to identify which environmental variables (age at harvest, water temperature, oxygen, and photoperiod) may have caused the observed GxE interaction. Data on body weight at harvest was recorded on 8976 offspring reared in various locations: (1) a breeding environment in the USA (nucleus), (2) a recirculating aquaculture system in the Freshwater Institute in West Virginia, USA, (3) a high-altitude farm in Peru, and (4) a low-water temperature farm in Germany. Akaike and Bayesian information criteria were used to compare models. Results The combination of days to harvest multiplied with daily temperature (Day*Degree) and photoperiod were identified by the reaction norm model as the environmental variables responsible for the GxE interaction. The latent common factor that was identified by the factor analytic model showed the highest correlation with Day*Degree. Day*Degree and photoperiod were the environmental variables that differed most between Peru and other environments. Akaike and Bayesian information criteria indicated that the factor analytical model was more parsimonious than the reaction norm model. Conclusions Day*Degree and

Predicting Ecologically Important Vegetation Variables from Remotely Sensed Optical/Radar Data Using Neural Networks

NASA Technical Reports Server (NTRS)

Kimes, Daniel S.; Nelson, Ross F.

1998-01-01

A number of satellite sensor systems will collect large data sets of the Earth's surface during NASA's Earth Observing System (EOS) era. Efforts are being made to develop efficient algorithms that can incorporate a wide variety of spectral data and ancillary data in order to extract vegetation variables required for global and regional studies of ecosystem processes, biosphere-atmosphere interactions, and carbon dynamics. These variables are, for the most part, continuous (e.g. biomass, leaf area index, fraction of vegetation cover, vegetation height, vegetation age, spectral albedo, absorbed photosynthetic active radiation, photosynthetic efficiency, etc.) and estimates may be made using remotely sensed data (e.g. nadir and directional optical wavelengths, multifrequency radar backscatter) and any other readily available ancillary data (e.g., topography, sun angle, ground data, etc.). Using these types of data, neural networks can: 1) provide accurate initial models for extracting vegetation variables when an adequate amount of data is available; 2) provide a performance standard for evaluating existing physically-based models; 3) invert multivariate, physically based models; 4) in a variable selection process, identify those independent variables which best infer the vegetation variable(s) of interest; and 5) incorporate new data sources that would be difficult or impossible to use with conventional techniques. In addition, neural networks employ a more powerful and adaptive nonlinear equation form as compared to traditional linear, index transformations, and simple nonlinear analyses. These neural networks attributes are discussed in the context of the authors' investigations of extracting vegetation variables of ecological interest.

Importance of fishing as a segmentation variable in the application of a social worlds model

USGS Publications Warehouse

Gigliotti, Larry M.; Chase, Loren

2017-01-01

Market segmentation is useful to understanding and classifying the diverse range of outdoor recreation experiences sought by different recreationists. Although many different segmentation methodologies exist, many are complex and difficult to measure accurately during in-person intercepts, such as that of creel surveys. To address that gap in the literature, we propose a single-item measure of the importance of fishing as a surrogate to often overly- or needlesslycomplex segmentation techniques. The importance of fishing item is a measure of the value anglers place on the activity or a coarse quantification of how central the activity is to the respondent’s lifestyle (scale: 0 = not important, 1 = slightly, 2 = moderately, 3 = very, and 4 = fishing is my most important recreational activity). We suggest the importance scale may be a proxy measurement for segmenting anglers using the social worlds model as a theoretical framework. Vaske (1980) suggested that commitment to recreational activities may be best understood in relation to social group participation and the social worlds model provides a rich theoretical framework for understanding social group segments. Unruh (1983) identified four types of actor involvement in social worlds: strangers, tourists, regulars, and insiders, differentiated by four characteristics (orientation, experiences, relationships, and commitment). We evaluated the importance of fishing as a segmentation variable using data collected by a mixed-mode survey of South Dakota anglers fishing in 2010. We contend that this straightforward measurement may be useful for segmenting outdoor recreation activities when more complicated segmentation schemes are not suitable. Further, this index, when coupled with the social worlds model, provides a valuable framework for understanding the segments and making management decisions.

Identifying Factors Causing Variability in Greenhouse Gas (GHG) Fluxes in a Polygonal Tundra Landscape

NASA Astrophysics Data System (ADS)

Arora, B.; Wainwright, H. M.; Vaughn, L. S.; Curtis, J. B.; Torn, M. S.; Dafflon, B.; Hubbard, S. S.

2017-12-01

Greenhouse gas (GHG) flux variations in Arctic tundra environments are important to understand because of the vast amount of soil carbon stored in these regions and the potential of these regions to convert from a global carbon sink to a source under warmer conditions. Multiple factors potentially contribute to GHG flux variations observed in these environments, including snowmelt timing, growing season length, active layer thickness, water table variations, and temperature fluctuations. The objectives of this study are to investigate temporal variability in CO2 and CH4 fluxes at Barrow, AK over three successive growing seasons (2012-14) and to determine the factors influencing this variability using a novel entropy-based classification scheme. We analyzed soil, vegetation, and climate parameters as well as GHG fluxes at multiple locations within low-, flat- and high-centered polygons at Barrow, AK as part of the Next Generation Ecosystem Experiment (NGEE) Arctic project. Entropy results indicate that different environmental factors govern variability in GHG fluxes under different spatiotemporal settings. In particular, flat-centered polygons are more likely to become significant sources of CO2 during warm and dry years as opposed to high-centered polygons that contribute considerably to CO2 emissions during cold and wet years. In contrast, the highest CH4 emissions were always associated with low-centered polygons. Temporal variability in CO2 fluxes was primarily associated with factors affecting soil temperature and/or vegetation dynamics during early and late season periods. Temporal variability in CH4 fluxes was primarily associated with changes in vegetation cover and its covariability with primary controls such as seasonal thaw—rather than direct response to changes in soil moisture. Overall, entropy results document which factors became important under different spatiotemporal settings, thus providing clues concerning the manner in which ecosystem

Individual variability in clinical effect and tolerability of opioid analgesics - Importance of drug interactions and pharmacogenetics.

PubMed

Solhaug, Vigdis; Molden, Espen

2017-10-01

As pain is often a comorbid condition, many patients use opioid analgesics in combination with several other drugs. This implies a generally increased risk of drug interactions, which along with inherent pharmacogenetic variability and other factors may cause differences in therapeutic response of opioids. To provide an overview of interactions and pharmacogenetic variability of relevance for individual differences in effect and tolerability of opioid analgesics, which physicians and other healthcare professionals should be aware of in clinical practice. The article was based on unsystematic searches in PubMed to identify literature highlighting the clinical impact of drug interactions and pharmacogenetics as sources of variable response of opioid analgesics. Cytochrome P450 (CYP)-mediated metabolism is an important process for both clinically relevant interactions and pharmacogenetic variability of several opioids. Concomitant use of CYP inhibitors (e.g. paroxetine, fluoxetine and bupropion) or inducers (e.g. carbamazepine, phenobarbital and phenytoin) could counteract the clinical effect or trigger side effects of analgesics in the same manner as genetically determined differences in CYP2D6-mediated metabolism of many opioids. Moreover, combination treatment with drugs that inhibit or induce P-glycoprotein (ABCB1), a blood-brain barrier efflux transporter, may alter the amount ('dose') of opioids distributed to the brain. At the pharmacodynamic level, it is crucial to be aware of the potential risk of interaction causing serotonergic syndrome when combining opioids and serotonergic drugs, in particular antidepressants inhibiting serotonin reuptake (SSRIs and SNRIs). Regarding pharmacogenetics at the receptor level of pain treatment, the knowledge is currently scarce, but an allelic variant of the μ1 opioid receptor (OPRM1) gene has been associated with higher dosage requirement to achieve analgesia. Drug interactions and pharmacogenetic differences may lead to

Using variable rate models to identify genes under selection in sequence pairs: their validity and limitations for EST sequences.

PubMed

Church, Sheri A; Livingstone, Kevin; Lai, Zhao; Kozik, Alexander; Knapp, Steven J; Michelmore, Richard W; Rieseberg, Loren H

2007-02-01

Using likelihood-based variable selection models, we determined if positive selection was acting on 523 EST sequence pairs from two lineages of sunflower and lettuce. Variable rate models are generally not used for comparisons of sequence pairs due to the limited information and the inaccuracy of estimates of specific substitution rates. However, previous studies have shown that the likelihood ratio test (LRT) is reliable for detecting positive selection, even with low numbers of sequences. These analyses identified 56 genes that show a signature of selection, of which 75% were not identified by simpler models that average selection across codons. Subsequent mapping studies in sunflower show four of five of the positively selected genes identified by these methods mapped to domestication QTLs. We discuss the validity and limitations of using variable rate models for comparisons of sequence pairs, as well as the limitations of using ESTs for identification of positively selected genes.

Resolving key drivers of variability through an important circulation choke point in the western Mediterranean Sea; using gliders, models & satellite remote sensing

NASA Astrophysics Data System (ADS)

Heslop, Emma; Aguiar, Eva; Mourre, Baptiste; Juza, Mélanie; Escudier, Romain; Tintoré, Joaquín

2017-04-01

The Ibiza Channel plays an important role in the circulation of the Western Mediterranean Sea, it governs the north/south exchange of different water masses that are known to affect regional ecosystems and is influenced by variability in the different drivers that affect sub-basins to the north (N) and south (S). A complex system. In this study we use a multi-platform approach to resolve the key drivers of this variability, and gain insight into the inter-connection between the N and S of the Western Mediterranean Sea through this choke point. The 6-year glider time series from the quasi-continuous glider endurance line monitoring of the Ibiza Channel, undertaken by SOCIB (Balearic Coastal Ocean observing and Forecasting System), is used as the base from which to identify key sub-seasonal to inter-annual patterns and shifts in water mass properties and transport volumes. The glider data indicates the following key components in the variability of the N/S flow of different water mass through the channel; regional winter mode water production, change in intermediate water mass properties, northward flows of a fresher water mass and the basin-scale circulation. To resolve the drivers of these components of variability, the strength of combining datasets from different sources, glider, modeling, altimetry and moorings, is harnessed. To the north atmospheric forcing in the Gulf of Lions is a dominant driver, while to the south the mesoscale circulation patterns of the Atlantic Jet and Alboran gyres dominate the variability but do not appear to influence the fresher inflows. Evidence of a connection between the northern and southern sub-basins is however indicated. The study highlights importance of sub-seasonal variability and the scale of rapid change possible in the Mediterranean, as well as the benefits of leveraging high resolution glider datasets within a multi-platform and modelling study.

Long-term variability of importance of brain regions in evolving epileptic brain networks

NASA Astrophysics Data System (ADS)

Geier, Christian; Lehnertz, Klaus

2017-04-01

We investigate the temporal and spatial variability of the importance of brain regions in evolving epileptic brain networks. We construct these networks from multiday, multichannel electroencephalographic data recorded from 17 epilepsy patients and use centrality indices to assess the importance of brain regions. Time-resolved indications of highest importance fluctuate over time to a greater or lesser extent, however, with some periodic temporal structure that can mostly be attributed to phenomena unrelated to the disease. In contrast, relevant aspects of the epileptic process contribute only marginally. Indications of highest importance also exhibit pronounced alternations between various brain regions that are of relevance for studies aiming at an improved understanding of the epileptic process with graph-theoretical approaches. Nonetheless, these findings may guide new developments for individualized diagnosis, treatment, and control.

Diminished FoxP2 levels affect dopaminergic modulation of corticostriatal signaling important to song variability.

PubMed

Murugan, Malavika; Harward, Stephen; Scharff, Constance; Mooney, Richard

2013-12-18

Mutations of the FOXP2 gene impair speech and language development in humans and shRNA-mediated suppression of the avian ortholog FoxP2 disrupts song learning in juvenile zebra finches. How diminished FoxP2 levels affect vocal control and alter the function of neural circuits important to learned vocalizations remains unclear. Here we show that FoxP2 knockdown in the songbird striatum disrupts developmental and social modulation of song variability. Recordings in anesthetized birds show that FoxP2 knockdown interferes with D1R-dependent modulation of activity propagation in a corticostriatal pathway important to song variability, an effect that may be partly attributable to reduced D1R and DARPP-32 protein levels. Furthermore, recordings in singing birds reveal that FoxP2 knockdown prevents social modulation of singing-related activity in this pathway. These findings show that reduced FoxP2 levels interfere with the dopaminergic modulation of vocal variability, which may impede song and speech development by disrupting reinforcement learning mechanisms. Copyright © 2013 Elsevier Inc. All rights reserved.

Diminished FoxP2 levels affect dopaminergic modulation of corticostriatal signaling important to song variability

PubMed Central

Murugan, Malavika; Harward, Stephen; Scharff, Constance; Mooney, Richard

2013-01-01

Summary Mutations of the FOXP2 gene impair speech and language development in humans and shRNA-mediated suppression of the avian orthologue FoxP2 disrupts song learning in juvenile zebra finches. How diminished FoxP2 levels affect vocal control and alter the function of neural circuits important to learned vocalizations remains unclear. Here we show that FoxP2 knockdown in the songbird striatum disrupts developmental and social modulation of song variability. Recordings in anaesthetized birds show that FoxP2 knockdown interferes with D1R-dependent modulation of activity propagation in a corticostriatal pathway important to song variability, an effect that may be partly attributable to reduced D1R and DARPP-32 protein levels. Furthermore, recordings in singing birds reveal that FoxP2 knockdown prevents social modulation of singing-related activity in this pathway. These findings show that reduced FoxP2 levels interfere with the dopaminergic modulation of vocal variability, which may impede song and speech development by disrupting reinforcement learning mechanisms. PMID:24268418

Relative controls of external and internal variability on time-variable transit time distributions, and the importance of StorAge Selection function approaches

NASA Astrophysics Data System (ADS)

Kim, M.; Pangle, L. A.; Cardoso, C.; Lora, M.; Meira, A.; Volkmann, T. H. M.; Wang, Y.; Harman, C. J.; Troch, P. A. A.

2015-12-01

Transit time distributions (TTDs) are an efficient way of characterizing complex transport dynamics of a hydrologic system. Time-invariant TTD has been studied extensively, but TTDs are time-varying under unsteady hydrologic systems due to both external variability (e.g., time-variability in fluxes), and internal variability (e.g., time-varying flow pathways). The use of "flow-weighted time" has been suggested to account for the effect of external variability on TTDs, but neglects the role of internal variability. Recently, to account both types of variability, StorAge Selection (SAS) function approaches were developed. One of these approaches enables the transport characteristics of a system - how the different aged water in the storage is sampled by the outflow - to be parameterized by time-variable probability distribution called the rank SAS (rSAS) function, and uses it directly to determine the time-variable TTDs resulting from a given timeseries of fluxes in and out of a system. Unlike TTDs, the form of the rSAS function varies only due to changes in flow pathways, but is not affected by the timing of fluxes alone. However, the relation between physical mechanisms and the time-varying rSAS functions are not well understood. In this study, relative effects of internal and external variability on the TTDs are examined using observations from a homogeneously packed 1 m3 sloping soil lysimeter. The observations suggest the importance of internal variability on TTDs, and reinforce the need to account for this variability using time-variable rSAS functions. Furthermore, the relative usefulness of two other formulations of SAS functions and the mortality rate (which plays a similar role to SAS functions in the McKendrick-von Foerster model of age-structured population dynamics) are also discussed. Finally, numerical modeling is used to explore the role of internal and external variability for hydrologic systems with diverse geomorphic and climate characteristics

Identifying student difficulties with basic scientific reasoning skills: An example from control of variables

NASA Astrophysics Data System (ADS)

Boudreaux, Andrew

2006-05-01

Current national and local standards for the science learning of K-12 students emphasize both basic concepts (such as density) and fundamental reasoning skills (such as proportional reasoning, the interpretation of graphs, and the use of control of variables). At Western Washington University (WWU) and the University of Washington (UW), an effort is underway to examine the ability of university students to apply these same concepts and skills. Populations include students in liberal arts physics courses, introductory calculus-based physics courses, and special courses for the preparation of teachers. One focus of the research has been on the idea of control of variables. This topic is studied by students at all levels, from the primary grades, in which the notion of a ``fair test,'' is sometimes used, to university courses. This talk will discuss research tasks in which students are expected to infer from experimental data whether a particular variable influences (i.e., affects) or by itself determines (i.e., predicts) a given result. Student responses will be presented to identify specific difficulties.

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

MicroRNA Expression in Formalin-fixed Paraffin-embedded Cancer Tissue: Identifying Reference MicroRNAs and Variability.

PubMed

Boisen, Mogens Karsbøl; Dehlendorff, Christian; Linnemann, Dorte; Schultz, Nicolai Aagaard; Jensen, Benny Vittrup; Høgdall, Estrid Vilma Solyom; Johansen, Julia Sidenius

2015-12-29

Archival formalin-fixed paraffin-embedded (FFPE) cancer tissue samples are a readily available resource for microRNA (miRNA) biomarker identification. No established standard for reference miRNAs in FFPE tissue exists. We sought to identify stable reference miRNAs for normalization of miRNA expression in FFPE tissue samples from patients with colorectal (CRC) and pancreatic (PC) cancer and to quantify the variability associated with sample age and fixation. High-throughput miRNA profiling results from 203 CRC and 256 PC FFPE samples as well as from 37 paired frozen/FFPE samples from nine other CRC tumors (methodological samples) were used. Candidate reference miRNAs were identified by their correlation with global mean expression. The stability of reference genes was analyzed according to published methods. The association between sample age and global mean miRNA expression was tested using linear regression. Variability was described using correlation coefficients and linear mixed effects models. Normalization effects were determined by changes in standard deviation and by hierarchical clustering. We created lists of 20 miRNAs with the best correlation to global mean expression in each cancer type. Nine of these miRNAs were present in both lists, and miR-103a-3p was the most stable reference miRNA for both CRC and PC FFPE tissue. The optimal number of reference miRNAs was 4 in CRC and 10 in PC. Sample age had a significant effect on global miRNA expression in PC (50% reduction over 20 years) but not in CRC. Formalin fixation for 2-6 days decreased miRNA expression 30-65%. Normalization using global mean expression reduced variability for technical and biological replicates while normalization using the expression of the identified reference miRNAs reduced variability only for biological replicates. Normalization only had a minor impact on clustering results. We identified suitable reference miRNAs for future miRNA expression experiments using CRC- and PC FFPE

PROMISE: a tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables.

PubMed

Pounds, Stan; Cheng, Cheng; Cao, Xueyuan; Crews, Kristine R; Plunkett, William; Gandhi, Varsha; Rubnitz, Jeffrey; Ribeiro, Raul C; Downing, James R; Lamba, Jatinder

2009-08-15

In some applications, prior biological knowledge can be used to define a specific pattern of association of multiple endpoint variables with a genomic variable that is biologically most interesting. However, to our knowledge, there is no statistical procedure designed to detect specific patterns of association with multiple endpoint variables. Projection onto the most interesting statistical evidence (PROMISE) is proposed as a general procedure to identify genomic variables that exhibit a specific biologically interesting pattern of association with multiple endpoint variables. Biological knowledge of the endpoint variables is used to define a vector that represents the biologically most interesting values for statistics that characterize the associations of the endpoint variables with a genomic variable. A test statistic is defined as the dot-product of the vector of the observed association statistics and the vector of the most interesting values of the association statistics. By definition, this test statistic is proportional to the length of the projection of the observed vector of correlations onto the vector of most interesting associations. Statistical significance is determined via permutation. In simulation studies and an example application, PROMISE shows greater statistical power to identify genes with the interesting pattern of associations than classical multivariate procedures, individual endpoint analyses or listing genes that have the pattern of interest and are significant in more than one individual endpoint analysis. Documented R routines are freely available from www.stjuderesearch.org/depts/biostats and will soon be available as a Bioconductor package from www.bioconductor.org.

27 CFR 478.92 - How must licensed manufacturers and licensed importers identify firearms, armor piercing...

Code of Federal Regulations, 2010 CFR

2010-04-01

... Conduct of Business § 478.92 How must licensed manufacturers and licensed importers identify firearms... business; and (E) In the case of an imported firearm, the name of the country in which it was manufactured... place of business. For additional requirements relating to imported firearms, see Customs regulations at...

Identifying hub stations and important lines of bus networks: A case study in Xiamen, China

NASA Astrophysics Data System (ADS)

Zhang, Hui; Zhuge, Chengxiang; Yu, Xiaohua

2018-07-01

Hub stations and important lines play key roles in transfers between stations. In this paper, a node failure model is proposed to identify hub stations. In the model, we introduce two new indicators called neighborhood degree ratio and transfer index to evaluate the importance of stations, which consider neighborhood stations' degree of station and the initial transfer times between stations. Moreover, line accessibility is developed to measure the importance of lines in the bus network. Xiamen bus network in 2016 is utilized to test the model. The results show that the two introduced indicators are more effective to identify hub stations compared with traditional complex network indicators such as degree, clustering coefficient and betweenness.

Important caves to be identified

NASA Astrophysics Data System (ADS)

Criteria to identify significant caves on federal land are being developed by the Interior Department's Bureau of Land Management and the Agriculture Department's Forest Service under requirements of the Federal Cave Resources Protection Act of 1988. The departments gave advance notice of proposed rulemaking March 3 and invited suggestions and comments from the public for 30 days.The law requires protection, to the extent practical, of significant caves on lands administered by the Secretaries of Agriculture and Interior and includes authority to issue and revoke permits for collection and removal of cave resources and special provisions for regulation of cave resources on Indian lands. Final regulations must be published by August 18, 1989.

Quantitative DNA Methylation Analysis Identifies a Single CpG Dinucleotide Important for ZAP-70 Expression and Predictive of Prognosis in Chronic Lymphocytic Leukemia

PubMed Central

Claus, Rainer; Lucas, David M.; Stilgenbauer, Stephan; Ruppert, Amy S.; Yu, Lianbo; Zucknick, Manuela; Mertens, Daniel; Bühler, Andreas; Oakes, Christopher C.; Larson, Richard A.; Kay, Neil E.; Jelinek, Diane F.; Kipps, Thomas J.; Rassenti, Laura Z.; Gribben, John G.; Döhner, Hartmut; Heerema, Nyla A.; Marcucci, Guido; Plass, Christoph; Byrd, John C.

2012-01-01

Purpose Increased ZAP-70 expression predicts poor prognosis in chronic lymphocytic leukemia (CLL). Current methods for accurately measuring ZAP-70 expression are problematic, preventing widespread application of these tests in clinical decision making. We therefore used comprehensive DNA methylation profiling of the ZAP-70 regulatory region to identify sites important for transcriptional control. Patients and Methods High-resolution quantitative DNA methylation analysis of the entire ZAP-70 gene regulatory regions was conducted on 247 samples from patients with CLL from four independent clinical studies. Results Through this comprehensive analysis, we identified a small area in the 5′ regulatory region of ZAP-70 that showed large variability in methylation in CLL samples but was universally methylated in normal B cells. High correlation with mRNA and protein expression, as well as activity in promoter reporter assays, revealed that within this differentially methylated region, a single CpG dinucleotide and neighboring nucleotides are particularly important in ZAP-70 transcriptional regulation. Furthermore, by using clustering approaches, we identified a prognostic role for this site in four independent data sets of patients with CLL using time to treatment, progression-free survival, and overall survival as clinical end points. Conclusion Comprehensive quantitative DNA methylation analysis of the ZAP-70 gene in CLL identified important regions responsible for transcriptional regulation. In addition, loss of methylation at a specific single CpG dinucleotide in the ZAP-70 5′ regulatory sequence is a highly predictive and reproducible biomarker of poor prognosis in this disease. This work demonstrates the feasibility of using quantitative specific ZAP-70 methylation analysis as a relevant clinically applicable prognostic test in CLL. PMID:22564988

Learner Variables Important for Success in L2 Listening Comprehension in French Immersion Classrooms

ERIC Educational Resources Information Center

Vandergrift, Larry; Baker, Susan C.

2018-01-01

Listening comprehension, which is relatively straightforward for native language (L1) speakers, is often frustrating for second language (L2) learners. Listening comprehension is important to L2 acquisition, but little is known about the variables that influence the development of L2 listening skills. The goal of this study was to determine which…

Different approaches for identifying important concepts in probabilistic biomedical text summarization.

PubMed

Moradi, Milad; Ghadiri, Nasser

2018-01-01

Automatic text summarization tools help users in the biomedical domain to acquire their intended information from various textual resources more efficiently. Some of biomedical text summarization systems put the basis of their sentence selection approach on the frequency of concepts extracted from the input text. However, it seems that exploring other measures rather than the raw frequency for identifying valuable contents within an input document, or considering correlations existing between concepts, may be more useful for this type of summarization. In this paper, we describe a Bayesian summarization method for biomedical text documents. The Bayesian summarizer initially maps the input text to the Unified Medical Language System (UMLS) concepts; then it selects the important ones to be used as classification features. We introduce six different feature selection approaches to identify the most important concepts of the text and select the most informative contents according to the distribution of these concepts. We show that with the use of an appropriate feature selection approach, the Bayesian summarizer can improve the performance of biomedical summarization. Using the Recall-Oriented Understudy for Gisting Evaluation (ROUGE) toolkit, we perform extensive evaluations on a corpus of scientific papers in the biomedical domain. The results show that when the Bayesian summarizer utilizes the feature selection methods that do not use the raw frequency, it can outperform the biomedical summarizers that rely on the frequency of concepts, domain-independent and baseline methods. Copyright © 2017 Elsevier B.V. All rights reserved.

Inter-Annual Variability of the Acoustic Propagation in the Mediterranean Sea Identified from a Synoptic Monthly Gridded Database as Compared with GDEM

DTIC Science & Technology

2016-12-01

VARIABILITY OF THE ACOUSTIC PROPAGATION IN THE MEDITERRANEAN SEA IDENTIFIED FROM A SYNOPTIC MONTHLY GRIDDED DATABASE AS COMPARED WITH GDEM by...ANNUAL VARIABILITY OF THE ACOUSTIC PROPAGATION IN THE MEDITERRANEAN SEA IDENTIFIED FROM A SYNOPTIC MONTHLY GRIDDED DATABASE AS COMPARED WITH GDEM 5...profiles obtained from the synoptic monthly gridded World Ocean Database (SMD-WOD) and Generalized Digital Environmental Model (GDEM) temperature (T

A framework for monitoring-based commissioning: Identifying variables that act as barriers and enablers to the process

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

Harris, Nora; Shealy, Tripp; Kramer, Hannah

The practice of monitoring-based commissioning (MBCx) using energy management and information systems (EMIS) has been shown to enable and help sustain up to 20% energy savings in buildings. Despite research that has quantified the costs, benefits, and energy savings of MBCx, the process remains under-utilized. To understand why MBCx is not more frequently adopted and how to encourage its use, this research synthesizes qualitative data from over 40 organizations, currently engaging in MBCx. The outcome of this research is a framework containing variables that emerged from the qualitative data, marked as barriers or enablers, organized by phases of the MBCxmore » process. The framework is comprised of 51 emergent variables that fall within 13 different categories. The variables that most frequently act as barriers are data configuration, measurement & verification (M&V), developing specifications for EMIS, and data architecture. Although some variables that act as barriers for one organization were identified as enablers for another. For example, payback/ROI was considered a barrier 7 times and an enabler 3 times. One organization had difficulty making the business case for the initial investment for MBCx due to lack of cost information, while another was able to justify large investments with documented savings of previously implemented measures identified through MBCx. The framework formally validates barriers found in previous research, and can be used by practitioners to better understand common experiences with MBCx. This research also highlights the need for a similar collective data set to validate common enablers to MBCx and also the need for empirical research to determine relationships between variables.« less

A framework for monitoring-based commissioning: Identifying variables that act as barriers and enablers to the process

DOE PAGES

Harris, Nora; Shealy, Tripp; Kramer, Hannah; ...

2018-03-16

The practice of monitoring-based commissioning (MBCx) using energy management and information systems (EMIS) has been shown to enable and help sustain up to 20% energy savings in buildings. Despite research that has quantified the costs, benefits, and energy savings of MBCx, the process remains under-utilized. To understand why MBCx is not more frequently adopted and how to encourage its use, this research synthesizes qualitative data from over 40 organizations, currently engaging in MBCx. The outcome of this research is a framework containing variables that emerged from the qualitative data, marked as barriers or enablers, organized by phases of the MBCxmore » process. The framework is comprised of 51 emergent variables that fall within 13 different categories. The variables that most frequently act as barriers are data configuration, measurement & verification (M&V), developing specifications for EMIS, and data architecture. Although some variables that act as barriers for one organization were identified as enablers for another. For example, payback/ROI was considered a barrier 7 times and an enabler 3 times. One organization had difficulty making the business case for the initial investment for MBCx due to lack of cost information, while another was able to justify large investments with documented savings of previously implemented measures identified through MBCx. The framework formally validates barriers found in previous research, and can be used by practitioners to better understand common experiences with MBCx. This research also highlights the need for a similar collective data set to validate common enablers to MBCx and also the need for empirical research to determine relationships between variables.« less

PROMISE: a tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables

PubMed Central

Pounds, Stan; Cheng, Cheng; Cao, Xueyuan; Crews, Kristine R.; Plunkett, William; Gandhi, Varsha; Rubnitz, Jeffrey; Ribeiro, Raul C.; Downing, James R.; Lamba, Jatinder

2009-01-01

Motivation: In some applications, prior biological knowledge can be used to define a specific pattern of association of multiple endpoint variables with a genomic variable that is biologically most interesting. However, to our knowledge, there is no statistical procedure designed to detect specific patterns of association with multiple endpoint variables. Results: Projection onto the most interesting statistical evidence (PROMISE) is proposed as a general procedure to identify genomic variables that exhibit a specific biologically interesting pattern of association with multiple endpoint variables. Biological knowledge of the endpoint variables is used to define a vector that represents the biologically most interesting values for statistics that characterize the associations of the endpoint variables with a genomic variable. A test statistic is defined as the dot-product of the vector of the observed association statistics and the vector of the most interesting values of the association statistics. By definition, this test statistic is proportional to the length of the projection of the observed vector of correlations onto the vector of most interesting associations. Statistical significance is determined via permutation. In simulation studies and an example application, PROMISE shows greater statistical power to identify genes with the interesting pattern of associations than classical multivariate procedures, individual endpoint analyses or listing genes that have the pattern of interest and are significant in more than one individual endpoint analysis. Availability: Documented R routines are freely available from www.stjuderesearch.org/depts/biostats and will soon be available as a Bioconductor package from www.bioconductor.org. Contact: stanley.pounds@stjude.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19528086

Permutation importance: a corrected feature importance measure.

PubMed

Altmann, André; Toloşi, Laura; Sander, Oliver; Lengauer, Thomas

2010-05-15

In life sciences, interpretability of machine learning models is as important as their prediction accuracy. Linear models are probably the most frequently used methods for assessing feature relevance, despite their relative inflexibility. However, in the past years effective estimators of feature relevance have been derived for highly complex or non-parametric models such as support vector machines and RandomForest (RF) models. Recently, it has been observed that RF models are biased in such a way that categorical variables with a large number of categories are preferred. In this work, we introduce a heuristic for normalizing feature importance measures that can correct the feature importance bias. The method is based on repeated permutations of the outcome vector for estimating the distribution of measured importance for each variable in a non-informative setting. The P-value of the observed importance provides a corrected measure of feature importance. We apply our method to simulated data and demonstrate that (i) non-informative predictors do not receive significant P-values, (ii) informative variables can successfully be recovered among non-informative variables and (iii) P-values computed with permutation importance (PIMP) are very helpful for deciding the significance of variables, and therefore improve model interpretability. Furthermore, PIMP was used to correct RF-based importance measures for two real-world case studies. We propose an improved RF model that uses the significant variables with respect to the PIMP measure and show that its prediction accuracy is superior to that of other existing models. R code for the method presented in this article is available at http://www.mpi-inf.mpg.de/ approximately altmann/download/PIMP.R CONTACT: altmann@mpi-inf.mpg.de, laura.tolosi@mpi-inf.mpg.de Supplementary data are available at Bioinformatics online.

Identifying populations sensitive to environmental chemicals by simulating toxicokinetic variability

EPA Science Inventory

We incorporate inter-individual variability, including variability across demographic subgroups, into an open-source high-throughput (HT) toxicokinetics (TK) modeling framework for use in a next-generation risk prioritization approach. Risk prioritization involves rapid triage of...

Variables Associated with First Year Teacher Morale Which Can Be Identified in a Teacher Education Program.

ERIC Educational Resources Information Center

Thomson, James R., Jr.; Schuck, Robert F.

This paper presents a study of the personal variables associated with first-year teacher morale that can be identified early in the training programs of novice teachers. This study is based on data derived from 96 (76.6 percent) of the graduates teaching in Mississippi. Data were collected through the use of five special instruments: (1)…

Identifying potential academic leaders

PubMed Central

White, David; Krueger, Paul; Meaney, Christopher; Antao, Viola; Kim, Florence; Kwong, Jeffrey C.

2016-01-01

Objective To identify variables associated with willingness to undertake leadership roles among academic family medicine faculty. Design Web-based survey. Bivariate and multivariable analyses (logistic regression) were used to identify variables associated with willingness to undertake leadership roles. Setting Department of Family and Community Medicine at the University of Toronto in Ontario. Participants A total of 687 faculty members. Main outcome measures Variables related to respondents’ willingness to take on various academic leadership roles. Results Of all 1029 faculty members invited to participate in the survey, 687 (66.8%) members responded. Of the respondents, 596 (86.8%) indicated their level of willingness to take on various academic leadership roles. Multivariable analysis revealed that the predictors associated with willingness to take on leadership roles were as follows: pursuit of professional development opportunities (odds ratio [OR] 3.79, 95% CI 2.29 to 6.27); currently holding at least 1 leadership role (OR 5.37, 95% CI 3.38 to 8.53); a history of leadership training (OR 1.86, 95% CI 1.25 to 2.78); the perception that mentorship is important for one’s current role (OR 2.25, 95% CI 1.40 to 3.60); and younger age (OR 0.97, 95% CI 0.95 to 0.99). Conclusion Willingness to undertake new or additional leadership roles was associated with 2 variables related to leadership experiences, 2 variables related to perceptions of mentorship and professional development, and 1 demographic variable (younger age). Interventions that support opportunities in these areas might expand the pool and strengthen the academic leadership potential of faculty members. PMID:27331226

PTEN IDENTIFIED AS IMPORTANT RISK FACTOR OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE

PubMed Central

Hosgood, H Dean; Menashe, Idan; He, Xingzhou; Chanock, Stephen; Lan, Qing

2009-01-01

Common genetic variation may play an important role in altering chronic obstructive pulmonary disease (COPD) risk. In Xuanwei, China, the COPD rate is more than twice the Chinese national average, and COPD is strongly associated with in-home coal use. To identify genetic variation that may be associated with COPD in a population with substantial in-home coal smoke exposures, we evaluated 1,261 single nucleotide polymorphisms (SNPs) in 380 candidate genes potentially relevant for cancer and other human diseases in a population-based case-control study in Xuanwei (53 cases; 107 controls). PTEN was the most significantly associated gene with COPD in a minP analysis using 20,000 permutations (P = 0.00005). SNP-based analyses found that homozygote variant carriers of PTEN rs701848 (ORTT = 0.12, 95%CI = 0.03 - 0.47) had a significant decreased risk of COPD. PTEN, or phosphatase and tensin homolog, is an important regulator of cell cycle progression and cellular survival via the AKT signaling pathway. Our exploratory analysis suggests that genetic variation in PTEN may be an important risk factor of COPD in Xuanwei. However, due to the small sample size, additional studies are needed to evaluate these associations within Xuanwei and other populations with coal smoke exposures. PMID:19625176

Importance-Performance Matrix Analysis (IPMA) Of Transport Disadvantage Variables on Social Exclusion in a Rural Context

NASA Astrophysics Data System (ADS)

Larasati, Ophilia; Puspita Dirgahayani, Eng., Dr.

2018-05-01

Transport services are essential to support daily life. A lack of transport supply leads to the existence of transport disadvantaged (TDA) groups who are vulnerable to social exclusion, which happens when a particular group or individual is having difficulties to access certain activities that are considered normal in society. To tackle this phenomenon, the understanding of the influence of TDA variables on social exclusion is needed. The aim of this study is to analyze the influences of TDA variables on social exclusion in a rural context, with Cibeureum Village (Bandung Barat Regency) and Bunikasih Village (Subang Regency) as the study case. Both case studies provide different characteristics of accessibility. Partial Least Squares (PLS) Structural Equation Modeling (SEM) is chosen as the method to analyze the influences of TDA variables on social exclusion. The PLS-SEM model is developed according to the social exclusion variable and four TDA variables, i.e., accessibility, individual characteristics, private vehicle existence, and travel behavior. IPMA is done after the PLS-SEM model is evaluated. The study reveals that among four of the TDA variables, accessibility has the most influence on social exclusion, hence interventions related to improving accessibility are needed to tackle social exclusion. More specifically, the provision of alternative modes is needed in both study areas, while in Bunikasih Village the cost of travel is also an important variable to consider.

Observing Two Important Teaching Variables.

ERIC Educational Resources Information Center

Gustafson, John A.

1986-01-01

Two behaviors essential to good teaching, teacher expectation and teacher flexibility, have been incorporated into the observation system used in the student teacher program at the University of New Mexico. The importance of these behaviors in teaching and in evaluating student teachers is discussed. (MT)

For the Love of Nature: Exploring the Importance of Species Diversity and Micro-Variables Associated with Favorite Outdoor Places.

PubMed

Schebella, Morgan F; Weber, Delene; Lindsey, Kiera; Daniels, Christopher B

2017-01-01

Although the restorative benefits of nature are widely acknowledged, there is a limited understanding of the attributes of natural environments that are fundamental to restorative experiences. Faced with growing human populations and a greater awareness of the wellbeing benefits natural environments provide, park agencies and planners are increasingly challenged with balancing human and ecological outcomes in natural areas. This study examines the physical and experiential qualities of natural environments people referred to when describing their connection to their most valued natural environments in an online questionnaire. Recruited primarily via a public radio program, respondents were asked to identify their favorite places and explain what they loved about those places. Favorite places are considered exemplars of restorative environments and were classified based on an existing park typology. Reasons people liked particular sites were classified into three domains: setting, activity, or benefit. Content analysis was used to identify the attributes most commonly associated with favorite places. These attributes were then related to the four components of restorative environments according to Attention Restoration Theory. In contrast to previous research, we found that "fascination" was the most important component of favorite places. Possible reasons for this contrast, namely, respondents' median age, and the likelihood of a high degree of ecological literacy amongst the study population are discussed. South Australians' favorite environments comprise primarily hilly, wooded nature parks, and botanical gardens, in stark contrast to the vast arid areas that dominate the state. Micro-variables such as birds, plants, wildlife, native species, and biodiversity appear particularly important elements used to explain people's love of these sites. We discuss the implications of these findings and their potential value as an anchor for marketing campaigns seeking to

For the Love of Nature: Exploring the Importance of Species Diversity and Micro-Variables Associated with Favorite Outdoor Places

PubMed Central

Schebella, Morgan F.; Weber, Delene; Lindsey, Kiera; Daniels, Christopher B.

2017-01-01

Although the restorative benefits of nature are widely acknowledged, there is a limited understanding of the attributes of natural environments that are fundamental to restorative experiences. Faced with growing human populations and a greater awareness of the wellbeing benefits natural environments provide, park agencies and planners are increasingly challenged with balancing human and ecological outcomes in natural areas. This study examines the physical and experiential qualities of natural environments people referred to when describing their connection to their most valued natural environments in an online questionnaire. Recruited primarily via a public radio program, respondents were asked to identify their favorite places and explain what they loved about those places. Favorite places are considered exemplars of restorative environments and were classified based on an existing park typology. Reasons people liked particular sites were classified into three domains: setting, activity, or benefit. Content analysis was used to identify the attributes most commonly associated with favorite places. These attributes were then related to the four components of restorative environments according to Attention Restoration Theory. In contrast to previous research, we found that “fascination” was the most important component of favorite places. Possible reasons for this contrast, namely, respondents' median age, and the likelihood of a high degree of ecological literacy amongst the study population are discussed. South Australians' favorite environments comprise primarily hilly, wooded nature parks, and botanical gardens, in stark contrast to the vast arid areas that dominate the state. Micro-variables such as birds, plants, wildlife, native species, and biodiversity appear particularly important elements used to explain people's love of these sites. We discuss the implications of these findings and their potential value as an anchor for marketing campaigns seeking

Identifying Social Trust in Cross-Country Analysis: Do We Really Measure the Same?

ERIC Educational Resources Information Center

Torpe, Lars; Lolle, Henrik

2011-01-01

Many see trust as an important social resource for the welfare of individuals as well as nations. It is therefore important to be able to identify trust and explain its sources. Cross-country survey analysis has been an important tool in this respect, and often one single variable is used to identify social trust understood as trust in strangers,…

Identifying obstacles and ranking common biological control research priorities for Europe to manage most economically important pests in arable, vegetable and perennial crops.

PubMed

Lamichhane, Jay Ram; Bischoff-Schaefer, Monika; Bluemel, Sylvia; Dachbrodt-Saaydeh, Silke; Dreux, Laure; Jansen, Jean-Pierre; Kiss, Jozsef; Köhl, Jürgen; Kudsk, Per; Malausa, Thibaut; Messéan, Antoine; Nicot, Philippe C; Ricci, Pierre; Thibierge, Jérôme; Villeneuve, François

2017-01-01

EU agriculture is currently in transition from conventional crop protection to integrated pest management (IPM). Because biocontrol is a key component of IPM, many European countries recently have intensified their national efforts on biocontrol research and innovation (R&I), although such initiatives are often fragmented. The operational outputs of national efforts would benefit from closer collaboration among stakeholders via transnationally coordinated approaches, as most economically important pests are similar across Europe. This paper proposes a common European framework on biocontrol R&I. It identifies generic R&I bottlenecks and needs as well as priorities for three crop types (arable, vegetable and perennial crops). The existing gap between the market offers of biocontrol solutions and the demand of growers, the lengthy and expensive registration process for biocontrol solutions and their varying effectiveness due to variable climatic conditions and site-specific factors across Europe are key obstacles hindering the development and adoption of biocontrol solutions in Europe. Considering arable, vegetable and perennial crops, a dozen common target pests are identified for each type of crop and ranked by order of importance at European level. Such a ranked list indicates numerous topics on which future joint transnational efforts would be justified. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

What weather variables are important in predicting heat-related mortality? A new application of statistical learning methods

PubMed Central

Zhang, Kai; Li, Yun; Schwartz, Joel D.; O'Neill, Marie S.

2014-01-01

Hot weather increases risk of mortality. Previous studies used different sets of weather variables to characterize heat stress, resulting in variation in heat-mortality- associations depending on the metric used. We employed a statistical learning method – random forests – to examine which of various weather variables had the greatest impact on heat-related mortality. We compiled a summertime daily weather and mortality counts dataset from four U.S. cities (Chicago, IL; Detroit, MI; Philadelphia, PA; and Phoenix, AZ) from 1998 to 2006. A variety of weather variables were ranked in predicting deviation from typical daily all-cause and cause-specific death counts. Ranks of weather variables varied with city and health outcome. Apparent temperature appeared to be the most important predictor of heat-related mortality for all-cause mortality. Absolute humidity was, on average, most frequently selected one of the top variables for all-cause mortality and seven cause-specific mortality categories. Our analysis affirms that apparent temperature is a reasonable variable for activating heat alerts and warnings, which are commonly based on predictions of total mortality in next few days. Additionally, absolute humidity should be included in future heat-health studies. Finally, random forests can be used to guide choice of weather variables in heat epidemiology studies. PMID:24834832

Quantifying Forest Soil Physical Variables Potentially Important for Site Growth Analyses

Treesearch

John S. Kush; Douglas G. Pitt; Phillip J. Craul; William D. Boyer

2004-01-01

Accurate mean plot values of forest soil factors are required for use as independent variables in site-growth analyses. Adequate accuracy is often difficult to attain because soils are inherently widely variable. Estimates of the variability of appropriate soil factors influencing growth can be used to determine the sampling intensity required to secure accurate mean...

Identifying emotional intelligence skills of Turkish clinical nurses according to sociodemographic and professional variables.

PubMed

Kahraman, Nilgün; Hiçdurmaz, Duygu

2016-04-01

This study aimed to identify the emotional intelligence skills of Turkish clinical nurses according to sociodemographic and professional variables. Emotional intelligence is "the ability of a person to comprehend self-emotions, to show empathy towards the feelings of others, and to control self-emotions in a way that enriches life." Nurses with a higher emotional intelligence level offer more efficient and professional care, and they accomplish more in their social and professional lives. We designed a descriptive cross-sectional study. The Introductory Information Form and the Bar-On emotional intelligence Inventory were used to collect data between 20th June and 20th August 2012. The study was conducted with 312 nurses from 37 hospitals located within the borders of the metropolitan municipality in Ankara. There were no significant differences between emotional intelligence scores of the nurses according to demographic variables such as age, gender, marital status, having children. Thus, sociodemographic factors did not appear to be key factors, but some professional variables did. Higher total emotional intelligence scores were observed in those who had 10 years or longer experience, who found oneself successful in professional life, who stated that emotional intelligence is an improvable skill and who previously received self-improvement training. Interpersonal skills were higher in those with a graduate degree and in nurses working in polyclinics and paediatric units. These findings indicate which groups require improvement in emotional intelligence skills and which skills need improvement. Additionally, these results provide knowledge and create awareness about emotional intelligence skills of nurses and the distribution of these skills according to sociodemographic and professional variables. Implementation of emotional intelligence improvement programmes targeting the determined clinical nursing groups by nursing administrations can help the increase in

Practices for Identifying and Rejecting Hemolyzed Specimens Are Highly Variable in Clinical Laboratories.

PubMed

Howanitz, Peter J; Lehman, Christopher M; Jones, Bruce A; Meier, Frederick A; Horowitz, Gary L

2015-08-01

Hemolysis is an important clinical laboratory quality attribute that influences result reliability. To determine hemolysis identification and rejection practices occurring in clinical laboratories. We used the College of American Pathologists Survey program to distribute a Q-Probes-type questionnaire about hemolysis practices to Chemistry Survey participants. Of 3495 participants sent the questionnaire, 846 (24%) responded. In 71% of 772 laboratories, the hemolysis rate was less than 3.0%, whereas in 5%, it was 6.0% or greater. A visual scale, an instrument scale, and combination of visual and instrument scales were used to identify hemolysis in 48%, 11%, and 41% of laboratories, respectively. A picture of the hemolysis level was used as an aid to technologists' visual interpretation of hemolysis levels in 40% of laboratories. In 7.0% of laboratories, all hemolyzed specimens were rejected; in 4% of laboratories, no hemolyzed specimens were rejected; and in 88% of laboratories, some specimens were rejected depending on hemolysis levels. Participants used 69 different terms to describe hemolysis scales, with 21 terms used in more than 10 laboratories. Slight and moderate were the terms used most commonly. Of 16 different cutoffs used to reject hemolyzed specimens, moderate was the most common, occurring in 30% of laboratories. For whole blood electrolyte measurements performed in 86 laboratories, 57% did not evaluate the presence of hemolysis, but for those that did, the most common practice in 21 laboratories (24%) was centrifuging and visually determining the presence of hemolysis in all specimens. Hemolysis practices vary widely. Standard assessment and consistent reporting are the first steps in reducing interlaboratory variability among results.

Importance of ocean mesoscale variability for air-sea interactions in the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Putrasahan, D. A.; Kamenkovich, I.; Le Hénaff, M.; Kirtman, B. P.

2017-06-01

Mesoscale variability of currents in the Gulf of Mexico (GoM) can affect oceanic heat advection and air-sea heat exchanges, which can influence climate extremes over North America. This study is aimed at understanding the influence of the oceanic mesoscale variability on the lower atmosphere and air-sea heat exchanges. The study contrasts global climate model (GCM) with 0.1° ocean resolution (high resolution; HR) with its low-resolution counterpart (1° ocean resolution with the same 0.5° atmosphere resolution; LR). The LR simulation is relevant to current generation of GCMs that are still unable to resolve the oceanic mesoscale. Similar to observations, HR exhibits positive correlation between sea surface temperature (SST) and surface turbulent heat flux anomalies, while LR has negative correlation. For HR, we decompose lateral advective heat fluxes in the upper ocean into mean (slowly varying) and mesoscale-eddy (fast fluctuations) components. We find that the eddy flux divergence/convergence dominates the lateral advection and correlates well with the SST anomalies and air-sea latent heat exchanges. This result suggests that oceanic mesoscale advection supports warm SST anomalies that in turn feed surface heat flux. We identify anticyclonic warm-core circulation patterns (associated Loop Current and rings) which have an average diameter of 350 km. These warm anomalies are sustained by eddy heat flux convergence at submonthly time scales and have an identifiable imprint on surface turbulent heat flux, atmospheric circulation, and convective precipitation in the northwest portion of an averaged anticyclone.

Prognostic importance of glycaemic variability on hospital mortality in patients hospitalised in Internal Medicine Departments.

PubMed

Sáenz-Abad, D; Gimeno-Orna, J A; Pérez-Calvo, J I

2015-12-01

The objective was to assess the prognostic importance of various glycaemic control measures on hospital mortality. Retrospective, analytical cohort study that included patients hospitalised in internal medicine departments with a diagnosis related to diabetes mellitus (DM), excluding acute decompensations. The clinical endpoint was hospital mortality. We recorded clinical, analytical and glycaemic control-related variables (scheduled insulin administration, plasma glycaemia at admission, HbA1c, mean glycaemia (MG) and in-hospital glycaemic variability and hypoglycaemia). The measurement of hospital mortality predictors was performed using univariate and multivariate logistic regression. A total of 384 patients (50.3% men) were included. The mean age was 78.5 (SD, 10.3) years. The DM-related diagnoses were type 2 diabetes (83.6%) and stress hyperglycaemia (6.8%). Thirty-one (8.1%) patients died while in hospital. In the multivariate analysis, the best model for predicting mortality (R(2)=0.326; P<.0001) consisted, in order of importance, of age (χ(2)=8.19; OR=1.094; 95% CI 1.020-1.174; P=.004), Charlson index (χ(2)=7.28; OR=1.48; 95% CI 1.11-1.99; P=.007), initial glycaemia (χ(2)=6.05; OR=1.007; 95% CI 1.001-1.014; P=.014), HbA1c (χ(2)=5.76; OR=0.59; 95% CI 0.33-1; P=.016), glycaemic variability (χ(2)=4.41; OR=1.031; 95% CI 1-1.062; P=.036), need for corticosteroid treatment (χ(2)=4.03; OR=3.1; 95% CI 1-9.64; P=.045), administration of scheduled insulin (χ(2)=3.98; OR=0.26; 95% CI 0.066-1; P=.046) and systolic blood pressure (χ(2)=2.92; OR=0.985; 95% CI 0.97-1.003; P=.088). An increase in initial glycaemia and in-hospital glycaemic variability predict the risk of mortality for hospitalised patients with DM. Copyright © 2015 Elsevier España, S.L.U. y Sociedad Española de Medicina Interna (SEMI). All rights reserved.

Discovering human germ cell mutagens with whole genome sequencing: Insights from power calculations reveal the importance of controlling for between-family variability.

PubMed

Webster, R J; Williams, A; Marchetti, F; Yauk, C L

2018-07-01

Mutations in germ cells pose potential genetic risks to offspring. However, de novo mutations are rare events that are spread across the genome and are difficult to detect. Thus, studies in this area have generally been under-powered, and no human germ cell mutagen has been identified. Whole Genome Sequencing (WGS) of human pedigrees has been proposed as an approach to overcome these technical and statistical challenges. WGS enables analysis of a much wider breadth of the genome than traditional approaches. Here, we performed power analyses to determine the feasibility of using WGS in human families to identify germ cell mutagens. Different statistical models were compared in the power analyses (ANOVA and multiple regression for one-child families, and mixed effect model sampling between two to four siblings per family). Assumptions were made based on parameters from the existing literature, such as the mutation-by-paternal age effect. We explored two scenarios: a constant effect due to an exposure that occurred in the past, and an accumulating effect where the exposure is continuing. Our analysis revealed the importance of modeling inter-family variability of the mutation-by-paternal age effect. Statistical power was improved by models accounting for the family-to-family variability. Our power analyses suggest that sufficient statistical power can be attained with 4-28 four-sibling families per treatment group, when the increase in mutations ranges from 40 to 10% respectively. Modeling family variability using mixed effect models provided a reduction in sample size compared to a multiple regression approach. Much larger sample sizes were required to detect an interaction effect between environmental exposures and paternal age. These findings inform study design and statistical modeling approaches to improve power and reduce sequencing costs for future studies in this area. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

Protein construct storage: Bayesian variable selection and prediction with mixtures.

PubMed

Clyde, M A; Parmigiani, G

1998-07-01

Determining optimal conditions for protein storage while maintaining a high level of protein activity is an important question in pharmaceutical research. A designed experiment based on a space-filling design was conducted to understand the effects of factors affecting protein storage and to establish optimal storage conditions. Different model-selection strategies to identify important factors may lead to very different answers about optimal conditions. Uncertainty about which factors are important, or model uncertainty, can be a critical issue in decision-making. We use Bayesian variable selection methods for linear models to identify important variables in the protein storage data, while accounting for model uncertainty. We also use the Bayesian framework to build predictions based on a large family of models, rather than an individual model, and to evaluate the probability that certain candidate storage conditions are optimal.

Diagnostic Value of Selected Echocardiographic Variables to Identify Pulmonary Hypertension in Dogs with Myxomatous Mitral Valve Disease.

PubMed

Tidholm, A; Höglund, K; Häggström, J; Ljungvall, I

2015-01-01

Pulmonary hypertension (PH) is commonly associated with myxomatous mitral valve disease (MMVD). Because dogs with PH present without measureable tricuspid regurgitation (TR), it would be useful to investigate echocardiographic variables that can identify PH. To investigate associations between estimated systolic TR pressure gradient (TRPG) and dog characteristics and selected echocardiographic variables. 156 privately owned dogs. Prospective observational study comparing the estimations of TRPG with dog characteristics and selected echocardiographic variables in dogs with MMVD and measureable TR. Tricuspid regurgitation pressure gradient was significantly (P < .05) associated with body weight corrected right (RVIDDn) and left (LVIDDn) ventricular end-diastolic and systolic (LVIDSn) internal diameters, pulmonary arterial (PA) acceleration to deceleration time ratio (AT/DT), heart rate, left atrial to aortic root ratio (LA/Ao), and the presence of congestive heart failure. Four variables remained significant in the multiple regression analysis with TRPG as a dependent variable: modeled as linear variables LA/Ao (P < .0001) and RVIDDn (P = .041), modeled as second order polynomial variables: AT/DT (P = .0039) and LVIDDn (P < .0001) The adjusted R(2) -value for the final model was 0.45 and receiver operating characteristic curve analysis suggested the model's performance to predict PH, defined as 36, 45, and 55 mmHg as fair (area under the curve [AUC] = 0.80), good (AUC = 0.86), and excellent (AUC = 0.92), respectively. In dogs with MMVD, the presence of PH might be suspected with the combination of decreased PA AT/DT, increased RVIDDn and LA/Ao, and a small or great LVIDDn. Copyright © 2015 The Authors Journal of Veterinary Internal Medicine published by Wiley Periodicals, Inc. on behalf of the American College of Veterinary Internal Medicine.

Utilizing the AAVSO's Variable Star Index (VSX) In Undergraduate Research Projects

NASA Astrophysics Data System (ADS)

Larsen, Kristine

2016-01-01

Among the many important services that the American Association of Variable Star Observers (AAVSO) provides to the astronomical community is the Variable Star Index (VSX - https://www.aavso.org/vsx/). This online catalog of variable stars is the repository of data on over 334,000 variable stars, including information on spectral type, range of magnitude, period, and type of variable, among other properties. A number of these stars were identified as being variable through automated telescope surveys, such as ASAS (All Sky Automated Survey). The computer code of this survey classified newly discovered variables as best it could, but a significant number of false classifications have been noted. The reclassification of ASAS variables in the VSX data, as well as a closer look at variables identified as miscellaneous type in VSX, are two of many projects that can be undertaken by interested undergraduates. In doing so, students learn about the physical properties of various types of variable stars as well as statistical analysis and computer software, especially the VStar variable star data visualization and analysis tool that is available to the astronomical community free of charge on the AAVSO website (https://www.aavso.org/vstar-overview). Two such projects are described in this presentation, the first to identify BY Draconis variables erroneously classified as Cepheids in ASAS data, and the second to identify SRD semiregular variables misidentified as "miscellaneous" in VSX.

Identification of Important Process Variables for Fiber Spinning of Protein Nanotubes Generated from Waste Materials

DTIC Science & Technology

2012-01-11

nanotubes , which sold at the same current cost as carbon nanotubes , this would equate to a $788 million industry. In the USA, the potential to source eye...advantages over carbon nanotubes due to the ability to functionalized them 31. The nanotubes are a highly ordered, insoluble form of protein. Fibrils...1756 Identification of important process variables for fiber spinning of protein nanotubes generated from waste materials. Research Team (listed

Determining the influence and effects of manufacturing variables on sulfur dioxide cells

NASA Technical Reports Server (NTRS)

Zajac, W. V.; Thomas, M. A.; Barnes, J. A.; Bis, R., F.; Davis, P. B.; Debold, F. C.; Gemmill, G. W.; Kowalchik, L. A.

1986-01-01

A survey of the Li/SO2 manufacturing community was conducted to determine where variability exists in processing. The upper and lower limits of these processing variables might, by themselves or by interacting with other variables, influence safety, performance, and reliability. A number of important variables were identified and a comprehensive design experiment is being proposed to make the proper determinations.

Importance of Non-invasive Right and Left Ventricular Variables on Exercise Capacity in Patients with Tetralogy of Fallot Hemodynamics.

PubMed

Meierhofer, Christian; Tavakkoli, Timon; Kühn, Andreas; Ulm, Kurt; Hager, Alfred; Müller, Jan; Martinoff, Stefan; Ewert, Peter; Stern, Heiko

2017-12-01

Good quality of life correlates with a good exercise capacity in daily life in patients with tetralogy of Fallot (ToF). Patients after correction of ToF usually develop residual defects such as pulmonary regurgitation or stenosis of variable severity. However, the importance of different hemodynamic parameters and their impact on exercise capacity is unclear. We investigated several hemodynamic parameters measured by cardiovascular magnetic resonance (CMR) and echocardiography and evaluated which parameter has the most pronounced effect on maximal exercise capacity determined by cardiopulmonary exercise testing (CPET). 132 patients with ToF-like hemodynamics were tested during routine follow-up with CMR, echocardiography and CPET. Right and left ventricular volume data, ventricular ejection fraction and pulmonary regurgitation were evaluated by CMR. Echocardiographic pressure gradients in the right ventricular outflow tract and through the tricuspid valve were measured. All data were classified and correlated with the results of CPET evaluations of these patients. The analysis was performed using the Random Forest model. In this way, we calculated the importance of the different hemodynamic variables related to the maximal oxygen uptake in CPET (VO 2 %predicted). Right ventricular pressure showed the most important influence on maximal oxygen uptake, whereas pulmonary regurgitation and right ventricular enddiastolic volume were not important hemodynamic variables to predict maximal oxygen uptake in CPET. Maximal exercise capacity was only very weakly influenced by right ventricular enddiastolic volume and not at all by pulmonary regurgitation in patients with ToF. The variable with the most pronounced influence was the right ventricular pressure.

Variable Selection for Nonparametric Quantile Regression via Smoothing Spline AN OVA

PubMed Central

Lin, Chen-Yen; Bondell, Howard; Zhang, Hao Helen; Zou, Hui

2014-01-01

Quantile regression provides a more thorough view of the effect of covariates on a response. Nonparametric quantile regression has become a viable alternative to avoid restrictive parametric assumption. The problem of variable selection for quantile regression is challenging, since important variables can influence various quantiles in different ways. We tackle the problem via regularization in the context of smoothing spline ANOVA models. The proposed sparse nonparametric quantile regression (SNQR) can identify important variables and provide flexible estimates for quantiles. Our numerical study suggests the promising performance of the new procedure in variable selection and function estimation. Supplementary materials for this article are available online. PMID:24554792

Aging and the Environment: Importance of Variability Issues in Understanding Risk

EPA Science Inventory

Of the many features of aging that could enhance susceptibility to environmental stressors, including toxic chemicals, the role of variability is arguably the least understood. This conclusion is surprising, since increased variability is a widely accepted feature of old age. In...

The behaviour of random forest permutation-based variable importance measures under predictor correlation.

PubMed

Nicodemus, Kristin K; Malley, James D; Strobl, Carolin; Ziegler, Andreas

2010-02-27

Random forests (RF) have been increasingly used in applications such as genome-wide association and microarray studies where predictor correlation is frequently observed. Recent works on permutation-based variable importance measures (VIMs) used in RF have come to apparently contradictory conclusions. We present an extended simulation study to synthesize results. In the case when both predictor correlation was present and predictors were associated with the outcome (HA), the unconditional RF VIM attributed a higher share of importance to correlated predictors, while under the null hypothesis that no predictors are associated with the outcome (H0) the unconditional RF VIM was unbiased. Conditional VIMs showed a decrease in VIM values for correlated predictors versus the unconditional VIMs under HA and was unbiased under H0. Scaled VIMs were clearly biased under HA and H0. Unconditional unscaled VIMs are a computationally tractable choice for large datasets and are unbiased under the null hypothesis. Whether the observed increased VIMs for correlated predictors may be considered a "bias" - because they do not directly reflect the coefficients in the generating model - or if it is a beneficial attribute of these VIMs is dependent on the application. For example, in genetic association studies, where correlation between markers may help to localize the functionally relevant variant, the increased importance of correlated predictors may be an advantage. On the other hand, we show examples where this increased importance may result in spurious signals.

Importance of coastal change variables in determining vulnerability to sea- and lake-level change

USGS Publications Warehouse

Pendleton, E.A.; Thieler, E.R.; Williams, S.J.

2010-01-01

In 2001, the U.S. Geological Survey began conducting scientific assessments of coastal vulnerability to potential future sea- and lake-level changes in 22 National Park Service sea- and lakeshore units. Coastal park units chosen for the assessment included a variety of geological and physical settings along the U.S. Atlantic, Pacific, Gulf of Mexico, Gulf of Alaska, Caribbean, and Great Lakes shorelines. This research is motivated by the need to understand and anticipate coastal changes caused by accelerating sea-level rise, as well as lake-level changes caused by climate change, over the next century. The goal of these assessments is to provide information that can be used to make long-term (decade to century) management decisions. Here we analyze the results of coastal vulnerability assessments for several coastal national park units. Index-based assessments quantify the likelihood that physical changes may occur based on analysis of the following variables: tidal range, ice cover, wave height, coastal slope, historical shoreline change rate, geomorphology, and historical rate of relative sea- or lake-level change. This approach seeks to combine a coastal system's susceptibility to change with its natural ability to adapt to changing environmental conditions, and it provides a measure of the system's potential vulnerability to the effects of sea- or lake-level change. Assessments for 22 park units are combined to evaluate relationships among the variables used to derive the index. Results indicate that Atlantic and Gulf of Mexico parks have the highest vulnerability rankings relative to other park regions. A principal component analysis reveals that 99% of the index variability can be explained by four variables: geomorphology, regional coastal slope, water-level change rate, and mean significant wave height. Tidal range, ice cover, and historical shoreline change are not as important when the index is evaluated at large spatial scales (thousands of kilometers

A tree-based statistical classification algorithm (CHAID) for identifying variables responsible for the occurrence of faecal indicator bacteria during waterworks operations

NASA Astrophysics Data System (ADS)

Bichler, Andrea; Neumaier, Arnold; Hofmann, Thilo

2014-11-01

Microbial contamination of groundwater used for drinking water can affect public health and is of major concern to local water authorities and water suppliers. Potential hazards need to be identified in order to protect raw water resources. We propose a non-parametric data mining technique for exploring the presence of total coliforms (TC) in a groundwater abstraction well and its relationship to readily available, continuous time series of hydrometric monitoring parameters (seven year records of precipitation, river water levels, and groundwater heads). The original monitoring parameters were used to create an extensive generic dataset of explanatory variables by considering different accumulation or averaging periods, as well as temporal offsets of the explanatory variables. A classification tree based on the Chi-Squared Automatic Interaction Detection (CHAID) recursive partitioning algorithm revealed statistically significant relationships between precipitation and the presence of TC in both a production well and a nearby monitoring well. Different secondary explanatory variables were identified for the two wells. Elevated water levels and short-term water table fluctuations in the nearby river were found to be associated with TC in the observation well. The presence of TC in the production well was found to relate to elevated groundwater heads and fluctuations in groundwater levels. The generic variables created proved useful for increasing significance levels. The tree-based model was used to predict the occurrence of TC on the basis of hydrometric variables.

Identifying Elements of ICU Care That Families Report as Important But Unsatisfactory

PubMed Central

Osborn, Tristan R.; Curtis, J. Randall; Nielsen, Elizabeth L.; Back, Anthony L.; Shannon, Sarah E.

2012-01-01

Background: One in five deaths in the United States occurs in the ICU, and many of these deaths are experienced as less than optimal by families of dying people. The current study investigated the relationship between family satisfaction with ICU care and overall ratings of the quality of dying as a means of identifying targets for improving end-of-life experiences for patients and families. Methods: This multisite cross-sectional study surveyed families of patients who died in the ICU in one of 15 hospitals in western Washington State. Measures included the Family Satisfaction in the ICU (FS-ICU) and the Single-Item Quality of Dying (QOD-1) questionnaires. Associations between FS-ICU items and the QOD-1 were examined using multivariate linear regression controlling for patient and family demographics and hospital site. Results: Questionnaires were returned for 1,290 of 2,850 decedents (45%). Higher QOD-1 scores were significantly associated (all P < .05) with (1) perceived nursing skill and competence (β = 0.15), (2) support for family as decision-makers (β = 0.10), (3) family control over the patient’s care (β = 0.18), and (4) ICU atmosphere (β = 0.12). FS-ICU items that received low ratings and correlated with higher QOD-1 scores (ie, important items with room for improvement) were (1) support of family as decision-maker, (2) family control over patient’s care, and (3) ICU atmosphere. Conclusions: Increased support for families as decision-makers and for their desired level of control over patient care along with improvements in the ICU atmosphere were identified as aspects of the ICU experience that may be important targets for quality improvement. Trial registry: ClinicalTrials.gov; No.: NCT00685893; URL: www.clinicaltrials.gov. PMID:22661455

Identifying uncontrolled asthma in young children: clinical scores or objective variables?

PubMed

Leung, T F; Ko, F W S; Sy, H Y; Wong, E; Li, C Y; Yung, E; Hui, D S C; Wong, G W K; Lai, C K W

2009-03-01

Several international asthma guidelines emphasize the importance of assessing asthma control. However, there is limited data on the usefulness of available assessment tools in indicating disease control in young asthmatics. This study investigated the ability of Chinese version of Childhood Asthma Control Test (C-ACT) and other disease-related factors in identifying uncontrolled asthma (UA) in young children. During the same clinic visit, asthma patients 4 to 11 years of age completed C-ACT and underwent exhaled nitric oxide and spirometric measurements. Blinded to these results, the same investigator assigned Disease Severity Score (DSS) and rated asthma control according to Global Initiative for Asthma. The mean (SD) age of 113 recruited patients was 9.1 (2.0) years, and 35% of them had UA. C-ACT, DSS and forced expiratory volume in 1 second (FEV(1)) differed among patients with different control status (p < 0.001 for C-ACT and DSS; p = 0.014 for FEV(1)). Logistic regression confirmed that UA was associated with DSS (p < 0.001), PEF (p = 0.002), C-ACT (p = 0.011), and FEV(1) (p = 0.012). By ROC analysis, C-ACT and DSS were the best predictors for UA (p < 0.001), followed by PEF (p = 0.006) and FEV(1) (p = 0.007). When analyzed by the Classification and Regression Tree (CART) approach, the sequential use of DSS and C-ACT had 77% sensitivity and 84% specificity in identifying UA. C-ACT is better than objective parameters in identifying young Chinese children with UA.

Identifying pneumonia outbreaks of public health importance: can emergency department data assist in earlier identification?

PubMed

Hope, Kirsty; Durrheim, David N; Muscatello, David; Merritt, Tony; Zheng, Wei; Massey, Peter; Cashman, Patrick; Eastwood, Keith

2008-08-01

To retrospectively review the performance of a near real-time Emergency Department (ED) Syndromic Surveillance System operating in New South Wales for identifying pneumonia outbreaks of public health importance. Retrospective data was obtained from the NSW Emergency Department data collection for a rural hospital that has experienced a cluster of pneumonia diagnoses among teenage males in August 2006. ED standard reports were examined for signals in the overall count for each respiratory syndrome, and for elevated counts in individual subgroups including; age, sex and admission to hospital status. Using the current thresholds, the ED syndromic surveillance system would have trigged a signal for pneumonia syndrome in children aged 5-16 years four days earlier than the notification by a paediatrician and this signal was maintained for 14 days. If the ED syndromic surveillance system had been operating it could have identified the outbreak earlier than the paediatrician's notification. This may have permitted an earlier public health response. By understanding the behaviour of syndromes during outbreaks of public health importance, response protocols could be developed to facilitate earlier implementation of control measures.

On the importance of identifying, characterizing, and predicting fundamental phenomena towards microbial electrochemistry applications.

PubMed

Torres, César Iván

2014-06-01

The development of microbial electrochemistry research toward technological applications has increased significantly in the past years, leading to many process configurations. This short review focuses on the need to identify and characterize the fundamental phenomena that control the performance of microbial electrochemical cells (MXCs). Specifically, it discusses the importance of recent efforts to discover and characterize novel microorganisms for MXC applications, as well as recent developments to understand transport limitations in MXCs. As we increase our understanding of how MXCs operate, it is imperative to continue modeling efforts in order to effectively predict their performance, design efficient MXC technologies, and implement them commercially. Thus, the success of MXC technologies largely depends on the path of identifying, understanding, and predicting fundamental phenomena that determine MXC performance. Copyright © 2013 Elsevier Ltd. All rights reserved.

Origins of extrinsic variability in eukaryotic gene expression

NASA Astrophysics Data System (ADS)

Volfson, Dmitri; Marciniak, Jennifer; Blake, William J.; Ostroff, Natalie; Tsimring, Lev S.; Hasty, Jeff

2006-02-01

Variable gene expression within a clonal population of cells has been implicated in a number of important processes including mutation and evolution, determination of cell fates and the development of genetic disease. Recent studies have demonstrated that a significant component of expression variability arises from extrinsic factors thought to influence multiple genes simultaneously, yet the biological origins of this extrinsic variability have received little attention. Here we combine computational modelling with fluorescence data generated from multiple promoter-gene inserts in Saccharomyces cerevisiae to identify two major sources of extrinsic variability. One unavoidable source arising from the coupling of gene expression with population dynamics leads to a ubiquitous lower limit for expression variability. A second source, which is modelled as originating from a common upstream transcription factor, exemplifies how regulatory networks can convert noise in upstream regulator expression into extrinsic noise at the output of a target gene. Our results highlight the importance of the interplay of gene regulatory networks with population heterogeneity for understanding the origins of cellular diversity.

Origins of extrinsic variability in eukaryotic gene expression

NASA Astrophysics Data System (ADS)

Volfson, Dmitri; Marciniak, Jennifer; Blake, William J.; Ostroff, Natalie; Tsimring, Lev S.; Hasty, Jeff

2006-03-01

Variable gene expression within a clonal population of cells has been implicated in a number of important processes including mutation and evolution, determination of cell fates and the development of genetic disease. Recent studies have demonstrated that a significant component of expression variability arises from extrinsic factors thought to influence multiple genes in concert, yet the biological origins of this extrinsic variability have received little attention. Here we combine computational modeling with fluorescence data generated from multiple promoter-gene inserts in Saccharomyces cerevisiae to identify two major sources of extrinsic variability. One unavoidable source arising from the coupling of gene expression with population dynamics leads to a ubiquitous noise floor in expression variability. A second source which is modeled as originating from a common upstream transcription factor exemplifies how regulatory networks can convert noise in upstream regulator expression into extrinsic noise at the output of a target gene. Our results highlight the importance of the interplay of gene regulatory networks with population heterogeneity for understanding the origins of cellular diversity.

Cancer family caregiver depression: are religion-related variables important?

PubMed

Williams, Anna-Leila; Dixon, Jane; Feinn, Richard; McCorkle, Ruth

2015-07-01

Prevalence estimates for clinical depression among cancer family caregivers (CFC) range upwards to 39%. Research inconsistently reports risk for CFC depressive symptoms when evaluating age, gender, ethnicity, or length of time as caregiver. The discrepant findings, coupled with emerging literature indicating religiosity may mitigate depression in some populations, led us to investigate religion-related variables to help predict CFC depressive symptoms. We conducted a cross-sectional study of 150 CFC. Explanatory variables included age, gender, spousal status, length of time as caregiver, attendance at religious services, and prayer. The outcome variable was the Center for Epidemiological Studies Depression Scale score. Compared with large national and state datasets, our sample has lower representation of individuals with no religious affiliation (10.7% vs. 16.1% national, p = 0.07 and 23.0% state, p = 0.001), higher rate of attendance at religious services (81.3% vs. 67.2% national, p < 0.001 and 30.0% state, p < 0.001), and higher rate of prayer (65.3% vs. 42.9% national, p < 0.001; no state data available). In unadjusted and adjusted models, prayer is not significantly associated with caregiver depressive symptoms or clinically significant depressive symptomology. Attendance at religious services is associated with depressive symptoms (p = 0.004) with an inversely linear trend (p = 0.002). The significant inverse association between attendance at religious services and depressive symptoms, despite no association between prayer and depressive symptoms, indicates that social or other factors may accompany attendance at religious services and contribute to the association. Clinicians can consider supporting a CFC's attendance at religious services as a potential preventive measure for depressive symptoms. Copyright © 2014 John Wiley & Sons, Ltd.

Global Sensitivity Analysis for Identifying Important Parameters of Nitrogen Nitrification and Denitrification under Model and Scenario Uncertainties

NASA Astrophysics Data System (ADS)

Ye, M.; Chen, Z.; Shi, L.; Zhu, Y.; Yang, J.

2017-12-01

Nitrogen reactive transport modeling is subject to uncertainty in model parameters, structures, and scenarios. While global sensitivity analysis is a vital tool for identifying the parameters important to nitrogen reactive transport, conventional global sensitivity analysis only considers parametric uncertainty. This may result in inaccurate selection of important parameters, because parameter importance may vary under different models and modeling scenarios. By using a recently developed variance-based global sensitivity analysis method, this paper identifies important parameters with simultaneous consideration of parametric uncertainty, model uncertainty, and scenario uncertainty. In a numerical example of nitrogen reactive transport modeling, a combination of three scenarios of soil temperature and two scenarios of soil moisture leads to a total of six scenarios. Four alternative models are used to evaluate reduction functions used for calculating actual rates of nitrification and denitrification. The model uncertainty is tangled with scenario uncertainty, as the reduction functions depend on soil temperature and moisture content. The results of sensitivity analysis show that parameter importance varies substantially between different models and modeling scenarios, which may lead to inaccurate selection of important parameters if model and scenario uncertainties are not considered. This problem is avoided by using the new method of sensitivity analysis in the context of model averaging and scenario averaging. The new method of sensitivity analysis can be applied to other problems of contaminant transport modeling when model uncertainty and/or scenario uncertainty are present.

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

Monitoring of airborne biological particles in outdoor atmosphere. Part 1: Importance, variability and ratios.

PubMed

Núñez, Andrés; Amo de Paz, Guillermo; Rastrojo, Alberto; García, Ana M; Alcamí, Antonio; Gutiérrez-Bustillo, A Montserrat; Moreno, Diego A

2016-03-01

The first part of this review ("Monitoring of airborne biological particles in outdoor atmosphere. Part 1: Importance, variability and ratios") describes the current knowledge on the major biological particles present in the air regarding their global distribution, concentrations, ratios and influence of meteorological factors in an attempt to provide a framework for monitoring their biodiversity and variability in such a singular environment as the atmosphere. Viruses, bacteria, fungi, pollen and fragments thereof are the most abundant microscopic biological particles in the air outdoors. Some of them can cause allergy and severe diseases in humans, other animals and plants, with the subsequent economic impact. Despite the harsh conditions, they can be found from land and sea surfaces to beyond the troposphere and have been proposed to play a role also in weather conditions and climate change by acting as nucleation particles and inducing water vapour condensation. In regards to their global distribution, marine environments act mostly as a source for bacteria while continents additionally provide fungal and pollen elements. Within terrestrial environments, their abundances and diversity seem to be influenced by the land-use type (rural, urban, coastal) and their particularities. Temporal variability has been observed for all these organisms, mostly triggered by global changes in temperature, relative humidity, et cetera. Local fluctuations in meteorological factors may also result in pronounced changes in the airbiota. Although biological particles can be transported several hundreds of meters from the original source, and even intercontinentally, the time and final distance travelled are strongly influenced by factors such as wind speed and direction. [Int Microbiol 2016; 19(1):1-1 3]. Copyright© by the Spanish Society for Microbiology and Institute for Catalan Studies.

On the importance of Sri Lanka for sea-level variability along the west coast of India

NASA Astrophysics Data System (ADS)

Suresh, I.; Vialard, J.; Izumo, T.; Lengaigne, M.; Han, W.; McCreary, J. P., Jr.; Pillathu Moolayil, M.

2015-12-01

Earlier studies have illustrated the strong influence of remote forcing from the equator and the Bay of Bengal on the sea-level variability off the west coast of India, especially at the seasonal timescale. More recently, Suresh et al. [2013] demonstrated with a simple, linear, continuously-stratified (LCS) model that the equatorial zonal winds contribute to more than 60% of intraseasonal sea-level variability along the Indian west coast. In the present study, we quantify the contributions from various processes to the sea-level variability along the west coast of India at different timescales with the help of a LCS model through both idealized and realistic sensitivity experiments. We demonstrate that remote forcing dominates the sea-level variability along the west coast of India at intraseasonal to interannual timescales. Sri Lanka and the southern tip of India play an important role on Indian west coast sea-level variability at all timescales for two reasons: First, the geometry of the coast favors a strong alongshore wind-stress forcing of coastal Kelvin waves across timescales there. Second, Sri Lanka interacts with low-order meridional mode equatorial Rossby waves forced by equatorial winds or southern Bay of Bengal wind- stress curl. This interaction of coastal waveguide with equatorial waveguide creates a new pathway for the equatorial signals to arrive at the west coast of India, alternative to the "classical" coastal waveguide around the rim of the Bay of Bengal. Reference: Suresh, I., J. Vialard, M. Lengaigne, W. Han, J. McCreary, F. Durand, and P. M. Muraleedharan (2013), Origins of wind-driven intraseasonal sea level variations in the North Indian Ocean coastal waveguide, Geophys. Res. Lett., 40, 5740-5744, doi:10.1002/2013GL058312.

Identifying novel genetic determinants of hemostatic balance.

PubMed

Ginsburg, D

2005-08-01

Incomplete penetrance and variable expressivity confound the diagnosis and therapy of most inherited thrombotic and hemorrhagic disorders. For many of these diseases, some or most of this variability is determined by genetic modifiers distinct from the primary disease gene itself. Clues toward identifying such modifier genes may come from studying rare Mendelian disorders of hemostasis. Examples include identification of the cause of combined factor V and VIII deficiency as mutations in the ER Golgi intermediate compartment proteins LMAN1 and MCFD2. These proteins form a cargo receptor that facilitates the transport of factors V and VIII, and presumably other proteins, from the ER to the Golgi. A similar positional cloning approach identified ADAMTS-13 as the gene responsible for familial TTP. Along with the work of many other groups, these findings identified VWF proteolysis by ADAMTS-13 as a key regulatory pathway for hemostasis. Recent advances in mouse genetics also provide powerful tools for the identification of novel genes contributing to hemostatic balance. Genetic studies of inbred mouse lines with unusually high and unusually low plasma VWF levels identified polymorphic variation in the expression of a glycosyltransferase gene, Galgt2, as an important determinant of plasma VWF levels in the mouse. Ongoing studies in mice genetically engineered to carry the factor V Leiden mutation may similarly identify novel genes contributing to thrombosis risk in humans.

Identifying 1st instar larvae for three forensically important blowfly species using "fingerprint" cuticular hydrocarbon analysis.

PubMed

Moore, Hannah E; Adam, Craig D; Drijfhout, Falko P

2014-07-01

Calliphoridae are known to be the most forensically important insects when it comes to establishing the minimum post mortem interval (PMImin) in criminal investigations. The first step in calculating the PMImin is to identify the larvae present to species level. Accurate identification which is conventionally carried out by morphological analysis is crucial because different insects have different life stage timings. Rapid identification in the immature larvae stages would drastically cut time in criminal investigations as it would eliminate the need to rear larvae to adult flies to determine the species. Cuticular hydrocarbon analysis on 1st instar larvae has been applied to three forensically important blowflies; Lucilia sericata, Calliphora vicina and Calliphora vomitoria, using gas chromatography-mass spectrometry (GC-MS) and principal component analysis (PCA). The results show that each species holds a distinct "fingerprint" hydrocarbon profile, allowing for accurate identification to be established in 1-day old larvae, when it can be challenging to apply morphological criteria. Consequently, this GC-MS based technique could accelerate and strengthen the identification process, not only for forensically important species, but also for other entomological samples which are hard to identify using morphological features. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A formal method for identifying distinct states of variability in time-varying sources: SGR A* as an example

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

Meyer, L.; Witzel, G.; Ghez, A. M.

2014-08-10

Continuously time variable sources are often characterized by their power spectral density and flux distribution. These quantities can undergo dramatic changes over time if the underlying physical processes change. However, some changes can be subtle and not distinguishable using standard statistical approaches. Here, we report a methodology that aims to identify distinct but similar states of time variability. We apply this method to the Galactic supermassive black hole, where 2.2 μm flux is observed from a source associated with Sgr A* and where two distinct states have recently been suggested. Our approach is taken from mathematical finance and works withmore » conditional flux density distributions that depend on the previous flux value. The discrete, unobserved (hidden) state variable is modeled as a stochastic process and the transition probabilities are inferred from the flux density time series. Using the most comprehensive data set to date, in which all Keck and a majority of the publicly available Very Large Telescope data have been merged, we show that Sgr A* is sufficiently described by a single intrinsic state. However, the observed flux densities exhibit two states: noise dominated and source dominated. Our methodology reported here will prove extremely useful to assess the effects of the putative gas cloud G2 that is on its way toward the black hole and might create a new state of variability.« less

Report: EPA Can Better Reduce Risks From Illegal Pesticides by Effectively Identifying Imports for Inspection and Sampling

EPA Pesticide Factsheets

Report #17-P-0412, September 28, 2017. Low rates of inspections and sampling can create a risk that the EPA may not be identifying and deterring the import of pesticides harmful to people or the environment.

Field variability and vulnerability index to identify precision agriculture opportunity

USDA-ARS?s Scientific Manuscript database

Innovations in precision agriculture (PA) have created opportunities to achieve a greater understanding of within-field variability. However, PA adoption has been hindered due to uncertainty about field-specific performance and return on investment. Uncertainty could be better addressed by analyzing...

Evolution of dispersal in spatially and temporally variable environments: The importance of life cycles.

PubMed

Massol, François; Débarre, Florence

2015-07-01

Spatiotemporal variability of the environment is bound to affect the evolution of dispersal, and yet model predictions strongly differ on this particular effect. Recent studies on the evolution of local adaptation have shown that the life cycle chosen to model the selective effects of spatiotemporal variability of the environment is a critical factor determining evolutionary outcomes. Here, we investigate the effect of the order of events in the life cycle on the evolution of unconditional dispersal in a spatially heterogeneous, temporally varying landscape. Our results show that the occurrence of intermediate singular strategies and disruptive selection are conditioned by the temporal autocorrelation of the environment and by the life cycle. Life cycles with dispersal of adults versus dispersal of juveniles, local versus global density regulation, give radically different evolutionary outcomes that include selection for total philopatry, evolutionary bistability, selection for intermediate stable states, and evolutionary branching points. Our results highlight the importance of accounting for life-cycle specifics when predicting the effects of the environment on evolutionarily selected trait values, such as dispersal, as well as the need to check the robustness of model conclusions against modifications of the life cycle. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Climate variables explain neutral and adaptive variation within salmonid metapopulations: The importance of replication in landscape genetics

USGS Publications Warehouse

Hand, Brian K.; Muhlfeld, Clint C.; Wade, Alisa A.; Kovach, Ryan; Whited, Diane C.; Narum, Shawn R.; Matala, Andrew P.; Ackerman, Michael W.; Garner, B. A.; Kimball, John S; Stanford, Jack A.; Luikart, Gordon

2016-01-01

Understanding how environmental variation influences population genetic structure is important for conservation management because it can reveal how human stressors influence population connectivity, genetic diversity and persistence. We used riverscape genetics modelling to assess whether climatic and habitat variables were related to neutral and adaptive patterns of genetic differentiation (population-specific and pairwise FST) within five metapopulations (79 populations, 4583 individuals) of steelhead trout (Oncorhynchus mykiss) in the Columbia River Basin, USA. Using 151 putatively neutral and 29 candidate adaptive SNP loci, we found that climate-related variables (winter precipitation, summer maximum temperature, winter highest 5% flow events and summer mean flow) best explained neutral and adaptive patterns of genetic differentiation within metapopulations, suggesting that climatic variation likely influences both demography (neutral variation) and local adaptation (adaptive variation). However, we did not observe consistent relationships between climate variables and FST across all metapopulations, underscoring the need for replication when extrapolating results from one scale to another (e.g. basin-wide to the metapopulation scale). Sensitivity analysis (leave-one-population-out) revealed consistent relationships between climate variables and FST within three metapopulations; however, these patterns were not consistent in two metapopulations likely due to small sample sizes (N = 10). These results provide correlative evidence that climatic variation has shaped the genetic structure of steelhead populations and highlight the need for replication and sensitivity analyses in land and riverscape genetics.

Intratumoral heterogeneity identified at the epigenetic, genetic and transcriptional level in glioblastoma.

PubMed

Parker, Nicole R; Hudson, Amanda L; Khong, Peter; Parkinson, Jonathon F; Dwight, Trisha; Ikin, Rowan J; Zhu, Ying; Cheng, Zhangkai Jason; Vafaee, Fatemeh; Chen, Jason; Wheeler, Helen R; Howell, Viive M

2016-03-04

Heterogeneity is a hallmark of glioblastoma with intratumoral heterogeneity contributing to variability in responses and resistance to standard treatments. Promoter methylation status of the DNA repair enzyme O(6)-methylguanine DNA methyltransferase (MGMT) is the most important clinical biomarker in glioblastoma, predicting for therapeutic response. However, it does not always correlate with response. This may be due to intratumoral heterogeneity, with a single biopsy unlikely to represent the entire lesion. Aberrations in other DNA repair mechanisms may also contribute. This study investigated intratumoral heterogeneity in multiple glioblastoma tumors with a particular focus on the DNA repair pathways. Transcriptional intratumoral heterogeneity was identified in 40% of cases with variability in MGMT methylation status found in 14% of cases. As well as identifying intratumoral heterogeneity at the transcriptional and epigenetic levels, targeted next generation sequencing identified between 1 and 37 unique sequence variants per specimen. In-silico tools were then able to identify deleterious variants in both the base excision repair and the mismatch repair pathways that may contribute to therapeutic response. As these pathways have roles in temozolomide response, these findings may confound patient management and highlight the importance of assessing multiple tumor biopsies.

Cluster Analysis of Clinical Data Identifies Fibromyalgia Subgroups

PubMed Central

Docampo, Elisa; Collado, Antonio; Escaramís, Geòrgia; Carbonell, Jordi; Rivera, Javier; Vidal, Javier; Alegre, José

2013-01-01

Introduction Fibromyalgia (FM) is mainly characterized by widespread pain and multiple accompanying symptoms, which hinder FM assessment and management. In order to reduce FM heterogeneity we classified clinical data into simplified dimensions that were used to define FM subgroups. Material and Methods 48 variables were evaluated in 1,446 Spanish FM cases fulfilling 1990 ACR FM criteria. A partitioning analysis was performed to find groups of variables similar to each other. Similarities between variables were identified and the variables were grouped into dimensions. This was performed in a subset of 559 patients, and cross-validated in the remaining 887 patients. For each sample and dimension, a composite index was obtained based on the weights of the variables included in the dimension. Finally, a clustering procedure was applied to the indexes, resulting in FM subgroups. Results Variables clustered into three independent dimensions: “symptomatology”, “comorbidities” and “clinical scales”. Only the two first dimensions were considered for the construction of FM subgroups. Resulting scores classified FM samples into three subgroups: low symptomatology and comorbidities (Cluster 1), high symptomatology and comorbidities (Cluster 2), and high symptomatology but low comorbidities (Cluster 3), showing differences in measures of disease severity. Conclusions We have identified three subgroups of FM samples in a large cohort of FM by clustering clinical data. Our analysis stresses the importance of family and personal history of FM comorbidities. Also, the resulting patient clusters could indicate different forms of the disease, relevant to future research, and might have an impact on clinical assessment. PMID:24098674

Using the Developmental Gene Bicoid to Identify Species of Forensically Important Blowflies (Diptera: Calliphoridae)

PubMed Central

Park, Seong Hwan; Park, Chung Hyun; Zhang, Yong; Piao, Huguo; Chung, Ukhee; Kim, Seong Yoon; Ko, Kwang Soo; Yi, Cheong-Ho; Jo, Tae-Ho; Hwang, Juck-Joon

2013-01-01

Identifying species of insects used to estimate postmortem interval (PMI) is a major subject in forensic entomology. Because forensic insect specimens are morphologically uniform and are obtained at various developmental stages, DNA markers are greatly needed. To develop new autosomal DNA markers to identify species, partial genomic sequences of the bicoid (bcd) genes, containing the homeobox and its flanking sequences, from 12 blowfly species (Aldrichina grahami, Calliphora vicina, Calliphora lata, Triceratopyga calliphoroides, Chrysomya megacephala, Chrysomya pinguis, Phormia regina, Lucilia ampullacea, Lucilia caesar, Lucilia illustris, Hemipyrellia ligurriens and Lucilia sericata; Calliphoridae: Diptera) were determined and analyzed. This study first sequenced the ten blowfly species other than C. vicina and L. sericata. Based on the bcd sequences of these 12 blowfly species, a phylogenetic tree was constructed that discriminates the subfamilies of Calliphoridae (Luciliinae, Chrysomyinae, and Calliphorinae) and most blowfly species. Even partial genomic sequences of about 500 bp can distinguish most blowfly species. The short intron 2 and coding sequences downstream of the bcd homeobox in exon 3 could be utilized to develop DNA markers for forensic applications. These gene sequences are important in the evolution of insect developmental biology and are potentially useful for identifying insect species in forensic science. PMID:23586044

Standard errors and confidence intervals for variable importance in random forest regression, classification, and survival.

PubMed

Ishwaran, Hemant; Lu, Min

2018-06-04

Random forests are a popular nonparametric tree ensemble procedure with broad applications to data analysis. While its widespread popularity stems from its prediction performance, an equally important feature is that it provides a fully nonparametric measure of variable importance (VIMP). A current limitation of VIMP, however, is that no systematic method exists for estimating its variance. As a solution, we propose a subsampling approach that can be used to estimate the variance of VIMP and for constructing confidence intervals. The method is general enough that it can be applied to many useful settings, including regression, classification, and survival problems. Using extensive simulations, we demonstrate the effectiveness of the subsampling estimator and in particular find that the delete-d jackknife variance estimator, a close cousin, is especially effective under low subsampling rates due to its bias correction properties. These 2 estimators are highly competitive when compared with the .164 bootstrap estimator, a modified bootstrap procedure designed to deal with ties in out-of-sample data. Most importantly, subsampling is computationally fast, thus making it especially attractive for big data settings. Copyright © 2018 John Wiley & Sons, Ltd.

American Bird conservancy's approach to the U.S. Important Bird Area Program - identifying the top 500 global sites

Treesearch

Robert M. Chipley

2005-01-01

The idea for the Important Bird Area Program originated in a series of studies in the early 1980s conducted by BirdLife International. Recognizing that these studies could become a powerful tool for conservation, BirdLife International began an effort to identify and gather data regarding the most important areas for birds in Europe and to make this information...

Metabolic Syndrome and Importance of Associated Variables in Children and Adolescents in Guabiruba - SC, Brazil

PubMed Central

Rosini, Nilton; Moura, Solange A. Z. Oppermann; Rosini, Rodrigo Diegoli; Machado, Marcos José; da Silva, Edson Luiz

2015-01-01

Background The risk factors that characterize metabolic syndrome (MetS) may be present in childhood and adolescence, increasing the risk of cardiovascular disease in adulthood. Objective Evaluate the prevalence of MetS and the importance of its associated variables, including insulin resistance (IR), in children and adolescents in the city of Guabiruba-SC, Brazil. Methods Cross-sectional study with 1011 students (6-14 years, 52.4% girls, 58.5% children). Blood samples were collected for measurement of biochemical parameters by routine laboratory methods. IR was estimated by the HOMA-IR index, and weight, height, waist circumference and blood pressure were determined. Multivariate logistic regression models were used to examine the associations between risk variables and MetS. Results The prevalence of MetS, IR, overweight and obesity in the cohort were 14%, 8.5%, 21% and 13%, respectively. Among students with MetS, 27% had IR, 33% were overweight, 45.5% were obese and 22% were eutrophic. IR was more common in overweight (48%) and obese (41%) students when compared with eutrophic individuals (11%; p = 0.034). The variables with greatest influence on the development of MetS were obesity (OR = 32.7), overweight (OR = 6.1), IR (OR = 4.4; p ≤ 0.0001 for all) and age (OR = 1.15; p = 0.014). Conclusion There was a high prevalence of MetS in children and adolescents evaluated in this study. Students who were obese, overweight or insulin resistant had higher chances of developing the syndrome. PMID:25993484

Mapping Variables.

ERIC Educational Resources Information Center

Stone, Mark H.; Wright, Benjamin D.; Stenner, A. Jackson

1999-01-01

Describes mapping variables, the principal technique for planning and constructing a test or rating instrument. A variable map is also useful for interpreting results. Provides several maps to show the importance and value of mapping a variable by person and item data. (Author/SLD)

The importance of environmental variability and management control error to optimal harvest policies

USGS Publications Warehouse

Hunter, C.M.; Runge, M.C.

2004-01-01

State-dependent strategies (SDSs) are the most general form of harvest policy because they allow the harvest rate to depend, without constraint, on the state of the system. State-dependent strategies that provide an optimal harvest rate for any system state can be calculated, and stochasticity can be appropriately accommodated in this optimization. Stochasticity poses 2 challenges to harvest policies: (1) the population will never be at the equilibrium state; and (2) stochasticity induces uncertainty about future states. We investigated the effects of 2 types of stochasticity, environmental variability and management control error, on SDS harvest policies for a white-tailed deer (Odocoileus virginianus) model, and contrasted these with a harvest policy based on maximum sustainable yield (MSY). Increasing stochasticity resulted in more conservative SDSs; that is, higher population densities were required to support the same harvest rate, but these effects were generally small. As stochastic effects increased, SDSs performed much better than MSY. Both deterministic and stochastic SDSs maintained maximum mean annual harvest yield (AHY) and optimal equilibrium population size (Neq) in a stochastic environment, whereas an MSY policy could not. We suggest 3 rules of thumb for harvest management of long-lived vertebrates in stochastic systems: (1) an SDS is advantageous over an MSY policy, (2) using an SDS rather than an MSY is more important than whether a deterministic or stochastic SDS is used, and (3) for SDSs, rankings of the variability in management outcomes (e.g., harvest yield) resulting from parameter stochasticity can be predicted by rankings of the deterministic elasticities.

Characterizing Temperature Variability and Associated Large Scale Meteorological Patterns Across South America

NASA Astrophysics Data System (ADS)

Detzer, J.; Loikith, P. C.; Mechoso, C. R.; Barkhordarian, A.; Lee, H.

2017-12-01

South America's climate varies considerably owing to its large geographic range and diverse topographical features. Spanning the tropics to the mid-latitudes and from high peaks to tropical rainforest, the continent experiences an array of climate and weather patterns. Due to this considerable spatial extent, assessing temperature variability at the continent scale is particularly challenging. It is well documented in the literature that temperatures have been increasing across portions of South America in recent decades, and while there have been many studies that have focused on precipitation variability and change, temperature has received less scientific attention. Therefore, a more thorough understanding of the drivers of temperature variability is critical for interpreting future change. First, k-means cluster analysis is used to identify four primary modes of temperature variability across the continent, stratified by season. Next, composites of large scale meteorological patterns (LSMPs) are calculated for months assigned to each cluster. Initial results suggest that LSMPs, defined using meteorological variables such as sea level pressure (SLP), geopotential height, and wind, are able to identify synoptic scale mechanisms important for driving temperature variability at the monthly scale. Some LSMPs indicate a relationship with known recurrent modes of climate variability. For example, composites of geopotential height suggest that the Southern Annular Mode is an important, but not necessarily dominant, component of temperature variability over southern South America. This work will be extended to assess the drivers of temperature extremes across South America.

Identifying suitable sites for Florida panther reintroduction

USGS Publications Warehouse

Thatcher, Cindy A.; van Manen, Frank T.; Clark, Joseph D.

2006-01-01

A major objective of the 1995 Florida Panther (Puma concolor cory) Recovery Plan is the establishment of 2 additional panther populations within the historic range. Our goal was to identify prospective sites for Florida panther reintroduction within the historic range based on quantitative landscape assessments. First, we delineated 86 panther home ranges using telemetry data collected from 1981 to 2001 in south Florida to develop a Mahalanobis distance (D2) habitat model, using 4 anthropogenic variables and 3 landscape variables mapped at a 500-m resolution. From that analysis, we identified 9 potential reintroduction sites of sufficient size to support a panther population. We then developed a similar D2 model at a higher spatial resolution to quantify the area of favorable panther habitat at each site. To address potential for the population to expand, we calculated the amount of favorable habitat adjacent to each prospective reintroduction site within a range of dispersal distances of female panthers. We then added those totals to the contiguous patches to estimate the total amount of effective panther habitat at each site. Finally, we developed an expert-assisted model to rank and incorporate potentially important habitat variables that were not appropriate for our empirical analysis (e.g., area of public lands, livestock density). Anthropogenic factors heavily influenced both the landscape and the expert-assisted models. Of the 9 areas we identified, the Okefenokee National Wildlife Refuge, Ozark National Forest, and Felsenthal National Wildlife Refuge regions had the highest combination of effective habitat area and expert opinion scores. Sensitivity analyses indicated that variability among key model parameters did not affect the high ranking of those sites. Those sites should be considered as starting points for the field evaluation of potential reintroduction sites.

Utilizing the AAVSO's Variable Star Index (VSX) in Undergraduate Research Projects (Poster abstract)

NASA Astrophysics Data System (ADS)

Larsen, K.

2016-12-01

(Abstract only) Among the many important services that the American Association of Variable Star Observers (AAVSO) provides to the astronomical community is the Variable Star Index (VSX; https://www.aavso.org/vsx/). This online catalog of variable stars is the repository of data on over 334,000 variable stars, including information on spectral type, range of magnitude, period, and type of variable, among other properties. A number of these stars were identified as being variable through automated telescope surveys, such as ASAS (All Sky Automated Survey). The computer code of this survey classified newly discovered variables as best it could, but a significant number of false classifications have been noted. The reclassification of ASAS variables in the VSX data, as well as a closer look at variables identified as miscellaneous type in VSX, are two of many projects that can be undertaken by interested undergraduates. In doing so, students learn about the physical properties of various types of variable stars as well as statistical analysis and computer software, especially the vstar variable star data visualization and analysis tool that is available to the astronomical community free of charge on the AAVSO website (https://www.aavso.org/vstar-overview). Three such projects are described in this presentation, to identify BY Draconis variables misidentified as Cepheids or "miscellaneous", and SRD semiregular variables and ELL (rotating ellipsoidal) variables misidentified as "miscellaneous", in ASAS data and VSX.

IUE observations of variability in winds from hot stars

NASA Technical Reports Server (NTRS)

Grady, C. A.; Snow, T. P., Jr.

1981-01-01

Observations of variability in stellar winds or envelopes provide an important probe of their dynamics. For this purpose a number of O, B, Be, and Wolf-Rayet stars were repeatedly observed with the IUE satellite in high resolution mode. In the course of analysis, instrumental and data handling effects were found to introduce spurious variability in many of the spectra. software was developed to partially compensate for these effects, but limitations remain on the type of variability that can be identified from IUE spectra. With these contraints, preliminary results of multiple observations of two OB stars, one Wolf-Rayet star, and a Be star are discussed.

Survival in macaroni penguins and the relative importance of different drivers: individual traits, predation pressure and environmental variability

PubMed Central

Horswill, Catharine; Matthiopoulos, Jason; Green, Jonathan A; Meredith, Michael P; Forcada, Jaume; Peat, Helen; Preston, Mark; Trathan, Phil N; Ratcliffe, Norman

2014-01-01

Understanding the demographic response of free-living animal populations to different drivers is the first step towards reliable prediction of population trends. Penguins have exhibited dramatic declines in population size, and many studies have linked this to bottom-up processes altering the abundance of prey species. The effects of individual traits have been considered to a lesser extent, and top-down regulation through predation has been largely overlooked due to the difficulties in empirically measuring this at sea where it usually occurs. For 10 years (2003–2012), macaroni penguins (Eudyptes chrysolophus) were marked with subcutaneous electronic transponder tags and re-encountered using an automated gateway system fitted at the entrance to the colony. We used multistate mark–recapture modelling to identify the different drivers influencing survival rates and a sensitivity analysis to assess their relative importance across different life stages. Survival rates were low and variable during the fledging year (mean = 0·33), increasing to much higher levels from age 1 onwards (mean = 0·89). We show that survival of macaroni penguins is driven by a combination of individual quality, top-down predation pressure and bottom-up environmental forces. The relative importance of these covariates was age specific. During the fledging year, survival rates were most sensitive to top-down predation pressure, followed by individual fledging mass, and finally bottom-up environmental effects. In contrast, birds older than 1 year showed a similar response to bottom-up environmental effects and top-down predation pressure. We infer from our results that macaroni penguins will most likely be negatively impacted by an increase in the local population size of giant petrels. Furthermore, this population is, at least in the short term, likely to be positively influenced by local warming. More broadly, our results highlight the importance of considering multiple causal

Predicting General Academic Performance and Identifying the Differential Contribution of Participating Variables Using Artificial Neural Networks

ERIC Educational Resources Information Center

Musso, Mariel F.; Kyndt, Eva; Cascallar, Eduardo C.; Dochy, Filip

2013-01-01

Many studies have explored the contribution of different factors from diverse theoretical perspectives to the explanation of academic performance. These factors have been identified as having important implications not only for the study of learning processes, but also as tools for improving curriculum designs, tutorial systems, and students'…

The Promise of Virtual Teams: Identifying Key Factors in Effectiveness and Failure

ERIC Educational Resources Information Center

Horwitz, Frank M.; Bravington, Desmond; Silvis, Ulrik

2006-01-01

Purpose: The aim of the investigation is to identify enabling and disenabling factors in the development and operation of virtual teams; to evaluate the importance of factors such as team development, cross-cultural variables, leadership, communication and social cohesion as contributors to virtual team effectiveness. Design/methodology/approach:…

Group Variable Selection Via Convex Log-Exp-Sum Penalty with Application to a Breast Cancer Survivor Study

PubMed Central

Geng, Zhigeng; Wang, Sijian; Yu, Menggang; Monahan, Patrick O.; Champion, Victoria; Wahba, Grace

2017-01-01

Summary In many scientific and engineering applications, covariates are naturally grouped. When the group structures are available among covariates, people are usually interested in identifying both important groups and important variables within the selected groups. Among existing successful group variable selection methods, some methods fail to conduct the within group selection. Some methods are able to conduct both group and within group selection, but the corresponding objective functions are non-convex. Such a non-convexity may require extra numerical effort. In this article, we propose a novel Log-Exp-Sum(LES) penalty for group variable selection. The LES penalty is strictly convex. It can identify important groups as well as select important variables within the group. We develop an efficient group-level coordinate descent algorithm to fit the model. We also derive non-asymptotic error bounds and asymptotic group selection consistency for our method in the high-dimensional setting where the number of covariates can be much larger than the sample size. Numerical results demonstrate the good performance of our method in both variable selection and prediction. We applied the proposed method to an American Cancer Society breast cancer survivor dataset. The findings are clinically meaningful and may help design intervention programs to improve the qualify of life for breast cancer survivors. PMID:25257196

Automatic classifier based on heart rate variability to identify fallers among hypertensive subjects.

PubMed

Melillo, Paolo; Jovic, Alan; De Luca, Nicola; Pecchia, Leandro

2015-08-01

Accidental falls are a major problem of later life. Different technologies to predict falls have been investigated, but with limited success, mainly because of low specificity due to a high false positive rate. This Letter presents an automatic classifier based on heart rate variability (HRV) analysis with the goal to identify fallers automatically. HRV was used in this study as it is considered a good estimator of autonomic nervous system (ANS) states, which are responsible, among other things, for human balance control. Nominal 24 h electrocardiogram recordings from 168 cardiac patients (age 72 ± 8 years, 60 female), of which 47 were fallers, were investigated. Linear and nonlinear HRV properties were analysed in 30 min excerpts. Different data mining approaches were adopted and their performances were compared with a subject-based receiver operating characteristic analysis. The best performance was achieved by a hybrid algorithm, RUSBoost, integrated with feature selection method based on principal component analysis, which achieved satisfactory specificity and accuracy (80 and 72%, respectively), but low sensitivity (51%). These results suggested that ANS states causing falls could be reliably detected, but also that not all the falls were due to ANS states.

Scanning genomic areas under selection sweep and association mapping as tools to identify horticultural important genes in watermelon

USDA-ARS?s Scientific Manuscript database

Watermelon (Citrullus lanatus var. lanatus) contains 88% water, sugars, and several important health-related compounds, including lycopene, citrulline, arginine, and glutathione. The current genetic diversity study uses microsatellites with known map positions to identify genomic regions that under...

Identification of Active Galactic Nuclei through HST optical variability in the GOODS South field

NASA Astrophysics Data System (ADS)

Pouliasis, Ektoras; Georgantopoulos; Bonanos, A.; HCV Team

2016-08-01

This work aims to identify AGN in the GOODS South deep field through optical variability. This method can easily identify low-luminosity AGN. In particular, we use images in the z-band obtained from the Hubble Space Telescope with the ACS/WFC camera over 5 epochs separated by ~45 days. Aperture photometry has been performed using SExtractor to extract the lightcurves. Several variability indices, such as the median absolute deviation, excess variance, and sigma were applied to automatically identify the variable sources. After removing artifacts, stars and supernovae from the variable selected sample and keeping only those sources with known photometric or spectroscopic redshift, the optical variability was compared to variability in other wavelengths (X-rays, mid-IR, radio). This multi-wavelength study provides important constraints on the structure and the properties of the AGN and their relation to their hosts. This work is a part of the validation of the Hubble Catalog of Variables (HCV) project, which has been launched at the National Observatory of Athens by ESA, and aims to identify all sources (pointlike and extended) showing variability, based on the Hubble Source Catalog (HSC, Whitmore et al. 2015). The HSC version 1 was released in February 2015 and includes 80 million sources imaged with the WFPC2, ACS/WFC, WFC3/UVIS and WFC3/IR cameras.

The Space-Time Variation of Global Crop Yields, Detecting Simultaneous Outliers and Identifying the Teleconnections with Climatic Patterns

NASA Astrophysics Data System (ADS)

Najafi, E.; Devineni, N.; Pal, I.; Khanbilvardi, R.

2017-12-01

An understanding of the climate factors that influence the space-time variability of crop yields is important for food security purposes and can help us predict global food availability. In this study, we address how the crop yield trends of countries globally were related to each other during the last several decades and the main climatic variables that triggered high/low crop yields simultaneously across the world. Robust Principal Component Analysis (rPCA) is used to identify the primary modes of variation in wheat, maize, sorghum, rice, soybeans, and barley yields. Relations between these modes of variability and important climatic variables, especially anomalous sea surface temperature (SSTa), are examined from 1964 to 2010. rPCA is also used to identify simultaneous outliers in each year, i.e. systematic high/low crop yields across the globe. The results demonstrated spatiotemporal patterns of these crop yields and the climate-related events that caused them as well as the connection of outliers with weather extremes. We find that among climatic variables, SST has had the most impact on creating simultaneous crop yields variability and yield outliers in many countries. An understanding of this phenomenon can benefit global crop trade networks.

A genome-wide methylation study on obesity: differential variability and differential methylation.

PubMed

Xu, Xiaojing; Su, Shaoyong; Barnes, Vernon A; De Miguel, Carmen; Pollock, Jennifer; Ownby, Dennis; Shi, Hidong; Zhu, Haidong; Snieder, Harold; Wang, Xiaoling

2013-05-01

Besides differential methylation, DNA methylation variation has recently been proposed and demonstrated to be a potential contributing factor to cancer risk. Here we aim to examine whether differential variability in methylation is also an important feature of obesity, a typical non-malignant common complex disease. We analyzed genome-wide methylation profiles of over 470,000 CpGs in peripheral blood samples from 48 obese and 48 lean African-American youth aged 14-20 y old. A substantial number of differentially variable CpG sites (DVCs), using statistics based on variances, as well as a substantial number of differentially methylated CpG sites (DMCs), using statistics based on means, were identified. Similar to the findings in cancers, DVCs generally exhibited an outlier structure and were more variable in cases than in controls. By randomly splitting the current sample into a discovery and validation set, we observed that both the DVCs and DMCs identified from the first set could independently predict obesity status in the second set. Furthermore, both the genes harboring DMCs and the genes harboring DVCs showed significant enrichment of genes identified by genome-wide association studies on obesity and related diseases, such as hypertension, dyslipidemia, type 2 diabetes and certain types of cancers, supporting their roles in the etiology and pathogenesis of obesity. We generalized the recent finding on methylation variability in cancer research to obesity and demonstrated that differential variability is also an important feature of obesity-related methylation changes. Future studies on the epigenetics of obesity will benefit from both statistics based on means and statistics based on variances.

Identifying community thresholds for lotic benthic diatoms in response to human disturbance.

PubMed

Tang, Tao; Tang, Ting; Tan, Lu; Gu, Yuan; Jiang, Wanxiang; Cai, Qinghua

2017-06-23

Although human disturbance indirectly influences lotic assemblages through modifying physical and chemical conditions, identifying thresholds of human disturbance would provide direct evidence for preventing anthropogenic degradation of biological conditions. In the present study, we used data obtained from tributaries of the Three Gorges Reservoir in China to detect effects of human disturbance on streams and to identify disturbance thresholds for benthic diatoms. Diatom species composition was significantly affected by three in-stream stressors including TP, TN and pH. Diatoms were also influenced by watershed % farmland and natural environmental variables. Considering three in-stream stressors, TP was positively influenced by % farmland and % impervious surface area (ISA). In contrast, TN and pH were principally affected by natural environmental variables. Among measured natural environmental variables, average annual air temperature, average annual precipitation, and topsoil % CaCO 3 , % gravel, and total exchangeable bases had significant effects on study streams. When effects of natural variables were accounted for, substantial compositional changes in diatoms occurred when farmland or ISA land use exceeded 25% or 0.3%, respectively. Our study demonstrated the rationale for identifying thresholds of human disturbance for lotic assemblages and addressed the importance of accounting for effects of natural factors for accurate disturbance thresholds.

Design study and performance analysis of a high-speed multistage variable-geometry fan for a variable cycle engine

NASA Technical Reports Server (NTRS)

Sullivan, T. J.; Parker, D. E.

1979-01-01

A design technology study was performed to identify a high speed, multistage, variable geometry fan configuration capable of achieving wide flow modulation with near optimum efficiency at the important operating condition. A parametric screening study of the front and rear block fans was conducted in which the influence of major fan design features on weight and efficiency was determined. Key design parameters were varied systematically to determine the fan configuration most suited for a double bypass, variable cycle engine. Two and three stage fans were considered for the front block. A single stage, core driven fan was studied for the rear block. Variable geometry concepts were evaluated to provide near optimum off design performance. A detailed aerodynamic design and a preliminary mechanical design were carried out for the selected fan configuration. Performance predictions were made for the front and rear block fans.

Surgeon and type of anesthesia predict variability in surgical procedure times.

PubMed

Strum, D P; Sampson, A R; May, J H; Vargas, L G

2000-05-01

Variability in surgical procedure times increases the cost of healthcare delivery by increasing both the underutilization and overutilization of expensive surgical resources. To reduce variability in surgical procedure times, we must identify and study its sources. Our data set consisted of all surgeries performed over a 7-yr period at a large teaching hospital, resulting in 46,322 surgical cases. To study factors associated with variability in surgical procedure times, data mining techniques were used to segment and focus the data so that the analyses would be both technically and intellectually feasible. The data were subdivided into 40 representative segments of manageable size and variability based on headers adopted from the common procedural terminology classification. Each data segment was then analyzed using a main-effects linear model to identify and quantify specific sources of variability in surgical procedure times. The single most important source of variability in surgical procedure times was surgeon effect. Type of anesthesia, age, gender, and American Society of Anesthesiologists risk class were additional sources of variability. Intrinsic case-specific variability, unexplained by any of the preceding factors, was found to be highest for shorter surgeries relative to longer procedures. Variability in procedure times among surgeons was a multiplicative function (proportionate to time) of surgical time and total procedure time, such that as procedure times increased, variability in surgeons' surgical time increased proportionately. Surgeon-specific variability should be considered when building scheduling heuristics for longer surgeries. Results concerning variability in surgical procedure times due to factors such as type of anesthesia, age, gender, and American Society of Anesthesiologists risk class may be extrapolated to scheduling in other institutions, although specifics on individual surgeons may not. This research identifies factors associated

Identifying the domains of context important to implementation science: a study protocol.

PubMed

Squires, Janet E; Graham, Ian D; Hutchinson, Alison M; Michie, Susan; Francis, Jill J; Sales, Anne; Brehaut, Jamie; Curran, Janet; Ivers, Noah; Lavis, John; Linklater, Stefanie; Fenton, Shannon; Noseworthy, Thomas; Vine, Jocelyn; Grimshaw, Jeremy M

2015-09-28

There is growing recognition that "context" can and does modify the effects of implementation interventions aimed at increasing healthcare professionals' use of research evidence in clinical practice. However, conceptual clarity about what exactly comprises "context" is lacking. The purpose of this research program is to develop, refine, and validate a framework that identifies the key domains of context (and their features) that can facilitate or hinder (1) healthcare professionals' use of evidence in clinical practice and (2) the effectiveness of implementation interventions. A multi-phased investigation of context using mixed methods will be conducted. The first phase is a concept analysis of context using the Walker and Avant method to distinguish between the defining and irrelevant attributes of context. This phase will result in a preliminary framework for context that identifies its important domains and their features according to the published literature. The second phase is a secondary analysis of qualitative data from 13 studies of interviews with 312 healthcare professionals on the perceived barriers and enablers to their application of research evidence in clinical practice. These data will be analyzed inductively using constant comparative analysis. For the third phase, we will conduct semi-structured interviews with key health system stakeholders and change agents to elicit their knowledge and beliefs about the contextual features that influence the effectiveness of implementation interventions and healthcare professionals' use of evidence in clinical practice. Results from all three phases will be synthesized using a triangulation protocol to refine the context framework drawn from the concept analysis. The framework will then be assessed for content validity using an iterative Delphi approach with international experts (researchers and health system stakeholders/change agents). This research program will result in a framework that identifies the

Assessment of oil content and fatty acid composition variability in two economically important Hibiscus species.

PubMed

Wang, Ming Li; Morris, Brad; Tonnis, Brandon; Davis, Jerry; Pederson, Gary A

2012-07-04

The Hibiscus genus encompasses more than 300 species, but kenaf (Hibiscus cannabinus L.) and roselle (Hibiscus sabdariffa L.) are the two most economically important species within the genus. Seeds from these two Hibiscus species contain a relatively high amount of oil with two unusual fatty acids: dihydrosterculic and vernolic acids. The fatty acid composition in the oil can directly affect oil quality and its utilization. However, the variability in oil content and fatty acid composition for these two species is unclear. For these two species, 329 available accessions were acquired from the USDA germplasm collection. Their oil content and fatty acid composition were determined by nuclear magnetic resonance (NMR) and gas chromatography (GC), respectively. Using NMR and GC analyses, we found that Hibiscus seeds on average contained 18% oil and seed oil was composed of six major fatty acids (each >1%) and seven minor fatty acids (each <1%). Hibiscus cannabinus seeds contained significantly higher amounts of oil (18.14%), palmitic (20.75%), oleic (28.91%), vernolic acids (VA, 4.16%), and significantly lower amounts of stearic (3.96%), linoleic (39.49%), and dihydrosterculic acids (DHSA, 1.08%) than H. sabdariffa seeds (17.35%, 18.52%, 25.16%, 3.52%, 4.31%, 44.72%, and 1.57%, respectively). For edible oils, a higher oleic/linoleic (O/L) ratio and lower level of DHSA are preferred, and for industrial oils a high level of VA is preferred. Our results indicate that seeds from H. cannabinus may be of higher quality than H. sabdariffa seeds for these reasons. Significant variability in oil content and major fatty acids was also detected within both species. The variability in oil content and fatty acid composition revealed from this study will be useful for exploring seed utilization and developing new cultivars in these Hibiscus species.

Why is seed production so variable among individuals? A ten-year study with oaks reveals the importance of soil environment.

PubMed

Pérez-Ramos, Ignacio M; Aponte, Cristina; García, Luis V; Padilla-Díaz, Carmen M; Marañón, Teodoro

2014-01-01

Mast-seeding species exhibit not only a large inter-annual variability in seed production but also considerable variability among individuals within the same year. However, very little is known about the causes and consequences for population dynamics of this potentially large between-individual variability. Here, we quantified seed production over ten consecutive years in two Mediterranean oak species - the deciduous Quercus canariensis and the evergreen Q. suber - that coexist in forests of southern Spain. First, we calibrated likelihood models to identify which abiotic and biotic variables best explain the magnitude (hereafter seed productivity) and temporal variation of seed production at the individual level (hereafter CVi), and infer whether reproductive effort results from the available soil resources for the plant or is primarily determined by selectively favoured strategies. Second, we explored the contribution of between-individual variability in seed production as a potential mechanism of satiation for predispersal seed predators. We found that Q. canariensis trees inhabiting moister and more fertile soils were more productive than those growing in more resource-limited sites. Regarding temporal variation, individuals of the two studied oak species inhabiting these resource-rich environments also exhibited larger values of CVi. Interestingly, we detected a satiating effect on granivorous insects at the tree level in Q. suber, which was evident in those years where between-individual variability in acorn production was higher. These findings suggest that individual seed production (both in terms of seed productivity and inter-annual variability) is strongly dependent on soil resource heterogeneity (at least for one of the two studied oak species) with potential repercussions for recruitment and population dynamics. However, other external factors (such as soil heterogeneity in pathogen abundance) or certain inherent characteristics of the tree might be

An Algorithm to Identify Compounded Non-Sterile Products that Can Be Formulated on a Commercial Scale or Imported to Promote Safer Medication Use in Children

PubMed Central

Bhatt-Mehta, Varsha; MacArthur, Robert B.; Löbenberg, Raimar; Cies, Jeffrey J.; Cernak, Ibolja; Parrish, Richard H.

2015-01-01

The lack of commercially-available pediatric drug products and dosage forms is well-known. A group of clinicians and scientists with a common interest in pediatric drug development and medicines-use systems developed a practical framework for identifying a list of active pharmaceutical ingredients (APIs) with the greatest market potential for development to use in pediatric patients. Reliable and reproducible evidence-based drug formulations designed for use in pediatric patients are needed vitally, otherwise safe and consistent clinical practices and outcomes assessments will continue to be difficult to ascertain. Identification of a prioritized list of candidate APIs for oral formulation using the described algorithm provides a broader integrated clinical, scientific, regulatory, and market basis to allow for more reliable dosage forms and safer, effective medicines use in children of all ages. Group members derived a list of candidate API molecules by factoring in a number of pharmacotherapeutic, scientific, manufacturing, and regulatory variables into the selection algorithm that were absent in other rubrics. These additions will assist in identifying and categorizing prime API candidates suitable for oral formulation development. Moreover, the developed algorithm aids in prioritizing useful APIs with finished oral liquid dosage forms available from other countries with direct importation opportunities to North America and beyond. PMID:28975916

Use of structured decision making to identify monitoring variables and management priorities for salt marsh ecosystems

USGS Publications Warehouse

Neckles, Hilary A.; Lyons, James E.; Guntenspergen, Glenn R.; Shriver, W. Gregory; Adamowicz, Susan C.

2015-01-01

Most salt marshes in the USA have been degraded by human activities, and coastal managers are faced with complex choices among possible actions to restore or enhance ecosystem integrity. We applied structured decision making (SDM) to guide selection of monitoring variables and management priorities for salt marshes within the National Wildlife Refuge System in the northeastern USA. In general, SDM is a systematic process for decomposing a decision into its essential elements. We first engaged stakeholders in clarifying regional salt marsh decision problems, defining objectives and attributes to evaluate whether objectives are achieved, and developing a pool of alternative management actions for achieving objectives. Through this process, we identified salt marsh attributes that were applicable to monitoring National Wildlife Refuges on a regional scale and that targeted management needs. We then analyzed management decisions within three salt marsh units at Prime Hook National Wildlife Refuge, coastal Delaware, as a case example of prioritizing management alternatives. Values for salt marsh attributes were estimated from 2 years of baseline monitoring data and expert opinion. We used linear value modeling to aggregate multiple attributes into a single performance score for each alternative, constrained optimization to identify alternatives that maximized total management benefits subject to refuge-wide cost constraints, and used graphical analysis to identify the optimal set of alternatives for the refuge. SDM offers an efficient, transparent approach for integrating monitoring into management practice and improving the quality of management decisions.

Spatial variability of methane production and methanogen communities within a eutrophic reservoir: evaluating the importance of organic matter source and quantity

EPA Science Inventory

Freshwater reservoirs are an important source of the greenhouse gas methane (CH4) to the atmosphere, but there is a wide range of estimates of global emissions, due in part to variability of methane emissions rates within reservoirs. While morphological characteristics, including...

An AUC-based permutation variable importance measure for random forests

PubMed Central

2013-01-01

Background The random forest (RF) method is a commonly used tool for classification with high dimensional data as well as for ranking candidate predictors based on the so-called random forest variable importance measures (VIMs). However the classification performance of RF is known to be suboptimal in case of strongly unbalanced data, i.e. data where response class sizes differ considerably. Suggestions were made to obtain better classification performance based either on sampling procedures or on cost sensitivity analyses. However to our knowledge the performance of the VIMs has not yet been examined in the case of unbalanced response classes. In this paper we explore the performance of the permutation VIM for unbalanced data settings and introduce an alternative permutation VIM based on the area under the curve (AUC) that is expected to be more robust towards class imbalance. Results We investigated the performance of the standard permutation VIM and of our novel AUC-based permutation VIM for different class imbalance levels using simulated data and real data. The results suggest that the new AUC-based permutation VIM outperforms the standard permutation VIM for unbalanced data settings while both permutation VIMs have equal performance for balanced data settings. Conclusions The standard permutation VIM loses its ability to discriminate between associated predictors and predictors not associated with the response for increasing class imbalance. It is outperformed by our new AUC-based permutation VIM for unbalanced data settings, while the performance of both VIMs is very similar in the case of balanced classes. The new AUC-based VIM is implemented in the R package party for the unbiased RF variant based on conditional inference trees. The codes implementing our study are available from the companion website: http://www.ibe.med.uni-muenchen.de/organisation/mitarbeiter/070_drittmittel/janitza/index.html. PMID:23560875

An AUC-based permutation variable importance measure for random forests.

PubMed

Janitza, Silke; Strobl, Carolin; Boulesteix, Anne-Laure

2013-04-05

The random forest (RF) method is a commonly used tool for classification with high dimensional data as well as for ranking candidate predictors based on the so-called random forest variable importance measures (VIMs). However the classification performance of RF is known to be suboptimal in case of strongly unbalanced data, i.e. data where response class sizes differ considerably. Suggestions were made to obtain better classification performance based either on sampling procedures or on cost sensitivity analyses. However to our knowledge the performance of the VIMs has not yet been examined in the case of unbalanced response classes. In this paper we explore the performance of the permutation VIM for unbalanced data settings and introduce an alternative permutation VIM based on the area under the curve (AUC) that is expected to be more robust towards class imbalance. We investigated the performance of the standard permutation VIM and of our novel AUC-based permutation VIM for different class imbalance levels using simulated data and real data. The results suggest that the new AUC-based permutation VIM outperforms the standard permutation VIM for unbalanced data settings while both permutation VIMs have equal performance for balanced data settings. The standard permutation VIM loses its ability to discriminate between associated predictors and predictors not associated with the response for increasing class imbalance. It is outperformed by our new AUC-based permutation VIM for unbalanced data settings, while the performance of both VIMs is very similar in the case of balanced classes. The new AUC-based VIM is implemented in the R package party for the unbiased RF variant based on conditional inference trees. The codes implementing our study are available from the companion website: http://www.ibe.med.uni-muenchen.de/organisation/mitarbeiter/070_drittmittel/janitza/index.html.

Identifying variably saturated water-flow patterns in a steep hillslope under intermittent heavy rainfall

USGS Publications Warehouse

El-Kadi, A. I.; Torikai, J.D.

2001-01-01

The objective of this paper is to identify water-flow patterns in part of an active landslide, through the use of numerical simulations and data obtained during a field study. The approaches adopted include measuring rainfall events and pore-pressure responses in both saturated and unsaturated soils at the site. To account for soil variability, the Richards equation is solved within deterministic and stochastic frameworks. The deterministic simulations considered average water-retention data, adjusted retention data to account for stones or cobbles, retention functions for a heterogeneous pore structure, and continuous retention functions for preferential flow. The stochastic simulations applied the Monte Carlo approach which considers statistical distribution and autocorrelation of the saturated conductivity and its cross correlation with the retention function. Although none of the models is capable of accurately predicting field measurements, appreciable improvement in accuracy was attained using stochastic, preferential flow, and heterogeneous pore-structure models. For the current study, continuum-flow models provide reasonable accuracy for practical purposes, although they are expected to be less accurate than multi-domain preferential flow models.

Variability in Adaptive Behavior in Autism: Evidence for the Importance of Family History

ERIC Educational Resources Information Center

Mazefsky, Carla A.; Williams, Diane L.; Minshew, Nancy J.

2008-01-01

Adaptive behavior in autism is highly variable and strongly related to prognosis. This study explored family history as a potential source of variability in adaptive behavior in autism. Participants included 77 individuals (mean age = 18) with average or better intellectual ability and autism. Parents completed the Family History Interview about…

How important is interannual variability in the climatic interpretation of moraine sequences?

NASA Astrophysics Data System (ADS)

Leonard, E. M.; Laabs, B. J. C.; Plummer, M. A.

2017-12-01

Mountain glaciers respond to both long-term climate and interannual forcing. Anderson et al. (2014) pointed out that kilometer-scale fluctuations in glacier length may result from interannual variability in temperature and precipitation given a "steady" climate with no long-term trends in mean or variability of temperature and precipitation. They cautioned that use of outermost moraines from the Last Glacial Maximum (LGM) as indicators of LGM climate will, because of the role of interannual forcing, result in overestimation of the magnitude of long-term temperature depression and/or precipitation enhancement. Here we assess the implications of these ideas, by examining the effect of interannual variability on glacier length and inferred magnitude of LGM climate change from present under both an assumed steady LGM climate and an LGM climate with low-magnitude, long-period variation in summer temperature and annual precipitation. We employ both the original 1-stage linear glacier model (Roe and O'Neal, 2009) used by Anderson et al. (2014) and a newer 3-stage linear model (Roe and Baker, 2014). We apply the models to two reconstructed LGM glaciers in the Colorado Sangre de Cristo Mountains. Three-stage-model results indicate that, absent long-term variations through a 7500-year-long LGM, interannual variability would result in overestimation of mean LGM temperature depression from the outermost moraine of 0.2-0.6°C. If small long-term cyclic variations of temperature (±0.5°C) and precipitation (±5%) are introduced, the overestimation of LGM temperature depression reduces to less than 0.4°C, and if slightly greater long-term variation (±1.0°C and ±10% precipitation) is introduced, the magnitude of overestimation is 0.3°C or less. Interannual variability may produce a moraine sequence that differs from the sequence that would be expected were glacier length forced only by long-term climate. With small amplitude (±0.5°C and ±5% precipitation) long

The interprocess NIR sampling as an alternative approach to multivariate statistical process control for identifying sources of product-quality variability.

PubMed

Marković, Snežana; Kerč, Janez; Horvat, Matej

2017-03-01

We are presenting a new approach of identifying sources of variability within a manufacturing process by NIR measurements of samples of intermediate material after each consecutive unit operation (interprocess NIR sampling technique). In addition, we summarize the development of a multivariate statistical process control (MSPC) model for the production of enteric-coated pellet product of the proton-pump inhibitor class. By developing provisional NIR calibration models, the identification of critical process points yields comparable results to the established MSPC modeling procedure. Both approaches are shown to lead to the same conclusion, identifying parameters of extrusion/spheronization and characteristics of lactose that have the greatest influence on the end-product's enteric coating performance. The proposed approach enables quicker and easier identification of variability sources during manufacturing process, especially in cases when historical process data is not straightforwardly available. In the presented case the changes of lactose characteristics are influencing the performance of the extrusion/spheronization process step. The pellet cores produced by using one (considered as less suitable) lactose source were on average larger and more fragile, leading to consequent breakage of the cores during subsequent fluid bed operations. These results were confirmed by additional experimental analyses illuminating the underlying mechanism of fracture of oblong pellets during the pellet coating process leading to compromised film coating.

Computer simulation models as tools for identifying research needs: A black duck population model

USGS Publications Warehouse

Ringelman, J.K.; Longcore, J.R.

1980-01-01

Existing data on the mortality and production rates of the black duck (Anas rubripes) were used to construct a WATFIV computer simulation model. The yearly cycle was divided into 8 phases: hunting, wintering, reproductive, molt, post-molt, and juvenile dispersal mortality, and production from original and renesting attempts. The program computes population changes for sex and age classes during each phase. After completion of a standard simulation run with all variable default values in effect, a sensitivity analysis was conducted by changing each of 50 input variables, 1 at a time, to assess the responsiveness of the model to changes in each variable. Thirteen variables resulted in a substantial change in population level. Adult mortality factors were important during hunting and wintering phases. All production and mortality associated with original nesting attempts were sensitive, as was juvenile dispersal mortality. By identifying those factors which invoke the greatest population change, and providing an indication of the accuracy required in estimating these factors, the model helps to identify those variables which would be most profitable topics for future research.

Triangulating Principal Effectiveness: How Perspectives of Parents, Teachers, and Assistant Principals Identify the Central Importance of Managerial Skills

ERIC Educational Resources Information Center

Grissom, Jason A.; Loeb, Susanna

2011-01-01

While the importance of effective principals is undisputed, few studies have identified specific skills that principals need to promote school success. This study draws on unique data combining survey responses from principals, assistant principals, teachers, and parents with rich administrative data to determine which principal skills correlate…

Spatial heterogeneity in ecologically important climate variables at coarse and fine scales in a high-snow mountain landscape.

PubMed

Ford, Kevin R; Ettinger, Ailene K; Lundquist, Jessica D; Raleigh, Mark S; Hille Ris Lambers, Janneke

2013-01-01

Climate plays an important role in determining the geographic ranges of species. With rapid climate change expected in the coming decades, ecologists have predicted that species ranges will shift large distances in elevation and latitude. However, most range shift assessments are based on coarse-scale climate models that ignore fine-scale heterogeneity and could fail to capture important range shift dynamics. Moreover, if climate varies dramatically over short distances, some populations of certain species may only need to migrate tens of meters between microhabitats to track their climate as opposed to hundreds of meters upward or hundreds of kilometers poleward. To address these issues, we measured climate variables that are likely important determinants of plant species distributions and abundances (snow disappearance date and soil temperature) at coarse and fine scales at Mount Rainier National Park in Washington State, USA. Coarse-scale differences across the landscape such as large changes in elevation had expected effects on climatic variables, with later snow disappearance dates and lower temperatures at higher elevations. However, locations separated by small distances (∼20 m), but differing by vegetation structure or topographic position, often experienced differences in snow disappearance date and soil temperature as great as locations separated by large distances (>1 km). Tree canopy gaps and topographic depressions experienced later snow disappearance dates than corresponding locations under intact canopy and on ridges. Additionally, locations under vegetation and on topographic ridges experienced lower maximum and higher minimum soil temperatures. The large differences in climate we observed over small distances will likely lead to complex range shift dynamics and could buffer species from the negative effects of climate change.

Spatial Heterogeneity in Ecologically Important Climate Variables at Coarse and Fine Scales in a High-Snow Mountain Landscape

PubMed Central

Ford, Kevin R.; Ettinger, Ailene K.; Lundquist, Jessica D.; Raleigh, Mark S.; Hille Ris Lambers, Janneke

2013-01-01

Climate plays an important role in determining the geographic ranges of species. With rapid climate change expected in the coming decades, ecologists have predicted that species ranges will shift large distances in elevation and latitude. However, most range shift assessments are based on coarse-scale climate models that ignore fine-scale heterogeneity and could fail to capture important range shift dynamics. Moreover, if climate varies dramatically over short distances, some populations of certain species may only need to migrate tens of meters between microhabitats to track their climate as opposed to hundreds of meters upward or hundreds of kilometers poleward. To address these issues, we measured climate variables that are likely important determinants of plant species distributions and abundances (snow disappearance date and soil temperature) at coarse and fine scales at Mount Rainier National Park in Washington State, USA. Coarse-scale differences across the landscape such as large changes in elevation had expected effects on climatic variables, with later snow disappearance dates and lower temperatures at higher elevations. However, locations separated by small distances (∼20 m), but differing by vegetation structure or topographic position, often experienced differences in snow disappearance date and soil temperature as great as locations separated by large distances (>1 km). Tree canopy gaps and topographic depressions experienced later snow disappearance dates than corresponding locations under intact canopy and on ridges. Additionally, locations under vegetation and on topographic ridges experienced lower maximum and higher minimum soil temperatures. The large differences in climate we observed over small distances will likely lead to complex range shift dynamics and could buffer species from the negative effects of climate change. PMID:23762277

Ecological niche models reveal the importance of climate variability for the biogeography of protosteloid amoebae

PubMed Central

Aguilar, María; Lado, Carlos

2012-01-01

Habitat availability and environmental preferences of species are among the most important factors in determining the success of dispersal processes and therefore in shaping the distribution of protists. We explored the differences in fundamental niches and potential distributions of an ecological guild of slime moulds—protosteloid amoebae—in the Iberian Peninsula. A large set of samples collected in a north-east to south-west transect of approximately 1000 km along the peninsula was used to test the hypothesis that, together with the existence of suitable microhabitats, climate conditions may determine the probability of survival of species. Although protosteloid amoebae share similar morphologies and life history strategies, canonical correspondence analyses showed that they have varied ecological optima, and that climate conditions have an important effect in niche differentiation. Maxent environmental niche models provided consistent predictions of the probability of presence of the species based on climate data, and they were used to generate maps of potential distribution in an ‘everything is everywhere' scenario. The most important climatic factors were, in both analyses, variables that measure changes in conditions throughout the year, confirming that the alternation of fruiting bodies, cysts and amoeboid stages in the life cycles of protosteloid amoebae constitutes an advantage for surviving in a changing environment. Microhabitat affinity seems to be influenced by climatic conditions, which suggests that the micro-environment may vary at a local scale and change together with the external climate at a larger scale. PMID:22402402

Ecological niche models reveal the importance of climate variability for the biogeography of protosteloid amoebae.

PubMed

Aguilar, María; Lado, Carlos

2012-08-01

Habitat availability and environmental preferences of species are among the most important factors in determining the success of dispersal processes and therefore in shaping the distribution of protists. We explored the differences in fundamental niches and potential distributions of an ecological guild of slime moulds-protosteloid amoebae-in the Iberian Peninsula. A large set of samples collected in a north-east to south-west transect of approximately 1000 km along the peninsula was used to test the hypothesis that, together with the existence of suitable microhabitats, climate conditions may determine the probability of survival of species. Although protosteloid amoebae share similar morphologies and life history strategies, canonical correspondence analyses showed that they have varied ecological optima, and that climate conditions have an important effect in niche differentiation. Maxent environmental niche models provided consistent predictions of the probability of presence of the species based on climate data, and they were used to generate maps of potential distribution in an 'everything is everywhere' scenario. The most important climatic factors were, in both analyses, variables that measure changes in conditions throughout the year, confirming that the alternation of fruiting bodies, cysts and amoeboid stages in the life cycles of protosteloid amoebae constitutes an advantage for surviving in a changing environment. Microhabitat affinity seems to be influenced by climatic conditions, which suggests that the micro-environment may vary at a local scale and change together with the external climate at a larger scale.

Does Distress Tolerance Moderate the Impact of Major Life Events on Psychosocial Variables and Behaviors Important in the Management of HIV?

ERIC Educational Resources Information Center

O'Cleirigh, Conall; Ironson, Gail; Smits, Jasper A. J.

2007-01-01

Living with HIV involves management of multiple stressful disease-related and other life events. Distress tolerance may provide a functional, individual-based context for qualifying the established relationships between major life events and psychosocial variables important in the management of HIV. The present study provided a preliminary test of…

Genome-Wide Association Study Identifying Candidate Genes Influencing Important Agronomic Traits of Flax (Linum usitatissimum L.) Using SLAF-seq

PubMed Central

Xie, Dongwei; Dai, Zhigang; Yang, Zemao; Sun, Jian; Zhao, Debao; Yang, Xue; Zhang, Liguo; Tang, Qing; Su, Jianguang

2018-01-01

Flax (Linum usitatissimum L.) is an important cash crop, and its agronomic traits directly affect yield and quality. Molecular studies on flax remain inadequate because relatively few flax genes have been associated with agronomic traits or have been identified as having potential applications. To identify markers and candidate genes that can potentially be used for genetic improvement of crucial agronomic traits, we examined 224 specimens of core flax germplasm; specifically, phenotypic data for key traits, including plant height, technical length, number of branches, number of fruits, and 1000-grain weight were investigated under three environmental conditions before specific-locus amplified fragment sequencing (SLAF-seq) was employed to perform a genome-wide association study (GWAS) for these five agronomic traits. Subsequently, the results were used to screen single nucleotide polymorphism (SNP) loci and candidate genes that exhibited a significant correlation with the important agronomic traits. Our analyses identified a total of 42 SNP loci that showed significant correlations with the five important agronomic flax traits. Next, candidate genes were screened in the 10 kb zone of each of the 42 SNP loci. These SNP loci were then analyzed by a more stringent screening via co-identification using both a general linear model (GLM) and a mixed linear model (MLM) as well as co-occurrences in at least two of the three environments, whereby 15 final candidate genes were obtained. Based on these results, we determined that UGT and PL are candidate genes for plant height, GRAS and XTH are candidate genes for the number of branches, Contig1437 and LU0019C12 are candidate genes for the number of fruits, and PHO1 is a candidate gene for the 1000-seed weight. We propose that the identified SNP loci and corresponding candidate genes might serve as a biological basis for improving crucial agronomic flax traits. PMID:29375606

Genome-Wide Association Study Identifying Candidate Genes Influencing Important Agronomic Traits of Flax (Linum usitatissimum L.) Using SLAF-seq.

PubMed

Xie, Dongwei; Dai, Zhigang; Yang, Zemao; Sun, Jian; Zhao, Debao; Yang, Xue; Zhang, Liguo; Tang, Qing; Su, Jianguang

2017-01-01

Flax ( Linum usitatissimum L.) is an important cash crop, and its agronomic traits directly affect yield and quality. Molecular studies on flax remain inadequate because relatively few flax genes have been associated with agronomic traits or have been identified as having potential applications. To identify markers and candidate genes that can potentially be used for genetic improvement of crucial agronomic traits, we examined 224 specimens of core flax germplasm; specifically, phenotypic data for key traits, including plant height, technical length, number of branches, number of fruits, and 1000-grain weight were investigated under three environmental conditions before specific-locus amplified fragment sequencing (SLAF-seq) was employed to perform a genome-wide association study (GWAS) for these five agronomic traits. Subsequently, the results were used to screen single nucleotide polymorphism (SNP) loci and candidate genes that exhibited a significant correlation with the important agronomic traits. Our analyses identified a total of 42 SNP loci that showed significant correlations with the five important agronomic flax traits. Next, candidate genes were screened in the 10 kb zone of each of the 42 SNP loci. These SNP loci were then analyzed by a more stringent screening via co-identification using both a general linear model (GLM) and a mixed linear model (MLM) as well as co-occurrences in at least two of the three environments, whereby 15 final candidate genes were obtained. Based on these results, we determined that UGT and PL are candidate genes for plant height, GRAS and XTH are candidate genes for the number of branches, Contig1437 and LU0019C12 are candidate genes for the number of fruits, and PHO1 is a candidate gene for the 1000-seed weight. We propose that the identified SNP loci and corresponding candidate genes might serve as a biological basis for improving crucial agronomic flax traits.

Directional semivariogram analysis to identify and rank controls on the spatial variability of fracture networks

NASA Astrophysics Data System (ADS)

Hanke, John R.; Fischer, Mark P.; Pollyea, Ryan M.

2018-03-01

In this study, the directional semivariogram is deployed to investigate the spatial variability of map-scale fracture network attributes in the Paradox Basin, Utah. The relative variability ratio (R) is introduced as the ratio of integrated anisotropic semivariogram models, and R is shown to be an effective metric for quantifying the magnitude of spatial variability for any two azimuthal directions. R is applied to a GIS-based data set comprising roughly 1200 fractures, in an area which is bounded by a map-scale anticline and a km-scale normal fault. This analysis reveals that proximity to the fault strongly influences the magnitude of spatial variability for both fracture intensity and intersection density within 1-2 km. Additionally, there is significant anisotropy in the spatial variability, which is correlated with trends of the anticline and fault. The direction of minimum spatial correlation is normal to the fault at proximal distances, and gradually rotates and becomes subparallel to the fold axis over the same 1-2 km distance away from the fault. We interpret these changes to reflect varying scales of influence of the fault and the fold on fracture network development: the fault locally influences the magnitude and variability of fracture network attributes, whereas the fold sets the background level and structure of directional variability.

Crowd-sourced Ontology for Photoleukocoria: Identifying Common Internet Search Terms for a Potentially Important Pediatric Ophthalmic Sign.

PubMed

Staffieri, Sandra E; Kearns, Lisa S; Sanfilippo, Paul G; Craig, Jamie E; Mackey, David A; Hewitt, Alex W

2018-02-01

Leukocoria is the most common presenting sign for pediatric eye disease including retinoblastoma and cataract, with worse outcomes if diagnosis is delayed. We investigated whether individuals could identify leukocoria in photographs (photoleukocoria) and examined their subsequent Internet search behavior. Using a web-based questionnaire, in this cross-sectional study we invited adults aged over 18 years to view two photographs of a child with photoleukocoria, and then search the Internet to determine a possible diagnosis and action plan. The most commonly used search terms and websites accessed were recorded. The questionnaire was completed by 1639 individuals. Facebook advertisement was the most effective recruitment strategy. The mean age of all respondents was 38.95 ± 14.59 years (range, 18-83), 94% were female, and 59.3% had children. An abnormality in the images presented was identified by 1613 (98.4%) participants. The most commonly used search terms were: "white," "pupil," "photo," and "eye" reaching a variety of appropriate websites or links to print or social media articles. Different words or phrases were used to describe the same observation of photoleukocoria leading to a range of websites. Variations in the description of observed signs and search words influenced the sites reached, information obtained, and subsequent help-seeking intentions. Identifying the most commonly used search terms for photoleukocoria is an important step for search engine optimization. Being directed to the most appropriate websites informing of the significance of photoleukocoria and the appropriate actions to take could improve delays in diagnosis of important pediatric eye disease such as retinoblastoma or cataract.

Collective feature selection to identify crucial epistatic variants.

PubMed

Verma, Shefali S; Lucas, Anastasia; Zhang, Xinyuan; Veturi, Yogasudha; Dudek, Scott; Li, Binglan; Li, Ruowang; Urbanowicz, Ryan; Moore, Jason H; Kim, Dokyoon; Ritchie, Marylyn D

2018-01-01

Machine learning methods have gained popularity and practicality in identifying linear and non-linear effects of variants associated with complex disease/traits. Detection of epistatic interactions still remains a challenge due to the large number of features and relatively small sample size as input, thus leading to the so-called "short fat data" problem. The efficiency of machine learning methods can be increased by limiting the number of input features. Thus, it is very important to perform variable selection before searching for epistasis. Many methods have been evaluated and proposed to perform feature selection, but no single method works best in all scenarios. We demonstrate this by conducting two separate simulation analyses to evaluate the proposed collective feature selection approach. Through our simulation study we propose a collective feature selection approach to select features that are in the "union" of the best performing methods. We explored various parametric, non-parametric, and data mining approaches to perform feature selection. We choose our top performing methods to select the union of the resulting variables based on a user-defined percentage of variants selected from each method to take to downstream analysis. Our simulation analysis shows that non-parametric data mining approaches, such as MDR, may work best under one simulation criteria for the high effect size (penetrance) datasets, while non-parametric methods designed for feature selection, such as Ranger and Gradient boosting, work best under other simulation criteria. Thus, using a collective approach proves to be more beneficial for selecting variables with epistatic effects also in low effect size datasets and different genetic architectures. Following this, we applied our proposed collective feature selection approach to select the top 1% of variables to identify potential interacting variables associated with Body Mass Index (BMI) in ~ 44,000 samples obtained from Geisinger

Observations of GAIA-identified Cataclysmic Variables Using the TUBITAK National Observatory

NASA Astrophysics Data System (ADS)

Esenoglu, Hasan H.; Kirbiyik, Halil; Kaynar, Suleyman; Okuyan, Oguzhan; Hamitoglu, Irek; Galeev, Almaz; Uluc, Kadir; Kocak, Murat; Kilic, Sila E.; Parmaksizoglu, Murat; Erece, Orhan; Ozisik, Tuncay; Gulsecen, Hulusi

2016-07-01

TUBITAK National Observatory supports the GAIA alerts with observations using three telescopes (RTT150, T100, T60) at the site with a limited time quota. We have observed 10 variable stars among GAIA sources discovered in the years 2014-2016 that may be candidate Cataclysmic Variables (CVs). Our TUG observations at this stage involve photometry and spectroscopy to aid the identification of these sources. The first preliminary result of our observations of Gaia14aat among them showed a dwarf nova outburst with an amplitude of 2.69 mag. We aim to construct a GAIA astrophysics group to study CVs along with supported studies using the SRG (Spectrum Roentgen Gamma astrophysical observatory) after the year of 2016. These observations will basically involve spectroscopy, narrow-band CCD imaging and photometry using several filters to aid the identification of these sources. RTT150 observations with very narrow filters (like H-alpha, SII, OIII with band width of range of 2 to 5 nm) will reveal whether shell around the SRG sources to aid identification novae among them.

Important variables for parents' postnatal sense of security: evaluating a new Swedish instrument (the PPSS instrument).

PubMed

Persson, Eva K; Dykes, Anna-Karin

2009-08-01

to evaluate dimensions of both parents' postnatal sense of security the first week after childbirth, and to determine associations between the PPSS instrument and different sociodemographic and situational background variables. evaluative, cross-sectional design. 113 mothers and 99 fathers with children live born at term, from five hospitals in southern Sweden. mothers and fathers had similar feelings concerning postnatal sense of security. Of the dimensions in the PPSS instrument, a sense of midwives'/nurses' empowering behaviour, a sense of one's own general well-being and a sense of the mother's well-being as experienced by the father were the most important dimensions for parents' experienced security. A sense of affinity within the family (for both parents) and a sense of manageable breast feeding (for mothers) were not significantly associated with their experienced security. A sense of participation during pregnancy and general anxiety were significantly associated background variables for postnatal sense of security for both parents. For the mothers, parity and a sense that the father was participating during pregnancy were also significantly associated. more focus on parents' participation during pregnancy as well as midwives'/nurses' empowering behaviour during the postnatal period will be beneficial for both parents' postnatal sense of security.

Importance and use of correlational research.

PubMed

Curtis, Elizabeth A; Comiskey, Catherine; Dempsey, Orla

2016-07-01

The importance of correlational research has been reported in the literature yet few research texts discuss design in any detail. To discuss important issues and considerations in correlational research, and suggest ways to avert potential problems during the preparation and application of the design. This article targets the gap identified in the literature regarding correlational research design. Specifically, it discusses the importance and purpose of correlational research, its application, analysis and interpretation with contextualisations to nursing and health research. Findings from correlational research can be used to determine prevalence and relationships among variables, and to forecast events from current data and knowledge. In spite of its many uses, prudence is required when using the methodology and analysing data. To assist researchers in reducing mistakes, important issues are singled out for discussion and several options put forward for analysing data. Correlational research is widely used and this paper should be particularly useful for novice nurse researchers. Furthermore, findings generated from correlational research can be used, for example, to inform decision-making, and to improve or initiate health-related activities or change.

Robust Machine Learning Variable Importance Analyses of Medical Conditions for Health Care Spending.

PubMed

Rose, Sherri

2018-03-11

To propose nonparametric double robust machine learning in variable importance analyses of medical conditions for health spending. 2011-2012 Truven MarketScan database. I evaluate how much more, on average, commercially insured enrollees with each of 26 of the most prevalent medical conditions cost per year after controlling for demographics and other medical conditions. This is accomplished within the nonparametric targeted learning framework, which incorporates ensemble machine learning. Previous literature studying the impact of medical conditions on health care spending has almost exclusively focused on parametric risk adjustment; thus, I compare my approach to parametric regression. My results demonstrate that multiple sclerosis, congestive heart failure, severe cancers, major depression and bipolar disorders, and chronic hepatitis are the most costly medical conditions on average per individual. These findings differed from those obtained using parametric regression. The literature may be underestimating the spending contributions of several medical conditions, which is a potentially critical oversight. If current methods are not capturing the true incremental effect of medical conditions, undesirable incentives related to care may remain. Further work is needed to directly study these issues in the context of federal formulas. © Health Research and Educational Trust.

Predictor variables of clergy pedophiles.

PubMed

Ruzicka, M F

1997-10-01

File data on familial traits, past sexual experience as a victim, and other traits identified in the literature as leading toward pedophilia, were summarized for 10 convicted clergy pedophiles to construct a set of variables possibly useful for screening. Further research is underway to identify trauma in early life and those personality-related variables current studies indicate as relevant.

Infrastructure features outperform environmental variables explaining rabbit abundance around motorways.

PubMed

Planillo, Aimara; Malo, Juan E

2018-01-01

Human disturbance is widespread across landscapes in the form of roads that alter wildlife populations. Knowing which road features are responsible for the species response and their relevance in comparison with environmental variables will provide useful information for effective conservation measures. We sampled relative abundance of European rabbits, a very widespread species, in motorway verges at regional scale, in an area with large variability in environmental and infrastructure conditions. Environmental variables included vegetation structure, plant productivity, distance to water sources, and altitude. Infrastructure characteristics were the type of vegetation in verges, verge width, traffic volume, and the presence of embankments. We performed a variance partitioning analysis to determine the relative importance of two sets of variables on rabbit abundance. Additionally, we identified the most important variables and their effects model averaging after model selection by AICc on hypothesis-based models. As a group, infrastructure features explained four times more variability in rabbit abundance than environmental variables, being the effects of the former critical in motorway stretches located in altered landscapes with no available habitat for rabbits, such as agricultural fields. Model selection and Akaike weights showed that verge width and traffic volume are the most important variables explaining rabbit abundance index, with positive and negative effects, respectively. In the light of these results, the response of species to the infrastructure can be modulated through the modification of motorway features, being some of them manageable in the design phase. The identification of such features leads to suggestions for improvement through low-cost corrective measures and conservation plans. As a general indication, keeping motorway verges less than 10 m wide will prevent high densities of rabbits and avoid the unwanted effects that rabbit populations

FIRE: an SPSS program for variable selection in multiple linear regression analysis via the relative importance of predictors.

PubMed

Lorenzo-Seva, Urbano; Ferrando, Pere J

2011-03-01

We provide an SPSS program that implements currently recommended techniques and recent developments for selecting variables in multiple linear regression analysis via the relative importance of predictors. The approach consists of: (1) optimally splitting the data for cross-validation, (2) selecting the final set of predictors to be retained in the equation regression, and (3) assessing the behavior of the chosen model using standard indices and procedures. The SPSS syntax, a short manual, and data files related to this article are available as supplemental materials from brm.psychonomic-journals.org/content/supplemental.

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

The brain map of gait variability in aging, cognitive impairment and dementia. A systematic review

PubMed Central

Tian, Qu; Chastan, Nathalie; Bair, Woei-Nan; Resnick, Susan M.; Ferrucci, Luigi; Studenski, Stephanie A.

2017-01-01

While gait variability may reflect subtle changes due to aging or cognitive impairment (CI), associated brain characteristics remain unclear. We summarize structural and functional neuroimaging findings associated with gait variability in older adults with and without CI and dementia. We identified 17 eligible studies; all were cross-sectional; few examined multiple brain areas. In older adults, temporal gait variability was associated with structural differences in medial areas important for lower limb coordination and balance. Both temporal and spatial gait variability were associated with structural and functional differences in hippocampus and primary sensorimotor cortex and structural differences in anterior cingulate cortex, basal ganglia, association tracts, and posterior thalamic radiation. In CI or dementia, some associations were found in primary motor cortex, hippocampus, prefrontal cortex and basal ganglia. In older adults, gait variability may be associated with areas important for sensorimotor integration and coordination. To comprehend the neural basis of gait variability with aging and CI, longitudinal studies of multiple brain areas are needed. PMID:28115194

A network-based approach for semi-quantitative knowledge mining and its application to yield variability

NASA Astrophysics Data System (ADS)

Schauberger, Bernhard; Rolinski, Susanne; Müller, Christoph

2016-12-01

Variability of crop yields is detrimental for food security. Under climate change its amplitude is likely to increase, thus it is essential to understand the underlying causes and mechanisms. Crop models are the primary tool to project future changes in crop yields under climate change. A systematic overview of drivers and mechanisms of crop yield variability (YV) can thus inform crop model development and facilitate improved understanding of climate change impacts on crop yields. Yet there is a vast body of literature on crop physiology and YV, which makes a prioritization of mechanisms for implementation in models challenging. Therefore this paper takes on a novel approach to systematically mine and organize existing knowledge from the literature. The aim is to identify important mechanisms lacking in models, which can help to set priorities in model improvement. We structure knowledge from the literature in a semi-quantitative network. This network consists of complex interactions between growing conditions, plant physiology and crop yield. We utilize the resulting network structure to assign relative importance to causes of YV and related plant physiological processes. As expected, our findings confirm existing knowledge, in particular on the dominant role of temperature and precipitation, but also highlight other important drivers of YV. More importantly, our method allows for identifying the relevant physiological processes that transmit variability in growing conditions to variability in yield. We can identify explicit targets for the improvement of crop models. The network can additionally guide model development by outlining complex interactions between processes and by easily retrieving quantitative information for each of the 350 interactions. We show the validity of our network method as a structured, consistent and scalable dictionary of literature. The method can easily be applied to many other research fields.

Lipoprotein(a): Biology and Clinical Importance

PubMed Central

McCormick, Sally P A

2004-01-01

Lipoprotein(a) [Lp(a)] is a unique lipoprotein that has emerged as an independent risk factor for developing vascular disease. Plasma Lp(a) levels above the common cut-off level of 300 mg/L place individuals at risk of developing heart disease particularly if combined with other lipid and thrombogenic risk factors. Studies in humans have shown Lp(a) levels to be hugely variable and under strict genetic control, largely by the apolipoprotein(a) [apo(a)] gene. In general, Lp(a) levels have proven difficult to manipulate, although some factors have been identified that can influence levels. Research has shown that Lp(a) has a high affinity for the arterial wall and displays many athero-thrombogenic properties. While a definite function for Lp(a) has not been identified, the last two decades of research have provided much information on the biology and clinical importance of Lp(a). PMID:18516206

Nutrition as an important mediator of the impact of background variables on outcome in middle childhood

PubMed Central

Kitsao-Wekulo, Patricia; Holding, Penny; Taylor, H. Gerry; Abubakar, Amina; Kvalsvig, Jane; Connolly, Kevin

2013-01-01

Adequate nutrition is fundamental to the development of a child's full potential. However, the extent to which malnutrition affects developmental and cognitive outcomes in the midst of co-occurring risk factors remains largely understudied. We sought to establish if the effects of nutritional status varied according to diverse background characteristics as well as to compare the relative strength of the effects of poor nutritional status on language skills, motor abilities, and cognitive functioning at school age. This cross-sectional study was conducted among school-age boys and girls resident in Kilifi District in Kenya. We hypothesized that the effects of area of residence, school attendance, household wealth, age and gender on child outcomes are experienced directly and indirectly through child nutritional status. The use of structural equation modeling (SEM) allowed the disaggregation of the total effect of the explanatory variables into direct effects (effects that go directly from one variable to another) and indirect effects. Each of the models tested for the four child outcomes had a good fit. However, the effects on verbal memory apart from being weaker than for the other outcomes, were not mediated through nutritional status. School attendance was the most influential predictor of nutritional status and child outcomes. The estimated models demonstrated the continued importance of child nutritional status at school-age. PMID:24298246

Identifying recycled ash in basaltic eruptions

PubMed Central

D'Oriano, Claudia; Bertagnini, Antonella; Cioni, Raffaello; Pompilio, Massimo

2014-01-01

Deposits of mid-intensity basaltic explosive eruptions are characterized by the coexistence of different types of juvenile clasts, which show a large variability of external properties and texture, reflecting alternatively the effects of primary processes related to magma storage or ascent, or of syn-eruptive modifications occurred during or immediately after their ejection. If fragments fall back within the crater area before being re-ejected during the ensuing activity, they are subject to thermally- and chemically-induced alterations. These ‘recycled' clasts can be considered as cognate lithic for the eruption/explosion they derive. Their exact identification has consequences for a correct interpretation of eruption dynamics, with important implications for hazard assessment. On ash erupted during selected basaltic eruptions (at Stromboli, Etna, Vesuvius, Gaua-Vanuatu), we have identified a set of characteristics that can be associated with the occurrence of intra-crater recycling processes, based also on the comparison with results of reheating experiments performed on primary juvenile material, at variable temperature and under different redox conditions. PMID:25069064

Limitations of variable number of tandem repeat typing identified through whole genome sequencing of Mycobacterium avium subsp. paratuberculosis on a national and herd level.

PubMed

Ahlstrom, Christina; Barkema, Herman W; Stevenson, Karen; Zadoks, Ruth N; Biek, Roman; Kao, Rowland; Trewby, Hannah; Haupstein, Deb; Kelton, David F; Fecteau, Gilles; Labrecque, Olivia; Keefe, Greg P; McKenna, Shawn L B; De Buck, Jeroen

2015-03-08

Mycobacterium avium subsp. paratuberculosis (MAP), the causative bacterium of Johne's disease in dairy cattle, is widespread in the Canadian dairy industry and has significant economic and animal welfare implications. An understanding of the population dynamics of MAP can be used to identify introduction events, improve control efforts and target transmission pathways, although this requires an adequate understanding of MAP diversity and distribution between herds and across the country. Whole genome sequencing (WGS) offers a detailed assessment of the SNP-level diversity and genetic relationship of isolates, whereas several molecular typing techniques used to investigate the molecular epidemiology of MAP, such as variable number of tandem repeat (VNTR) typing, target relatively unstable repetitive elements in the genome that may be too unpredictable to draw accurate conclusions. The objective of this study was to evaluate the diversity of bovine MAP isolates in Canadian dairy herds using WGS and then determine if VNTR typing can distinguish truly related and unrelated isolates. Phylogenetic analysis based on 3,039 SNPs identified through WGS of 124 MAP isolates identified eight genetically distinct subtypes in dairy herds from seven Canadian provinces, with the dominant type including over 80% of MAP isolates. VNTR typing of 527 MAP isolates identified 12 types, including "bison type" isolates, from seven different herds. At a national level, MAP isolates differed from each other by 1-2 to 239-240 SNPs, regardless of whether they belonged to the same or different VNTR types. A herd-level analysis of MAP isolates demonstrated that VNTR typing may both over-estimate and under-estimate the relatedness of MAP isolates found within a single herd. The presence of multiple MAP subtypes in Canada suggests multiple introductions into the country including what has now become one dominant type, an important finding for Johne's disease control. VNTR typing often failed to

Identifying the interferences of irrigation on evapotranspiration variability over the Northern High Plains

NASA Astrophysics Data System (ADS)

Zeng, R.; Cai, X.

2016-12-01

Irrigation has considerably interfered with hydrological processes in arid and semi-arid areas with heavy irrigated agriculture. With the increasing demand for food production and evaporative demand due to climate change, irrigation water consumption is expected to increase, which would aggravate the interferences to hydrologic processes. Current studies focus on the impact of irrigation on the mean value of evapotranspiration (ET) at either local or regional scale, however, how irrigation changes the variability of ET has not been well understood. This study analyzes the impact of extensive irrigation on ET variability in the Northern High Plains. We apply an ET variance decomposition framework developed from our previous work to quantify the effects of both climate and irrigation on ET variance in the Northern High Plains watersheds. Based on climate and water table observations, we assess the monthly ET variance and its components for two periods: 1930s-1960s with less irrigation development 970s-2010s with more development. It is found that irrigation not only caused the well-recognized groundwater drawdown and stream depletion problems in the region, but also buffered ET variance from climatic fluctuations. In addition to increasing food productivity, irrigation also stabilizes crop yield by mitigating the impact of hydroclimatic variability. With complementary water supply from irrigation, ET often approaches to the potential ET, and thus the observed ET variance is more attributed to climatic variables especially temperature; meanwhile irrigation causes significant seasonal fluctuations to groundwater storage. For sustainable water resources management in the Northern High Plains, we argue that both the mean value and the variance of ET should be considered together for the regulation of irrigation in this region.

Identifying the needs of elderly, hearing-impaired persons: the importance and utility of hearing aid attributes.

PubMed

Meister, Hartmut; Lausberg, Isabel; Kiessling, Juergen; von Wedel, Hasso; Walger, Martin

2002-11-01

Older patients represent the majority of hearing-aid users. The needs of elderly, hearing-impaired subjects are not entirely identified. The present study aims to determine the importance of fundamental hearing-aid attributes and to elicit the utility of associated hypothetical hearing aids for older patients. This was achieved using a questionnaire-based conjoint analysis--a decompositional approach to preference measurement offering a realistic study design. A random sample of 200 experienced hearing-aid users participated in the study. Though three out of the six examined attributes revealed age-related dependencies, the only significant effect was found for the attribute "handling", which was considerably more important for older than younger hearing-aid users. A trend of decreasing importance of speech intelligibility in noise and increasing significance of speech in quiet was observed for subjects older than 70 years. In general, the utility of various hypothetical hearing aids was similar for older and younger subjects. Apart from the attribute "handling", older and younger subjects have comparable needs regarding hearing-aid features. On the basis of the examined attributes, there is no requirement for hearing aids designed specifically for elderly hearing-aid users, provided that ergonomic features are considered and the benefits of modern technology are made fully available for older patients.

Inter Annual Variability of the Acoustic Propagation in the Yellow Sea Identified from a Synoptic Monthly Gridded Database as Compared with GDEM

DTIC Science & Technology

2016-09-01

the world climate is in fact warming due to anthropogenic causes (Anderegg et al. 2010; Solomon et al. 2009). To put this in terms for this research ...2006). The present research uses a 0.5’ resolution. B. SEDIMENTS DATABASE There are four openly available sediment databases: Enhanced, Standard...DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) This research investigates the inter-annual acoustic variability in the Yellow Sea identified from

A multivariate and stochastic approach to identify key variables to rank dairy farms on profitability.

PubMed

Atzori, A S; Tedeschi, L O; Cannas, A

2013-05-01

The economic efficiency of dairy farms is the main goal of farmers. The objective of this work was to use routinely available information at the dairy farm level to develop an index of profitability to rank dairy farms and to assist the decision-making process of farmers to increase the economic efficiency of the entire system. A stochastic modeling approach was used to study the relationships between inputs and profitability (i.e., income over feed cost; IOFC) of dairy cattle farms. The IOFC was calculated as: milk revenue + value of male calves + culling revenue - herd feed costs. Two databases were created. The first one was a development database, which was created from technical and economic variables collected in 135 dairy farms. The second one was a synthetic database (sDB) created from 5,000 synthetic dairy farms using the Monte Carlo technique and based on the characteristics of the development database data. The sDB was used to develop a ranking index as follows: (1) principal component analysis (PCA), excluding IOFC, was used to identify principal components (sPC); and (2) coefficient estimates of a multiple regression of the IOFC on the sPC were obtained. Then, the eigenvectors of the sPC were used to compute the principal component values for the original 135 dairy farms that were used with the multiple regression coefficient estimates to predict IOFC (dRI; ranking index from development database). The dRI was used to rank the original 135 dairy farms. The PCA explained 77.6% of the sDB variability and 4 sPC were selected. The sPC were associated with herd profile, milk quality and payment, poor management, and reproduction based on the significant variables of the sPC. The mean IOFC in the sDB was 0.1377 ± 0.0162 euros per liter of milk (€/L). The dRI explained 81% of the variability of the IOFC calculated for the 135 original farms. When the number of farms below and above 1 standard deviation (SD) of the dRI were calculated, we found that 21

Environmental Controls on Multi-Scale Soil Nutrient Variability in the Tropics: the Importance of Land-Cover Change

NASA Astrophysics Data System (ADS)

Holmes, K. W.; Kyriakidis, P. C.; Chadwick, O. A.; Matricardi, E.; Soares, J. V.; Roberts, D. A.

2003-12-01

The natural controls on soil variability and the spatial scales at which correlation exists among soil and environmental variables are critical information for evaluating the effects of deforestation. We detect different spatial scales of variability in soil nutrient levels over a large region (hundreds of thousands of km2) in the Amazon, analyze correlations among soil properties at these different scales, and evaluate scale-specific relationships among soil properties and the factors potentially driving soil development. Statistical relationships among physical drivers of soil formation, namely geology, precipitation, terrain attributes, classified soil types, and land cover derived from remote sensing, were included to determine which factors are related to soil biogeochemistry at each spatial scale. Surface and subsurface soil profile data from a 3000 sample database collected in Rond“nia, Brazil, were used to investigate patterns in pH, phosphorus, nitrogen, organic carbon, effective cation exchange capacity, calcium, magnesium, potassium, aluminum, sand, and clay in this environment grading from closed canopy tropical forest to savanna. We focus on pH in this presentation for simplicity, because pH is the single most important soil characteristic for determining the chemical environment of higher plants and soil microbial activity. We determined four spatial scales which characterize integrated patterns of soil chemistry: less than 3 km; 3 to 10 km; 10 to 68 km; and from 68 to 550 km (extent of study area). Although the finest observable scale was fixed by the field sampling density, the coarser scales were determined from relationships in the data through coregionalization modeling, rather than being imposed by the researcher. Processes which affect soils over short distances, such as land cover and terrain attributes, were good predictors of fine scale spatial components of nutrients; processes which affect soils over very large distances, such as

Systematic reviews identify important methodological flaws in stroke rehabilitation therapy primary studies: review of reviews.

PubMed

Santaguida, Pasqualina; Oremus, Mark; Walker, Kathryn; Wishart, Laurie R; Siegel, Karen Lohmann; Raina, Parminder

2012-04-01

A "review of reviews" was undertaken to assess methodological issues in studies evaluating nondrug rehabilitation interventions in stroke patients. MEDLINE, CINAHL, PsycINFO, and the Cochrane Database of Systematic Reviews were searched from January 2000 to January 2008 within the stroke rehabilitation setting. Electronic searches were supplemented by reviews of reference lists and citations identified by experts. Eligible studies were systematic reviews; excluded citations were narrative reviews or reviews of reviews. Review characteristics and criteria for assessing methodological quality of primary studies within them were extracted. The search yielded 949 English-language citations. We included a final set of 38 systematic reviews. Cochrane reviews, which have a standardized methodology, were generally of higher methodological quality than non-Cochrane reviews. Most systematic reviews used standardized quality assessment criteria for primary studies, but not all were comprehensive. Reviews showed that primary studies had problems with randomization, allocation concealment, and blinding. Baseline comparability, adverse events, and co-intervention or contamination were not consistently assessed. Blinding of patients and providers was often not feasible and was not evaluated as a source of bias. The eligible systematic reviews identified important methodological flaws in the evaluated primary studies, suggesting the need for improvement of research methods and reporting. Copyright © 2012 Elsevier Inc. All rights reserved.

Using high-frequency sensors to identify hydroclimatological controls on storm-event variability in catchment nutrient fluxes and source zone activation

NASA Astrophysics Data System (ADS)

Blaen, Phillip; Khamis, Kieran; Lloyd, Charlotte; Krause, Stefan

2017-04-01

At the river catchment scale, storm events can drive highly variable behaviour in nutrient and water fluxes, yet short-term dynamics are frequently missed by low resolution sampling regimes. In addition, nutrient source contributions can vary significantly within and between storm events. Our inability to identify and characterise time dynamic source zone contributions severely hampers the adequate design of land use management practices in order to control nutrient exports from agricultural landscapes. Here, we utilise an 8-month high-frequency (hourly) time series of streamflow, nitrate concentration (NO3) and fluorescent dissolved organic matter concentration (FDOM) derived from optical in-situ sensors located in a headwater agricultural catchment. We characterised variability in flow and nutrient dynamics across 29 storm events. Storm events represented 31% of the time series and contributed disproportionately to nutrient loads (43% of NO3 and 36% of CDOM) relative to their duration. Principal components analysis of potential hydroclimatological controls on nutrient fluxes demonstrated that a small number of components, representing >90% of variance in the dataset, were highly significant model predictors of inter-event variability in catchment nutrient export. Hysteresis analysis of nutrient concentration-discharge relationships suggested spatially discrete source zones existed for NO3 and FDOM, and that activation of these zones varied on an event-specific basis. Our results highlight the benefits of high-frequency in-situ monitoring for characterising complex short-term nutrient dynamics and unravelling connections between hydroclimatological variability and river nutrient export and source zone activation under extreme flow conditions. These new process-based insights are fundamental to underpinning the development of targeted management measures to reduce nutrient loading of surface waters.

Clustering and variable selection in the presence of mixed variable types and missing data.

PubMed

Storlie, C B; Myers, S M; Katusic, S K; Weaver, A L; Voigt, R G; Croarkin, P E; Stoeckel, R E; Port, J D

2018-05-17

We consider the problem of model-based clustering in the presence of many correlated, mixed continuous, and discrete variables, some of which may have missing values. Discrete variables are treated with a latent continuous variable approach, and the Dirichlet process is used to construct a mixture model with an unknown number of components. Variable selection is also performed to identify the variables that are most influential for determining cluster membership. The work is motivated by the need to cluster patients thought to potentially have autism spectrum disorder on the basis of many cognitive and/or behavioral test scores. There are a modest number of patients (486) in the data set along with many (55) test score variables (many of which are discrete valued and/or missing). The goal of the work is to (1) cluster these patients into similar groups to help identify those with similar clinical presentation and (2) identify a sparse subset of tests that inform the clusters in order to eliminate unnecessary testing. The proposed approach compares very favorably with other methods via simulation of problems of this type. The results of the autism spectrum disorder analysis suggested 3 clusters to be most likely, while only 4 test scores had high (>0.5) posterior probability of being informative. This will result in much more efficient and informative testing. The need to cluster observations on the basis of many correlated, continuous/discrete variables with missing values is a common problem in the health sciences as well as in many other disciplines. Copyright © 2018 John Wiley & Sons, Ltd.

Tree-ring based reconstruction of spring hydroclimate variability in the Caucasus

NASA Astrophysics Data System (ADS)

Martin-Benito, Dario; Köse, Nesibe; Güner, Tuncay; Pederson, Neil

2015-04-01

The Caucasus region has been identified as one of the most prominent biodiversity hotspots in the world. The region experiences recurrent droughts that not only affect natural vegetation but also the agriculturally-based economies in the Caucasus. Across northeastern Turkey and the Caucasus region, instrumental records providing information on climate variability are generally scarce. Thus the magnitude and frequency of past droughts in this biologically important region are less known. Additionally, despite the increase of climate reconstructions in the past decades for many parts of Europe and Asia, relatively little work has been done to understand hydroclimate variability in the Caucasus region. Nearly all efforts in the region have focused on the Mediterranean part of Turkey and the Middle East region. We developed new tree-ring width chronologies from different elevation sites in northeastern Turkey with the goal to reconstruct annually-resolved estimates of temperature and hydroclimate across the region. We developed the first reconstruction of spring hydroclimate variability for the Caucasus and the southeastern Black Sea Region since 1750 CE using a nested procedure. Despite the high mean annual precipitation in the region, our reconstruction accounted for over 45% of May-June precipitation variability from 1925 to 2006. We observed no evidence of a decrease in spring precipitation during the recent decades. However, we do see a decrease in precipitation variability over the last 75 years with respect to previous periods that, at this time, does not appear to be related to sample replication. Although our reconstructed precipitation shows important similarities with previous work from Mediterranean and northern Turkey, we find distinct drought periods are also evident suggesting a wider range of climate dynamics in the broader Black Sea region than what has been previously identified. Distinct episodes of drought at the larger scales could have important

Identifying Demographic Variables Influencing the Nature of Science (NOS) Conceptions of Teachers

ERIC Educational Resources Information Center

Karaman, Ayhan

2017-01-01

In this survey research study, the views of practicing teachers in select aspects of NOS were investigated in connection with the effects of several variables (teaching discipline, gender, education level, teaching experience and regional work location). The instrument used to collect data was an adapted version of "Scientific Epistemological…

The importance of stochasticity and internal variability in geomorphic erosion system

NASA Astrophysics Data System (ADS)

Kim, J.; Ivanov, V. Y.; Fatichi, S.

2016-12-01

Understanding soil erosion is essential for a range of studies but the predictive skill of prognostic models and reliability of national-scale assessments have been repeatedly questioned. Indeed, data from multiple environments indicate that fluvial soil loss is highly non-unique and its frequency distributions exhibit heavy tails. We reveal that these features are attributed to the high sensitivity of erosion response to micro-scale variations of soil erodibility - `geomorphic internal variability'. The latter acts as an intermediary between forcing and erosion dynamics, augmenting the conventionally emphasized effects of `external variability' (climate, topography, land use, management form). Furthermore, we observe a reduction of erosion non-uniqueness at larger temporal scales that correlates with environment stochasticity. Our analysis shows that this effect can be attributed to the larger likelihood of alternating characteristic regimes of sediment dynamics. The corollary of this study is that the glaring gap - the inherently large uncertainties and the fallacy of representativeness of central tendencies - must be conceded in soil loss assessments. Acknowledgement: This research was supported by a grant (16AWMP-B083066-03) from Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government, and by the faculty research fund of Sejong University in 2016.

Forced Expiratory Volume in 1 Second Variability Helps Identify Patients with Cystic Fibrosis at Risk of Greater Loss of Lung Function.

PubMed

Morgan, Wayne J; VanDevanter, Donald R; Pasta, David J; Foreman, Aimee J; Wagener, Jeffrey S; Konstan, Michael W

2016-02-01

To evaluate several alternative measures of forced expiratory volume in 1 second percent predicted (FEV1 %pred) variability as potential predictors of future FEV1 %pred decline in patients with cystic fibrosis. We included 13,827 patients age ≥6 years from the Epidemiologic Study of Cystic Fibrosis 1994-2002 with ≥4 FEV1 %pred measurements spanning ≥366 days in both a 2-year baseline period and a 2-year follow-up period. We predicted change from best baseline FEV1 %pred to best follow-up FEV1 %pred and change from baseline to best in the second follow-up year by using multivariable regression stratified by 4 lung-disease stages. We assessed 5 measures of variability (some as deviations from the best and some as deviations from the trend line) both alone and after controlling for demographic and clinical factors and for the slope and level of FEV1 %pred. All 5 measures of FEV1 %pred variability were predictive, but the strongest predictor was median deviation from the best FEV1 %pred in the baseline period. The contribution to explanatory power (R(2)) was substantial and exceeded the total contribution of all other factors excluding the FEV1 %pred rate of decline. Adding the other variability measures provided minimal additional value. Median deviation from the best FEV1 %pred is a simple metric that markedly improves prediction of FEV1 %pred decline even after the inclusion of demographic and clinical characteristics and the FEV1 %pred rate of decline. The routine calculation of this variability measure could allow clinicians to better identify patients at risk and therefore in need of increased intervention. Copyright © 2016 Elsevier Inc. All rights reserved.

Identifying important comorbidity among cancer populations using administrative data: Prevalence and impact on survival.

PubMed

Sarfati, Diana; Gurney, Jason; Lim, Bee Teng; Bagheri, Nasser; Simpson, Andrew; Koea, Jonathan; Dennett, Elizabeth

2016-03-01

Our study sought to optimize the identification and investigate the impact of comorbidity in cancer patients using routinely collected hospitalization data. We undertook an iterative process of classification of important clinical conditions involving evaluation of relevant literature and consultation with clinicians. Patients diagnosed with colon, rectal, breast, ovarian, uterine, stomach, liver, renal or bladder cancers (n = 14,096) between 2006 and 2008 were identified from the New Zealand Cancer Registry. Conditions were identified using data on diagnoses from hospital admissions for 5 years prior to cancer diagnosis. Patients were followed up until end of 2009 using routine mortality data. Prevalence estimates for each condition by site were calculated. All-cause mortality impact of common conditions was investigated using Cox regression models adjusted for age and stage at diagnosis. Patients with liver and stomach cancers tended to have higher comorbidity and those with breast cancer, lower comorbidity than other cancer patients. Of the 50 conditions, the most common were hypertension (prevalence 8.0-20.9%), cardiac conditions (2.1-13.5%) and diabetes with (2.3-13.3%) and without (2.9-12.9%) complications. Comorbidity was associated with higher all-cause mortality but the impact varied by condition and across cancer site, with impact less for cancers with poor prognoses. Conditions most consistently associated with adverse outcomes across all cancer sites were renal disease, coagulopathies and congestive heart failure. Comorbidity is highly prevalent in cancer populations, but prevalence and impact of conditions differ markedly by cancer type. © 2013 Wiley Publishing Asia Pty Ltd.

Predicting suicidal ideation in primary care: An approach to identify easily assessable key variables.

PubMed

Jordan, Pascal; Shedden-Mora, Meike C; Löwe, Bernd

To obtain predictors of suicidal ideation, which can also be used for an indirect assessment of suicidal ideation (SI). To create a classifier for SI based on variables of the Patient Health Questionnaire (PHQ) and sociodemographic variables, and to obtain an upper bound on the best possible performance of a predictor based on those variables. From a consecutive sample of 9025 primary care patients, 6805 eligible patients (60% female; mean age = 51.5 years) participated. Advanced methods of machine learning were used to derive the prediction equation. Various classifiers were applied and the area under the curve (AUC) was computed as a performance measure. Classifiers based on methods of machine learning outperformed ordinary regression methods and achieved AUCs around 0.87. The key variables in the prediction equation comprised four items - namely feelings of depression/hopelessness, low self-esteem, worrying, and severe sleep disturbances. The generalized anxiety disorder scale (GAD-7) and the somatic symptom subscale (PHQ-15) did not enhance prediction substantially. In predicting suicidal ideation researchers should refrain from using ordinary regression tools. The relevant information is primarily captured by the depression subscale and should be incorporated in a nonlinear model. For clinical practice, a classification tree using only four items of the whole PHQ may be advocated. Copyright © 2018 Elsevier Inc. All rights reserved.

Identifying demographic variables related to failed dental appointments in a university hospital-based residency program.

PubMed

Mathu-Muju, Kavita R; Li, Hsin-Fang; Hicks, James; Nash, David A; Kaplan, Alan; Bush, Heather M

2014-01-01

The objective of this study was to identify characteristics of pediatric patients who failed to keep the majority of their scheduled dental appointments in a pediatric dental clinic staffed by pediatric dental residents and faculty members. The electronic records of all patients appointed over a continuous 54 month period were analyzed. Appointment history and demographic variables were collected. The rate of failed appointments was calculated by dividing the number of failed appointments with the total number of appointments scheduled for the patient. There were 7,591 patients in the analyzable dataset scheduled with a total of 48,932 appointments. Factors associated with an increased rate of failed appointments included self-paying for dental care, having a resident versus a faculty member as the provider, rural residence, and adolescent aged patients. Multivariable regression models indicated self-paying patients had higher odds and rates of failed appointments than patients with Medicaid and private insurance. Access to care for children may be improved by increasing the availability of private and public insurance. The establishment of a dental home and its relationship to a child receiving continuous care in an institutional setting depends upon establishing a relationship with a specific dentist.

Application of classification-tree methods to identify nitrate sources in ground water

USGS Publications Warehouse

Spruill, T.B.; Showers, W.J.; Howe, S.S.

2002-01-01

A study was conducted to determine if nitrate sources in ground water (fertilizer on crops, fertilizer on golf courses, irrigation spray from hog (Sus scrofa) wastes, and leachate from poultry litter and septic systems) could be classified with 80% or greater success. Two statistical classification-tree models were devised from 48 water samples containing nitrate from five source categories. Model I was constructed by evaluating 32 variables and selecting four primary predictor variables (??15N, nitrate to ammonia ratio, sodium to potassium ratio, and zinc) to identify nitrate sources. A ??15N value of nitrate plus potassium 18.2 indicated inorganic or soil organic N. A nitrate to ammonia ratio 575 indicated nitrate from golf courses. A sodium to potassium ratio 3.2 indicated spray or poultry wastes. A value for zinc 2.8 indicated poultry wastes. Model 2 was devised by using all variables except ??15N. This model also included four variables (sodium plus potassium, nitrate to ammonia ratio, calcium to magnesium ratio, and sodium to potassium ratio) to distinguish categories. Both models were able to distinguish all five source categories with better than 80% overall success and with 71 to 100% success in individual categories using the learning samples. Seventeen water samples that were not used in model development were tested using Model 2 for three categories, and all were correctly classified. Classification-tree models show great potential in identifying sources of contamination and variables important in the source-identification process.

Sea Surface Salinity Variability from Simulations and Observations: Preparing for Aquarius

NASA Technical Reports Server (NTRS)

Jacob, S. Daniel; LeVine, David M.

2010-01-01

Oceanic fresh water transport has been shown to play an important role in the global hydrological cycle. Sea surface salinity (SSS) is representative of the surface fresh water fluxes and the upcoming Aquarius mission scheduled to be launched in December 2010 will provide excellent spatial and temporal SSS coverage to better estimate the net exchange. In most ocean general circulation models, SSS is relaxed to climatology to prevent model drift. While SST remains a well observed variable, relaxing to SST reduces the range of SSS variability in the simulations (Fig.1). The main objective of the present study is to simulate surface tracers using a primitive equation ocean model for multiple forcing data sets to identify and establish a baseline SSS variability. The simulated variability scales are compared to those from near-surface argo salinity measurements.

Variable Selection in the Presence of Missing Data: Imputation-based Methods.

PubMed

Zhao, Yize; Long, Qi

2017-01-01

Variable selection plays an essential role in regression analysis as it identifies important variables that associated with outcomes and is known to improve predictive accuracy of resulting models. Variable selection methods have been widely investigated for fully observed data. However, in the presence of missing data, methods for variable selection need to be carefully designed to account for missing data mechanisms and statistical techniques used for handling missing data. Since imputation is arguably the most popular method for handling missing data due to its ease of use, statistical methods for variable selection that are combined with imputation are of particular interest. These methods, valid used under the assumptions of missing at random (MAR) and missing completely at random (MCAR), largely fall into three general strategies. The first strategy applies existing variable selection methods to each imputed dataset and then combine variable selection results across all imputed datasets. The second strategy applies existing variable selection methods to stacked imputed datasets. The third variable selection strategy combines resampling techniques such as bootstrap with imputation. Despite recent advances, this area remains under-developed and offers fertile ground for further research.

A new process sensitivity index to identify important system processes under process model and parametric uncertainty

DOE PAGES

Dai, Heng; Ye, Ming; Walker, Anthony P.; ...

2017-03-28

A hydrological model consists of multiple process level submodels, and each submodel represents a process key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this study develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods withmore » variance-based global sensitivity analysis. A process sensitivity index is derived as a single summary measure of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and their parameters. Here, for demonstration, the new index is used to assign importance to the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that convert precipitation to recharge, and the geology process is simulated by two models of hydraulic conductivity. Each process model has its own random parameters. Finally, the new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less

A new process sensitivity index to identify important system processes under process model and parametric uncertainty

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

Dai, Heng; Ye, Ming; Walker, Anthony P.

A hydrological model consists of multiple process level submodels, and each submodel represents a process key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this study develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods withmore » variance-based global sensitivity analysis. A process sensitivity index is derived as a single summary measure of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and their parameters. Here, for demonstration, the new index is used to assign importance to the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that convert precipitation to recharge, and the geology process is simulated by two models of hydraulic conductivity. Each process model has its own random parameters. Finally, the new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less

Global sensitivity analysis for identifying important parameters of nitrogen nitrification and denitrification under model uncertainty and scenario uncertainty

NASA Astrophysics Data System (ADS)

Chen, Zhuowei; Shi, Liangsheng; Ye, Ming; Zhu, Yan; Yang, Jinzhong

2018-06-01

Nitrogen reactive transport modeling is subject to uncertainty in model parameters, structures, and scenarios. By using a new variance-based global sensitivity analysis method, this paper identifies important parameters for nitrogen reactive transport with simultaneous consideration of these three uncertainties. A combination of three scenarios of soil temperature and two scenarios of soil moisture creates a total of six scenarios. Four alternative models describing the effect of soil temperature and moisture content are used to evaluate the reduction functions used for calculating actual reaction rates. The results show that for nitrogen reactive transport problem, parameter importance varies substantially among different models and scenarios. Denitrification and nitrification process is sensitive to soil moisture content status rather than to the moisture function parameter. Nitrification process becomes more important at low moisture content and low temperature. However, the changing importance of nitrification activity with respect to temperature change highly relies on the selected model. Model-averaging is suggested to assess the nitrification (or denitrification) contribution by reducing the possible model error. Despite the introduction of biochemical heterogeneity or not, fairly consistent parameter importance rank is obtained in this study: optimal denitrification rate (Kden) is the most important parameter; reference temperature (Tr) is more important than temperature coefficient (Q10); empirical constant in moisture response function (m) is the least important one. Vertical distribution of soil moisture but not temperature plays predominant role controlling nitrogen reaction. This study provides insight into the nitrogen reactive transport modeling and demonstrates an effective strategy of selecting the important parameters when future temperature and soil moisture carry uncertainties or when modelers face with multiple ways of establishing nitrogen

BIOPHYSICAL CHARACTERISATION OF THE UNDER-APPRECIATED AND IMPORTANT RELATIONSHIP BETWEEN HEART RATE VARIABILITY AND HEART RATE

PubMed Central

Monfredi, Oliver; Lyashkov, Alexey E; Johnsen, Anne-Berit; Inada, Shin; Schneider, Heiko; Wang, Ruoxi; Nirmalan, Mahesh; Wisloff, Ulrik; Maltsev, Victor A; Lakatta, Edward G; Zhang, Henggui; Boyett, Mark R

2014-01-01

Heart rate variability (beat-to-beat changes in the RR interval) has attracted considerable attention over the last 30+ years (PubMed currently lists >17,000 publications). Clinically, a decrease in heart rate variability is correlated to higher morbidity and mortality in diverse conditions, from heart disease to foetal distress. It is usually attributed to fluctuation in cardiac autonomic nerve activity. We calculated heart rate variability parameters from a variety of cardiac preparations (including humans, living animals, Langendorff-perfused heart and single sinoatrial nodal cell) in diverse species, combining this with data from previously published papers. We show that regardless of conditions, there is a universal exponential decay-like relationship between heart rate variability and heart rate. Using two biophysical models, we develop a theory for this, and confirm that heart rate variability is primarily dependent on heart rate and cannot be used in any simple way to assess autonomic nerve activity to the heart. We suggest that the correlation between a change in heart rate variability and altered morbidity and mortality is substantially attributable to the concurrent change in heart rate. This calls for re-evaluation of the findings from many papers that have not adjusted properly or at all for heart rate differences when comparing heart rate variability in multiple circumstances. PMID:25225208

Prioritising the placement of riparian vegetation to reduce flood risk and end-of-catchment sediment yields: Important considerations in hydrologically-variable regions.

PubMed

Croke, Jacky; Thompson, Chris; Fryirs, Kirstie

2017-04-01

In perennial stream settings, there is abundant literature confirming that riparian vegetation affects flood hydrology by attenuating the flood wave, enhancing deposition and reducing bank erosion. In contrast, relatively little is known about the effectiveness of riparian vegetation during floods in hydrologically-variable regions. The dominant channel form in these settings is often referred to as a 'macrochannel' or compound channel-in-channel which displays multiple inundation surfaces where it is often difficult to identify the active channel bank and bank top. This study uses the inundation pattern of recent flood events in the Lockyer Valley of South East Queensland (SEQ), Australia to present a framework which specifically considers the interaction between inundation frequency and trapping potential on a range of inundation surfaces. Using hydrological modelling and a consistent definition of floodplains and within-channel features, it outlines five key priority areas for the placement of riparian vegetation to alleviate common flood problems within the catchment. The highest priority for the placement of riparian vegetation to ameliorate the effects of small-moderate floods is on within-channel benches. For out-of-macrochannel flows, riparian vegetation is most effective on genetic floodplains which occupy the largest spatial extent within the valley. In particular, it identifies the need for, and benefits of, revegetation in spill out zones (SOZ) which occur where upstream channel capacity is larger and flow is funnelled at high velocity onto the floodplain downstream. This study highlights the importance of understanding the key geomorphic processes occurring within a catchment and developing effective catchment management plans to suit these conditions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Principal component analysis of normalized full spectrum mass spectrometry data in multiMS-toolbox: An effective tool to identify important factors for classification of different metabolic patterns and bacterial strains.

PubMed

Cejnar, Pavel; Kuckova, Stepanka; Prochazka, Ales; Karamonova, Ludmila; Svobodova, Barbora

2018-06-15

Explorative statistical analysis of mass spectrometry data is still a time-consuming step. We analyzed critical factors for application of principal component analysis (PCA) in mass spectrometry and focused on two whole spectrum based normalization techniques and their application in the analysis of registered peak data and, in comparison, in full spectrum data analysis. We used this technique to identify different metabolic patterns in the bacterial culture of Cronobacter sakazakii, an important foodborne pathogen. Two software utilities, the ms-alone, a python-based utility for mass spectrometry data preprocessing and peak extraction, and the multiMS-toolbox, an R software tool for advanced peak registration and detailed explorative statistical analysis, were implemented. The bacterial culture of Cronobacter sakazakii was cultivated on Enterobacter sakazakii Isolation Agar, Blood Agar Base and Tryptone Soya Agar for 24 h and 48 h and applied by the smear method on an Autoflex speed MALDI-TOF mass spectrometer. For three tested cultivation media only two different metabolic patterns of Cronobacter sakazakii were identified using PCA applied on data normalized by two different normalization techniques. Results from matched peak data and subsequent detailed full spectrum analysis identified only two different metabolic patterns - a cultivation on Enterobacter sakazakii Isolation Agar showed significant differences to the cultivation on the other two tested media. The metabolic patterns for all tested cultivation media also proved the dependence on cultivation time. Both whole spectrum based normalization techniques together with the full spectrum PCA allow identification of important discriminative factors in experiments with several variable condition factors avoiding any problems with improper identification of peaks or emphasis on bellow threshold peak data. The amounts of processed data remain still manageable. Both implemented software utilities are available

Windthrow Variability in Central Amazonia

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

Negrón-Juárez, Robinson; Jenkins, Hillary; Raupp, Carlos

Windthrows are a recurrent disturbance in Amazonia and are an important driver of forest dynamics and carbon storage. In this study, we present for the first time the seasonal and interannual variability of windthrows, focusing on Central Amazonia, and discuss the potential meteorological factors associated with this variability. Landsat images over the 1998-2010 time period were used to detect the occurrence of windthrows, which were identified based on their spectral characteristics and shape. Here, we found that windthrows occurred every year but were more frequent between September and February. Organized convective activity associated with multicell storms embedded in mesoscale convectivemore » systems, such as northerly squall lines (that move from northeast to southwest) and southerly squall lines (that move from southwest to northeast) can cause windthrows. We also found that southerly squall lines occurred more frequently than their previously reported ~50 year interval. At the interannual scale, we did not find an association between El Niño-Southern Oscillation (ENSO) and windthrows.« less

Windthrow Variability in Central Amazonia

DOE PAGES

Negrón-Juárez, Robinson; Jenkins, Hillary; Raupp, Carlos; ...

2017-02-04

Windthrows are a recurrent disturbance in Amazonia and are an important driver of forest dynamics and carbon storage. In this study, we present for the first time the seasonal and interannual variability of windthrows, focusing on Central Amazonia, and discuss the potential meteorological factors associated with this variability. Landsat images over the 1998-2010 time period were used to detect the occurrence of windthrows, which were identified based on their spectral characteristics and shape. Here, we found that windthrows occurred every year but were more frequent between September and February. Organized convective activity associated with multicell storms embedded in mesoscale convectivemore » systems, such as northerly squall lines (that move from northeast to southwest) and southerly squall lines (that move from southwest to northeast) can cause windthrows. We also found that southerly squall lines occurred more frequently than their previously reported ~50 year interval. At the interannual scale, we did not find an association between El Niño-Southern Oscillation (ENSO) and windthrows.« less

Identifying specific beliefs to target to improve restaurant employees' intentions for performing three important food safety behaviors.

PubMed

Pilling, Valerie K; Brannon, Laura A; Shanklin, Carol W; Howells, Amber D; Roberts, Kevin R

2008-06-01

Current national food safety training programs appear ineffective at improving food safety practices in foodservice operations, given the substantial number of Americans affected by foodborne illnesses after eating in restaurants each year. The Theory of Planned Behavior (TpB) was used to identify important beliefs that may be targeted to improve foodservice employees' intentions for three food safety behaviors that have the most substantial affect on public health: hand washing, using thermometers, and proper handling of food contact surfaces. In a cross-sectional design, foodservice employees (n=190) across three midwestern states completed a survey assessing TpB components and knowledge for the three food safety behaviors. Multiple regression analyses were performed on the TpB components for each behavior. Independent-samples t tests identified TpB beliefs that discriminated between participants who absolutely intend to perform the behaviors and those with lower intention. Employees' attitudes were the one consistent predictor of intentions for performing all three behaviors. However, a unique combination of important predictors existed for each separate behavior. Interventions for improving employees' behavioral intentions for food safety should focus on TpB components that predict intentions for each behavior and should bring all employees' beliefs in line with those of the employees who already intend to perform the food safety behaviors. Registered dietitians; dietetic technicians, registered; and foodservice managers can use these results to enhance training sessions and motivational programs to improve employees' food safety behaviors. Results also assist these professionals in recognizing their responsibility for enforcing and providing adequate resources for proper food safety behaviors.

Variability in, variability out: best practice recommendations to standardize pre-analytical variables in the detection of circulating and tissue microRNAs.

PubMed

Khan, Jenna; Lieberman, Joshua A; Lockwood, Christina M

2017-05-01

microRNAs (miRNAs) hold promise as biomarkers for a variety of disease processes and for determining cell differentiation. These short RNA species are robust, survive harsh treatment and storage conditions and may be extracted from blood and tissue. Pre-analytical variables are critical confounders in the analysis of miRNAs: we elucidate these and identify best practices for minimizing sample variation in blood and tissue specimens. Pre-analytical variables addressed include patient-intrinsic variation, time and temperature from sample collection to storage or processing, processing methods, contamination by cells and blood components, RNA extraction method, normalization, and storage time/conditions. For circulating miRNAs, hemolysis and blood cell contamination significantly affect profiles; samples should be processed within 2 h of collection; ethylene diamine tetraacetic acid (EDTA) is preferred while heparin should be avoided; samples should be "double spun" or filtered; room temperature or 4 °C storage for up to 24 h is preferred; miRNAs are stable for at least 1 year at -20 °C or -80 °C. For tissue-based analysis, warm ischemic time should be <1 h; cold ischemic time (4 °C) <24 h; common fixative used for all specimens; formalin fix up to 72 h prior to processing; enrich for cells of interest; validate candidate biomarkers with in situ visualization. Most importantly, all specimen types should have standard and common workflows with careful documentation of relevant pre-analytical variables.

Imported Wines: Identifying and Removing Wines Contaminated with Diethylene Glycol.

DTIC Science & Technology

1986-03-01

at controlling health risks, BATF has used its labeling authority to prohibit the marketing of alcoholic beverages that are mislabeled by virtue of...or beverages contaminated with harmful substances into the U.S. market . DEG, a toxic substance, would be such a contaminant. The BATF’S authority in...representing a significant risk to health are identified and removed from k the market . BATF did not conduct a risk assessment or seek an assess- ment from

External forcing as a metronome for Atlantic multidecadal variability

NASA Astrophysics Data System (ADS)

Otterå, Odd Helge; Bentsen, Mats; Drange, Helge; Suo, Lingling

2010-10-01

Instrumental records, proxy data and climate modelling show that multidecadal variability is a dominant feature of North Atlantic sea-surface temperature variations, with potential impacts on regional climate. To understand the observed variability and to gauge any potential for climate predictions it is essential to identify the physical mechanisms that lead to this variability, and to explore the spatial and temporal characteristics of multidecadal variability modes. Here we use a coupled ocean-atmosphere general circulation model to show that the phasing of the multidecadal fluctuations in the North Atlantic during the past 600 years is, to a large degree, governed by changes in the external solar and volcanic forcings. We find that volcanoes play a particularly important part in the phasing of the multidecadal variability through their direct influence on tropical sea-surface temperatures, on the leading mode of northern-hemisphere atmosphere circulation and on the Atlantic thermohaline circulation. We suggest that the implications of our findings for decadal climate prediction are twofold: because volcanic eruptions cannot be predicted a decade in advance, longer-term climate predictability may prove challenging, whereas the systematic post-eruption changes in ocean and atmosphere may hold promise for shorter-term climate prediction.

Genomic Analyses Yield Markers for Identifying Agronomically Important Genes in Potato

USDA-ARS?s Scientific Manuscript database

This study explores the genetic architecture underling the potato evolution through a comprehensive assessment of wild and cultivated potato species based on the re-sequencing of 201 accessions of Solanum section Petota with >12 × genome coverage. We identified 450 domesticated genes, which showed e...

A Locus Encoding Variable Defense Systems against Invading DNA Identified in Streptococcus suis

PubMed Central

Okura, Masatoshi; Nozawa, Takashi; Watanabe, Takayasu; Murase, Kazunori; Nakagawa, Ichiro; Takamatsu, Daisuke; Osaki, Makoto; Sekizaki, Tsutomu; Gottschalk, Marcelo; Hamada, Shigeyuki

2017-01-01

Streptococcus suis, an important zoonotic pathogen, is known to have an open pan-genome and to develop a competent state. In S. suis, limited genetic lineages are suggested to be associated with zoonosis. However, little is known about the evolution of diversified lineages and their respective phenotypic or ecological characteristics. In this study, we performed comparative genome analyses of S. suis, with a focus on the competence genes, mobile genetic elements, and genetic elements related to various defense systems against exogenous DNAs (defense elements) that are associated with gene gain/loss/exchange mediated by horizontal DNA movements and their restrictions. Our genome analyses revealed a conserved competence-inducing peptide type (pherotype) of the competence system and large-scale genome rearrangements in certain clusters based on the genome phylogeny of 58 S. suis strains. Moreover, the profiles of the defense elements were similar or identical to each other among the strains belonging to the same genomic clusters. Our findings suggest that these genetic characteristics of each cluster might exert specific effects on the phenotypic or ecological differences between the clusters. We also found certain loci that shift several types of defense elements in S. suis. Of note, one of these loci is a previously unrecognized variable region in bacteria, at which strains of distinct clusters code for different and various defense elements. This locus might represent a novel defense mechanism that has evolved through an arms race between bacteria and invading DNAs, mediated by mobile genetic elements and genetic competence. PMID:28379509

Phenotypic variability in Patau syndrome.

PubMed

Caba, Lavinia; Rusu, Cristina; Butnariu, Lacramioara; Panzaru, Monica; Braha, Elena; Volosciuc, M; Popescu, Roxana; Gramescu, Mihaela; Bujoran, C; Martiniuc, Violeta; Covic, M; Gorduza, E V

2013-01-01

Patau syndrome has an incidence of 1/10.000-20.000, the clinical diagnosis being suggested by the triad cleft lip and palate, microphthalmia/anophthalmia and postaxial polydactyly. Most frequent cytogenetic abnormality is free and homogeneous trisomy 13 (80.0%), rarely being detected trisomy mosaics or Robertsonian translocations. The objective of the study was to identify phenotypic features of trisomy 13. The retrospective study was conducted on a trial group of 14 cases diagnosed cytogenetically with trisomy 13 between January 2000 and December 2012 at lasi Medical Genetics Centre. Of the 14 cases, 3 were evaluated pathologically (two aborted foetuses and one stillborn), 8 cases were detected in the neonatal period, and 3 in infancy. Clinical diagnosis was supported by the identification of a model of abnormal development, mainly characterized by: maxillary cleft (lip and palate--5 cases; lip--1 case), ocular abnormalities (microphthalmia/anophthalmia--7 cases; cyclopia--1 case), postaxial polydactyly (7 cases), scalp defects (6 cases), congenital heart anomalies (10 cases, 6 patients with atrial septal defect), complete holoprosencephaly (4 cases), ear abnormalities (11 cases), broad nasal root (10 cases). An important issue in confirming the phenotypic variability of Patau syndrome is that the classic clinical triad was identified only in one case. Patau syndrome is a disease with variable expression and is characterized by a pattern of abnormal prenatal development characterized by facial dysmorphia, polydactyly and severe birth defects (heart, brain) that generate an increased in utero and perinatal mortality.

Relative importance and interrelations between psychosocial factors and individualized quality of life of hemodialysis patients.

PubMed

Tovbin, David; Gidron, Yori; Jean, Tzipora; Granovsky, Ricardo; Schnieder, Alla

2003-09-01

Since quality of life (QOL) of hemodialysis (HD) patients is low and frequently difficult to improve by medical therapy, it is important to identify psychosocial correlates and life-domains important for HD patients' QOL. Our hypothesis was that psychosocial factors reflecting appraisal, external and internal resources/impediments correlate with QOL and compensate for adverse effects of disease-related variables on QOL. Forty-eight chronic HD-patients identified and rank-ordered life-domains important for QOL and rated their level of satisfaction with those domains. This was performed using a slightly modified version of the Self-Evaluated Individualized QOL (SEiQOL) Scale. Psychosocial factors included perceived-control (PC), social-support and hostility. Demographic and disease-related factors included age, gender, cardiovascular disease (CVD), diabetes, hematocrit, albumin and C-reactive protein. QOL was significantly correlated with PC (r = 0.65) and social-support (r = 0.38), and inversely correlated with hostility (r = -0.31), diabetes and hypoalbuminemia (all at least p < 0.05). PC mediated effects of certain variables (e.g., albumin, gender, hostility) and moderated effects of little social-support and hypoalbuminemia on QOL. Patients' most important QOL domains were health, with which satisfaction was lowest, followed by family, with which satisfaction was highest. Pending replication with larger samples, assessment and enhancement of PC may improve HD patients' QOL.

Drivers for spatial variability in agricultural soil organic carbon stocks in Germany

NASA Astrophysics Data System (ADS)

Vos, Cora; Don, Axel; Hobley, Eleanor; Prietz, Roland; Heidkamp, Arne; Freibauer, Annette

2017-04-01

Soil organic carbon is one of the largest components of the global carbon cycle. It has recently gained importance in global efforts to mitigate climate change through carbon sequestration. In order to find locations suitable for carbon sequestration, and estimate the sequestration potential, however, it is necessary to understand the factors influencing the high spatial variability of soil organic carbon stocks. Due to numerous interacting factors that influence its dynamics, soil organic carbon stocks are difficult to predict. In the course of the German Agricultural Soil Inventory over 2500 agricultural sites were sampled and their soil organic carbon stocks determined. Data relating to more than 200 potential drivers of SOC stocks were compiled from laboratory measurements, farmer questionnaires and climate stations. The aims of this study were to 1) give an overview of soil organic carbon stocks in Germany's agricultural soils, 2) to quantify and explain the influence of explanatory variables on soil organic carbon stocks. Two different machine learning algorithms were used to identify the most important variables and multiple regression models were used to explore the influence of those variables. Models for predicting carbon stocks in different depth increments between 0-100 cm were developed, explaining up to 62% (validation, 98% calibration) of total variance. Land-use, land-use history, clay content and electrical conductivity were main predictors in the topsoil, while bedrock material, relief and electrical conductivity governed the variability of subsoil carbon stocks. We found 32% of all soils to be deeply anthropogenically transformed. The influence of climate related variables was surprisingly small (≤5% of explained variance), while site variables explained a large share of soil carbon variability (46-100% of explained variance), in particular in the subsoil. Thus, the understanding of SOC dynamics at regional scale requires a thorough description

Short-term favorable weather conditions are an important control of interannual variability in carbon and water fluxes

Treesearch

Jakob Zscheischler; Simone Fatichi; Sebastian Wolf; Peter D. Blanken; Gil Bohrer; Ken Clark; Ankur R. Desai; David Hollinger; Trevor Keenan; Kimberly A. Novick; Sonia I. Seneviratne

2016-01-01

Ecosystem models often perform poorly in reproducing interannual variability in carbon and water fluxes, resulting in considerable uncertainty when estimating the land-carbon sink. While many aggregated variables (growing season length, seasonal precipitation, or temperature) have been suggested as predictors for interannual variability in carbon fluxes, their...

Cataclysmic Variable Stars

NASA Astrophysics Data System (ADS)

Hellier, Coel

2001-01-01

Cataclysmic variable stars are the most variable stars in the night sky, fluctuating in brightness continually on timescales from seconds to hours to weeks to years. The changes can be recorded using amateur telescopes, yet are also the subject of intensive study by professional astronomers. That study has led to an understanding of cataclysmic variables as binary stars, orbiting so closely that material transfers from one star to the other. The resulting process of accretion is one of the most important in astrophysics. This book presents the first account of cataclysmic variables at an introductory level. Assuming no previous knowledge of the field, it explains the basic principles underlying the variability, while providing an extensive compilation of cataclysmic variable light curves. Aimed at amateur astronomers, undergraduates, and researchers, the main text is accessible to those with no mathematical background, while supplementary boxes present technical details and equations.

A Detailed Survey of Pulsating Variables in Five Globular Clusters (Abstract)

NASA Astrophysics Data System (ADS)

Murphy, B. W.

2016-12-01

(Abstract only) Globular clusters are ideal laboratories for conducting a stellar census. Of particular interest are pulsating variables, which provide astronomers with a tool to probe the properties of the stars and the cluster. We observed each of five globular clusters hundreds to thousands of times over a time span ranging from 2 to 4 years in B, V, and I filters using the SARA 0.6-meter telescope located at Cerro Tololo Interamerican Observatory and the 0.9-meter telescope located at Kitt Peak, Arizona. The images were analyzed using difference image analysis to identify and produce light curves of all variables found in each cluster. In total we identified 377 variables with 140 of these being newly discovered increasing the number of known variables stars in these clusters by 60%. Of the total we have identified 319 RR Lyrae variables (193 RR0, 18 RR01, 101 RR1, 7 RR2), 9 SX Phe stars, 5 Cepheid variables, 11 eclipsing variables, and 33 long period variables. For IC4499 we identified 64 RR0, 18 RR01, 14 RR1, 4 RR2, 1 SX Phe, 1 eclipsing binary, and 2 long period variables. For NGC4833 we identified 10 RR0, 7 RR1, 3 RR2, 6 SX Phe, 5 eclipsing binaries, and 9 long period variables. For NGC6171 (M107) we identified 14 RR0, 7 RR1, and 1 SX Phe. For NGC6402 (M14) we identified 55 RR0, 57 RR1, 1 RR2, 1 SX Phe, 6 Cepheids, 1 eclipsing binary, and 15 long period variables. For NGC6584 we identified 50 RR0, 16 RR1, 4 eclipsing binaries, and 7 long period variables. From our extensive data set we were able to obtain sufficient temporal and complete phase coverage of the RR Lyrae variables. This has allowed us not only to properly classify each of the RR Lyrae variables but also to use Fourier decomposition of the B, V, and I light curves to further analyze the properties of the variable stars and hence the physical properties of each globular cluster.

Identifying selectively important amino acid positions associated with alternative habitat environments in fish mitochondrial genomes.

PubMed

Xia, Jun Hong; Li, Hong Lian; Zhang, Yong; Meng, Zi Ning; Lin, Hao Ran

2018-05-01

Fish species inhabitating seawater (SW) or freshwater (FW) habitats have to develop genetic adaptations to alternative environment factors, especially salinity. Functional consequences of the protein variations associated with habitat environments in fish mitochondrial genomes have not yet received much attention. We analyzed 829 complete fish mitochondrial genomes and compared the amino acid differences of 13 mitochondrial protein families between FW and SW fish groups. We identified 47 specificity determining sites (SDS) that associated with FW or SW environments from 12 mitochondrial protein families. Thirty-two (68%) of the SDS sites are hydrophobic, 13 (28%) are neutral, and the remaining sites are acidic or basic. Seven of those SDS from ND1, ND2 and ND5 were scored as probably damaging to the protein structures. Furthermore, phylogenetic tree based Bayes Empirical Bayes analysis also detected 63 positive sites associated with alternative habitat environments across ten mtDNA proteins. These signatures could be important for studying mitochondrial genetic variation relevant to fish physiology and ecology.

Energy Storage on the Grid and the Short-term Variability of Wind

NASA Astrophysics Data System (ADS)

Hittinger, Eric Stephen

Wind generation presents variability on every time scale, which must be accommodated by the electric grid. Limited quantities of wind power can be successfully integrated by the current generation and demand-side response mix but, as deployment of variable resources increases, the resulting variability becomes increasingly difficult and costly to mitigate. In Chapter 2, we model a co-located power generation/energy storage block composed of wind generation, a gas turbine, and fast-ramping energy storage. A scenario analysis identifies system configurations that can generate power with 30% of energy from wind, a variability of less than 0.5% of the desired power level, and an average cost around $70/MWh. While energy storage technologies have existed for decades, fast-ramping grid-level storage is still an immature industry and is experiencing relatively rapid improvements in performance and cost across a variety of technologies. Decreased capital cost, increased power capability, and increased efficiency all would improve the value of an energy storage technology and each has cost implications that vary by application, but there has not yet been an investigation of the marginal rate of technical substitution between storage properties. The analysis in chapter 3 uses engineering-economic models of four emerging fast-ramping energy storage technologies to determine which storage properties have the greatest effect on cost-of-service. We find that capital cost of storage is consistently important, and identify applications for which power/energy limitations are important. In some systems with a large amount of wind power, the costs of wind integration have become significant and market rules have been slowly changing in order to internalize or control the variability of wind generation. Chapter 4 examines several potential market strategies for mitigating the effects of wind variability and estimate the effect that each strategy would have on the operation and

Triangulating Principal Effectiveness: How Perspectives of Parents, Teachers, and Assistant Principals Identify the Central Importance of Managerial Skills. Working Paper 35

ERIC Educational Resources Information Center

Grissom, Jason A.; Loeb, Susanna

2009-01-01

While the importance of effective principals is undisputed, few studies have addressed what specific skills principals need to promote school success. This study draws on unique data combining survey responses from principals, assistant principals, teachers and parents with rich administrative data to identify which principal skills matter most…

Identifying driver characteristics influencing overtaking crashes.

PubMed

Mohaymany, Afshin Shariat; Kashani, Ali Tavakoli; Ranjbari, Andishe

2010-08-01

To identify the most important driver characteristics influencing crash-causing overtaking maneuvers on 2-lane, 2-way rural roads of Iran. Based on the crash data for rural roads of Iran over 3 years from 2006 to 2008, the classification and regression tree (CART) method combined with the quasi-induced exposure concept was applied for 4 independent variables and one target variable of "driver status" with 2 classes of at fault and not at fault. The independent variables were vehicle type, driver's age, driving license, and driving experience of the driver-the latter 2 driver characteristics are relatively new in traffic safety studies. According to the data set, 16,809 drivers were involved in 2-lane, 2-way rural roads overtaking crashes. The analysis revealed that drivers who are younger than 28 years old, whose driving license is type 2--a common driving license that is for driving with passenger car and light vehicles--and whose driving experience is less than 2 years are most probably responsible for overtaking crashes. It was indicated that vehicle type is the most important factor associated with drivers being responsible for the crashes. The results also revealed that younger drivers (18-28 years) are most likely to be at fault in overtaking crashes. Therefore, enforcement and education should be more concentrated on this age group. Due to the incompliant nature of this group, changing the type and amount of traffic fines is essential for more preventing objectives. The research also found 2 relatively new factors of driving license and driving experience to have considerable effects on drivers being at fault, such that type 2 licensed drivers are more responsible compared to type 1 (a driving license for driving with all motor vehicles, which has some age and experience requirements) licensed drivers or drivers with a special license (a driving license with special vehicle types). Moreover, drivers with less than 2 years' driving experience are more

Determining the spatial variability of crop yields of two different climatic regions in Southwest Germany

NASA Astrophysics Data System (ADS)

Eshonkulov, Ravshan; Poyda, Arne; Ingwersen, Joachim; Streck, Thilo

2017-04-01

Assessing the spatial variability of soil physical properties is crucial for agricultural land management. We determined the spatial variability within two agricultural fields in the regions of Kraichgau and Swabian Jura in Southwest Germany. We determined soil physical properties and recorded the temporal development of soil mineral nitrogen (N) and water content as well as that of plant variables (phenology, biomass, leaf area index (LAI), N content, green vegetation fraction (GVF). The work was conducted during the vegetation periods of 2015 and 2016 in winter wheat, and winter rapeseed in Kraichgau and winter barley and silage maize on Swabian Jura. Measurements were taken in three-weekly intervals. On each field, we identified three plots with reduced plant development using high-resolution (RapidEye) satellite images ("cold spots"). Measurements taken on these cold spots were compared to those from five established (long-term) reference plots representing the average field variability. The software EXPERT-N was used to simulate the soil crop system at both cold spots and reference plots. Sensitivity analyses were conducted to identify the most important parameters for the determination of spatial variability in crop growth dynamics.

MHC variability in heritage breeds of chickens.

PubMed

Fulton, J E; Lund, A R; McCarron, A M; Pinegar, K N; Korver, D R; Classen, H L; Aggrey, S; Utterbach, C; Anthony, N B; Berres, M E

2016-02-01

The chicken Major Histocompatibility Complex (MHC) is very strongly associated with disease resistance and thus is a very important region of the chicken genome. Historically, MHC (B locus) has been identified by the use of serology with haplotype specific alloantisera. These antisera can be difficult to produce and frequently cross-react with multiple haplotypes and hence their application is generally limited to inbred and MHC-defined lines. As a consequence, very little information about MHC variability in heritage chicken breeds is available. DNA-based methods are now available for examining MHC variability in these previously uncharacterized populations. A high density SNP panel consisting of 101 SNP that span a 230,000 bp region of the chicken MHC was used to examine MHC variability in 17 heritage populations of chickens from five universities from Canada and the United States. The breeds included 6 heritage broiler lines, 3 Barred Plymouth Rock, 2 New Hampshire and one each of Rhode Island Red, Light Sussex, White Leghorn, Dark Brown Leghorn, and 2 synthetic lines. These heritage breeds contained from one to 11 haplotypes per line. A total of 52 unique MHC haplotypes were found with only 10 of them identical to serologically defined haplotypes. Furthermore, nine MHC recombinants with their respective parental haplotypes were identified. This survey confirms the value of these non-commercially utilized lines in maintaining genetic diversity. The identification of multiple MHC haplotypes and novel MHC recombinants indicates that diversity is being generated and maintained within these heritage populations. © 2016 Poultry Science Association Inc.

Cross-Regional Assessment Of Coupling And Variability In Precipitation-Runoff Relationships

NASA Astrophysics Data System (ADS)

Carey, S. K.; Tetzlaff, D.; Soulsby, C.; Buttle, J. M.; Laudon, H.; McDonnell, J. J.; McGuire, K. J.; Seibert, J.; Shanley, J. B.

2011-12-01

The higher mid-latitudes of the northern hemisphere are particularly sensitive to change due to the important role the zero-degree isotherm plays in the phase of precipitation and intermediate storage as snow. An international inter-catchment comparison program North-Watch seeks to improve our understanding of the sensitivity of northern catchments to change by examining their hydrological and biogeochemical variability and response. The catchments are located in Sweden (Krycklan), Scotland (Mharcaidh, Girnock and Strontian), the United States (Sleepers River, Hubbard Brook and HJ Andrews) and Canada (Catamaran, Dorset and Wolf Creek). For this study, 8 catchments with 10 continuous years of daily precipitation and runoff data were selected to assess the seasonal coupling of rainfall and runoff and the memory effect of runoff events on the hydrograph at different time scales. To assess the coupling and synchroneity of precipitation, continuous wavelet transforms and wavelet coherence were used. Wavelet spectra identified the relative importance of both annual versus seasonal flows while wavelet coherence was applied to identify over different time scales along the 10-year window how well precipitation and runoff were coupled. For example, while on a given day, precipitation may be closely coupled to runoff, a wet year may not necessarily be a high runoff year in catchments with large storage. Assessing different averaging periods in the variation of daily flows highlights the importance of seasonality in runoff response and the relative influence of rain versus snowmelt on flow magnitude and variability. Wet catchments with limited seasonal precipitation variability (Strontian, Girnock) have precipitation signals more closely coupled with runoff, whereas dryer catchments dominated by snow (Wolf Creek, Krycklan) have strongly coupling only during freshet. Most catchments with highly seasonal precipitation show strong intermittent coupling during their wet season. At

Comparative genomics of wild type yeast strains unveils important genome diversity

PubMed Central

Carreto, Laura; Eiriz, Maria F; Gomes, Ana C; Pereira, Patrícia M; Schuller, Dorit; Santos, Manuel AS

2008-01-01

Background Genome variability generates phenotypic heterogeneity and is of relevance for adaptation to environmental change, but the extent of such variability in natural populations is still poorly understood. For example, selected Saccharomyces cerevisiae strains are variable at the ploidy level, have gene amplifications, changes in chromosome copy number, and gross chromosomal rearrangements. This suggests that genome plasticity provides important genetic diversity upon which natural selection mechanisms can operate. Results In this study, we have used wild-type S. cerevisiae (yeast) strains to investigate genome variation in natural and artificial environments. We have used comparative genome hybridization on array (aCGH) to characterize the genome variability of 16 yeast strains, of laboratory and commercial origin, isolated from vineyards and wine cellars, and from opportunistic human infections. Interestingly, sub-telomeric instability was associated with the clinical phenotype, while Ty element insertion regions determined genomic differences of natural wine fermentation strains. Copy number depletion of ASP3 and YRF1 genes was found in all wild-type strains. Other gene families involved in transmembrane transport, sugar and alcohol metabolism or drug resistance had copy number changes, which also distinguished wine from clinical isolates. Conclusion We have isolated and genotyped more than 1000 yeast strains from natural environments and carried out an aCGH analysis of 16 strains representative of distinct genotype clusters. Important genomic variability was identified between these strains, in particular in sub-telomeric regions and in Ty-element insertion sites, suggesting that this type of genome variability is the main source of genetic diversity in natural populations of yeast. The data highlights the usefulness of yeast as a model system to unravel intraspecific natural genome diversity and to elucidate how natural selection shapes the yeast genome

The effect of virtual reality on gait variability.

PubMed

Katsavelis, Dimitrios; Mukherjee, Mukul; Decker, Leslie; Stergiou, Nicholas

2010-07-01

Optic Flow (OF) plays an important role in human locomotion and manipulation of OF characteristics can cause changes in locomotion patterns. The purpose of the study was to investigate the effect of the velocity of optic flow on the amount and structure of gait variability. Each subject underwent four conditions of treadmill walking at their self-selected pace. In three conditions the subjects walked in an endless virtual corridor, while a fourth control condition was also included. The three virtual conditions differed in the speed of the optic flow displayed as follows--same speed (OFn), faster (OFf), and slower (OFs) than that of the treadmill. Gait kinematics were tracked with an optical motion capture system. Gait variability measures of the hip, knee and ankle range of motion and stride interval were analyzed. Amount of variability was evaluated with linear measures of variability--coefficient of variation, while structure of variability i.e., its organization over time, were measured with nonlinear measures--approximate entropy and detrended fluctuation analysis. The linear measures of variability, CV, did not show significant differences between Non-VR and VR conditions while nonlinear measures of variability identified significant differences at the hip, ankle, and in stride interval. In response to manipulation of the optic flow, significant differences were observed between the three virtual conditions in the following order: OFn greater than OFf greater than OFs. Measures of structure of variability are more sensitive to changes in gait due to manipulation of visual cues, whereas measures of the amount of variability may be concealed by adaptive mechanisms. Visual cues increase the complexity of gait variability and may increase the degrees of freedom available to the subject. Further exploration of the effects of optic flow manipulation on locomotion may provide us with an effective tool for rehabilitation of subjects with sensorimotor issues.

Cellular signaling identifiability analysis: a case study.

PubMed

Roper, Ryan T; Pia Saccomani, Maria; Vicini, Paolo

2010-05-21

Two primary purposes for mathematical modeling in cell biology are (1) simulation for making predictions of experimental outcomes and (2) parameter estimation for drawing inferences from experimental data about unobserved aspects of biological systems. While the former purpose has become common in the biological sciences, the latter is less common, particularly when studying cellular and subcellular phenomena such as signaling-the focus of the current study. Data are difficult to obtain at this level. Therefore, even models of only modest complexity can contain parameters for which the available data are insufficient for estimation. In the present study, we use a set of published cellular signaling models to address issues related to global parameter identifiability. That is, we address the following question: assuming known time courses for some model variables, which parameters is it theoretically impossible to estimate, even with continuous, noise-free data? Following an introduction to this problem and its relevance, we perform a full identifiability analysis on a set of cellular signaling models using DAISY (Differential Algebra for the Identifiability of SYstems). We use our analysis to bring to light important issues related to parameter identifiability in ordinary differential equation (ODE) models. We contend that this is, as of yet, an under-appreciated issue in biological modeling and, more particularly, cell biology. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Local short-term variability in solar irradiance

NASA Astrophysics Data System (ADS)

Lohmann, Gerald M.; Monahan, Adam H.; Heinemann, Detlev

2016-05-01

Characterizing spatiotemporal irradiance variability is important for the successful grid integration of increasing numbers of photovoltaic (PV) power systems. Using 1 Hz data recorded by as many as 99 pyranometers during the HD(CP)2 Observational Prototype Experiment (HOPE), we analyze field variability of clear-sky index k* (i.e., irradiance normalized to clear-sky conditions) and sub-minute k* increments (i.e., changes over specified intervals of time) for distances between tens of meters and about 10 km. By means of a simple classification scheme based on k* statistics, we identify overcast, clear, and mixed sky conditions, and demonstrate that the last of these is the most potentially problematic in terms of short-term PV power fluctuations. Under mixed conditions, the probability of relatively strong k* increments of ±0.5 is approximately twice as high compared to increment statistics computed without conditioning by sky type. Additionally, spatial autocorrelation structures of k* increment fields differ considerably between sky types. While the profiles for overcast and clear skies mostly resemble the predictions of a simple model published by , this is not the case for mixed conditions. As a proxy for the smoothing effects of distributed PV, we finally show that spatial averaging mitigates variability in k* less effectively than variability in k* increments, for a spatial sensor density of 2 km-2.

Knowledge Importance in Rehabilitation Counseling.

ERIC Educational Resources Information Center

Leahy, Michael J.; And Others

1993-01-01

Examined differences among certified rehabilitation counselors (n=1,535) in level of importance attributed to various knowledge domains. Found that grouping respondents according to employment setting and job title accounted for most frequent differences in knowledge importance among all variables examined. Respondents' educational background and…

Study of process variables associated with manufacturing hermetically-sealed nickel-cadmium cells

NASA Technical Reports Server (NTRS)

Miller, L.

1974-01-01

A two year study of the major process variables associated with the manufacturing process for sealed, nickel-cadmium, areospace cells is summarized. Effort was directed toward identifying the major process variables associated with a manufacturing process, experimentally assessing each variable's effect, and imposing the necessary changes (optimization) and controls for the critical process variables to improve results and uniformity. A critical process variable associated with the sintered nickel plaque manufacturing process was identified as the manual forming operation. Critical process variables identified with the positive electrode impregnation/polarization process were impregnation solution temperature, free acid content, vacuum impregnation, and sintered plaque strength. Positive and negative electrodes were identified as a major source of carbonate contamination in sealed cells.

Low-Frequency Temporal Variability in Mira and Semiregular Variables

NASA Astrophysics Data System (ADS)

Templeton, Matthew R.; Karovska, M.; Waagen, E. O.

2012-01-01

We investigate low-frequency variability in a large sample of Mira and semiregular variables with long-term visual light curves from the AAVSO International Database. Our aim is to determine whether we can detect and measure long-timescale variable phenomena in these stars, for example photometric variations that might be associated with supergranular convection. We analyzed the long-term light curves of 522 variable stars of the Mira and SRa, b, c, and d classes. We calculated their low-frequency time-series spectra to characterize rednoise with the power density spectrum index, and then correlate this index with other observable characteristics such as spectral type and primary pulsation period. In our initial analysis of the sample, we see that the semiregular variables have a much broader range of spectral index than the Mira types, with the SRb subtype having the broadest range. Among Mira variables we see that the M- and S-type Miras have similarly wide ranges of index, while the C-types have the narrowest with generally shallower slopes. There is also a trend of steeper slope with larger amplitude, but at a given amplitude, a wide range of slopes are seen. The ultimate goal of the project is to identify stars with strong intrinsic red noise components as possible targets for resolved surface imaging with interferometry.

Identifying environmental correlates of intraspecific genetic variation.

PubMed

Harrisson, K A; Yen, J D L; Pavlova, A; Rourke, M L; Gilligan, D; Ingram, B A; Lyon, J; Tonkin, Z; Sunnucks, P

2016-09-01

Genetic variation is critical to the persistence of populations and their capacity to adapt to environmental change. The distribution of genetic variation across a species' range can reveal critical information that is not necessarily represented in species occurrence or abundance patterns. We identified environmental factors associated with the amount of intraspecific, individual-based genetic variation across the range of a widespread freshwater fish species, the Murray cod Maccullochella peelii. We used two different approaches to statistically quantify the relative importance of predictor variables, allowing for nonlinear relationships: a random forest model and a Bayesian approach. The latter also accounted for population history. Both approaches identified associations between homozygosity by locus and both disturbance to the natural flow regime and mean annual flow. Homozygosity by locus was negatively associated with disturbance to the natural flow regime, suggesting that river reaches with more disturbed flow regimes may support larger, more genetically diverse populations. Our findings are consistent with the hypothesis that artificially induced perennial flows in regulated channels may provide greater and more consistent habitat and reduce the frequency of population bottlenecks that can occur frequently under the highly variable and unpredictable natural flow regime of the system. Although extensive river regulation across eastern Australia has not had an overall positive effect on Murray cod numbers over the past century, regulation may not represent the primary threat to Murray cod survival. Instead, pressures other than flow regulation may be more critical to the persistence of Murray cod (for example, reduced frequency of large floods, overfishing and chemical pollution).

Impact of Antarctic Polar Front Variability on Southern Ocean Biogeochemistry

NASA Astrophysics Data System (ADS)

Freeman, N. M.; Lovenduski, N. S.; Gent, P. R.

2016-12-01

The Antarctic Polar Front (PF) is an important biogeochemical divide in the Southern Ocean, often coinciding with sharp gradients in silicate and nitrate concentration at the surface. Variability in the PF has the potential to influence Southern Ocean biogeochemistry and biological productivity both locally and at the basin scale. Characterizing PF variability is important for contextualizing recent biogeochemical observations from ORCAS, SOCCOM, and the Drake Passage time-series, as well as for understanding how anthropogenic change is influencing Southern Ocean biogeochemistry. Here, we employ a suite of remote sensing observations and output from the Community Earth System Model (CESM) to better understand the relationship between the PF and local biogeochemistry in the Southern Ocean. Using microwave SST measurements spanning 2002-2014 that avoid cloud contamination, we show that the PF has shifted northward (southward) in the Pacific (Indian) sector and intensified at nearly all longitudes along its circumpolar path. We identify the PF in CESM at both coarse (1°x1°) and fine (0.1°x0.1°) horizontal resolutions using temperature and silicate gradient maxima, and quantify its spatial and temporal variability. We further investigate co-variance between the position and intensity of the PF and local phytoplankton community structure.

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.

How spatial and temporal rainfall variability affect runoff across basin scales: insights from field observations in the (semi-)urbanised Charlotte watershed

NASA Astrophysics Data System (ADS)

Ten Veldhuis, M. C.; Smith, J. A.; Zhou, Z.

2017-12-01

Impacts of rainfall variability on runoff response are highly scale-dependent. Sensitivity analyses based on hydrological model simulations have shown that impacts are likely to depend on combinations of storm type, basin versus storm scale, temporal versus spatial rainfall variability. So far, few of these conclusions have been confirmed on observational grounds, since high quality datasets of spatially variable rainfall and runoff over prolonged periods are rare. Here we investigate relationships between rainfall variability and runoff response based on 30 years of radar-rainfall datasets and flow measurements for 16 hydrological basins ranging from 7 to 111 km2. Basins vary not only in scale, but also in their degree of urbanisation. We investigated temporal and spatial variability characteristics of rainfall fields across a range of spatial and temporal scales to identify main drivers for variability in runoff response. We identified 3 ranges of basin size with different temporal versus spatial rainfall variability characteristics. Total rainfall volume proved to be the dominant agent determining runoff response at all basin scales, independent of their degree of urbanisation. Peak rainfall intensity and storm core volume are of secondary importance. This applies to all runoff parameters, including runoff volume, runoff peak, volume-to-peak and lag time. Position and movement of the storm with respect to the basin have a negligible influence on runoff response, with the exception of lag times in some of the larger basins. This highlights the importance of accuracy in rainfall estimation: getting the position right but the volume wrong will inevitably lead to large errors in runoff prediction. Our study helps to identify conditions where rainfall variability matters for correct estimation of the rainfall volume as well as the associated runoff response.

Spatial Scaling of Environmental Variables Improves Species-Habitat Models of Fishes in a Small, Sand-Bed Lowland River

PubMed Central

Radinger, Johannes; Wolter, Christian; Kail, Jochem

2015-01-01

Habitat suitability and the distinct mobility of species depict fundamental keys for explaining and understanding the distribution of river fishes. In recent years, comprehensive data on river hydromorphology has been mapped at spatial scales down to 100 m, potentially serving high resolution species-habitat models, e.g., for fish. However, the relative importance of specific hydromorphological and in-stream habitat variables and their spatial scales of influence is poorly understood. Applying boosted regression trees, we developed species-habitat models for 13 fish species in a sand-bed lowland river based on river morphological and in-stream habitat data. First, we calculated mean values for the predictor variables in five distance classes (from the sampling site up to 4000 m up- and downstream) to identify the spatial scale that best predicts the presence of fish species. Second, we compared the suitability of measured variables and assessment scores related to natural reference conditions. Third, we identified variables which best explained the presence of fish species. The mean model quality (AUC = 0.78, area under the receiver operating characteristic curve) significantly increased when information on the habitat conditions up- and downstream of a sampling site (maximum AUC at 2500 m distance class, +0.049) and topological variables (e.g., stream order) were included (AUC = +0.014). Both measured and assessed variables were similarly well suited to predict species’ presence. Stream order variables and measured cross section features (e.g., width, depth, velocity) were best-suited predictors. In addition, measured channel-bed characteristics (e.g., substrate types) and assessed longitudinal channel features (e.g., naturalness of river planform) were also good predictors. These findings demonstrate (i) the applicability of high resolution river morphological and instream-habitat data (measured and assessed variables) to predict fish presence, (ii) the

A new process sensitivity index to identify important system processes under process model and parametric uncertainty

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

Dai, Heng; Ye, Ming; Walker, Anthony P.

Hydrological models are always composed of multiple components that represent processes key to intended model applications. When a process can be simulated by multiple conceptual-mathematical models (process models), model uncertainty in representing the process arises. While global sensitivity analysis methods have been widely used for identifying important processes in hydrologic modeling, the existing methods consider only parametric uncertainty but ignore the model uncertainty for process representation. To address this problem, this study develops a new method to probe multimodel process sensitivity by integrating the model averaging methods into the framework of variance-based global sensitivity analysis, given that the model averagingmore » methods quantify both parametric and model uncertainty. A new process sensitivity index is derived as a metric of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and model parameters. For demonstration, the new index is used to evaluate the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that converting precipitation to recharge, and the geology process is also simulated by two models of different parameterizations of hydraulic conductivity; each process model has its own random parameters. The new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less

The spatial variability of water chemistry and DOC in bog pools: the importance of slope position, diurnal turnover and pool type

NASA Astrophysics Data System (ADS)

Holden, Joseph; Turner, Ed; Baird, Andy; Beadle, Jeannie; Billett, Mike; Brown, Lee; Chapman, Pippa; Dinsmore, Kerry; Dooling, Gemma; Grayson, Richard; Moody, Catherine; Gee, Clare

2017-04-01

We have previously shown that marine influence is an important factor controlling regional variability of pool water chemistry in blanket peatlands. Here we examine within-site controls on pool water chemistry. We surveyed natural and artificial (restoration sites) bog pools at blanket peatland sites in northern Scotland and Sweden. DOC, pH, conductivity, dissolved oxygen, temperature, cations, anions and absorbance spectra from 220-750nm were sampled. We sampled changes over time but also conducted intensive spatial surveys within individual pools and between pools on the same sampling days at individual study sites. Artificial pools had significantly greater DOC concentrations and different spectral absorbance characteristics when compared to natural pools at all sites studied. Within-pool variability in water chemistry tended to be small, even for very large pools ( 400 m2), except where pools had a layer of loose, mobile detritus on their beds. In these instances rapid changes took place between the overlying water column and the mobile sediment layer wherein dissolved oxygen concentrations dropped from values of around 12-10 mg/L to values less than 0.5 mg/L over just 2-3 cm of the depth profile. Such strong contrasts were not observed for pools which had a hard peat floor and which lacked a significant detritus layer. Strong diurnal turnover occurred within the pools on summer days, including within small, shallow pools (e.g. < 30 cm deep, 1 m2 area). For many pools on these summer days there was an evening spike in dissolved oxygen concentrations which originated at the surface and was then cycled downwards as the pool surface waters cooled. Slope location was a significant control on several pool water chemistry variables including pH and DOC concentration with accumulation (higher concentrations) in pools that were located further downslope in both natural and artificial pool systems. These processes have important implications for our interpretation of

Variability of isotope and major ion chemistry in the Allequash Basin, Wisconsin

USGS Publications Warehouse

Walker, John F.; Hunt, Randall J.; Bullen, Thomas D.; Krabbenhoft, David P.; Kendall, Carol

2003-01-01

As part of ongoing research conducted at one of the U.S. Geological Survey's Water, Energy, and Biogeochem-ical Budgets sites, work was undertaken to describe the spatial and temporal variability of stream and ground water isotopic composition and cation chemistry in the Trout Lake watershed, to relate the variability to the watershed flow system, and to identify the linkages of geochemical evolution and source of water in the watershed. The results are based on periodic sampling of sites at two scales along Allequash Creek, a small headwater stream in northern Wisconsin. Based on this sampling, there are distinct water isotopic and geochemical differences observed at a smaller hillslope scale and the larger Allequash Creek scale. The variability was larger than expected for this simple watershed, and is likely to be seen in more complex basins. Based on evidence from multiple isotopes and stream chemistry, the flow system arises from three main source waters (terrestrial-, lake-, or wetland-derived recharge) that can be identified along any flowpath using water isotopes together with geochemical characteristics such as iron concentrations. The ground water chemistry demonstrates considerable spatial variability that depends mainly on the flow-path length and water mobility through the aquifer. Calcium concentrations increase with increasing flowpath length, whereas strontium isotope ratios increase with increasing extent of stagnation in either the unsaturated or saturated zones as waters move from source to sink. The flowpath distribution we identify provides important constraints on the calibration of ground water flow models such as that undertaken by Pint et al. (this issue).

Identifying the Most Important 21st Century Workforce Competencies: An Analysis of the Occupational Information Network (O*NET). Research Report. ETS RR-13-21

ERIC Educational Resources Information Center

Burrus, Jeremy; Jackson, Teresa; Xi, Nuo; Steinberg, Jonathan

2013-01-01

To identify the most important competencies for college graduates to succeed in the 21st century workforce, we conducted an analysis of the Occupational Information Network (O*NET) database. O*NET is a large job analysis operated and maintained by the U.S. Department of Labor. We specifically analyzed ratings of the importance of abilities (52…

Estimating Regions of Oceanographic Importance for Seabirds Using A-Spatial Data.

PubMed

Humphries, Grant Richard Woodrow

2015-01-01

Advances in GPS tracking technologies have allowed for rapid assessment of important oceanographic regions for seabirds. This allows us to understand seabird distributions, and the characteristics which determine the success of populations. In many cases, quality GPS tracking data may not be available; however, long term population monitoring data may exist. In this study, a method to infer important oceanographic regions for seabirds will be presented using breeding sooty shearwaters as a case study. This method combines a popular machine learning algorithm (generalized boosted regression modeling), geographic information systems, long-term ecological data and open access oceanographic datasets. Time series of chick size and harvest index data derived from a long term dataset of Maori 'muttonbirder' diaries were obtained and used as response variables in a gridded spatial model. It was found that areas of the sub-Antarctic water region best capture the variation in the chick size data. Oceanographic features including wind speed and charnock (a derived variable representing ocean surface roughness) came out as top predictor variables in these models. Previously collected GPS data demonstrates that these regions are used as "flyways" by sooty shearwaters during the breeding season. It is therefore likely that wind speeds in these flyways affect the ability of sooty shearwaters to provision for their chicks due to changes in flight dynamics. This approach was designed to utilize machine learning methodology but can also be implemented with other statistical algorithms. Furthermore, these methods can be applied to any long term time series of population data to identify important regions for a species of interest.

Identifying organisational principles and management practices important to the quality of health care services for chronic conditions.

PubMed

Frølich, Anne

2012-02-01

effect of financial incentives and public performance reporting on the behaviour of professionals and quality of care. Using secondary data, KP and the Danish health care system were compared in terms of six central dimensions: population, health care professionals, health care organisations, utilization patterns, quality measurements, and costs. Differences existed between the two systems on all dimensions, complicating the interpretation of findings. For instance, observed differences might be due to similar tendencies in the two health care systems that were observed at different times, rather than true structural differences. The expenses in the two health care systems were corrected for differences in the populations served and the purchasing power of currencies. However, no validated methods existed to correct for observed differences in case-mixes of chronic conditions. Data from a population of about half a million patients with diabetes in a large U.S. integrated health care delivery system affiliated with 41 medical centers employing 15 different CCM management practices was the basis for identifying effective management practices. Through the use of statistical modelling, the management practice of provider alerts was identified as most effective for promoting screening for hemoglobin A1c and lipid profile. The CCM was used as a framework for implementing four rehabilitation programs. The model promoted continuity of care and quality of health care services. New management practices were developed in the study, and known practices were further developed. However, the observational nature of the study limited the generalisability of the findings. In a structured literature survey focusing on the effect of financial incentives and public performance reporting on the quality of health care services, few studies documenting an effect were identified. The results varied, and important program aspects or contextual variables were often omitted. A model describing

Short-term favorable weather conditions are an important control of interannual variability in carbon and water fluxes

DOE PAGES

Zscheischler, Jakob; Fatichi, Simone; Wolf, Sebastian; ...

2016-08-08

Ecosystem models often perform poorly in reproducing interannual variability in carbon and water fluxes, resulting in considerable uncertainty when estimating the land-carbon sink. While many aggregated variables (growing season length, seasonal precipitation, or temperature) have been suggested as predictors for interannual variability in carbon fluxes, their explanatory power is limited and uncertainties remain as to their relative contributions. Recent results show that the annual count of hours where evapotranspiration (ET) is larger than its 95th percentile is strongly correlated with the annual variability of ET and gross primary production (GPP) in an ecosystem model. This suggests that the occurrence ofmore » favorable conditions has a strong influence on the annual carbon budget. Here we analyzed data from eight forest sites of the AmeriFlux network with at least 7 years of continuous measurements. We show that for ET and the carbon fluxes GPP, ecosystem respiration (RE), and net ecosystem production, counting the “most active hours/days” (i.e., hours/days when the flux exceeds a high percentile) correlates well with the respective annual sums, with correlation coefficients generally larger than 0.8. Phenological transitions have much weaker explanatory power. By exploiting the relationship between most active hours and interannual variability, we classify hours as most active or less active and largely explain interannual variability in ecosystem fluxes, particularly for GPP and RE. Our results suggest that a better understanding and modeling of the occurrence of large values in high-frequency ecosystem fluxes will result in a better understanding of interannual variability of these fluxes.« less

Isolated severe tricuspid regurgitation: the importance of identifying underlying mechanism.

PubMed

Poh, Kian Keong; Solis, Jorge; Hung, Judy

2008-07-21

An 88-year-old woman presented with right heart failure, history of diarrhoea, abdominal pain, weight lost, dyspnoea over several weeks and a new pan-systolic murmur. Echocardiography showed retracted tricuspid leaflets with incomplete coaptation resulting in severe regurgitation. Subcostal view showed an adjacent hepatic cyst leading to biopsy, which revealed neoplastic neuroendocrine cells. Her 24-hour urinary 5-hydroxyindoleacetic acid level was elevated. The unifying diagnosis was carcinoid syndrome for which she was treated. Echocardiography is an important tool for diagnosis, management and prognosis of carcinoid heart disease.

Perceived cultural importance and actual self-importance of values in cultural identification.

PubMed

Wan, Ching; Chiu, Chi-yue; Tam, Kim-pong; Lee, Sau-lai; Lau, Ivy Yee-man; Peng, Siqing

2007-02-01

Cross-cultural psychologists assume that core cultural values define to a large extent what a culture is. Typically, core values are identified through an actual self-importance approach, in which core values are those that members of the culture as a group strongly endorse. In this article, the authors propose a perceived cultural importance approach to identifying core values, in which core values are values that members of the culture as a group generally believe to be important in the culture. In 5 studies, the authors examine the utility of the perceived cultural importance approach. Results consistently showed that, compared with values of high actual self-importance, values of high perceived cultural importance play a more important role in cultural identification. These findings have important implications for conceptualizing and measuring cultures. ((c) 2007 APA, all rights reserved).

An integrative framework for Bayesian variable selection with informative priors for identifying genes and pathways.

PubMed

Peng, Bin; Zhu, Dianwen; Ander, Bradley P; Zhang, Xiaoshuai; Xue, Fuzhong; Sharp, Frank R; Yang, Xiaowei

2013-01-01

The discovery of genetic or genomic markers plays a central role in the development of personalized medicine. A notable challenge exists when dealing with the high dimensionality of the data sets, as thousands of genes or millions of genetic variants are collected on a relatively small number of subjects. Traditional gene-wise selection methods using univariate analyses face difficulty to incorporate correlational, structural, or functional structures amongst the molecular measures. For microarray gene expression data, we first summarize solutions in dealing with 'large p, small n' problems, and then propose an integrative Bayesian variable selection (iBVS) framework for simultaneously identifying causal or marker genes and regulatory pathways. A novel partial least squares (PLS) g-prior for iBVS is developed to allow the incorporation of prior knowledge on gene-gene interactions or functional relationships. From the point view of systems biology, iBVS enables user to directly target the joint effects of multiple genes and pathways in a hierarchical modeling diagram to predict disease status or phenotype. The estimated posterior selection probabilities offer probabilitic and biological interpretations. Both simulated data and a set of microarray data in predicting stroke status are used in validating the performance of iBVS in a Probit model with binary outcomes. iBVS offers a general framework for effective discovery of various molecular biomarkers by combining data-based statistics and knowledge-based priors. Guidelines on making posterior inferences, determining Bayesian significance levels, and improving computational efficiencies are also discussed.

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.

Identification of solid state fermentation degree with FT-NIR spectroscopy: Comparison of wavelength variable selection methods of CARS and SCARS.

PubMed

Jiang, Hui; Zhang, Hang; Chen, Quansheng; Mei, Congli; Liu, Guohai

2015-01-01

The use of wavelength variable selection before partial least squares discriminant analysis (PLS-DA) for qualitative identification of solid state fermentation degree by FT-NIR spectroscopy technique was investigated in this study. Two wavelength variable selection methods including competitive adaptive reweighted sampling (CARS) and stability competitive adaptive reweighted sampling (SCARS) were employed to select the important wavelengths. PLS-DA was applied to calibrate identified model using selected wavelength variables by CARS and SCARS for identification of solid state fermentation degree. Experimental results showed that the number of selected wavelength variables by CARS and SCARS were 58 and 47, respectively, from the 1557 original wavelength variables. Compared with the results of full-spectrum PLS-DA, the two wavelength variable selection methods both could enhance the performance of identified models. Meanwhile, compared with CARS-PLS-DA model, the SCARS-PLS-DA model achieved better results with the identification rate of 91.43% in the validation process. The overall results sufficiently demonstrate the PLS-DA model constructed using selected wavelength variables by a proper wavelength variable method can be more accurate identification of solid state fermentation degree. Copyright © 2015 Elsevier B.V. All rights reserved.

Identification of solid state fermentation degree with FT-NIR spectroscopy: Comparison of wavelength variable selection methods of CARS and SCARS

NASA Astrophysics Data System (ADS)

Jiang, Hui; Zhang, Hang; Chen, Quansheng; Mei, Congli; Liu, Guohai

2015-10-01

The use of wavelength variable selection before partial least squares discriminant analysis (PLS-DA) for qualitative identification of solid state fermentation degree by FT-NIR spectroscopy technique was investigated in this study. Two wavelength variable selection methods including competitive adaptive reweighted sampling (CARS) and stability competitive adaptive reweighted sampling (SCARS) were employed to select the important wavelengths. PLS-DA was applied to calibrate identified model using selected wavelength variables by CARS and SCARS for identification of solid state fermentation degree. Experimental results showed that the number of selected wavelength variables by CARS and SCARS were 58 and 47, respectively, from the 1557 original wavelength variables. Compared with the results of full-spectrum PLS-DA, the two wavelength variable selection methods both could enhance the performance of identified models. Meanwhile, compared with CARS-PLS-DA model, the SCARS-PLS-DA model achieved better results with the identification rate of 91.43% in the validation process. The overall results sufficiently demonstrate the PLS-DA model constructed using selected wavelength variables by a proper wavelength variable method can be more accurate identification of solid state fermentation degree.

Enhancing Important Fluctuations: Rare Events and Metadynamics from a Conceptual Viewpoint

NASA Astrophysics Data System (ADS)

Valsson, Omar; Tiwary, Pratyush; Parrinello, Michele

2016-05-01

Atomistic simulations play a central role in many fields of science. However, their usefulness is often limited by the fact that many systems are characterized by several metastable states separated by high barriers, leading to kinetic bottlenecks. Transitions between metastable states are thus rare events that occur on significantly longer timescales than one can simulate in practice. Numerous enhanced sampling methods have been introduced to alleviate this timescale problem, including methods based on identifying a few crucial order parameters or collective variables and enhancing the sampling of these variables. Metadynamics is one such method that has proven successful in a great variety of fields. Here we review the conceptual and theoretical foundations of metadynamics. As demonstrated, metadynamics is not just a practical tool but can also be considered an important development in the theory of statistical mechanics.

Effects of Microstructural Variability on Thermo-Mechanical Properties of a Woven Ceramic Matrix Composite

NASA Technical Reports Server (NTRS)

Goldsmith, Marlana B.; Sankar, Bhavani V.; Haftka, Raphael T.; Goldberg, Robert K.

2013-01-01

The objectives of this paper include identifying important architectural parameters that describe the SiC/SiC five-harness satin weave composite and characterizing the statistical distributions and correlations of those parameters from photomicrographs of various cross sections. In addition, realistic artificial cross sections of a 2D representative volume element (RVE) are generated reflecting the variability found in the photomicrographs, which are used to determine the effects of architectural variability on the thermo-mechanical properties. Lastly, preliminary information is obtained on the sensitivity of thermo-mechanical properties to architectural variations. Finite element analysis is used in combination with a response surface and it is shown that the present method is effective in determining the effects of architectural variability on thermo-mechanical properties.

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.

Relationships between pediatric asthma and socioeconomic/urban variables in Baltimore, Maryland

NASA Technical Reports Server (NTRS)

Kimes, Daniel; Ullah, Asad; Levine, Elissa; Nelson, Ross; Timmins, Sidey; Weiss, Sheila; Bollinger, Mary E.; Blaisdell, Carol

2004-01-01

Spatial relationships between clinical data for pediatric asthmatics (hospital and emergency department utilization rates), and socioeconomic and urban characteristics in Baltimore City were analyzed with the aim of identifying factors that contribute to increased asthma rates. Socioeconomic variables and urban characteristics derived from satellite data explained 95% of the spatial variation in hospital rates. The proportion of families headed by a single female was the most important variable accounting for 89% of the spatial variation. Evidence suggests that the high rates of hospital admissions and emergency department (ED) visits may partially be due to the difficulty of single parents with limited resources managing their child's asthma condition properly. This knowledge can be used for education towards mitigating ED and hospital events in Baltimore City.

Genotypic variability-based genome-wide association study identifies non-additive loci HLA-C and IL12B for psoriasis.

PubMed

Wei, Wen-Hua; Massey, Jonathan; Worthington, Jane; Barton, Anne; Warren, Richard B

2018-03-01

Genome-wide association studies (GWASs) have identified a number of loci for psoriasis but largely ignored non-additive effects. We report a genotypic variability-based GWAS (vGWAS) that can prioritize non-additive loci without requiring prior knowledge of interaction types or interacting factors in two steps, using a mixed model to partition dichotomous phenotypes into an additive component and non-additive environmental residuals on the liability scale and then the Levene's (Brown-Forsythe) test to assess equality of the residual variances across genotype groups genome widely. The vGWAS identified two genome-wide significant (P < 5.0e-08) non-additive loci HLA-C and IL12B that were also genome-wide significant in an accompanying GWAS in the discovery cohort. Both loci were statistically replicated in vGWAS of an independent cohort with a small sample size. HLA-C and IL12B were reported in moderate gene-gene and/or gene-environment interactions in several occasions. We found a moderate interaction with age-of-onset of psoriasis, which was replicated indirectly. The vGWAS also revealed five suggestive loci (P < 6.76e-05) including FUT2 that was associated with psoriasis with environmental aspects triggered by virus infection and/or metabolic factors. Replication and functional investigation are needed to validate the suggestive vGWAS loci.

Identifying Important Career Indicators of Undergraduate Geoscience Students Upon Completion of Their Degree

NASA Astrophysics Data System (ADS)

Wilson, C. E.; Keane, C. M.; Houlton, H. R.

2012-12-01

The American Geosciences Institute (AGI) decided to create the National Geoscience Student Exit Survey in order to identify the initial pathways into the workforce for these graduating students, as well as assess their preparedness for entering the workforce upon graduation. The creation of this survey stemmed from a combination of experiences with the AGI/AGU Survey of Doctorates and discussions at the following Science Education Research Center (SERC) workshops: "Developing Pathways to Strong Programs for the Future", "Strengthening Your Geoscience Program", and "Assessing Geoscience Programs". These events identified distinct gaps in understanding the experiences and perspectives of geoscience students during one of their most profound professional transitions. Therefore, the idea for the survey arose as a way to evaluate how the discipline is preparing and educating students, as well as identifying the students' desired career paths. The discussions at the workshops solidified the need for this survey and created the initial framework for the first pilot of the survey. The purpose of this assessment tool is to evaluate student preparedness for entering the geosciences workforce; identify student decision points for entering geosciences fields and remaining in the geosciences workforce; identify geosciences fields that students pursue in undergraduate and graduate school; collect information on students' expected career trajectories and geosciences professions; identify geosciences career sectors that are hiring new graduates; collect information about salary projections; overall effectiveness of geosciences departments regionally and nationally; demonstrate the value of geosciences degrees to future students, the institutions, and employers; and establish a benchmark to perform longitudinal studies of geosciences graduates to understand their career pathways and impacts of their educational experiences on these decisions. AGI's Student Exit Survey went through

Experimental assessment of the importance of amino acid positions identified by an entropy-based correlation analysis of multiple-sequence alignments.

PubMed

Dietrich, Susanne; Borst, Nadine; Schlee, Sandra; Schneider, Daniel; Janda, Jan-Oliver; Sterner, Reinhard; Merkl, Rainer

2012-07-17

The analysis of a multiple-sequence alignment (MSA) with correlation methods identifies pairs of residue positions whose occupation with amino acids changes in a concerted manner. It is plausible to assume that positions that are part of many such correlation pairs are important for protein function or stability. We have used the algorithm H2r to identify positions k in the MSAs of the enzymes anthranilate phosphoribosyl transferase (AnPRT) and indole-3-glycerol phosphate synthase (IGPS) that show a high conn(k) value, i.e., a large number of significant correlations in which k is involved. The importance of the identified residues was experimentally validated by performing mutagenesis studies with sAnPRT and sIGPS from the archaeon Sulfolobus solfataricus. For sAnPRT, five H2r mutant proteins were generated by replacing nonconserved residues with alanine or the prevalent residue of the MSA. As a control, five residues with conn(k) values of zero were chosen randomly and replaced with alanine. The catalytic activities and conformational stabilities of the H2r and control mutant proteins were analyzed by steady-state enzyme kinetics and thermal unfolding studies. Compared to wild-type sAnPRT, the catalytic efficiencies (k(cat)/K(M)) were largely unaltered. In contrast, the apparent thermal unfolding temperature (T(M)(app)) was lowered in most proteins. Remarkably, the strongest observed destabilization (ΔT(M)(app) = 14 °C) was caused by the V284A exchange, which pertains to the position with the highest correlation signal [conn(k) = 11]. For sIGPS, six H2r mutant and four control proteins with alanine exchanges were generated and characterized. The k(cat)/K(M) values of four H2r mutant proteins were reduced between 13- and 120-fold, and their T(M)(app) values were decreased by up to 5 °C. For the sIGPS control proteins, the observed activity and stability decreases were much less severe. Our findings demonstrate that positions with high conn(k) values have an

The Unknown Variable: Identifying Learning Disabilities with Pupil Behavior Rating Scales.

ERIC Educational Resources Information Center

Winzer, Margret; Malarczyk, Barbara

Difficulties in identifying learning disabilities (LD) are examined, and special problems presented by hearing impaired children with LD are considered. The value of rating scales as a quick instrument for obtaining, measuring, recording and communicating information is emphasized. Adaptations of the Pupil Rating Scale for hearing impaired…

Simulation of crop yield variability by improved root-soil-interaction modelling

NASA Astrophysics Data System (ADS)

Duan, X.; Gayler, S.; Priesack, E.

2009-04-01

Understanding the processes and factors that govern the within-field variability in crop yield has attached great importance due to applications in precision agriculture. Crop response to environment at field scale is a complex dynamic process involving the interactions of soil characteristics, weather conditions and crop management. The numerous static factors combined with temporal variations make it very difficult to identify and manage the variability pattern. Therefore, crop simulation models are considered to be useful tools in analyzing separately the effects of change in soil or weather conditions on the spatial variability, in order to identify the cause of yield variability and to quantify the spatial and temporal variation. However, tests showed that usual crop models such as CERES-Wheat and CERES-Maize were not able to quantify the observed within-field yield variability, while their performance on crop growth simulation under more homogeneous and mainly non-limiting conditions was sufficent to simulate average yields at the field-scale. On a study site in South Germany, within-field variability in crop growth has been documented since years. After detailed analysis and classification of the soil patterns, two site specific factors, the plant-available-water and the O2 deficiency, were considered as the main causes of the crop growth variability in this field. Based on our measurement of root distribution in the soil profile, we hypothesize that in our case the insufficiency of the applied crop models to simulate the yield variability can be due to the oversimplification of the involved root models which fail to be sensitive to different soil conditions. In this study, the root growth model described by Jones et al. (1991) was adapted by using data of root distributions in the field and linking the adapted root model to the CERES crop model. The ability of the new root model to increase the sensitivity of the CERES crop models to different enviromental

A landscape ecology approach identifies important drivers of urban biodiversity.

PubMed

Turrini, Tabea; Knop, Eva

2015-04-01

Cities are growing rapidly worldwide, yet a mechanistic understanding of the impact of urbanization on biodiversity is lacking. We assessed the impact of urbanization on arthropod diversity (species richness and evenness) and abundance in a study of six cities and nearby intensively managed agricultural areas. Within the urban ecosystem, we disentangled the relative importance of two key landscape factors affecting biodiversity, namely the amount of vegetated area and patch isolation. To do so, we a priori selected sites that independently varied in the amount of vegetated area in the surrounding landscape at the 500-m scale and patch isolation at the 100-m scale, and we hold local patch characteristics constant. As indicator groups, we used bugs, beetles, leafhoppers, and spiders. Compared to intensively managed agricultural ecosystems, urban ecosystems supported a higher abundance of most indicator groups, a higher number of bug species, and a lower evenness of bug and beetle species. Within cities, a high amount of vegetated area increased species richness and abundance of most arthropod groups, whereas evenness showed no clear pattern. Patch isolation played only a limited role in urban ecosystems, which contrasts findings from agro-ecological studies. Our results show that urban areas can harbor a similar arthropod diversity and abundance compared to intensively managed agricultural ecosystems. Further, negative consequences of urbanization on arthropod diversity can be mitigated by providing sufficient vegetated space in the urban area, while patch connectivity is less important in an urban context. This highlights the need for applying a landscape ecological approach to understand the mechanisms shaping urban biodiversity and underlines the potential of appropriate urban planning for mitigating biodiversity loss. © 2015 John Wiley & Sons Ltd.

Petroleomics by electrospray ionization FT-ICR mass spectrometry coupled to partial least squares with variable selection methods: prediction of the total acid number of crude oils.

PubMed

Terra, Luciana A; Filgueiras, Paulo R; Tose, Lílian V; Romão, Wanderson; de Souza, Douglas D; de Castro, Eustáquio V R; de Oliveira, Mirela S L; Dias, Júlio C M; Poppi, Ronei J

2014-10-07

Negative-ion mode electrospray ionization, ESI(-), with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was coupled to a Partial Least Squares (PLS) regression and variable selection methods to estimate the total acid number (TAN) of Brazilian crude oil samples. Generally, ESI(-)-FT-ICR mass spectra present a power of resolution of ca. 500,000 and a mass accuracy less than 1 ppm, producing a data matrix containing over 5700 variables per sample. These variables correspond to heteroatom-containing species detected as deprotonated molecules, [M - H](-) ions, which are identified primarily as naphthenic acids, phenols and carbazole analog species. The TAN values for all samples ranged from 0.06 to 3.61 mg of KOH g(-1). To facilitate the spectral interpretation, three methods of variable selection were studied: variable importance in the projection (VIP), interval partial least squares (iPLS) and elimination of uninformative variables (UVE). The UVE method seems to be more appropriate for selecting important variables, reducing the dimension of the variables to 183 and producing a root mean square error of prediction of 0.32 mg of KOH g(-1). By reducing the size of the data, it was possible to relate the selected variables with their corresponding molecular formulas, thus identifying the main chemical species responsible for the TAN values.

Importance of blood pressure variability in organ protection in spontaneously hypertensive rats treated with combination of nitrendipine and atenolol.

PubMed

Xie, He-Hui; Miao, Chao-Yu; Liu, Jian-Guo; Su, Ding-Feng

2002-12-01

To study the importance of reduction of blood pressure variability (BPV) in the organ protection of long-term treatment with combination of nitrendipine and atenolol, which was abbreviated as Nile, in spontaneously hypertensive rats (SHR). Combination of nitrendipine (10 mg/kg/d) and atenolol (20 mg/kg/d) was given in SHR chow for 12 weeks. Blood pressure (BP) was then recorded during 24 h in conscious state. After the determination of baroreflex sensitivity (BRS), rats were killed for organ-damage evaluation. Long-term treatment with Nile significantly decreased BP and BPV, ameliorated impaired BRS, and obviously diminished end-organ damage in SHR. The indices of left ventricular and aortic hypertrophy, and glomerulosclerosis score were all positively related to BP and BPV, and negatively related to BRS in untreated and Nile-treated SHR. Multiple-regression analysis showed that decrease in left ventricular and aortic hypertrophy was mainly related to the decrease in systolic BPV, and amelioration in renal lesion was mainly determined by increase in BRS. Long-term treatment with Nile possessed obvious organ protection in SHR. Besides the BP reduction, the decrease in BPV and the restoration of BRS may importantly contribute to this organ protection.

Periodic and Aperiodic Variability in the Molecular Cloud ρ Ophiuchus

NASA Astrophysics Data System (ADS)

Parks, J. Robert; Plavchan, Peter; White, Russel J.; Gee, Alan H.

2014-03-01

Presented are the results of a near-IR photometric survey of 1678 stars in the direction of the ρ Ophiuchus (ρ Oph) star forming region using data from the 2MASS Calibration Database. For each target in this sample, up to 1584 individual J-, H-, and Ks -band photometric measurements with a cadence of ~1 day are obtained over three observing seasons spanning ~2.5 yr it is the most intensive survey of stars in this region to date. This survey identifies 101 variable stars with ΔKs -band amplitudes from 0.044 to 2.31 mag and Δ(J - Ks ) color amplitudes ranging from 0.053 to 1.47 mag. Of the 72 young ρ Oph star cluster members included in this survey, 79% are variable; in addition, 22 variable stars are identified as candidate members. Based on the temporal behavior of the Ks time-series, the variability is distinguished as either periodic, long time-scale or irregular. This temporal behavior coupled with the behavior of stellar colors is used to assign a dominant variability mechanism. A new period-searching algorithm finds periodic signals in 32 variable stars with periods between 0.49 to 92 days. The chief mechanism driving the periodic variability for 18 stars is rotational modulation of cool starspots while 3 periodically vary due to accretion-induced hot spots. The time-series for six variable stars contains discrete periodic "eclipse-like" features with periods ranging from 3 to 8 days. These features may be asymmetries in the circumstellar disk, potentially sustained or driven by a proto-planet at or near the co-rotation radius. Aperiodic, long time-scale variations in stellar flux are identified in the time-series for 31 variable stars with time-scales ranging from 64 to 790 days. The chief mechanism driving long time-scale variability is variable extinction or mass accretion rates. The majority of the variable stars (40) exhibit sporadic, aperiodic variability over no discernable time-scale. No chief variability mechanism could be identified for these

Groundwater level responses to precipitation variability in Mediterranean insular aquifers

NASA Astrophysics Data System (ADS)

Lorenzo-Lacruz, Jorge; Garcia, Celso; Morán-Tejeda, Enrique

2017-09-01

Groundwater is one of the largest and most important sources of fresh water on many regions under Mediterranean climate conditions, which are exposed to large precipitation variability that includes frequent meteorological drought episodes, and present high evapotranspiration rates and water demand during the dry season. The dependence on groundwater increases in those areas with predominant permeable lithologies, contributing to aquifer recharge and the abundance of ephemeral streams. The increasing pressure of tourism on water resources in many Mediterranean coastal areas, and uncertainty related to future precipitation and water availability, make it urgent to understand the spatio-temporal response of groundwater bodies to precipitation variability, if sustainable use of the resource is to be achieved. We present an assessment of the response of aquifers to precipitation variability based on correlations between the Standardized Precipitation Index (SPI) at various time scales and the Standardized Groundwater Index (SGI) across a Mediterranean island. We detected three main responses of aquifers to accumulated precipitation anomalies: (i) at short time scales of the SPI (<6 months); (ii) at medium time scales (6-24 months); and at long time scales (>24 months). The differing responses were mainly explained by differences in lithology and the percentage of highly permeable rock strata in the aquifer recharge areas. We also identified differences in the months and seasons when aquifer storages are more dependent on precipitation; these were related to climate seasonality and the degree of aquifer exploitation or underground water extraction. The recharge of some aquifers, especially in mountainous areas, is related to precipitation variability within a limited spatial extent, whereas for aquifers located in the plains, precipitation variability influence much larger areas; the topography and geological structure of the island explain these differences. Results

The role of impulse parameters in force variability

NASA Technical Reports Server (NTRS)

Carlton, L. G.; Newell, K. M.

1986-01-01

One of the principle limitations of the human motor system is the ability to produce consistent motor responses. When asked to repeatedly make the same movement, performance outcomes are characterized by a considerable amount of variability. This occurs whether variability is expressed in terms of kinetics or kinematics. Variability in performance is of considerable importance because for tasks requiring accuracy it is a critical variable in determining the skill of the performer. What has long been sought is a description of the parameter or parameters that determine the degree of variability. Two general experimental protocals were used. One protocal is to use dynamic actions and record variability in kinematic parameters such as spatial or temporal error. A second strategy was to use isometric actions and record kinetic variables such as peak force produced. What might be the important force related factors affecting variability is examined and an experimental approach to examine the influence of each of these variables is provided.

Physical attraction to reliable, low variability nervous systems: Reaction time variability predicts attractiveness.

PubMed

Butler, Emily E; Saville, Christopher W N; Ward, Robert; Ramsey, Richard

2017-01-01

The human face cues a range of important fitness information, which guides mate selection towards desirable others. Given humans' high investment in the central nervous system (CNS), cues to CNS function should be especially important in social selection. We tested if facial attractiveness preferences are sensitive to the reliability of human nervous system function. Several decades of research suggest an operational measure for CNS reliability is reaction time variability, which is measured by standard deviation of reaction times across trials. Across two experiments, we show that low reaction time variability is associated with facial attractiveness. Moreover, variability in performance made a unique contribution to attractiveness judgements above and beyond both physical health and sex-typicality judgements, which have previously been associated with perceptions of attractiveness. In a third experiment, we empirically estimated the distribution of attractiveness preferences expected by chance and show that the size and direction of our results in Experiments 1 and 2 are statistically unlikely without reference to reaction time variability. We conclude that an operating characteristic of the human nervous system, reliability of information processing, is signalled to others through facial appearance. Copyright © 2016 Elsevier B.V. All rights reserved.

Using naturalistic driving data to identify variables associated with infrequent, occasional, and consistent seat belt use.

PubMed

Reagan, Ian J; McClafferty, Julie A; Berlin, Sharon P; Hankey, Jonathan M

2013-01-01

Seat belt use is one of the most effective countermeasures to reduce traffic fatalities and injuries. The success of efforts to increase use is measured by road side observations and self-report questionnaires. These methods have shortcomings, with the former requiring a binary point estimate and the latter being subjective. The 100-car naturalistic driving study presented a unique opportunity to study seat belt use in that seat belt status was known for every trip each driver made during a 12-month period. Drivers were grouped into infrequent, occasional, or consistent seat belt users based on the frequency of belt use. Analyses were then completed to assess if these groups differed on several measures including personality, demographics, self-reported driving style variables as well as measures from the 100-car study instrumentation suite (average trip speed, trips per day). In addition, detailed analyses of the occasional belt user group were completed to identify factors that were predictive of occasional belt users wearing their belts. The analyses indicated that consistent seat belt users took fewer trips per day, and that increased average trip speed was associated with increased belt use among occasional belt users. The results of this project may help focus messaging efforts to convert occasional and inconsistent seat belt users to consistent users. Copyright © 2012 Elsevier Ltd. All rights reserved.

Exploring Relationships between Personal Variables, Programmatic Variables, and Self-Efficacy in School-Based Agricultural Education

ERIC Educational Resources Information Center

McKim, Aaron J.; Velez, Jonathan J.; Clement, Haley Q.

2017-01-01

The educational importance of teacher self-efficacy necessitates research into variables presumed to significantly influence teacher self-efficacy. In the current study, the role of personal and programmatic variables on the self-efficacy of school-based agriculture teachers was explored. Self-efficacy was measured in five aspects of the…

An Integrative Framework for Bayesian Variable Selection with Informative Priors for Identifying Genes and Pathways

PubMed Central

Ander, Bradley P.; Zhang, Xiaoshuai; Xue, Fuzhong; Sharp, Frank R.; Yang, Xiaowei

2013-01-01

The discovery of genetic or genomic markers plays a central role in the development of personalized medicine. A notable challenge exists when dealing with the high dimensionality of the data sets, as thousands of genes or millions of genetic variants are collected on a relatively small number of subjects. Traditional gene-wise selection methods using univariate analyses face difficulty to incorporate correlational, structural, or functional structures amongst the molecular measures. For microarray gene expression data, we first summarize solutions in dealing with ‘large p, small n’ problems, and then propose an integrative Bayesian variable selection (iBVS) framework for simultaneously identifying causal or marker genes and regulatory pathways. A novel partial least squares (PLS) g-prior for iBVS is developed to allow the incorporation of prior knowledge on gene-gene interactions or functional relationships. From the point view of systems biology, iBVS enables user to directly target the joint effects of multiple genes and pathways in a hierarchical modeling diagram to predict disease status or phenotype. The estimated posterior selection probabilities offer probabilitic and biological interpretations. Both simulated data and a set of microarray data in predicting stroke status are used in validating the performance of iBVS in a Probit model with binary outcomes. iBVS offers a general framework for effective discovery of various molecular biomarkers by combining data-based statistics and knowledge-based priors. Guidelines on making posterior inferences, determining Bayesian significance levels, and improving computational efficiencies are also discussed. PMID:23844055

Identifying Recent HIV Infections: From Serological Assays to Genomics.

PubMed

Moyo, Sikhulile; Wilkinson, Eduan; Novitsky, Vladimir; Vandormael, Alain; Gaseitsiwe, Simani; Essex, Max; Engelbrecht, Susan; de Oliveira, Tulio

2015-10-23

In this paper, we review serological and molecular based methods to identify HIV infection recency. The accurate identification of recent HIV infection continues to be an important research area and has implications for HIV prevention and treatment interventions. Longitudinal cohorts that follow HIV negative individuals over time are the current gold standard approach, but they are logistically challenging, time consuming and an expensive enterprise. Methods that utilize cross-sectional testing and biomarker information have become an affordable alternative to the longitudinal approach. These methods use well-characterized biological makers to differentiate between recent and established HIV infections. However, recent results have identified a number of limitations in serological based assays that are sensitive to the variability in immune responses modulated by HIV subtypes, viral load and antiretroviral therapy. Molecular methods that explore the dynamics between the timing of infection and viral evolution are now emerging as a promising approach. The combination of serological and molecular methods may provide a good solution to identify recent HIV infection in cross-sectional data. As part of this review, we present the advantages and limitations of serological and molecular based methods and their potential complementary role for the identification of HIV infection recency.

Interannual Variability of Ammonia Concentrations over the United States: Sources and Implications for Inorganic Particulate Matter

NASA Astrophysics Data System (ADS)

Schiferl, L. D.; Heald, C. L.; Van Damme, M.; Pierre-Francois, C.; Clerbaux, C.

2015-12-01

Modern agricultural practices have greatly increased the emission of ammonia (NH3) to the atmosphere. Recent controls to reduce the emissions of sulfur and nitrogen oxides (SOX and NOX) have increased the importance of understanding the role ammonia plays in the formation of surface fine inorganic particulate matter (PM2.5) in the United States. In this study, we identify the interannual variability in ammonia concentration, explore the sources of this variability and determine their contribution to the variability in surface PM2.5 concentration. Over the summers of 2008-2012, measurements from the Ammonia Monitoring Network (AMoN) and the Infrared Atmospheric Sounding Interferometer (IASI) satellite instrument show considerable variability in both surface and column ammonia concentrations (+/- 29% and 28% of the mean), respectively. This observed variability is larger than that simulated by the GEOS-Chem chemical transport model, where meteorology dominates the variability in ammonia and PM2.5 concentrations compared to the changes caused by SOX and NOX reductions. Our initial simulation does not include year-to-year changes in ammonia agricultural emissions. We use county-wide information on fertilizer sales and livestock populations, as well as meteorological variations to account for the interannual variability in agricultural activity and ammonia volatilization. These sources of ammonia emission variability are important for replicating observed variations in ammonia and PM2.5, highlighting how accurate ammonia emissions characterization is central to PM air quality prediction.

Variables involved in the perception of psychological harassment in the nursing work environment.

PubMed

Fontes, Kátia Biagio; Carvalho, Maria Dalva de Barros

2012-01-01

This is a descriptive-exploratory study with a quantitative approach, with the objective of identifying how nurses perceive psychological harassment at work, the behaviors experienced and the variables involved. In collecting data, two questionnaires were used: one socio-professional and another for identifying the behaviors involving psychological harassment experienced by the subjects in the previous twelve months, along with the duration and frequency of the behaviors. At the end of the questionnaire, a dichotomous question was added, which addressed nurses' perceptions in relation to feeling victimized by psychological harassment at work. Both the questionnaires were applied in electronic and print format between May and September 2010. The data was analyzed through descriptive statistics. The results showed that some of the subjects felt that they were victims of psychological harassment. Only the variables related to characterization of the psychological harassment presented significant association. The following were highlighted among the most-referred-to behaviors: "They question your decisions" and "You receive verbal attacks criticizing work you have done". It's important to open spaces for discussing violence at work, so that managers may establish strategic measures for preventing and containing this type of violence, so as to ensure health, dignity and well-being at work. It is also important to discuss this issue in the academic space, so as to give the theme greater visibility, such that future nurses will be able to identify and appropriately confront this type of violence.

Forge into the Future: Identifying Core Competencies and Important Skills, Knowledge, and Abilities (SKAs) for Junior Navy Medical Service Corps Officers

DTIC Science & Technology

2008-10-20

operations and business practices, drug therapy management, and leadership, where as senior pharmacists placed a greater emphasis on the importance of SKAs...Commanders reviewed , sorted, and identified competencies from Wave I into 11 domains. From the expert analysis, the researcher developed a ...Y, a force of as many as 70 million are now beginning to embark on their career including the military health system. This generation as suggested

The Importance of Flexibility of Pronunciation in Learning to Decode: A Training Study in Set for Variability

ERIC Educational Resources Information Center

Zipke, Marcy

2016-01-01

The ability to flexibly approach the pronunciation of unknown words, or set "for variability", has been shown to contribute to word recognition skills. However, this is the first study that has attempted to teach students strategies for increasing their set for variability. Beginning readers (N = 15) were instructed to correct oral…

On the Nature of the Mesoscale Variability in Denmark Strait

NASA Astrophysics Data System (ADS)

Pickart, Robert; von Appen, Wilken; Mastropole, Dana; Valdimarsson, Hedinn; Vage, Kjetil; Jonsson, Steingriumur; Jochumsen, Kerstin; Girton, James

2017-04-01

The dense overflow through Denmark Strait is the largest contributor to the lower limb of the Atlantic Meridional Overturning Circulation. As such, it is important to understand the sources of water feeding the overflow and how the water negotiates the sill as it passes into the Irminger Sea. Here we use a large collection of shipboard hydrographic transects occupied across the strait, together with 6-years of mooring data from the sill, to investigate the water masses and mesoscale variability of the overflow water. Two dominant types of mesoscale features were identified, referred to as a "bolus" and a "pulse". The former is a large lens of weakly stratified water corresponding to a slight increase in along-strait velocity. The latter is a thin layer with greater stratification and strongly enhanced along-strait flow. The boluses, which are often noted in the historical literature, are associated with cyclonic circulation, while pulses, which have not been previously identified, are associated with anti-cyclonic circulation. Both features result in increased transport of overflow water. It is argued that these fluctuations at the sill trigger energetic variability downstream in the Deep Western Boundary Current.

Exploring the Hard and Soft X-ray Emission of Magnetic Cataclysmic Variables

NASA Astrophysics Data System (ADS)

de Martino, D.; Anzolin, G.; Bonnet-Bidaud, J.-M.; Falanga, M.; Matt, G.; Mouchet, M.; Mukai, K.; Masetti, N.

2009-05-01

A non-negligible fraction of galactic hard (>20 keV) X-ray sources were identified as CVs of the magnetic Intermediate Polar type in INTEGRAL, SWIFT and RXTE surveys, that suggests a still hidden but potentially important population of faint hard X-ray sources. Simbol-X has the unique potential to simultaneously characterize their variable and complex soft and hard X-ray emission thus allowing to understand their putative role in galactic populations of X-ray sources.

Arctic Sea Ice Basal Melt Onset Variability and Associated Ocean Surface Heating

NASA Astrophysics Data System (ADS)

Merrick, R. A.; Hutchings, J. K.

2015-12-01

The interannual and regional variability in Arctic sea ice melt has previously been characterized only in terms of surface melting. A focus on the variability in the onset of basal melt is additionally required to understand Arctic melt patterns. Monitoring basal melt provides a glimpse into the importance of ocean heating to sea ice melt. This warming is predominantly through seawater exposure due to lead opening and the associated solar warming at the ocean's surface. We present the temporal variability in basal melt onset observed by ice mass balance buoys throughout the Arctic Ocean since 2003, providing a different perspective than the satellite microwave data used to measure the onset of surface melt. We found that melt onset varies greatly, even for buoys deployed within 100km of each other. Therefore large volumes of data are necessary to accurately estimate the variability of basal melt onset. Once the variability of basal melt onset has been identified, we can investigate how this range has been changing as a response to atmospheric and oceanic warming, changes in ice morphology as well as the intensification of the ice albedo feedback.

The Hubble Catalog of Variables

NASA Astrophysics Data System (ADS)

Gavras, P.; Bonanos, A. Z.; Bellas-Velidis, I.; Charmandaris, V.; Georgantopoulos, I.; Hatzidimitriou, D.; Kakaletris, G.; Karampelas, A.; Laskaris, N.; Lennon, D. J.; Moretti, M. I.; Pouliasis, E.; Sokolovsky, K.; Spetsieri, Z. T.; Tsinganos, K.; Whitmore, B. C.; Yang, M.

2017-06-01

The Hubble Catalog of Variables (HCV) is a 3 year ESA funded project that aims to develop a set of algorithms to identify variables among the sources included in the Hubble Source Catalog (HSC) and produce the HCV. We will process all HSC sources with more than a predefined number of measurements in a single filter/instrument combination and compute a range of lightcurve features to determine the variability status of each source. At the end of the project, the first release of the Hubble Catalog of Variables will be made available at the Mikulski Archive for Space Telescopes (MAST) and the ESA Science Archives. The variability detection pipeline will be implemented at the Space Telescope Science Institute (STScI) so that updated versions of the HCV may be created following the future releases of the HSC.

A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method.

PubMed

Yang, Jun-He; Cheng, Ching-Hsue; Chan, Chia-Pan

2017-01-01

Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir's water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

K2 Variable Catalogue: Variable stars and eclipsing binaries in K2 campaigns 1 and 0

NASA Astrophysics Data System (ADS)

Armstrong, D. J.; Kirk, J.; Lam, K. W. F.; McCormac, J.; Walker, S. R.; Brown, D. J. A.; Osborn, H. P.; Pollacco, D. L.; Spake, J.

2015-07-01

Aims: We have created a catalogue of variable stars found from a search of the publicly available K2 mission data from Campaigns 1 and 0. This catalogue provides the identifiers of 8395 variable stars, including 199 candidate eclipsing binaries with periods up to 60 d and 3871 periodic or quasi-periodic objects, with periods up to 20 d for Campaign 1 and 15 d for Campaign 0. Methods: Lightcurves are extracted and detrended from the available data. These are searched using a combination of algorithmic and human classification, leading to a classifier for each object as an eclipsing binary, sinusoidal periodic, quasi periodic, or aperiodic variable. The source of the variability is not identified, but could arise in the non-eclipsing binary cases from pulsation or stellar activity. Each object is cross-matched against variable star related guest observer proposals to the K2 mission, which specifies the variable type in some cases. The detrended lightcurves are also compared to lightcurves currently publicly available. Results: The resulting catalogue gives the ID, type, period, semi-amplitude, and range of the variation seen. We also make available the detrended lightcurves for each object. The catalogue is available at http://deneb.astro.warwick.ac.uk/phrlbj/k2varcat/ and at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/579/A19

On the spatial decorrelation of stochastic solar resource variability at long timescales

DOE PAGES

Perez, Marc J. R.; Fthenakis, Vasilis M.

2015-05-16

Understanding the spatial and temporal characteristics of solar resource variability is important because it helps inform the discussion surrounding the merits of geographic dispersion and subsequent electrical interconnection of photovoltaics as part of a portfolio of future solutions for coping with this variability. The unpredictable resource variability arising from the stochastic nature of meteorological phenomena (from the passage of clouds to the movement of weather systems) is of most concern for achieving high PV penetration because unlike the passage of seasons or the shift from day to night, the uncertainty makes planning a challenge. A suitable proxy for unpredictable solarmore » resource variability at any given location is the series of variations in the clearness index from one time period to the next because the clearness index is largely independent of the predictable influence of solar geometry. At timescales shorter than one day, the correlation between these variations in clearness index at pairs of distinct geographic locations decreases with spatial extent and with timescale. As the aggregate variability across N decorrelated locations decreases as 1/√N, identifying the distance required to achieve this decorrelation is critical to quantifying the expected reduction in variability from geographic dispersion.« less

Bayesian inference for the genetic control of water deficit tolerance in spring wheat by stochastic search variable selection.

PubMed

Safari, Parviz; Danyali, Syyedeh Fatemeh; Rahimi, Mehdi

2018-06-02

Drought is the main abiotic stress seriously influencing wheat production. Information about the inheritance of drought tolerance is necessary to determine the most appropriate strategy to develop tolerant cultivars and populations. In this study, generation means analysis to identify the genetic effects controlling grain yield inheritance in water deficit and normal conditions was considered as a model selection problem in a Bayesian framework. Stochastic search variable selection (SSVS) was applied to identify the most important genetic effects and the best fitted models using different generations obtained from two crosses applying two water regimes in two growing seasons. The SSVS is used to evaluate the effect of each variable on the dependent variable via posterior variable inclusion probabilities. The model with the highest posterior probability is selected as the best model. In this study, the grain yield was controlled by the main effects (additive and non-additive effects) and epistatic. The results demonstrate that breeding methods such as recurrent selection and subsequent pedigree method and hybrid production can be useful to improve grain yield.

The functional importance of sequence versus expression variability of MHC alleles in parasite resistance.

PubMed

Axtner, Jan; Sommer, Simone

2012-12-01

Understanding selection processes driving the pronounced allelic polymorphism of the major histocompatibility complex (MHC) genes and its functional associations to parasite load have been the focus of many recent wildlife studies. Two main selection scenarios are currently debated which explain the susceptibility or resistance to parasite infections either by the effects of (1) specific MHC alleles which are selected frequency-dependent in space and time or (2) a heterozygote or divergent allele advantage. So far, most studies have focused only on structural variance in co-evolutionary processes although this might not be the only trait subject to natural selection. In the present study, we analysed structural variance stretching from exon1 through exon3 of MHC class II DRB genes as well as genotypic expression variance in relation to the gastrointestinal helminth prevalence and infection intensity in wild yellow-necked mice (Apodemus flavicollis). We found support for the functional importance of specific alleles both on the sequence and expression level. By resampling a previously investigated study population we identified specific MHC alleles affected by temporal shifts in parasite pressure and recorded associated changes in allele frequencies. The allele Apfl-DRB*23 was associated with resistance to infections by the oxyurid nematode Syphacia stroma and at the same time with susceptibility to cestode infection intensity. In line with our expectation, MHC mRNA transcript levels tended to be higher in cestode-infected animals carrying the allele Apfl-DRB*23. However, no support for a heterozygote or divergent allele advantage on the sequence or expression level was detected. The individual amino acid distance of genotypes did not explain individual differences in parasite loads and the genetic distance had no effect on MHC genotype expression. For ongoing studies on the functional importance of expression variance in parasite resistance, allele

How important is importance for prospective memory? A review

PubMed Central

Walter, Stefan; Meier, Beat

2014-01-01

Forgetting to carry out an intention as planned can have serious consequences in everyday life. People sometimes even forget intentions that they consider as very important. Here, we review the literature on the impact of importance on prospective memory performance. We highlight different methods used to manipulate the importance of a prospective memory task such as providing rewards, importance relative to other ongoing activities, absolute importance, and providing social motives. Moreover, we address the relationship between importance and other factors known to affect prospective memory and ongoing task performance such as type of prospective memory task (time-, event-, or activity-based), cognitive loads, and processing overlaps. Finally, we provide a connection to motivation, we summarize the effects of task importance and we identify important venues for future research. PMID:25018743

[Strategies to identify supernumerary chromosomal markers in constitutional cytogenetics].

PubMed

Douet-Guilbert, N; Basinko, A; Le Bris, M-J; Herry, A; Morel, F; De Braekeleer, M

2008-09-01

Supernumerary marker chromosomes (SMCs) are defined as extrastructurally abnormal chromosomes which origin and composition cannot be determined by conventional cytogenetics. SMCs are an heterogeneous group of abnormalities concerning all chromosomes with variable structure and size and are associated with phenotypic heterogeneity. The characterisation of SMCs is of utmost importance for genetic counselling. Different molecular techniques are used to identify chromosomal material present in markers such as 24-colour FISH (MFISH, SKY), centromere specific multicolour FISH (cenMFISH) and derivatives (acroMFISH, subcenMFISH), comparative genomic hybridisation (CGH), arrayCGH, and targeted FISH techniques (banding techniques, whole chromosome painting...). Based on the morphology of SMC with conventional cytogenetic and clinical data, we tried to set up different molecular strategies with all available techniques.

Childhood Depression: Relation to Adaptive, Clinical and Predictor Variables

PubMed Central

Garaigordobil, Maite; Bernarás, Elena; Jaureguizar, Joana; Machimbarrena, Juan M.

2017-01-01

The study had two goals: (1) to explore the relations between self-assessed childhood depression and other adaptive and clinical variables (2) to identify predictor variables of childhood depression. Participants were 420 students aged 7–10 years old (53.3% boys, 46.7% girls). Results revealed: (1) positive correlations between depression and clinical maladjustment, school maladjustment, emotional symptoms, internalizing and externalizing problems, problem behaviors, emotional reactivity, and childhood stress; and (2) negative correlations between depression and personal adaptation, global self-concept, social skills, and resilience (sense of competence and affiliation). Linear regression analysis including the global dimensions revealed 4 predictors of childhood depression that explained 50.6% of the variance: high clinical maladjustment, low global self-concept, high level of stress, and poor social skills. However, upon introducing the sub-dimensions, 9 predictor variables emerged that explained 56.4% of the variance: many internalizing problems, low family self-concept, high anxiety, low responsibility, low personal self-assessment, high social stress, few aggressive behaviors toward peers, many health/psychosomatic problems, and external locus of control. The discussion addresses the importance of implementing prevention programs for childhood depression at early ages. PMID:28572787

Importance of multi-modal approaches to effectively identify cataract cases from electronic health records.

PubMed

Peissig, Peggy L; Rasmussen, Luke V; Berg, Richard L; Linneman, James G; McCarty, Catherine A; Waudby, Carol; Chen, Lin; Denny, Joshua C; Wilke, Russell A; Pathak, Jyotishman; Carrell, David; Kho, Abel N; Starren, Justin B

2012-01-01

There is increasing interest in using electronic health records (EHRs) to identify subjects for genomic association studies, due in part to the availability of large amounts of clinical data and the expected cost efficiencies of subject identification. We describe the construction and validation of an EHR-based algorithm to identify subjects with age-related cataracts. We used a multi-modal strategy consisting of structured database querying, natural language processing on free-text documents, and optical character recognition on scanned clinical images to identify cataract subjects and related cataract attributes. Extensive validation on 3657 subjects compared the multi-modal results to manual chart review. The algorithm was also implemented at participating electronic MEdical Records and GEnomics (eMERGE) institutions. An EHR-based cataract phenotyping algorithm was successfully developed and validated, resulting in positive predictive values (PPVs) >95%. The multi-modal approach increased the identification of cataract subject attributes by a factor of three compared to single-mode approaches while maintaining high PPV. Components of the cataract algorithm were successfully deployed at three other institutions with similar accuracy. A multi-modal strategy incorporating optical character recognition and natural language processing may increase the number of cases identified while maintaining similar PPVs. Such algorithms, however, require that the needed information be embedded within clinical documents. We have demonstrated that algorithms to identify and characterize cataracts can be developed utilizing data collected via the EHR. These algorithms provide a high level of accuracy even when implemented across multiple EHRs and institutional boundaries.

Importance of multi-modal approaches to effectively identify cataract cases from electronic health records

PubMed Central

Rasmussen, Luke V; Berg, Richard L; Linneman, James G; McCarty, Catherine A; Waudby, Carol; Chen, Lin; Denny, Joshua C; Wilke, Russell A; Pathak, Jyotishman; Carrell, David; Kho, Abel N; Starren, Justin B

2012-01-01

Objective There is increasing interest in using electronic health records (EHRs) to identify subjects for genomic association studies, due in part to the availability of large amounts of clinical data and the expected cost efficiencies of subject identification. We describe the construction and validation of an EHR-based algorithm to identify subjects with age-related cataracts. Materials and methods We used a multi-modal strategy consisting of structured database querying, natural language processing on free-text documents, and optical character recognition on scanned clinical images to identify cataract subjects and related cataract attributes. Extensive validation on 3657 subjects compared the multi-modal results to manual chart review. The algorithm was also implemented at participating electronic MEdical Records and GEnomics (eMERGE) institutions. Results An EHR-based cataract phenotyping algorithm was successfully developed and validated, resulting in positive predictive values (PPVs) >95%. The multi-modal approach increased the identification of cataract subject attributes by a factor of three compared to single-mode approaches while maintaining high PPV. Components of the cataract algorithm were successfully deployed at three other institutions with similar accuracy. Discussion A multi-modal strategy incorporating optical character recognition and natural language processing may increase the number of cases identified while maintaining similar PPVs. Such algorithms, however, require that the needed information be embedded within clinical documents. Conclusion We have demonstrated that algorithms to identify and characterize cataracts can be developed utilizing data collected via the EHR. These algorithms provide a high level of accuracy even when implemented across multiple EHRs and institutional boundaries. PMID:22319176

Pancreatic islet isolation variables in non-human primates (rhesus macaques).

PubMed

Andrades, P; Asiedu, C K; Gansuvd, B; Inusah, S; Goodwin, K J; Deckard, L A; Jargal, U; Thomas, J M

2008-07-01

Non-human primates (NHPs) are important preclinical models for pancreatic islet transplantation (PIT) because of their close phylogenetic and immunological relationship with humans. However, low availability of NHP tissue, long learning curves and prohibitive expenses constrain the consistency of isolated NHP islets for PIT studies. To advance preclinical studies, we attempted to identify key variables that consistently influence the quantity and quality of NHP islets. Seventy-two consecutive pancreatic islet isolations from rhesus macaques were reviewed retrospectively. A scaled down, semi-automated islet isolation method was used, and monkeys with streptozotocin-induced diabetes, weighing 3-7 kg, served as recipients for allotransplantation. We analysed the effects of 22 independent variables grouped as donor factors, surgical factors and isolation technique factors. Islet yields, success of isolation and transplantation results were used as quantitative and qualitative outcomes. In the multivariate analysis, variables that significantly affected islet yield were the type of monkey, pancreas preservation, enzyme lot and volume of enzyme delivered. The variables associated with successful isolation were the enzyme lot and volume delivered. The transplant result was correlated with pancreas preservation, enzyme lot, endotoxin levels and COBE collection method. Islet quantity and quality are highly variable between isolations. The data reviewed suggest that future NHP isolations should use bilayer preservation, infuse more than 80 ml of Liberase into the pancreas, collect non-fractioned tissue from the COBE, and strictly monitor for infection.

Evaluating the importance of policy amenable factors in explaining influenza vaccination: a cross-sectional multinational study

PubMed Central

Wheelock, Ana; Miraldo, Marisa; Thomson, Angus; Vincent, Charles; Sevdalis, Nick

2017-01-01

Objectives Despite continuous efforts to improve influenza vaccination coverage, uptake among high-risk groups remains suboptimal. We aimed to identify policy amenable factors associated with vaccination and to measure their importance in order to assist in the monitoring of vaccination sentiment and the design of communication strategies and interventions to improve vaccination rates. Setting The USA, the UK and France. Participants A total of 2412 participants were surveyed across the three countries. Outcome measures Self-reported influenza vaccination. Methods Between March and April 2014, a stratified random sampling strategy was employed with the aim of obtaining nationally representative samples in the USA, the UK and France through online databases and random-digit dialling. Participants were asked about vaccination practices, perceptions and feelings. Multivariable logistic regression was used to identify factors associated with past influenza vaccination. Results The models were able to explain 64%–80% of the variance in vaccination behaviour. Overall, sociopsychological variables, which are inherently amenable to policy, were better at explaining past vaccination behaviour than demographic, socioeconomic and health variables. Explanatory variables included social influence (physician), influenza and vaccine risk perceptions and traumatic childhood experiences. Conclusions Our results indicate that evidence-based sociopsychological items should be considered for inclusion into national immunisation surveys to gauge the public’s views, identify emerging concerns and thus proactively and opportunely address potential barriers and harness vaccination drivers. PMID:28706088

Intraindividual variability of sleep/wake patterns in relation to child and adolescent functioning: A systematic review.

PubMed

Becker, Stephen P; Sidol, Craig A; Van Dyk, Tori R; Epstein, Jeffery N; Beebe, Dean W

2017-08-01

Substantial research attention has been devoted to understanding the importance and impact of sleep in children and adolescents. Traditionally, this has focused on mean sleep variables (e.g., a child's "typical" or average sleep duration), yet research increasingly suggests that intraindividual variability (IIV) of sleep/wake patterns (sometimes referred to as sleep variability or night-to-night variability) regularly occurs and may have implications for adjustment. A systematic search of five electronic databases identified 52 empirical studies published between 2000 and 2015 that examined correlates of sleep IIV in children and adolescents, with a recent increase in the publication rate of such studies. Identified studies were often atheoretical and included post hoc analyses, though IIV in select aspects of sleep does appear to be associated with increasing age/pubertal status, non-White race, physical and neurodevelopmental conditions (e.g., attention-deficit/hyperactivity disorder; autism), psychopathology symptoms (e.g., anxiety, depression, inattention), body weight, stress, aspects of cognitive functioning, and poorer sleep functioning/habits. The limited intervention work examining sleep IIV in adolescents is promising, though studies are needed using more rigorous intervention designs. Clinical sleep recommendations may not only need to address overall sleep duration and sleep habits but also the stability of sleep duration and timing. It will be important for future research examining sleep IIV in children and adolescents to use a developmental framework in advancing theory pertaining to the causes, mechanisms, moderators, and outcomes of sleep IIV in youth, and a conceptual model is proposed to help guide such efforts. Copyright © 2016 Elsevier Ltd. All rights reserved.

Assessing the accuracy and stability of variable selection ...

EPA Pesticide Factsheets

Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological datasets there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used, or stepwise procedures are employed which iteratively add/remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating dataset consists of the good/poor condition of n=1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p=212) of landscape features from the StreamCat dataset. Two types of RF models are compared: a full variable set model with all 212 predictors, and a reduced variable set model selected using a backwards elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors, and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substanti

Identifying biotic integrity and water chemistry relations in nonwadeable rivers of Wisconsin: Toward the development of nutrient criteria

USGS Publications Warehouse

Weigel, B.M.; Robertson, Dale M.

2007-01-01

We sampled 41 sites on 34 nonwadeable rivers that represent the types of rivers in Wisconsin, and the kinds and intensities of nutrient and other anthropogenic stressors upon each river type. Sites covered much of United States Environmental Protection Agency national nutrient ecoregions VII-Mostly Glaciated Dairy Region, and VIII-Nutrient Poor, Largely Glaciated upper Midwest. Fish, macroinvertebrates, and three categories of environmental variables including nutrients, other water chemistry, and watershed features were collected using standard protocols. We summarized fish assemblages by index of biotic integrity (IBI) and its 10 component measures, and macroinvertebrates by 2 organic pollution tolerance and 12 proportional richness measures. All biotic and environmental variables represented a wide range of conditions, with biotic measures ranging from poor to excellent status, despite nutrient concentrations being consistently higher than reference concentrations reported for the regions. Regression tree analyses of nutrients on a suite of biotic measures identified breakpoints in total phosphorus (~0.06 mg/l) and total nitrogen (~0.64 mg/l) concentrations at which biotic assemblages were consistently impaired. Redundancy analyses (RDA) were used to identify the most important variables within each of the three environmental variable categories, which were then used to determine the relative influence of each variable category on the biota. Nutrient measures, suspended chlorophyll a, water clarity, and watershed land cover type (forest or row-crop agriculture) were the most important variables and they explained significant amounts of variation within the macroinvertebrate (R 2 = 60.6%) and fish (R 2 = 43.6%) assemblages. The environmental variables selected in the macroinvertebrate model were correlated to such an extent that partial RDA analyses could not attribute variation explained to individual environmental categories, assigning 89% of the explained

Identifying biotic integrity and water chemistry relations in nonwadeable rivers of Wisconsin: toward the development of nutrient criteria.

PubMed

Weigel, Brian M; Robertson, Dale M

2007-10-01

We sampled 41 sites on 34 nonwadeable rivers that represent the types of rivers in Wisconsin, and the kinds and intensities of nutrient and other anthropogenic stressors upon each river type. Sites covered much of United States Environmental Protection Agency national nutrient ecoregions VII--Mostly Glaciated Dairy Region, and VIII--Nutrient Poor, Largely Glaciated upper Midwest. Fish, macroinvertebrates, and three categories of environmental variables including nutrients, other water chemistry, and watershed features were collected using standard protocols. We summarized fish assemblages by index of biotic integrity (IBI) and its 10 component measures, and macroinvertebrates by 2 organic pollution tolerance and 12 proportional richness measures. All biotic and environmental variables represented a wide range of conditions, with biotic measures ranging from poor to excellent status, despite nutrient concentrations being consistently higher than reference concentrations reported for the regions. Regression tree analyses of nutrients on a suite of biotic measures identified breakpoints in total phosphorus (approximately 0.06 mg/l) and total nitrogen (approximately 0.64 mg/l) concentrations at which biotic assemblages were consistently impaired. Redundancy analyses (RDA) were used to identify the most important variables within each of the three environmental variable categories, which were then used to determine the relative influence of each variable category on the biota. Nutrient measures, suspended chlorophyll a, water clarity, and watershed land cover type (forest or row-crop agriculture) were the most important variables and they explained significant amounts of variation within the macroinvertebrate (R(2) = 60.6%) and fish (R(2) = 43.6%) assemblages. The environmental variables selected in the macroinvertebrate model were correlated to such an extent that partial RDA analyses could not attribute variation explained to individual environmental categories

Does ecosystem variability explain phytoplankton diversity? Solving an ecological puzzle with long-term data sets

NASA Astrophysics Data System (ADS)

Sarker, Subrata; Lemke, Peter; Wiltshire, Karen H.

2018-05-01

Explaining species diversity as a function of ecosystem variability is a long-term discussion in community-ecology research. Here, we aimed to establish a causal relationship between ecosystem variability and phytoplankton diversity in a shallow-sea ecosystem. We used long-term data on biotic and abiotic factors from Helgoland Roads, along with climate data to assess the effect of ecosystem variability on phytoplankton diversity. A point cumulative semi-variogram method was used to estimate the long-term ecosystem variability. A Markov chain model was used to estimate dynamical processes of species i.e. occurrence, absence and outcompete probability. We identified that the 1980s was a period of high ecosystem variability while the last two decades were comparatively less variable. Ecosystem variability was found as an important predictor of phytoplankton diversity at Helgoland Roads. High diversity was related to low ecosystem variability due to non-significant relationship between probability of a species occurrence and absence, significant negative relationship between probability of a species occurrence and probability of a species to be outcompeted by others, and high species occurrence at low ecosystem variability. Using an exceptional marine long-term data set, this study established a causal relationship between ecosystem variability and phytoplankton diversity.

Input variable selection and calibration data selection for storm water quality regression models.

PubMed

Sun, Siao; Bertrand-Krajewski, Jean-Luc

2013-01-01

Storm water quality models are useful tools in storm water management. Interest has been growing in analyzing existing data for developing models for urban storm water quality evaluations. It is important to select appropriate model inputs when many candidate explanatory variables are available. Model calibration and verification are essential steps in any storm water quality modeling. This study investigates input variable selection and calibration data selection in storm water quality regression models. The two selection problems are mutually interacted. A procedure is developed in order to fulfil the two selection tasks in order. The procedure firstly selects model input variables using a cross validation method. An appropriate number of variables are identified as model inputs to ensure that a model is neither overfitted nor underfitted. Based on the model input selection results, calibration data selection is studied. Uncertainty of model performances due to calibration data selection is investigated with a random selection method. An approach using the cluster method is applied in order to enhance model calibration practice based on the principle of selecting representative data for calibration. The comparison between results from the cluster selection method and random selection shows that the former can significantly improve performances of calibrated models. It is found that the information content in calibration data is important in addition to the size of calibration data.

Head lice prevalence among households in Norway: importance of spatial variables and individual and household characteristics

PubMed Central

RUKKE, BJØRN ARNE; BIRKEMOE, TONE; SOLENG, ARNULF; LINDSTEDT, HEIDI HEGGEN; OTTESEN, PREBEN

2011-01-01

SUMMARY Head lice prevalence varies greatly between and within countries, and more knowledge is needed to approach causes of this variation. In the present study, we investigated head lice prevalence among elementary school students and their households in relation to individual and household characteristics as well as spatial variables. The investigation included households from 5 geographically separated municipalities. Present infestations among household members as well as previous infestations in the household were reported in a questionnaire. In elementary school students prevalence was low (1·63%), but more than one-third of the households (36·43%) had previously experienced pediculosis. Prevalence was higher in elementary school students than in other household members, and highest in third-grade children. Prevalence was also influenced by the school attended, which suggested that interactions between children in the same school are important for head lice transmission. Previous occurrence of head lice in homes also increased the risk of present infestation. Prevalence of previous infestations was higher in households with more children and in more densely populated municipalities, indicating that the density of hosts or groups of hosts influences transmission rates. These results demonstrate that information of hosts’ spatial distribution as well as household and individual characteristics is needed to better understand head lice population dynamics. PMID:21767439

Head lice prevalence among households in Norway: importance of spatial variables and individual and household characteristics.

PubMed

Rukke, Bjørn Arne; Birkemoe, Tone; Soleng, Arnulf; Lindstedt, Heidi Heggen; Ottesen, Preben

2011-09-01

Head lice prevalence varies greatly between and within countries, and more knowledge is needed to approach causes of this variation. In the present study, we investigated head lice prevalence among elementary school students and their households in relation to individual and household characteristics as well as spatial variables. The investigation included households from 5 geographically separated municipalities. Present infestations among household members as well as previous infestations in the household were reported in a questionnaire. In elementary school students prevalence was low (1·63%), but more than one-third of the households (36·43%) had previously experienced pediculosis. Prevalence was higher in elementary school students than in other household members, and highest in third-grade children. Prevalence was also influenced by the school attended, which suggested that interactions between children in the same school are important for head lice transmission. Previous occurrence of head lice in homes also increased the risk of present infestation. Prevalence of previous infestations was higher in households with more children and in more densely populated municipalities, indicating that the density of hosts or groups of hosts influences transmission rates. These results demonstrate that information of hosts' spatial distribution as well as household and individual characteristics is needed to better understand head lice population dynamics.

Comparative genomics of biotechnologically important yeasts

PubMed Central

Riley, Robert; Haridas, Sajeet; Wolfe, Kenneth H.; Lopes, Mariana R.; Hittinger, Chris Todd; Göker, Markus; Salamov, Asaf A.; Wisecaver, Jennifer H.; Long, Tanya M.; Aerts, Andrea L.; Barry, Kerrie W.; Choi, Cindy; Clum, Alicia; Coughlan, Aisling Y.; Deshpande, Shweta; Douglass, Alexander P.; Hanson, Sara J.; Klenk, Hans-Peter; LaButti, Kurt M.; Lapidus, Alla; Lindquist, Erika A.; Lipzen, Anna M.; Meier-Kolthoff, Jan P.; Ohm, Robin A.; Otillar, Robert P.; Pangilinan, Jasmyn L.; Peng, Yi; Rosa, Carlos A.; Scheuner, Carmen; Sibirny, Andriy A.; Slot, Jason C.; Stielow, J. Benjamin; Sun, Hui; Kurtzman, Cletus P.; Blackwell, Meredith; Grigoriev, Igor V.

2016-01-01

Ascomycete yeasts are metabolically diverse, with great potential for biotechnology. Here, we report the comparative genome analysis of 29 taxonomically and biotechnologically important yeasts, including 16 newly sequenced. We identify a genetic code change, CUG-Ala, in Pachysolen tannophilus in the clade sister to the known CUG-Ser clade. Our well-resolved yeast phylogeny shows that some traits, such as methylotrophy, are restricted to single clades, whereas others, such as l-rhamnose utilization, have patchy phylogenetic distributions. Gene clusters, with variable organization and distribution, encode many pathways of interest. Genomics can predict some biochemical traits precisely, but the genomic basis of others, such as xylose utilization, remains unresolved. Our data also provide insight into early evolution of ascomycetes. We document the loss of H3K9me2/3 heterochromatin, the origin of ascomycete mating-type switching, and panascomycete synteny at the MAT locus. These data and analyses will facilitate the engineering of efficient biosynthetic and degradative pathways and gateways for genomic manipulation. PMID:27535936

Symptoms of subordinated importance in fibromyalgia when differentiating working from non-working women.

PubMed

Liedberg And, G M; Björk, M

2014-01-01

The aim was to identify differences in self-reported symptoms among working (W) and non-working (NW) women, and to determine the most important biopsychosocial variables in differentiating one group from the other. A questionnaire was mailed to 524 members of a local chapter of the Swedish Rheumatology Association. A total of 362 persons responded (69%); 96% of which were women. Women older than 64 years and all men were excluded. The final study group consisted of 95 W, and 227 NW women. The questionnaire included data on demographics, employment, support, exercise, daily activities and symptoms. Data were analysed using univariate statistics and a partial least squares discriminant analysis (PLS-DA). The results showed that 41% of the W and 42% of the NW women were/had been employed in service,care or business. The NW women reported a significantly higher severity of symptoms compared with the W women. The most important variable when differentiating the W from the NW women was social support from colleagues and employers. To change prevailing attitudes and values towards persons with a work disability, a process of active intervention involving staff is needed. Educating employers as to how a disability may influence a work situation, and the importance of social support, can be improved.

Beyond imperviousness: A statistical approach to identifying functional differences between development morphologies on variable source area-type response in urbanized watersheds

NASA Astrophysics Data System (ADS)

Lim, T. C.

2016-12-01

Empirical evidence has shown linkages between urbanization, hydrological regime change, and degradation of water quality and aquatic habitat. Percent imperviousness, has long been suggested as the dominant source of these negative changes. However, recent research identifying alternative pathways of runoff production at the watershed scale have called into question percent impervious surface area's primacy in urban runoff production compared to other aspects of urbanization including change in vegetative cover, imported water and water leakages, and the presence of drainage infrastructure. In this research I show how a robust statistical methodology can detect evidence of variable source area (VSA)-type hydrologic response associated with incremental hydraulic connectivity in watersheds. I then use logistic regression to explore how evidence of VSA-type response relates to the physical and meterological characteristics of the watershed. I find that impervious surface area is highly correlated with development, but does not add significant explanatory power beyond percent developed in predicting VSA-type response. Other aspects of development morphology, including percent developed open space and type of drainage infrastructure also do not add to the explanatory power of undeveloped land in predicting VSA-type response. Within only developed areas, the effect of developed open space was found to be more similar to that of total impervious area than to undeveloped land. These findings were consistent when tested across a national cross-section of urbanized watersheds, a higher resolution dataset of Baltimore Metropolitan Area watersheds, and a subsample of watersheds confirmed not to be served by combined sewer systems. These findings suggest that land development policies that focus on lot coverage should be revisited, and more focus should be placed on preserving native vegetation and soil conditions alongside development.

Wireless Monitoring of Induction Machine Rotor Physical Variables

PubMed Central

Doolan Fernandes, Jefferson; Carvalho Souza, Francisco Elvis; de Paiva, José Alvaro

2017-01-01

With the widespread use of electric machines, there is a growing need to extract information from the machines to improve their control systems and maintenance management. The present work shows the development of an embedded system to perform the monitoring of the rotor physical variables of a squirrel cage induction motor. The system is comprised of: a circuit to acquire desirable rotor variable(s) and value(s) that send it to the computer; a rectifier and power storage circuit that converts an alternating current in a continuous current but also stores energy for a certain amount of time to wait for the motor’s shutdown; and a magnetic generator that harvests energy from the rotating field to power the circuits mentioned above. The embedded system is set on the rotor of a 5 HP squirrel cage induction motor, making it difficult to power the system because it is rotating. This problem can be solved with the construction of a magnetic generator device to avoid the need of using batteries or collector rings and will send data to the computer using a wireless NRF24L01 module. For the proposed system, initial validation tests were made using a temperature sensor (DS18b20), as this variable is known as the most important when identifying the need for maintenance and control systems. Few tests have shown promising results that, with further improvements, can prove the feasibility of using sensors in the rotor. PMID:29156564

Wireless Monitoring of Induction Machine Rotor Physical Variables.

PubMed

Doolan Fernandes, Jefferson; Carvalho Souza, Francisco Elvis; Cipriano Maniçoba, Glauco George; Salazar, Andrés Ortiz; de Paiva, José Alvaro

2017-11-18

With the widespread use of electric machines, there is a growing need to extract information from the machines to improve their control systems and maintenance management. The present work shows the development of an embedded system to perform the monitoring of the rotor physical variables of a squirrel cage induction motor. The system is comprised of: a circuit to acquire desirable rotor variable(s) and value(s) that send it to the computer; a rectifier and power storage circuit that converts an alternating current in a continuous current but also stores energy for a certain amount of time to wait for the motor's shutdown; and a magnetic generator that harvests energy from the rotating field to power the circuits mentioned above. The embedded system is set on the rotor of a 5 HP squirrel cage induction motor, making it difficult to power the system because it is rotating. This problem can be solved with the construction of a magnetic generator device to avoid the need of using batteries or collector rings and will send data to the computer using a wireless NRF24L01 module. For the proposed system, initial validation tests were made using a temperature sensor (DS18b20), as this variable is known as the most important when identifying the need for maintenance and control systems. Few tests have shown promising results that, with further improvements, can prove the feasibility of using sensors in the rotor.

Spatio-temporal atmospheric circulation variability around the Antarctic Peninsula based on hemispheric circulation modes and weather types

NASA Astrophysics Data System (ADS)

Wachter, Paul; Beck, Christoph; Philipp, Andreas; Jacobeit, Jucundus; Höppner, Kathrin

2017-04-01

Large parts of the Polar Regions are affected by a warming trend associated with substantial changes in the cryosphere. In Antarctica this positive trend pattern is most dominant in the western part of the continent and on the Antarctic Peninsula (AP). An important driving mechanism of temperature variability and trends in this region is the atmospheric circulation. Changes in atmospheric circulation modes and frequencies of circulation types have major impacts on temperature characteristics at a certain station or region. We present results of a statistical downscaling study focused on AP temperature variability showing both results of large-scale atmospheric circulation modes and regional weather type classifications derived from monthly and daily gridded reanalysis data sets. In order to investigate spatial trends and variabilities of the Southern Annular Mode (SAM), we analyze spatio-temporally resolved SAM-pattern maps from 1979 to 2015. First results show dominant multi-annual to decadal pattern variabilities which can be directly linked to temperature variabilities at the Antarctic Peninsula. A sub-continental to regional view on the influence of atmospheric circulation on AP temperature variability is given by the analysis of weather type classifications (WTC). With this analysis we identify significant changes in the frequency of occurrence of highly temperature-relevant circulation patterns. The investigated characteristics of weather type frequencies can also be related to the identified changes of the SAM.

Application of an artificial neural network model for diagnosing type 2 diabetes mellitus and determining the relative importance of risk factors.

PubMed

Borzouei, Shiva; Soltanian, Ali Reza

2018-01-01

To identify the most important demographic risk factors for a diagnosis of type 2 diabetes mellitus (T2DM) using a neural network model. This study was conducted on a sample of 234 individuals, in whom T2DM was diagnosed using hemoglobin A1c levels. A multilayer perceptron artificial neural network was used to identify demographic risk factors for T2DM and their importance. The DeLong method was used to compare the models by fitting in sequential steps. Variables found to be significant at a level of p<0.2 in a univariate logistic regression analysis (age, hypertension, waist circumference, body mass index [BMI], sedentary lifestyle, smoking, vegetable consumption, family history of T2DM, stress, walking, fruit consumption, and sex) were entered into the model. After 7 stages of neural network modeling, only waist circumference (100.0%), age (78.5%), BMI (78.2%), hypertension (69.4%), stress (54.2%), smoking (49.3%), and a family history of T2DM (37.2%) were identified as predictors of the diagnosis of T2DM. In this study, waist circumference and age were the most important predictors of T2DM. Due to the sensitivity, specificity, and accuracy of the final model, it is suggested that these variables should be used for T2DM risk assessment in screening tests.

Identifying Important Atlantic Areas for the conservation of Balearic shearwaters: Spatial overlap with conservation areas

NASA Astrophysics Data System (ADS)

Pérez-Roda, Amparo; Delord, Karine; Boué, Amélie; Arcos, José Manuel; García, David; Micol, Thierry; Weimerskirch, Henri; Pinaud, David; Louzao, Maite

2017-07-01

Marine protected areas (MPAs) are considered one of the main tools in both fisheries and conservation management to protect threatened species and their habitats around the globe. However, MPAs are underrepresented in marine environments compared to terrestrial environments. Within this context, we studied the Atlantic non-breeding distribution of the southern population of Balearic shearwaters (Puffinus mauretanicus) breeding in Eivissa during the 2011-2012 period based on global location sensing (GLS) devices. Our objectives were (1) to identify overall Important Atlantic Areas (IAAs) from a southern population, (2) to describe spatio-temporal patterns of oceanographic habitat use, and (3) to assess whether existing conservation areas (Natura 2000 sites and marine Important Bird Areas (IBAs)) cover the main IAAs of Balearic shearwaters. Our results highlighted that the Atlantic staging (from June to October in 2011) dynamic of the southern population was driven by individual segregation at both spatial and temporal scales. Individuals ranged in the North-East Atlantic over four main IAAs (Bay of Biscay: BoB, Western Iberian shelf: WIS, Gulf of Cadiz: GoC, West of Morocco: WoM). While most individuals spent more time on the WIS or in the GoC, a small number of birds visited IAAs at the extremes of their Atlantic distribution range (i.e., BoB and WoM). The chronology of the arrivals to the IAAs showed a latitudinal gradient with northern areas reached earlier during the Atlantic staging. The IAAs coincided with the most productive areas (higher chlorophyll a values) in the NE Atlantic between July and October. The spatial overlap between IAAs and conservation areas was higher for Natura 2000 sites than marine IBAs (areas with and without legal protection, respectively). Concerning the use of these areas, a slightly higher proportion of estimated positions fell within marine IBAs compared to designated Natura 2000 sites, with Spanish and Portuguese conservation

Temporal variability of glucocorticoid receptor activity is functionally important for the therapeutic action of fluoxetine in the hippocampus.

PubMed

Lee, M-S; Kim, Y-H; Park, W-S; Park, O-K; Kwon, S-H; Hong, K S; Rhim, H; Shim, I; Morita, K; Wong, D L; Patel, P D; Lyons, D M; Schatzberg, A F; Her, S

2016-02-01

Previous studies have shown inconsistent results regarding the actions of antidepressants on glucocorticoid receptor (GR) signalling. To resolve these inconsistencies, we used a lentiviral-based reporter system to directly monitor rat hippocampal GR activity during stress adaptation. Temporal GR activation was induced significantly by acute stress, as demonstrated by an increase in the intra-individual variability of the acute stress group compared with the variability of the non-stress group. However, the increased intra-individual variability was dampened by exposure to chronic stress, which was partly restored by fluoxetine treatment without affecting glucocorticoid secretion. Immobility in the forced-swim test was negatively correlated with the intra-individual variability, but was not correlated with the quantitative GR activity during fluoxetine therapy; this highlights the temporal variability in the neurobiological links between GR signalling and the therapeutic action of fluoxetine. Furthermore, we demonstrated sequential phosphorylation between GR (S224) and (S232) following fluoxetine treatment, showing a molecular basis for hormone-independent nuclear translocation and transcriptional enhancement. Collectively, these results suggest a neurobiological mechanism by which fluoxetine treatment confers resilience to the chronic stress-mediated attenuation of hypothalamic-pituitary-adrenal axis activity.

Climate variability drives recent tree mortality in Europe.

PubMed

Neumann, Mathias; Mues, Volker; Moreno, Adam; Hasenauer, Hubert; Seidl, Rupert

2017-11-01

Tree mortality is an important process in forest ecosystems, frequently hypothesized to be highly climate sensitive. Yet, tree death remains one of the least understood processes of forest dynamics. Recently, changes in tree mortality have been observed in forests around the globe, which could profoundly affect ecosystem functioning and services provisioning to society. We describe continental-scale patterns of recent tree mortality from the only consistent pan-European forest monitoring network, identifying recent mortality hotspots in southern and northern Europe. Analyzing 925,462 annual observations of 235,895 trees between 2000 and 2012, we determine the influence of climate variability and tree age on interannual variation in tree mortality using Cox proportional hazard models. Warm summers as well as high seasonal variability in precipitation increased the likelihood of tree death. However, our data also suggest that reduced cold-induced mortality could compensate increased mortality related to peak temperatures in a warming climate. Besides climate variability, age was an important driver of tree mortality, with individual mortality probability decreasing with age over the first century of a trees life. A considerable portion of the observed variation in tree mortality could be explained by satellite-derived net primary productivity, suggesting that widely available remote sensing products can be used as an early warning indicator of widespread tree mortality. Our findings advance the understanding of patterns of large-scale tree mortality by demonstrating the influence of seasonal and diurnal climate variation, and highlight the potential of state-of-the-art remote sensing to anticipate an increased likelihood of tree mortality in space and time. © 2017 John Wiley & Sons Ltd.

Variability of western Amazon dry-season precipitation extremes: importance of decadal fluctuations and implications for predictability

NASA Astrophysics Data System (ADS)

Fernandes, K.; Baethgen, W.; Verchot, L. V.; Giannini, A.; Pinedo-Vasquez, M.

2014-12-01

A complete assessment of climate change projections requires understanding the combined effects of decadal variability and long-term trends and evaluating the ability of models to simulate them. The western Amazon severe droughts of the 2000s were the result of a modest drying trend enhanced by reduced moisture transport from the tropical Atlantic. Most of the WA dry-season precipitation decadal variability is attributable to decadal fluctuations of the north-south gradient (NSG) in Atlantic sea surface temperature (SST). The observed WA and NSG decadal co-variability is well reproduced in Global Climate Models (GCMs) pre-industrial control (PIC) and historical (HIST) experiments that were part of the Intergovernmental Panel on Climate Change fifth assessment report (IPCC-AR5). This suggests that unforced or natural climate variability, characteristic of the PIC simulations, determines the nature of this coupling, as the results from HIST simulations (forced with greenhouse gases (GHG) and natural and anthropogenic aerosols) are comparable in magnitude and spatial distribution. Decadal fluctuation in the NSG also determines shifts in the probability of repeated droughts and pluvials in WA, as there is a 65% chance of 3 or more years of droughts per decade when NSG>0 compared to 18% when NSG<0. The HIST and PIC model simulations also reproduce the observed shifts in probability distribution of droughts and pluvials as a function of the NSG decadal phase, suggesting there is great potential for decadal predictability based on GCMs. Persistence of the current NSG positive phase may lead to continuing above normal frequencies of western Amazon dry-season droughts.

What Does It Take to Change an Editor's Mind? Identifying Minimally Important Difference Thresholds for Peer Reviewer Rating Scores of Scientific Articles.

PubMed

Callaham, Michael; John, Leslie K

2018-01-05

We define a minimally important difference for the Likert-type scores frequently used in scientific peer review (similar to existing minimally important differences for scores in clinical medicine). The magnitude of score change required to change editorial decisions has not been studied, to our knowledge. Experienced editors at a journal in the top 6% by impact factor were asked how large a change of rating in "overall desirability for publication" was required to trigger a change in their initial decision on an article. Minimally important differences were assessed twice for each editor: once assessing the rating change required to shift the editor away from an initial decision to accept, and the other assessing the magnitude required to shift away from an initial rejection decision. Forty-one editors completed the survey (89% response rate). In the acceptance frame, the median minimally important difference was 0.4 points on a scale of 1 to 5. Editors required a greater rating change to shift from an initial rejection decision; in the rejection frame, the median minimally important difference was 1.2 points. Within each frame, there was considerable heterogeneity: in the acceptance frame, 38% of editors did not change their decision within the maximum available range; in the rejection frame, 51% did not. To our knowledge, this is the first study to determine the minimally important difference for Likert-type ratings of research article quality, or in fact any nonclinical scientific assessment variable. Our findings may be useful for future research assessing whether changes to the peer review process produce clinically meaningful differences in editorial decisionmaking. Copyright © 2017 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

Identifying factors which enhance capacity to engage in clinical education among podiatry practitioners: an action research project.

PubMed

Abey, Sally; Lea, Susan; Callaghan, Lynne; Shaw, Steve; Cotton, Debbie

2015-01-01

Health profession students develop practical skills whilst integrating theory with practice in a real world environment as an important component of their training. Research in the area of practice placements has identified challenges and barriers to the delivery of effective placement learning. However, there has been little research in podiatry and the question of which factors impact upon clinical educators' capacity to engage with the role remains an under-researched area. This paper presents the second phase of an action research project designed to determine the factors that impact upon clinical educators' capacity to engage with the mentorship role. An online survey was developed and podiatry clinical educators recruited through National Health Service (NHS) Trusts. The survey included socio-demographic items, and questions relating to the factors identified as possible variables influencing clinical educator capacity; the latter was assessed using the 'Clinical Educator Capacity to Engage' scale (CECE). Descriptive statistics were used to explore demographic data whilst the relationship between the CECE and socio-demographic factors were examined using inferential statistics in relation to academic profile, career profile and organisation of the placement. The survey response rate was 42 % (n = 66). Multiple linear regression identified four independent variables which explain a significant proportion of the variability of the dependent variable, 'capacity to engage with clinical education', with an adjusted R2 of 0.428. The four variables were: protected mentorship time, clinical educator relationship with university, sign-off responsibility, and volunteer status. The identification of factors that impact upon clinical educators' capacity to engage in mentoring of students has relevance for strategic planning and policy-making with the emphasis upon capacity-building at an individual level, so that the key attitudes and characteristics that are linked

Parenting Behaviors, Parent Heart Rate Variability, and Their Associations with Adolescent Heart Rate Variability.

PubMed

Graham, Rebecca A; Scott, Brandon G; Weems, Carl F

2017-05-01

Adolescence is a potentially important time in the development of emotion regulation and parenting behaviors may play a role. We examined associations among parenting behaviors, parent resting heart rate variability, adolescent resting heart rate variability and parenting behaviors as moderators of the association between parent and adolescent resting heart rate variability. Ninety-seven youth (11-17 years; 49.5 % female; 34 % African American, 37.1 % Euro-American, 22.6 % other/mixed ethnic background, and 7.2 % Hispanic) and their parents (n = 81) completed a physiological assessment and questionnaires assessing parenting behaviors. Inconsistent discipline and corporal punishment were negatively associated with adolescent resting heart rate variability, while positive parenting and parental involvement were positively associated. Inconsistent discipline and parental involvement moderated the relationship between parent and adolescent resting heart rate variability. The findings provide evidence for a role of parenting behaviors in shaping the development of adolescent resting heart rate variability with inconsistent discipline and parental involvement potentially influencing the entrainment of resting heart rate variability in parents and their children.

Identifying Human Factors Issues in Aircraft Maintenance Operations

NASA Technical Reports Server (NTRS)

Veinott, Elizabeth S.; Kanki, Barbara G.; Shafto, Michael G. (Technical Monitor)

1995-01-01

Maintenance operations incidents submitted to the Aviation Safety Reporting System (ASRS) between 1986-1992 were systematically analyzed in order to identify issues relevant to human factors and crew coordination. This exploratory analysis involved 95 ASRS reports which represented a wide range of maintenance incidents. The reports were coded and analyzed according to the type of error (e.g, wrong part, procedural error, non-procedural error), contributing factors (e.g., individual, within-team, cross-team, procedure, tools), result of the error (e.g., aircraft damage or not) as well as the operational impact (e.g., aircraft flown to destination, air return, delay at gate). The main findings indicate that procedural errors were most common (48.4%) and that individual and team actions contributed to the errors in more than 50% of the cases. As for operational results, most errors were either corrected after landing at the destination (51.6%) or required the flight crew to stop enroute (29.5%). Interactions among these variables are also discussed. This analysis is a first step toward developing a taxonomy of crew coordination problems in maintenance. By understanding what variables are important and how they are interrelated, we may develop intervention strategies that are better tailored to the human factor issues involved.

Identification of critical process variables affecting particle size following precipitation using a supercritical fluid.

PubMed

Sacha, Gregory A; Schmitt, William J; Nail, Steven L

2006-01-01

The critical processing parameters affecting average particle size, particle size distribution, yield, and level of residual carrier solvent using the supercritical anti-solvent method (SAS) were identified. Carbon dioxide was used as the supercritical fluid. Methylprednisolone acetate was used as the model solute in tetrahydrofuran. Parameters examined included pressure of the supercritical fluid, agitation rate, feed solution flow rate, impeller diameter, and nozzle design. Pressure was identified as the most important process parameter affecting average particle size, either through the effect of pressure on dispersion of the feed solution into the precipitation vessel or through the effect of pressure on solubility of drug in the CO2/organic solvent mixture. Agitation rate, impeller diameter, feed solution flow rate, and nozzle design had significant effects on particle size, which suggests that dispersion of the feed solution is important. Crimped HPLC tubing was the most effective method of introducing feed solution into the precipitation vessel, largely because it resulted in the least amount of clogging during the precipitation. Yields of 82% or greater were consistently produced and were not affected by the processing variables. Similarly, the level of residual solvent was independent of the processing variables and was present at 0.0002% wt/wt THF or less.

Neuroticism Combined With Slower and More Variable Reaction Time: Synergistic Risk Factors for 7-Year Cognitive Decline in Females

PubMed Central

Shickle, Darren A.; Roberts, Beverly A.; Deary, Ian J.

2012-01-01

Objective. Among adults, slower and more variable reaction times are associated with worse cognitive function and increased mortality risk. Therefore, it is important to elucidate risk factors for reaction time change over the life course. Method. Data from the Health and Lifestyle Survey (HALS) were used to examine predictors of 7-year decline in reaction time (N = 4,260). Regression-derived factor scores were used to summarize general change across 4 reaction time variables: simple mean, 4-choice mean, simple variability, and 4-choice variability (53.52% of variance). Results. Age (B = .02, p < .001) and HALS1 baseline reaction time (B = −.10, p = .001) were significant risk factors for males (N = 1,899). In addition to these variables, in females (N = 2,361), neuroticism was significant and interacted synergistically with baseline reaction time (B = .06, p = .04). Adjustment for physiological variables explained the interaction with neuroticism, suggesting that candidate mechanisms had been identified. Discussion. A priority for future research is to replicate interactions between personality and reaction time in other samples and find specific mechanisms. Stratification of population data on cognitive health by personality and reaction time could improve strategies for identifying those at greater risk of cognitive decline. PMID:22367712

Biodiversity in canopy-forming algae: Structure and spatial variability of the Mediterranean Cystoseira assemblages

NASA Astrophysics Data System (ADS)

Piazzi, L.; Bonaviri, C.; Castelli, A.; Ceccherelli, G.; Costa, G.; Curini-Galletti, M.; Langeneck, J.; Manconi, R.; Montefalcone, M.; Pipitone, C.; Rosso, A.; Pinna, S.

2018-07-01

In the Mediterranean Sea, Cystoseira species are the most important canopy-forming algae in shallow rocky bottoms, hosting high biodiverse sessile and mobile communities. A large-scale study has been carried out to investigate the structure of the Cystoseira-dominated assemblages at different spatial scales and to test the hypotheses that alpha and beta diversity of the assemblages, the abundance and the structure of epiphytic macroalgae, epilithic macroalgae, sessile macroinvertebrates and mobile macroinvertebrates associated to Cystoseira beds changed among scales. A hierarchical sampling design in a total of five sites across the Mediterranean Sea (Croatia, Montenegro, Sardinia, Tuscany and Balearic Islands) was used. A total of 597 taxa associated to Cystoseira beds were identified with a mean number per sample ranging between 141.1 ± 6.6 (Tuscany) and 173.9 ± 8.5(Sardinia). A high variability at small (among samples) and large (among sites) scale was generally highlighted, but the studied assemblages showed different patterns of spatial variability. The relative importance of the different scales of spatial variability should be considered to optimize sampling designs and propose monitoring plans of this habitat.

Variability of Massive Young Stellar Objects in Cygnus-X

NASA Astrophysics Data System (ADS)

Thomas, Nancy H.; Hora, J. L.; Smith, H. A.

2013-01-01

Young stellar objects (YSOs) are stars in the process of formation. Several recent investigations have shown a high rate of photometric variability in YSOs at near- and mid-infrared wavelengths. Theoretical models for the formation of massive stars (1-10 solar masses) remain highly idealized, and little is known about the mechanisms that produce the variability. An ongoing Spitzer Space Telescope program is studying massive star formation in the Cygnus-X region. In conjunction with the Spitzer observations, we have conducted a ground-based near-infrared observing program of the Cygnus-X DR21 field using PAIRITEL, the automated infrared telescope at Whipple Observatory. Using the Stetson index for variability, we identified variable objects and a number of variable YSOs in our time-series PAIRITEL data of DR21. We have searched for periodicity among our variable objects using the Lomb-Scargle algorithm, and identified periodic variable objects with an average period of 8.07 days. Characterization of these variable and periodic objects will help constrain models of star formation present. This work is supported in part by the NSF REU and DOD ASSURE programs under NSF grant no. 0754568 and by the Smithsonian Institution.

Two centuries of observed atmospheric variability and change over the North Sea region

NASA Astrophysics Data System (ADS)

Stendel, Martin; van den Besselaar, Else; Hannachi, Abdel; Kent, Elizabeth; Lefebvre, Christiana; van Oldenborgh, Geert Jan; Rosenhagen, Gudrun; Schenk, Frederik; van der Schrier, Gerard

2015-04-01

Situated in northwestern Europe, the North Sea region is under influence of air masses from subtropical to arctic origin, and thus exhibits significant natural climate variability. As the land areas surrounding the North Sea are densely populated, climate change is an important issue in terms of e.g. coastal protection, fishery and trade. This study is part of the NOSCCA initiative (North Sea Region Climate Change Assessment) and presents observed variability and changes in atmospheric parameters during the last roughly 200 years. Circulation patterns show considerable decadal variability. In recent decades, a northward shift of storm tracks and increased cyclonic activity has been observed. There is also an indication of increased persistence of weather types. The wind climate is dominated by large multidecadal variability, and no robust long-term trends can be identified in the available datasets. There is a clear positive trend in near-surface temperatures, in particular during spring and winter. Over the region as a whole, no clear long-term precipitation trends are visible, although regional indications exist for an increased risk of extreme precipitation events.

Environmental variables measured at multiple spatial scales exert uneven influence on fish assemblages of floodplain lakes

USGS Publications Warehouse

Dembkowski, Daniel J.; Miranda, Leandro E.

2014-01-01

We examined the interaction between environmental variables measured at three different scales (i.e., landscape, lake, and in-lake) and fish assemblage descriptors across a range of over 50 floodplain lakes in the Mississippi Alluvial Valley of Mississippi and Arkansas. Our goal was to identify important local- and landscape-level determinants of fish assemblage structure. Relationships between fish assemblage structure and variables measured at broader scales (i.e., landscape-level and lake-level) were hypothesized to be stronger than relationships with variables measured at finer scales (i.e., in-lake variables). Results suggest that fish assemblage structure in floodplain lakes was influenced by variables operating on three different scales. However, and contrary to expectations, canonical correlations between in-lake environmental characteristics and fish assemblage structure were generally stronger than correlations between landscape-level and lake-level variables and fish assemblage structure, suggesting a hierarchy of influence. From a resource management perspective, our study suggests that landscape-level and lake-level variables may be manipulated for conservation or restoration purposes, and in-lake variables and fish assemblage structure may be used to monitor the success of such efforts.

Variability in size-selective mortality obscures the importance of larval traits to recruitment success in a temperate marine fish.

PubMed

Murphy, Hannah M; Warren-Myers, Fletcher W; Jenkins, Gregory P; Hamer, Paul A; Swearer, Stephen E

2014-08-01

In fishes, the growth-mortality hypothesis has received broad acceptance as a driver of recruitment variability. Recruitment is likely to be lower in years when the risk of starvation and predation in the larval stage is greater, leading to higher mortality. Juvenile snapper, Pagrus auratus (Sparidae), experience high recruitment variation in Port Phillip Bay, Australia. Using a 5-year (2005, 2007, 2008, 2010, 2011) data set of larval and juvenile snapper abundances and their daily growth histories, based on otolith microstructure, we found selective mortality acted on larval size at 5 days post-hatch in 4 low and average recruitment years. The highest recruitment year (2005) was characterised by no size-selective mortality. Larval growth of the initial larval population was related to recruitment, but larval growth of the juveniles was not. Selective mortality may have obscured the relationship between larval traits of the juveniles and recruitment as fast-growing and large larvae preferentially survived in lower recruitment years and fast growth was ubiquitous in high recruitment years. An index of daily mortality within and among 3 years (2007, 2008, 2010), where zooplankton were concurrently sampled with ichthyoplankton, was related to per capita availability of preferred larval prey, providing support for the match-mismatch hypothesis. In 2010, periods of low daily mortality resulted in no selective mortality. Thus both intra- and inter-annual variability in the magnitude and occurrence of selective mortality in species with complex life cycles can obscure relationships between larval traits and population replenishment, leading to underestimation of their importance in recruitment studies.

The relationship between biomechanical variables and driving performance during the golf swing.

PubMed

Chu, Yungchien; Sell, Timothy C; Lephart, Scott M

2010-09-01

Swing kinematic and ground reaction force data from 308 golfers were analysed to identify the variables important to driving ball velocity. Regression models were applied at four selected events in the swing. The models accounted for 44-74% of variance in ball velocity. Based on the regression analyses, upper torso-pelvis separation (the X-Factor), delayed release (i.e. the initiation of movement) of the arms and wrists, trunk forward and lateral tilting, and weight-shifting during the swing were significantly related to ball velocity. Our results also verify several general coaching ideas that were considered important to increased ball velocity. The results of this study may serve as both skill and strength training guidelines for golfers.

Computational methods using genome-wide association studies to predict radiotherapy complications and to identify correlative molecular processes

NASA Astrophysics Data System (ADS)

Oh, Jung Hun; Kerns, Sarah; Ostrer, Harry; Powell, Simon N.; Rosenstein, Barry; Deasy, Joseph O.

2017-02-01

The biological cause of clinically observed variability of normal tissue damage following radiotherapy is poorly understood. We hypothesized that machine/statistical learning methods using single nucleotide polymorphism (SNP)-based genome-wide association studies (GWAS) would identify groups of patients of differing complication risk, and furthermore could be used to identify key biological sources of variability. We developed a novel learning algorithm, called pre-conditioned random forest regression (PRFR), to construct polygenic risk models using hundreds of SNPs, thereby capturing genomic features that confer small differential risk. Predictive models were trained and validated on a cohort of 368 prostate cancer patients for two post-radiotherapy clinical endpoints: late rectal bleeding and erectile dysfunction. The proposed method results in better predictive performance compared with existing computational methods. Gene ontology enrichment analysis and protein-protein interaction network analysis are used to identify key biological processes and proteins that were plausible based on other published studies. In conclusion, we confirm that novel machine learning methods can produce large predictive models (hundreds of SNPs), yielding clinically useful risk stratification models, as well as identifying important underlying biological processes in the radiation damage and tissue repair process. The methods are generally applicable to GWAS data and are not specific to radiotherapy endpoints.

Critical shear stress measurement of cohesive soils in streams: identifying device-dependent variability using an in-situ jet test device and conduit flume

NASA Astrophysics Data System (ADS)

Mahalder, B.; Schwartz, J. S.; Palomino, A.; Papanicolaou, T.

2016-12-01

Cohesive soil erodibility and threshold shear stress for stream bed and bank are dependent on both soil physical and geochemical properties in association with the channel vegetative conditions. These properties can be spatially variable therefore making critical shear stress measurement in cohesive soil challenging and leads to a need for a more comprehensive understanding of the erosional processes in streams. Several in-situ and flume-type test devices for estimating critical shear stress have been introduced by different researchers; however reported shear stress estimates per device vary widely in orders of magnitude. Advantages and disadvantages exist between these devices. Development of in-situ test devices leave the bed and/or bank material relatively undisturbed and can capture the variable nature of field soil conditions. However, laboratory flumes provide a means to control environmental conditions that can be quantify and tested. This study was conducted to observe differences in critical shear stress using jet tester and a well-controlled conduit flume. Soil samples were collected from the jet test locations and tested in a pressurized flume following standard operational procedure to calculate the critical shear stress. The results were compared using statistical data analysis (mean-separation ANOVA procedure) to identify possible differences. In addition to the device comparison, the mini jet device was used to measure critical shear stress across geologically diverse regions of Tennessee, USA. Statistical correlation between critical shear stress and the soil physical, and geochemical properties were completed identifying that geological origin plays a significant role in critical shear stress prediction for cohesive soils. Finally, the critical shear stress prediction equations using the jet test data were examined with possible suggestions to modify based on the flume test results.

Exploratory Spectroscopy of Magnetic Cataclysmic Variables Candidates and Other Variable Objects

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

Oliveira, A. S.; Palhares, M. S.; Rodrigues, C. V.

2017-04-01

The increasing number of synoptic surveys made by small robotic telescopes, such as the photometric Catalina Real-Time Transient Survey (CRTS), provides a unique opportunity to discover variable sources and improves the statistical samples of such classes of objects. Our goal is the discovery of magnetic Cataclysmic Variables (mCVs). These are rare objects that probe interesting accretion scenarios controlled by the white-dwarf magnetic field. In particular, improved statistics of mCVs would help to address open questions on their formation and evolution. We performed an optical spectroscopy survey to search for signatures of magnetic accretion in 45 variable objects selected mostly from themore » CRTS. In this sample, we found 32 CVs, 22 being mCV candidates, 13 of which were previously unreported as such. If the proposed classifications are confirmed, it would represent an increase of 4% in the number of known polars and 12% in the number of known IPs. A fraction of our initial sample was classified as extragalactic sources or other types of variable stars by the inspection of the identification spectra. Despite the inherent complexity in identifying a source as an mCV, variability-based selection, followed by spectroscopic snapshot observations, has proved to be an efficient strategy for their discoveries, being a relatively inexpensive approach in terms of telescope time.« less

Identifying Signs of Tinea Pedis: A Key to Understanding Clinical Variables.

PubMed

Canavan, Theresa N; Elewski, Boni E

2015-10-01

Tinea pedis is a frequently encountered dermatophytosis affecting the superficial skin of the feet, primarily of adults. The prevalence of tinea pedis has increased over the last several decades due to an increase in multiple risk factors. Infection from dermatophytes is most common, but infection from other fungi can also result in tinea pedis. Four distinct clinical presentations occur: interdigital, moccasin, vesicular, and acute ulcerative types. A variety of physical exam findings can help the clinician identify patients with tinea pedis.

Identifying potential academic leaders: Predictors of willingness to undertake leadership roles in an academic department of family medicine.

PubMed

White, David; Krueger, Paul; Meaney, Christopher; Antao, Viola; Kim, Florence; Kwong, Jeffrey C

2016-02-01

To identify variables associated with willingness to undertake leadership roles among academic family medicine faculty. Web-based survey. Bivariate and multivariable analyses (logistic regression) were used to identify variables associated with willingness to undertake leadership roles. Department of Family and Community Medicine at the University of Toronto in Ontario. A total of 687 faculty members. Variables related to respondents' willingness to take on various academic leadership roles. Of all 1029 faculty members invited to participate in the survey, 687 (66.8%) members responded. Of the respondents, 596 (86.8%) indicated their level of willingness to take on various academic leadership roles. Multivariable analysis revealed that the predictors associated with willingness to take on leadership roles were as follows: pursuit of professional development opportunities (odds ratio [OR] 3.79, 95% CI 2.29 to 6.27); currently holding at least 1 leadership role (OR 5.37, 95% CI 3.38 to 8.53); a history of leadership training (OR 1.86, 95% CI 1.25 to 2.78); the perception that mentorship is important for one's current role (OR 2.25, 95% CI 1.40 to 3.60); and younger age (OR 0.97, 95% CI 0.95 to 0.99). Willingness to undertake new or additional leadership roles was associated with 2 variables related to leadership experiences, 2 variables related to perceptions of mentorship and professional development, and 1 demographic variable (younger age). Interventions that support opportunities in these areas might expand the pool and strengthen the academic leadership potential of faculty members.

Does bisphenol A induce superfeminization in Marisa cornuarietis? Part I: intra- and inter-laboratory variability in test endpoints.

PubMed

Forbes, Valery E; Selck, Henriette; Palmqvist, Annemette; Aufderheide, John; Warbritton, Ryan; Pounds, Nadine; Thompson, Roy; van der Hoeven, Nelly; Caspers, Norbert

2007-03-01

It has been claimed that bisphenol A (BPA) induces superfeminization in the freshwater gastropod, Marisa cornuarietis. To explore the reproducibility of prior work, here we present results from a three-laboratory study, the objectives of which were to determine the mean and variability in test endpoints (i.e., adult fecundity, egg hatchability, and juvenile growth) under baseline conditions and to identify the sources of variability. A major source of variability for all of the measured endpoints was due to differences within and among individuals. With few exceptions, variability among laboratories and among replicate tanks within laboratories contributed little to the observed variability in endpoints. The results highlight the importance of obtaining basic knowledge of husbandry requirements and baseline information on life-history traits of potential test species prior to designing toxicity test protocols. Understanding of the levels and sources of endpoint variability is essential so that statistically robust and ecologically relevant tests of chemicals can be conducted.

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

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

The active liquid Earth - importance of temporal and spatial variability

NASA Astrophysics Data System (ADS)

Arheimer, Berit

2016-04-01

The Planet Earth is indeed liquid and active - 71 percent of its surface is water-covered and this water never rests. Thanks to the water cycle, our planet's water supply is constantly moving from one place to another and from one form to another. Only 2.5% of the water is freshwater and it exists in the air as water vapor; it hits the ground as rain and snow; it flows on the surface from higher to lower altitudes in rivers, lakes, and glaciers; and it flows in the ground in soil, aquifers, and in all living organisms until it reaches the sea. On its way over the Earth's crust, some returns quickly to vapor again, while some is trapped and exposed to many "fill and spill" situations for a long journey. The variability in the water balance is crucial for hydrological understanding and modelling. The water cycle may appear simple, but magnitudes and rates in fluxes are very different from one place to another, resulting from variable drivers such as solar energy, precipitation and gravity in co-evolution with geology, soil, vegetation and fauna. The historical evolution, the temporal fluxes and diversity in space continue to fascinate hydrological scientists. Specific physical processes may be well known, but their boundary conditions, interactions and rate often remain unknown at a specific site and are difficult to monitor in nature. This results in mysterious features where trends in drivers do not match runoff, like the Sahelian Paradox or discharge to the Arctic Ocean. Humans have always interfered with the water cycle and engineering is fundamental for water regulation and re-allocation. Some 80% of the river flow from the northern part of the Earth is affected by fragmentation of the river channels by dams. In water management, there is always a tradeoff between upstream and downstream activities, not only regarding total water quantities but also for temporal patterns and water quality aspects. Sharing a water resource can generate conflicts but geopolitical

Quantifying the importance of model-to-model variability in integrated assessments of 21st century climate

NASA Astrophysics Data System (ADS)

Bond-Lamberty, B. P.; Jones, A. D.; Shi, X.; Calvin, K. V.

2016-12-01

The C4MIP and CMIP5 model intercomparison projects (MIPs) highlighted uncertainties in climate projections, driven to a large extent by interactions between the terrestrial carbon cycle and climate feedbacks. In addition, the importance of feedbacks between human (energy and economic) systems and natural (carbon and climate) systems is poorly understood, and not considered in the previous MIP protocols. The experiments conducted under the previous Integrated Earth System Model (iESM) project, which coupled a earth system model with an integrated assessment model (GCAM), found that the inclusion of climate feedbacks on the terrestrial system in an RCP4.5 scenario increased ecosystem productivity, resulting in declines in cropland extent and increases in bioenergy production and forest cover. As a follow-up to these studies and to further understand climate-carbon cycle interactions and feedbacks, we examined the robustness of these results by running a suite of GCAM-only experiments using changes in ecosystem productivity derived from both the CMIP5 archive and the Agricultural Model Intercomparison Project. In our results, the effects of climate on yield in an RCP8.5 scenario tended to be more positive than those of AgMIP, but more negative than those of the other CMIP models. We discuss these results and the implications of model-to-model variability for integrated coupling studies of the future earth system.

Dissolving variables in connectionist combinatory logic

NASA Technical Reports Server (NTRS)

Barnden, John; Srinivas, Kankanahalli

1990-01-01

A connectionist system which can represent and execute combinator expressions to elegantly solve the variable binding problem in connectionist networks is presented. This system is a graph reduction machine utilizing graph representations and traversal mechanisms similar to ones described in the BoltzCONS system of Touretzky (1986). It is shown that, as combinators eliminate variables by introducing special functions, these functions can be connectionistically implemented without reintroducing variable binding. This approach 'dissolves' an important part of the variable binding problem, in that a connectionist system still has to manipulate complex data structures, but those structures and their manipulations are rendered more uniform.

A parallel genome-wide RNAi screening strategy to identify host proteins important for entry of Marburg virus and H5N1 influenza virus.

PubMed

Cheng, Han; Koning, Katie; O'Hearn, Aileen; Wang, Minxiu; Rumschlag-Booms, Emily; Varhegyi, Elizabeth; Rong, Lijun

2015-11-24

Genome-wide RNAi screening has been widely used to identify host proteins involved in replication and infection of different viruses, and numerous host factors are implicated in the replication cycles of these viruses, demonstrating the power of this approach. However, discrepancies on target identification of the same viruses by different groups suggest that high throughput RNAi screening strategies need to be carefully designed, developed and optimized prior to the large scale screening. Two genome-wide RNAi screens were performed in parallel against the entry of pseudotyped Marburg viruses and avian influenza virus H5N1 utilizing an HIV-1 based surrogate system, to identify host factors which are important for virus entry. A comparative analysis approach was employed in data analysis, which alleviated systematic positional effects and reduced the false positive number of virus-specific hits. The parallel nature of the strategy allows us to easily identify the host factors for a specific virus with a greatly reduced number of false positives in the initial screen, which is one of the major problems with high throughput screening. The power of this strategy is illustrated by a genome-wide RNAi screen for identifying the host factors important for Marburg virus and/or avian influenza virus H5N1 as described in this study. This strategy is particularly useful for highly pathogenic viruses since pseudotyping allows us to perform high throughput screens in the biosafety level 2 (BSL-2) containment instead of the BSL-3 or BSL-4 for the infectious viruses, with alleviated safety concerns. The screening strategy together with the unique comparative analysis approach makes the data more suitable for hit selection and enables us to identify virus-specific hits with a much lower false positive rate.

The Importance of Protesters' Morals: Moral Obligation as a Key Variable to Understand Collective Action.

PubMed

Sabucedo, José-Manuel; Dono, Marcos; Alzate, Mónica; Seoane, Gloria

2018-01-01

Collective action and protest have become a normalized political behavior that in many cases defines the political agenda. The reasons why people take to the streets constitute a central subject within the study of social psychology. In the literature, three precedents of protest that have been established as central to the study of this phenomenon are: injustice, efficacy, and identity. But political action is also deeply related to moral values. This explains why in recent years some moral constructs have also been pointed out as predictors of collective action. Moral variables have been introduced into the literature with little consideration to how they relate to each other. Thus, work in this direction is needed. The general aim of this research is to differentiate moral obligation from moral norms and moral conviction, as well as to compare their ability to predict collective action. In order to do so, the research objectives are: (a) conceptualize and operationalize moral obligation (Study 1, N = 171); (b) test its predictive power for intention to participate in protests (Study 2, N = 622); and (c) test moral obligation in a real context (Study 3, N = 407). Results are encouraging, showing not only that moral obligation is different to moral conviction and moral norm, but also that it is a more effective predictor working both for intention and real participation. This work therefore presents moral obligation as a key precedent of protest participation, prompting its future use as a variable that can enhance existing predictive models of collective action. Results regarding other variables are also discussed.

The Importance of Protesters’ Morals: Moral Obligation as a Key Variable to Understand Collective Action

PubMed Central

Sabucedo, José-Manuel; Dono, Marcos; Alzate, Mónica; Seoane, Gloria

2018-01-01

Collective action and protest have become a normalized political behavior that in many cases defines the political agenda. The reasons why people take to the streets constitute a central subject within the study of social psychology. In the literature, three precedents of protest that have been established as central to the study of this phenomenon are: injustice, efficacy, and identity. But political action is also deeply related to moral values. This explains why in recent years some moral constructs have also been pointed out as predictors of collective action. Moral variables have been introduced into the literature with little consideration to how they relate to each other. Thus, work in this direction is needed. The general aim of this research is to differentiate moral obligation from moral norms and moral conviction, as well as to compare their ability to predict collective action. In order to do so, the research objectives are: (a) conceptualize and operationalize moral obligation (Study 1, N = 171); (b) test its predictive power for intention to participate in protests (Study 2, N = 622); and (c) test moral obligation in a real context (Study 3, N = 407). Results are encouraging, showing not only that moral obligation is different to moral conviction and moral norm, but also that it is a more effective predictor working both for intention and real participation. This work therefore presents moral obligation as a key precedent of protest participation, prompting its future use as a variable that can enhance existing predictive models of collective action. Results regarding other variables are also discussed. PMID:29636720

Variability of cost-effectiveness estimates for pharmaceuticals in Western Europe: lessons for inferring generalizability.

PubMed

Barbieri, Marco; Drummond, Michael; Willke, Richard; Chancellor, Jeremy; Jolain, Bruno; Towse, Adrian

2005-01-01

It has long been suggested that, whereas the results of clinical studies of pharmaceuticals are generalizable from one jurisdiction to another, the results of economic evaluations are location dependent. There has been, however, little study of the causes of variation, whether differences in study results among countries are systematic, or whether they are important for decision making. A literature search was conducted to identify economic evaluations of pharmaceuticals conducted in two or more European countries. The studies identified were then classified by methodological type and analyzed to assess their level of variability and to identify the main causes of variation. Assessments were also made of the extent to which differences in study results among countries were systematic and whether they would lead to a different decision, assuming a range of values of the threshold willingness-to-pay for a life-year or quality-adjusted life-year (QALY). In total 46 intercountry drug comparisons were identified, 29 in multicountry studies and 17 in comparable single country studies that were considered to be sufficiently similar in terms of methodology. The type of study (i.e., trial-based or modeling study) had some impact on variability, but the most important factor was the extent of variation across countries in effectiveness, resource use or unit costs, allowed by the researcher's chosen methodology. There were few systematic differences in study results among countries, so a decision maker in country B, on seeing a recent economic evaluation of a new drug in country A, would have little basis on which to predict whether the drug, if evaluated, would be more or less cost-effective in his or her country. Given the extent of variation in cost-effectiveness estimates among countries, the importance of this for decision making depends on decision makers' thresholds in willingness-to-pay for a QALY or life-year. If a cost-effectiveness threshold (i.e., willingness

Evaluating the importance of policy amenable factors in explaining influenza vaccination: a cross-sectional multinational study.

PubMed

Wheelock, Ana; Miraldo, Marisa; Thomson, Angus; Vincent, Charles; Sevdalis, Nick

2017-07-12

Despite continuous efforts to improve influenza vaccination coverage, uptake among high-risk groups remains suboptimal. We aimed to identify policy amenable factors associated with vaccination and to measure their importance in order to assist in the monitoring of vaccination sentiment and the design of communication strategies and interventions to improve vaccination rates. The USA, the UK and France. A total of 2412 participants were surveyed across the three countries. Self-reported influenza vaccination. Between March and April 2014, a stratified random sampling strategy was employed with the aim of obtaining nationally representative samples in the USA, the UK and France through online databases and random-digit dialling. Participants were asked about vaccination practices, perceptions and feelings. Multivariable logistic regression was used to identify factors associated with past influenza vaccination. The models were able to explain 64%-80% of the variance in vaccination behaviour. Overall, sociopsychological variables, which are inherently amenable to policy, were better at explaining past vaccination behaviour than demographic, socioeconomic and health variables. Explanatory variables included social influence (physician), influenza and vaccine risk perceptions and traumatic childhood experiences. Our results indicate that evidence-based sociopsychological items should be considered for inclusion into national immunisation surveys to gauge the public's views, identify emerging concerns and thus proactively and opportunely address potential barriers and harness vaccination drivers. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

The Importance of Patient Involvement in Stroke Rehabilitation

PubMed Central

2016-01-01

Objective To investigate the perceived needs for health services by persons with stroke within the first year after rehabilitation, and associations between perceived impact of stroke, involvement in decisions regarding care/treatment, and having health services needs met. Method Data was collected, through a mail survey, from patients with stroke who were admitted to a university hospital in 2012 and had received rehabilitation after discharge from the stroke unit. The rehabilitation lasted an average of 2 to 4.6 months. The Stroke Survivor Needs Survey Questionnaire was used to assess the participants' perceptions of involvement in decisions on care or treatment and needs for health services in 11 problem areas: mobility, falls, incontinence, pain, fatigue, emotion, concentration, memory, speaking, reading, and sight. The perceived impact of stroke in eight areas was assessed using the Stroke Impact Scale (SIS) 3.0. Eleven logistic regression models were created to explore associations between having health services needs met in each problem area respectively (dependent variable) and the independent variables. In all models the independent variables were: age, sex, SIS domain corresponding to the dependent variable, or stroke severity in cases when no corresponding SIS domain was identified, and involvement in decisions on care and treatment. Results The 63 participants who returned the questionnaires had a mean age of 72 years, 33 were male and 30 were female. Eighty percent had suffered a mild stroke. The number of participants who reported problems varied between 51 (80%, mobility) and 24 (38%, sight). Involvement in decisions on care and treatment was found to be associated with having health services needs met in six problem areas: falls, fatigue, emotion, memory, speaking, and reading. Conclusions The results highlight the importance of involving patients in making decisions on stroke rehabilitation, as it appears to be associated with meeting their health

Assessment of published models and prognostic variables in epithelial ovarian cancer at Mayo Clinic

PubMed Central

Hendrickson, Andrea Wahner; Hawthorne, Kieran M.; Goode, Ellen L.; Kalli, Kimberly R.; Goergen, Krista M.; Bakkum-Gamez, Jamie N.; Cliby, William A.; Keeney, Gary L.; Visscher, Dan W.; Tarabishy, Yaman; Oberg, Ann L.; Hartmann, Lynn C.; Maurer, Matthew J.

2015-01-01

Objectives Epithelial ovarian cancer (EOC) is an aggressive disease in which first line therapy consists of a surgical staging/debulking procedure and platinum based chemotherapy. There is significant interest in clinically applicable, easy to use prognostic tools to estimate risk of recurrence and overall survival. In this study we used a large prospectively collected cohort of women with EOC to validate currently published models and assess prognostic variables. Methods Women with invasive ovarian, peritoneal, or fallopian tube cancer diagnosed between 2000-2011 and prospectively enrolled into the Mayo Clinic Ovarian Cancer registry were identified. Demographics and known prognostic markers as well as epidemiologic exposure variables were abstracted from the medical record and collected via questionnaire. Six previously published models of overall and recurrence-free survival were assessed for external validity. In addition, predictors of outcome were assessed in our dataset. Results Previously published models validated with a range of c-statistics (0.587-0.827), though application of models containing variables not part of routine practice were somewhat limited by missing data; utilization of all applicable models and comparison of results is suggested. Examination of prognostic variables identified only the presence of ascites and ASA score to be independent predictors of prognosis in our dataset, albeit with marginal gain in prognostic information, after accounting for stage and debulking. Conclusions Existing prognostic models for newly diagnosed EOC showed acceptable calibration in our cohort for clinical application. However, modeling of prospective variables in our dataset reiterates that stage and debulking remain the most important predictors of prognosis in this setting. PMID:25620544

Use of color maps and wavelet coherence to discern seasonal and interannual climate influences on streamflow variability in northern catchments

NASA Astrophysics Data System (ADS)

Carey, Sean K.; Tetzlaff, Doerthe; Buttle, Jim; Laudon, Hjalmar; McDonnell, Jeff; McGuire, Kevin; Seibert, Jan; Soulsby, Chris; Shanley, Jamie

2013-10-01

The higher midlatitudes of the northern hemisphere are particularly sensitive to change due to the important role the 0°C isotherm plays in the phase of precipitation and intermediate storage as snow. An international intercatchment comparison program called North-Watch seeks to improve our understanding of the sensitivity of northern catchments to change by examining their hydrological and biogeochemical variability and response. Here eight North-Watch catchments located in Sweden (Krycklan), Scotland (Girnock and Strontian), the United States (Sleepers River, Hubbard Brook, and HJ Andrews), and Canada (Dorset and Wolf Creek) with 10 continuous years of daily precipitation and runoff data were selected to assess daily to seasonal coupling of precipitation (P) and runoff (Q) using wavelet coherency, and to explore the patterns and scales of variability in streamflow using color maps. Wavelet coherency revealed that P and Q were decoupled in catchments with cold winters, yet were strongly coupled during and immediately following the spring snowmelt freshet. In all catchments, coupling at shorter time scales occurred during wet periods when the catchment was responsive and storage deficits were small. At longer time scales, coupling reflected coherence between seasonal cycles, being enhanced at sites with enhanced seasonality in P. Color maps were applied as an alternative method to identify patterns and scales of flow variability. Seasonal versus transient flow variability was identified along with the persistence of that variability on influencing the flow regime. While exploratory in nature, this intercomparison exercise highlights the importance of climate and the 0°C isotherm on the functioning of northern catchments.

Using Multiple-Variable Matching to Identify Cultural Sources of Differential Item Functioning

ERIC Educational Resources Information Center

Wu, Amery D.; Ercikan, Kadriye

2006-01-01

Identifying the sources of differential item functioning (DIF) in international assessments is very challenging, because such sources are often nebulous and intertwined. Even though researchers frequently focus on test translation and content area, few actually go beyond these factors to investigate other cultural sources of DIF. This article…

Identifying DNA-binding proteins using structural motifs and the electrostatic potential

PubMed Central

Shanahan, Hugh P.; Garcia, Mario A.; Jones, Susan; Thornton, Janet M.

2004-01-01

Robust methods to detect DNA-binding proteins from structures of unknown function are important for structural biology. This paper describes a method for identifying such proteins that (i) have a solvent accessible structural motif necessary for DNA-binding and (ii) a positive electrostatic potential in the region of the binding region. We focus on three structural motifs: helix–turn-helix (HTH), helix–hairpin–helix (HhH) and helix–loop–helix (HLH). We find that the combination of these variables detect 78% of proteins with an HTH motif, which is a substantial improvement over previous work based purely on structural templates and is comparable to more complex methods of identifying DNA-binding proteins. Similar true positive fractions are achieved for the HhH and HLH motifs. We see evidence of wide evolutionary diversity for DNA-binding proteins with an HTH motif, and much smaller diversity for those with an HhH or HLH motif. PMID:15356290

Using Instrumental Variable (IV) Tests to Evaluate Model Specification in Latent Variable Structural Equation Models*

PubMed Central

Kirby, James B.; Bollen, Kenneth A.

2009-01-01

Structural Equation Modeling with latent variables (SEM) is a powerful tool for social and behavioral scientists, combining many of the strengths of psychometrics and econometrics into a single framework. The most common estimator for SEM is the full-information maximum likelihood estimator (ML), but there is continuing interest in limited information estimators because of their distributional robustness and their greater resistance to structural specification errors. However, the literature discussing model fit for limited information estimators for latent variable models is sparse compared to that for full information estimators. We address this shortcoming by providing several specification tests based on the 2SLS estimator for latent variable structural equation models developed by Bollen (1996). We explain how these tests can be used to not only identify a misspecified model, but to help diagnose the source of misspecification within a model. We present and discuss results from a Monte Carlo experiment designed to evaluate the finite sample properties of these tests. Our findings suggest that the 2SLS tests successfully identify most misspecified models, even those with modest misspecification, and that they provide researchers with information that can help diagnose the source of misspecification. PMID:20419054

North Tropical Atlantic Climate Variability and Model Biases

NASA Astrophysics Data System (ADS)

Yang, Y.

2017-12-01

Remote forcing from El Niño-Southern Oscillation (ENSO) and local ocean-atmosphere feedback are important for climate variability over the North Tropical Atlantic. These two factors are extracted by the ensemble mean and inter-member difference of a 10-member Pacific Ocean-Global Atmosphere (POGA) experiment, in which sea surface temperatures (SSTs) are restored to the observed anomalies over the tropical Pacific but fully coupled to the atmosphere elsewhere. POGA reasonably captures main features of observed North Tropical Atlantic variability. ENSO forced and local North Tropical Atlantic modes (NTAMs) develop with wind-evaporation-SST feedback, explaining one third and two thirds of total variance respectively. Notable biases, however, exist. The seasonality of the simulated NTAM is delayed by one month, due to the late development of the North Atlantic Oscillation (NAO) in the model. A spurious band of enhanced sea surface temperature (SST) variance (SBEV) is identified over the northern equatorial Atlantic in POGA and 14 out of 23 CMIP5 models. The SBEV is especially pronounced in boreal spring and due to the combined effect of both anomalous atmospheric thermal forcing and oceanic vertical upwelling. While the tropical North Atlantic variability is only weakly correlated with the Atlantic Zonal Mode (AZM) in observations, the SBEV in CMIP5 produces conditions that drive and intensify the AZM variability via triggering the Bjerknes feedback. This partially explains why AZM is strong in some CMIP5 models even though the equatorial cold tongue and easterly trades are biased low.

Identification of young stellar variables with KELT for K2 - II. The Upper Scorpius association

NASA Astrophysics Data System (ADS)

Ansdell, Megan; Oelkers, Ryan J.; Rodriguez, Joseph E.; Gaidos, Eric; Somers, Garrett; Mamajek, Eric; Cargile, Phillip A.; Stassun, Keivan G.; Pepper, Joshua; Stevens, Daniel J.; Beatty, Thomas G.; Siverd, Robert J.; Lund, Michael B.; Kuhn, Rudolf B.; James, David; Gaudi, B. Scott

2018-01-01

High-precision photometry from space-based missions such as K2 and Transiting Exoplanet Survey Satellite enables detailed studies of young star variability. However, because space-based observing campaigns are often short (e.g. 80 d for K2), complementary long-baseline photometric surveys are critical for obtaining a complete understanding of young star variability, which can change on time-scales of minutes to years. We therefore present and analyse light curves of members of the Upper Scorpius association made over 5.5 yr by the ground-based Kilodegree Extremely Little Telescope (KELT), which complement the high-precision observations of this region taken by K2 during its Campaigns 2 and 15. We show that KELT data accurately identify the periodic signals found with high-precision K2 photometry, demonstrating the power of ground-based surveys in deriving stellar rotation periods of young stars. We also use KELT data to identify sources exhibiting variability that is likely related to circumstellar material and/or stellar activity cycles; these signatures are often unseen in the short-term K2 data, illustrating the importance of long-term monitoring surveys for studying the full range of young star variability. We provide the KELT light curves as electronic tables in an ongoing effort to establish legacy time series data sets for young stellar clusters.

Variability of faint ROSAT field sources

NASA Astrophysics Data System (ADS)

Nicholson, K. L.; Mittaz, J. P. D.; Mason, K. O.

1997-03-01

We describe a technique to search for variability in faint X-ray sources, based on Poisson statistics. This is applied to data in the field of the detached white dwarf binary RE J1629+781 which has been observed repeatedly with the ROSAT Position Sensitive Proportional Counter (PSPC) over a period of 2.5yr as part of the calibration programme of the co-aligned extreme ultraviolet (EUV) sensitive Wide Field Camera. The field contains eight other identified sources comprising four active galactic nuclei (AGN), a LINER, a probable cluster of galaxies and two stars. Variability is detected in three of the AGN, which all have redshifts between 0.35 and 0.38. The amplitude of variability ranges between one and three times the mean count rate, but is only detected on time-scales of less than 3-5 months. No variability is found in the fourth AGN which is at a redshift of 1.1, nor in the LINER galaxy, Arp 185. The X-ray emission from Arp 185 is relatively bright, and the upper limit to flux variations is 27 per cent of the mean flux. This result is consistent with a non-AGN origin for the X-ray emission from this galaxy. Variability is detected from one of the identified stars in the field, of spectral type dM5.5e. No variations were seen in the flux of the other star (spectral type G) or from the probable cluster of galaxies.

Hydrothermal activity at slow-spreading ridges: variability and importance of magmatic controls

NASA Astrophysics Data System (ADS)

Escartin, Javier

2016-04-01

Hydrothermal activity along mid-ocean ridge axes is ubiquitous, associated with mass, chemical, and heat exchanges between the deep lithosphere and the overlying envelopes, and sustaining chemiosynthetic ecosystems at the seafloor. Compared with hydrothermal fields at fast-spreading ridges, those at slow spreading ones show a large variability as their location and nature is controlled or influenced by several parameters that are inter-related: a) tectonic setting, ranging from 'volcanic systems' (along the rift valley floor, volcanic ridges, seamounts), to 'tectonic' ones (rift-bounding faults, oceanic detachment faults); b) the nature of the host rock, owing to compositional heterogeneity of slow-spreading lithosphere (basalt, gabbro, peridotite); c) the type of heat source (magmatic bodies at depth, hot lithosphere, serpentinization reactions); d) and the associated temperature of outflow fluids (high- vs.- low temperature venting and their relative proportion). A systematic review of the distribution and characteristics of hydrothermal fields along the slow-spreading Mid-Atlantic Ridge suggests that long-lived hydrothermal activity is concentrated either at oceanic detachment faults, or along volcanic segments with evidence of robust magma supply to the axis. A detailed study of the magmatically robust Lucky Strike segment suggests that all present and past hydrothermal activity is found at the center of the segment. The association of these fields to central volcanos, and the absence of indicators of hydrothermal activity along the remaining of the ridge segment, suggests that long-lived hydrothermal activity in these volcanic systems is maintained by the enhanced melt supply and the associated magma chamber(s) required to build these volcanic edifices. In this setting, hydrothermal outflow zones at the seafloor are systematically controlled by faults, indicating that hydrothermal fluids in the shallow crust exploit permeable fault zones to circulate. While

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.

Combining Methods to Describe Important Marine Habitats for Top Predators: Application to Identify Biological Hotspots in Tropical Waters.

PubMed

Thiers, Laurie; Louzao, Maite; Ridoux, Vincent; Le Corre, Matthieu; Jaquemet, Sébastien; Weimerskirch, Henri

2014-01-01

In tropical waters resources are usually scarce and patchy, and predatory species generally show specific adaptations for foraging. Tropical seabirds often forage in association with sub-surface predators that create feeding opportunities by bringing prey close to the surface, and the birds often aggregate in large multispecific flocks. Here we hypothesize that frigatebirds, a tropical seabird adapted to foraging with low energetic costs, could be a good predictor of the distribution of their associated predatory species, including other seabirds (e.g. boobies, terns) and subsurface predators (e.g., dolphins, tunas). To test this hypothesis, we compared distribution patterns of marine predators in the Mozambique Channel based on a long-term dataset of both vessel- and aerial surveys, as well as tracking data of frigatebirds. By developing species distribution models (SDMs), we identified key marine areas for tropical predators in relation to contemporaneous oceanographic features to investigate multi-species spatial overlap areas and identify predator hotspots in the Mozambique Channel. SDMs reasonably matched observed patterns and both static (e.g. bathymetry) and dynamic (e.g. Chlorophyll a concentration and sea surface temperature) factors were important explaining predator distribution patterns. We found that the distribution of frigatebirds included the distributions of the associated species. The central part of the channel appeared to be the best habitat for the four groups of species considered in this study (frigatebirds, brown terns, boobies and sub-surface predators).

Variables Affecting Readiness to Benefit from Career Interventions

ERIC Educational Resources Information Center

Sampson, James P., Jr.; McClain, Mary-Catherine; Musch, Elisabeth; Reardon, Robert C.

2013-01-01

This article identifies and briefly describes the broad range of variables that may influence clients' readiness to benefit from career interventions. The article also discusses consequences of low readiness for effective use of career interventions and addresses implications for practice as well as for future research. Variables contributing to…

Soil moisture profile variability in land-vegetation- atmosphere continuum

NASA Astrophysics Data System (ADS)

Wu, Wanru

Soil moisture is of critical importance to the physical processes governing energy and water exchanges at the land-air boundary. With respect to the exchange of water mass, soil moisture controls the response of the land surface to atmospheric forcing and determines the partitioning of precipitation into infiltration and runoff. Meanwhile, the soil acts as a reservoir for the storage of liquid water and slow release of water vapor into the atmosphere. The major motivation of the study is that the soil moisture profile is thought to make a substantial contribution to the climate variability through two-way interactions between the land-surface and the atmosphere in the coupled ocean-atmosphere-land climate system. The characteristics of soil moisture variability with soil depth may be important in affecting the atmosphere. The natural variability of soil moisture profile is demonstrated using observations. The 16-year field observational data of soil moisture with 11-layer (top 2.0 meters) measured soil depths over Illinois are analyzed and used to identify and quantify the soil moisture profile variability, where the atmospheric forcing (precipitation) anomaly propagates down through the land-branch of the hydrological cycle with amplitude damping, phase shift, and increasing persistence. Detailed statistical data analyses, which include application of the periodogram method, the wavelet method and the band-pass filter, are made of the variations of soil moisture profile and concurrently measured precipitation for comparison. Cross-spectral analysis is performed to obtain the coherence pattern and phase correlation of two time series for phase shift and amplitude damping calculation. A composite of the drought events during this time period is analyzed and compared with the normal (non-drought) case. A multi-layer land surface model is applied for modeling the soil moisture profile variability characteristics and investigating the underlying mechanisms. Numerical

ROTSE All-Sky Surveys for Variable Stars. I. Test Fields

NASA Astrophysics Data System (ADS)

Akerlof, C.; Amrose, S.; Balsano, R.; Bloch, J.; Casperson, D.; Fletcher, S.; Gisler, G.; Hills, J.; Kehoe, R.; Lee, B.; Marshall, S.; McKay, T.; Pawl, A.; Schaefer, J.; Szymanski, J.; Wren, J.

2000-04-01

The Robotic Optical Transient Search Experiment I (ROTSE-I) experiment has generated CCD photometry for the entire northern sky in two epochs nightly since 1998 March. These sky patrol data are a powerful resource for studies of astrophysical transients. As a demonstration project, we present first results of a search for periodic variable stars derived from ROTSE-I observations. Variable identification, period determination, and type classification are conducted via automatic algorithms. In a set of nine ROTSE-I sky patrol fields covering roughly 2000 deg2, we identify 1781 periodic variable stars with mean magnitudes between mv=10.0 and mv=15.5. About 90% of these objects are newly identified as variable. Examples of many familiar types are presented. All classifications for this study have been manually confirmed. The selection criteria for this analysis have been conservatively defined and are known to be biased against some variable classes. This preliminary study includes only 5.6% of the total ROTSE-I sky coverage, suggesting that the full ROTSE-I variable catalog will include more than 32,000 periodic variable stars.

Biopsy variability of lymphocytic infiltration in breast cancer subtypes and the ImmunoSkew score

NASA Astrophysics Data System (ADS)

Khan, Adnan Mujahid; Yuan, Yinyin

2016-11-01

The number of tumour biopsies required for a good representation of tumours has been controversial. An important factor to consider is intra-tumour heterogeneity, which can vary among cancer types and subtypes. Immune cells in particular often display complex infiltrative patterns, however, there is a lack of quantitative understanding of the spatial heterogeneity of immune cells and how this fundamental biological nature of human tumours influences biopsy variability and treatment resistance. We systematically investigate biopsy variability for the lymphocytic infiltrate in 998 breast tumours using a novel virtual biopsy method. Across all breast cancers, we observe a nonlinear increase in concordance between the biopsy and whole-tumour score of lymphocytic infiltrate with increasing number of biopsies, yet little improvement is gained with more than four biopsies. Interestingly, biopsy variability of lymphocytic infiltrate differs considerably among breast cancer subtypes, with the human epidermal growth factor receptor 2-positive (HER2+) subtype having the highest variability. We subsequently identify a quantitative measure of spatial variability that predicts disease-specific survival in HER2+ subtype independent of standard clinical variables (node status, tumour size and grade). Our study demonstrates how systematic methods provide new insights that can influence future study design based on a quantitative knowledge of tumour heterogeneity.

Identification of Cepheid Variables in ASAS Data (Poster abstract)

NASA Astrophysics Data System (ADS)

Johnson, J.; Larsen, K.

2014-06-01

(Abstract only) Cepheid variables are well-known to be important to astronomers, as their period-luminosity relationship is used to determine the distances to galaxies. The unambiguous identification of newly discovered Cepheid variables in large photometric data sets is therefore of significance. A data set of 3,548 candidate Cepheid variable stars in the ASAS data was provided by Patrick Wils (through Doug Welch). A computer program had originally identified these candidates; however, Wils investigated a small subset of the data by hand and discovered that the vast majority of these stars were misidentified. The most common misidentification was of BY Draconis stars (rotating spotted K and M dwarfs). In a companion piece, Swenton and Larsen sought out the most likely Cepheid candidates in the data; the work discussed here is instead focused on looking at stars that had properties that were clearly different from Cepheids, more specifically properties likely to be seen in BY Dra stars. We are sorting the spreadsheet stars by characteristics in order to find as many BY Dra variables as possible (since they seem to be the most commonly misidentified stars). These characteristics include newly available infrared photometry (2MASS), proper motion (PPMXL), and X-Ray emission (ROTSE) data (for which we received helpful guidance from Sebastian Otero) as well as VSX information. The first 103 stars to be studied are those with the smallest range in magnitude (less than or equal to 0.1). An analysis of their light curves and other available data is being undertaken in order to determine whether or not they are indeed BY Dra-type variables. In doing so the goal is to be able to submit and publish the correct identifications for these stars to the International Variable Star Index (VSX) and the JAAVSO.

Genotype heterogeneity of Mycobacterium tuberculosis within geospatial hotspots suggests foci of imported infection in Sydney, Australia.

PubMed

Gurjav, Ulziijargal; Jelfs, Peter; Hill-Cawthorne, Grant A; Marais, Ben J; Sintchenko, Vitali

2016-06-01

In recent years the State of New South Wales (NSW), Australia, has maintained a low tuberculosis incidence rate with little evidence of local transmission. Nearly 90% of notified tuberculosis cases occurred in people born in tuberculosis-endemic countries. We analyzed geographic, epidemiological and genotypic data of all culture-confirmed tuberculosis cases to identify the bacterial and demographic determinants of tuberculosis hotspot areas in NSW. Standard 24-loci mycobacterium interspersed repetitive unit-variable number tandem repeat (MIRU-24) typing was performed on all isolates recovered between 2009 and 2013. In total 1692/1841 (91.9%) cases with confirmed Mycobacterium tuberculosis infection had complete MIRU-24 and demographic data and were included in the study. Despite some year-to-year variability, spatio-temporal analysis identified four tuberculosis hotspots. The incidence rate and the relative risk of tuberculosis in these hotspots were 2- to 10-fold and 4- to 8-fold higher than the state average, respectively. MIRU-24 profiles of M. tuberculosis isolates associated with these hotspots revealed high levels of heterogeneity. This suggests that these spatio-temporal hotspots, within this low incidence setting, can represent areas of predominantly imported infection rather than clusters of cases due to local transmission. These findings provide important epidemiological insight and demonstrate the value of combining tuberculosis genotyping and spatiotemporal data to guide better-targeted public health interventions. Copyright © 2015 Elsevier B.V. All rights reserved.

Body composition and morphological assessment of nutritional status in adults: a review of anthropometric variables.

PubMed

Madden, A M; Smith, S

2016-02-01

Evaluation of body composition is an important part of assessing nutritional status and provides prognostically useful data and an opportunity to monitor the effects of nutrition-related disease progression and nutritional intervention. The aim of this narrative review is to critically evaluate body composition methodology in adults, focusing on anthropometric variables. The variables considered include height, weight, body mass index and alternative indices, trunk measurements (waist and hip circumferences and sagittal abdominal diameter) and limb measurements (mid-upper arm and calf circumferences) and skinfold thickness. The importance of adhering to a defined measurement protocol, checking measurement error and the need to interpret measurements using appropriate population-specific cut-off values to identify health risks were highlighted. Selecting the optimum method for assessing body composition using anthropometry depends on the purpose (i.e. evaluating obesity or undernutrition) and requires practitioners to have a good understanding of both practical and theoretical limitations and to be able to interpret the results wisely. © 2014 The British Dietetic Association Ltd.

Detection limits of tidal-wetland sequences to identify variable rupture modes of megathrust earthquakes

NASA Astrophysics Data System (ADS)

Shennan, Ian; Garrett, Ed; Barlow, Natasha

2016-10-01

Recent paleoseismological studies question whether segment boundaries identified for 20th and 21st century great, >M8, earthquakes persist through multiple earthquake cycles or whether smaller segments with different boundaries rupture and cause significant hazards. The smaller segments may include some currently slipping rather than locked. In this review, we outline general principles regarding indicators of relative sea-level change in tidal wetlands and the conditions in which paleoseismic indicators must be distinct from those resulting from non-seismic processes. We present new evidence from sites across southcentral Alaska to illustrate different detection limits of paleoseismic indicators and consider alternative interpretations for marsh submergence and emergence. We compare predictions of coseismic uplift and subsidence derived from geophysical models of earthquakes with different rupture modes. The spatial patterns of agreement and misfits between model predictions and quantitative reconstructions of coseismic submergence and emergence suggest that no earthquake within the last 4000 years had a pattern of rupture the same as the Mw 9.2 Alaska earthquake in 1964. From the Alaska examples and research from other subduction zones we suggest that If we want to understand whether a megathrust ruptures in segments of variable length in different earthquakes, we need to be site-specific as to what sort of geological-based criteria eliminate the possibility of a particular rupture mode in different earthquakes. We conclude that coastal paleoseismological studies benefit from a methodological framework that employs rigorous evaluation of five essential criteria and a sixth which may be very robust but only occur at some sites: 1 - lateral extent of peat-mud or mud-peat couplets with sharp contacts; 2 - suddenness of submergence or emergence, and replicated within each site; 3 - amount of vertical motion, quantified with 95% error terms and replicated within each

Freshwater ecosystems and resilience of Pacific salmon: Habitat Management based on natural variability

USGS Publications Warehouse

Bisson, P.A.; Dunham, J.B.; Reeves, G.H.

2009-01-01

In spite of numerous habitat restoration programs in fresh waters with an aggregate annual funding of millions of dollars, many populations of Pacific salmon remain significantly imperiled. Habitat restoration strategies that address limited environmental attributes and partial salmon life-history requirements or approaches that attempt to force aquatic habitat to conform to idealized but ecologically unsustainable conditions may partly explain this lack of response. Natural watershed processes generate highly variable environmental conditions and population responses, i.e., multiple life histories, that are often not considered in restoration. Examples from several locations underscore the importance of natural variability to the resilience of Pacific salmon. The implication is that habitat restoration efforts will be more likely to foster salmon resilience if they consider processes that generate and maintain natural variability in fresh water. We identify three specific criteria for management based on natural variability: the capacity of aquatic habitat to recover from disturbance, a range of habitats distributed across stream networks through time sufficient to fulfill the requirements of diverse salmon life histories, and ecological connectivity. In light of these considerations, we discuss current threats to habitat resilience and describe how regulatory and restoration approaches can be modified to better incorporate natural variability. ?? 2009 by the author(s).

Quantifying Grain-Size Variability of Metal Pollutants in Road-Deposited Sediments Using the Coefficient of Variation

PubMed Central

Wang, Xiaoxue; Li, Xuyong

2017-01-01

Particle grain size is an important indicator for the variability in physical characteristics and pollutants composition of road-deposited sediments (RDS). Quantitative assessment of the grain-size variability in RDS amount, metal concentration, metal load and GSFLoad is essential to elimination of the uncertainty it causes in estimation of RDS emission load and formulation of control strategies. In this study, grain-size variability was explored and quantified using the coefficient of variation (Cv) of the particle size compositions, metal concentrations, metal loads, and GSFLoad values in RDS. Several trends in grain-size variability of RDS were identified: (i) the medium class (105–450 µm) variability in terms of particle size composition, metal loads, and GSFLoad values in RDS was smaller than the fine (<105 µm) and coarse (450–2000 µm) class; (ii) The grain-size variability in terms of metal concentrations increased as the particle size increased, while the metal concentrations decreased; (iii) When compared to the Lorenz coefficient (Lc), the Cv was similarly effective at describing the grain-size variability, whereas it is simpler to calculate because it did not require the data to be pre-processed. The results of this study will facilitate identification of the uncertainty in modelling RDS caused by grain-size class variability. PMID:28788078

The Body of Knowledge & Content Framework. Identifying the Important Knowledge Required for Productive Performance of a Plastics Machine Operator. Blow Molding, Extrusion, Injection Molding, Thermoforming.

ERIC Educational Resources Information Center

Society of the Plastics Industry, Inc., Washington, DC.

Designed to guide training and curriculum development to prepare machine operators for the national certification exam, this publication identifies the important knowledge required for productive performance by a plastics machine operator. Introductory material discusses the rationale for a national standard, uses of the Body of Knowledge,…

Imaging Variable Stars with HST

NASA Astrophysics Data System (ADS)

Karovska, Margarita

2011-05-01

The Hubble Space Telescope (HST) observations of astronomical sources, ranging from objects in our solar system to objects in the early Universe, have revolutionized our knowledge of the Universe its origins and contents.I will highlight results from HST observations of variable stars obtained during the past twenty or so years. Multiwavelength observations of numerous variable stars and stellar systems were obtained using the superb HST imaging capabilities and its unprecedented angular resolution, especially in the UV and optical. The HST provided the first detailed images probing the structure of variable stars including their atmospheres and circumstellar environments. AAVSO observations and light curves have been critical for scheduling of many of these observations and provided important information and context for understanding of the imaging results of many variable sources. I will describe the scientific results from the imaging observations of variable stars including AGBs, Miras, Cepheids, semi-regular variables (including supergiants and giants), YSOs and interacting stellar systems with a variable stellar components. These results have led to an unprecedented understanding of the spatial and temporal characteristics of these objects and their place in the stellar evolutionary chains, and in the larger context of the dynamic evolving Universe.

Imaging Variable Stars with HST

NASA Astrophysics Data System (ADS)

Karovska, M.

2012-06-01

(Abstract only) The Hubble Space Telescope (HST) observations of astronomical sources, ranging from objects in our solar system to objects in the early Universe, have revolutionized our knowledge of the Universe its origins and contents. I highlight results from HST observations of variable stars obtained during the past twenty or so years. Multiwavelength observations of numerous variable stars and stellar systems were obtained using the superb HST imaging capabilities and its unprecedented angular resolution, especially in the UV and optical. The HST provided the first detailed images probing the structure of variable stars including their atmospheres and circumstellar environments. AAVSO observations and light curves have been critical for scheduling of many of these observations and provided important information and context for understanding of the imaging results of many variable sources. I describe the scientific results from the imaging observations of variable stars including AGBs, Miras, Cepheids, semiregular variables (including supergiants and giants), YSOs and interacting stellar systems with a variable stellar components. These results have led to an unprecedented understanding of the spatial and temporal characteristics of these objects and their place in the stellar evolutionary chains, and in the larger context of the dynamic evolving Universe.

The importance of normalisation in the construction of deprivation indices.

PubMed

Gilthorpe, M S

1995-12-01

Measuring socio-economic deprivation is a major challenge usually addressed through the use of composite indices. This paper aims to clarify the technical details regarding composite index construction. The distribution of some variables, for example unemployment, varies over time, and these variations must be considered when composite indices are periodically re-evaluated. The process of normalisation is examined in detail and particular attention is paid to the importance of symmetry and skewness of the composite variable distributions. Four different solutions of the Townsend index of socioeconomic deprivation are compared to reveal the effects that differing transformation processes have on the meaning or interpretation of the final index values. Differences in the rank order and the relative separation between values are investigated. Constituent variables which have been transformed to yield a more symmetric distribution provide indices that behave similarly, irrespective of the actual transformation methods adopted. Normalisation is seen to be of less importance than the removal of variable skewness. Furthermore, the degree of success of the transformation in removing skewness has a major effect in determining the variation between the individual electoral ward scores. Constituent variables undergoing no transformation produce an index that is distorted by the inherent variable skewness, and this index is not consistent between re-evaluations, either temporally or spatially. Effective transformation of constituent variables should always be undertaken when generating a composite index. The most important aspect is the removal of variable skewness. There is no need for the transformed variables to be normally distributed, only symmetrically distributed, before standardisation. Even where additional parameter weights are to be applied, which significantly alter the final index, appropriate transformation procedures should be adopted for the purpose of

IDENTIFYING GENETIC ASSOCIATIONS WITH VARIABILITY IN METABOLIC HEALTH AND BLOOD COUNT LABORATORY VALUES: DIVING INTO THE QUANTITATIVE TRAITS BY LEVERAGING LONGITUDINAL DATA FROM AN EHR.

PubMed

Verma, Shefali S; Lucas, Anastasia M; Lavage, Daniel R; Leader, Joseph B; Metpally, Raghu; Krishnamurthy, Sarathbabu; Dewey, Frederick; Borecki, Ingrid; Lopez, Alexander; Overton, John; Penn, John; Reid, Jeffrey; Pendergrass, Sarah A; Breitwieser, Gerda; Ritchie, Marylyn D

2017-01-01

A wide range of patient health data is recorded in Electronic Health Records (EHR). This data includes diagnosis, surgical procedures, clinical laboratory measurements, and medication information. Together this information reflects the patient's medical history. Many studies have efficiently used this data from the EHR to find associations that are clinically relevant, either by utilizing International Classification of Diseases, version 9 (ICD-9) codes or laboratory measurements, or by designing phenotype algorithms to extract case and control status with accuracy from the EHR. Here we developed a strategy to utilize longitudinal quantitative trait data from the EHR at Geisinger Health System focusing on outpatient metabolic and complete blood panel data as a starting point. Comprehensive Metabolic Panel (CMP) as well as Complete Blood Counts (CBC) are parts of routine care and provide a comprehensive picture from high level screening of patients' overall health and disease. We randomly split our data into two datasets to allow for discovery and replication. We first conducted a genome-wide association study (GWAS) with median values of 25 different clinical laboratory measurements to identify variants from Human Omni Express Exome beadchip data that are associated with these measurements. We identified 687 variants that associated and replicated with the tested clinical measurements at p<5×10-08. Since longitudinal data from the EHR provides a record of a patient's medical history, we utilized this information to further investigate the ICD-9 codes that might be associated with differences in variability of the measurements in the longitudinal dataset. We identified low and high variance patients by looking at changes within their individual longitudinal EHR laboratory results for each of the 25 clinical lab values (thus creating 50 groups - a high variance and a low variance for each lab variable). We then performed a PheWAS analysis with ICD-9 diagnosis codes

Nationwide outbreak of Salmonella Montevideo infections associated with contaminated imported black and red pepper: warehouse membership cards provide critical clues to identify the source.

PubMed

Gieraltowski, L; Julian, E; Pringle, J; Macdonald, K; Quilliam, D; Marsden-Haug, N; Saathoff-Huber, L; Von Stein, D; Kissler, B; Parish, M; Elder, D; Howard-King, V; Besser, J; Sodha, S; Loharikar, A; Dalton, S; Williams, I; Barton Behravesh, C

2013-06-01

In November 2009, we initiated a multistate investigation of Salmonella Montevideo infections with pulsed-field gel electrophoresis pattern JIXX01.0011. We identified 272 cases in 44 states with illness onset dates ranging from 1 July 2009 to 14 April 2010. To help generate hypotheses, warehouse store membership card information was collected to identify products consumed by cases. These records identified 19 ill persons who purchased company A salami products before onset of illness. A case-control study was conducted. Ready-to-eat salami consumption was significantly associated with illness (matched odds ratio 8·5, 95% confidence interval 2·1-75·9). The outbreak strain was isolated from company A salami products from an environmental sample from one manufacturing plant, and sealed containers of black and red pepper at the facility. This outbreak illustrates the importance of using membership card information to assist in identifying suspect vehicles, the potential for spices to contaminate ready-to-eat products, and preventing raw ingredient contamination of these products.

Evaluation of response variables in computer-simulated virtual cataract surgery

NASA Astrophysics Data System (ADS)

Söderberg, Per G.; Laurell, Carl-Gustaf; Simawi, Wamidh; Nordqvist, Per; Skarman, Eva; Nordh, Leif

2006-02-01

We have developed a virtual reality (VR) simulator for phacoemulsification (phaco) surgery. The current work aimed at evaluating the precision in the estimation of response variables identified for measurement of the performance of VR phaco surgery. We identified 31 response variables measuring; the overall procedure, the foot pedal technique, the phacoemulsification technique, erroneous manipulation, and damage to ocular structures. Totally, 8 medical or optometry students with a good knowledge of ocular anatomy and physiology but naive to cataract surgery performed three sessions each of VR Phaco surgery. For measurement, the surgical procedure was divided into a sculpting phase and an evacuation phase. The 31 response variables were measured for each phase in all three sessions. The variance components for individuals and iterations of sessions within individuals were estimated with an analysis of variance assuming a hierarchal model. The consequences of estimated variabilities for sample size requirements were determined. It was found that generally there was more variability for iterated sessions within individuals for measurements of the sculpting phase than for measurements of the evacuation phase. This resulted in larger required sample sizes for detection of difference between independent groups or change within group, for the sculpting phase as compared to for the evacuation phase. It is concluded that several of the identified response variables can be measured with sufficient precision for evaluation of VR phaco surgery.

Bacterial community assembly in activated sludge: mapping beta diversity across environmental variables.

PubMed

Isazadeh, Siavash; Jauffur, Shameem; Frigon, Dominic

2016-12-01

Effect of ecological variables on community assembly of heterotrophic bacteria at eight full-scale and two pilot-scale activated sludge wastewater treatment plants (AS-WWTPs) were explored by pyrosequencing of 16S rRNA gene amplicons. In total, 39 samples covering a range of abiotic factors spread over space and time were analyzed. A core bacterial community of 24 families detected in at least six of the eight AS-WWTPs was defined. In addition to the core families, plant-specific families (observed at <50% AS-WWTPs) were found to be also important in the community structure. Observed beta diversity was partitioned with respect to ecological variables. Specifically, the following variables were considered: influent wastewater characteristics, season (winter vs. summer), process operations (conventional, oxidation ditch, and sequence batch reactor), reactor sizes (pilot-scale vs. full-scale reactors), chemical stresses defined by ozonation of return activated sludge, interannual variation, and geographical locations. Among the assessed variables, influent wastewater characteristics and geographical locations contributed more in explaining the differences between AS-WWTP bacterial communities with a maximum of approximately 26% of the observed variations. Partitioning of beta diversity is necessary to interpret the inherent variability in microbial community assembly and identify the driving forces at play in engineered microbial ecosystem. © 2016 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

Revealing the ultrafast outflow in IRAS 13224-3809 through spectral variability

NASA Astrophysics Data System (ADS)

Parker, M. L.; Alston, W. N.; Buisson, D. J. K.; Fabian, A. C.; Jiang, J.; Kara, E.; Lohfink, A.; Pinto, C.; Reynolds, C. S.

2017-08-01

We present an analysis of the long-term X-ray variability of the extreme narrow-line Seyfert 1 galaxy IRAS 13224-3809 using principal component analysis (PCA) and fractional excess variability (Fvar) spectra to identify model-independent spectral components. We identify a series of variability peaks in both the first PCA component and Fvar spectrum which correspond to the strongest predicted absorption lines from the ultrafast outflow (UFO) discovered by Parker et al. (2017). We also find higher order PCA components, which correspond to variability of the soft excess and reflection features. The subtle differences between RMS and PCA results argue that the observed flux-dependence of the absorption is due to increased ionization of the gas, rather than changes in column density or covering fraction. This result demonstrates that we can detect outflows from variability alone and that variability studies of UFOs are an extremely promising avenue for future research.

A plant’s perspective of extremes: Terrestrial plant responses to changing climatic variability

PubMed Central

Reyer, C.; Leuzinger, S.; Rammig, A.; Wolf, A.; Bartholomeus, R. P.; Bonfante, A.; de Lorenzi, F.; Dury, M.; Gloning, P.; Abou Jaoudé, R.; Klein, T.; Kuster, T. M.; Martins, M.; Niedrist, G.; Riccardi, M.; Wohlfahrt, G.; de Angelis, P.; de Dato, G.; François, L.; Menzel, A.; Pereira, M.

2013-01-01

We review observational, experimental and model results on how plants respond to extreme climatic conditions induced by changing climatic variability. Distinguishing between impacts of changing mean climatic conditions and changing climatic variability on terrestrial ecosystems is generally underrated in current studies. The goals of our review are thus (1) to identify plant processes that are vulnerable to changes in the variability of climatic variables rather than to changes in their mean, and (2) to depict/evaluate available study designs to quantify responses of plants to changing climatic variability. We find that phenology is largely affected by changing mean climate but also that impacts of climatic variability are much less studied but potentially damaging. We note that plant water relations seem to be very vulnerable to extremes driven by changes in temperature and precipitation and that heatwaves and flooding have stronger impacts on physiological processes than changing mean climate. Moreover, interacting phenological and physiological processes are likely to further complicate plant responses to changing climatic variability. Phenological and physiological processes and their interactions culminate in even more sophisticated responses to changing mean climate and climatic variability at the species and community level. Generally, observational studies are well suited to study plant responses to changing mean climate, but less suitable to gain a mechanistic understanding of plant responses to climatic variability. Experiments seem best suited to simulate extreme events. In models, temporal resolution and model structure are crucial to capture plant responses to changing climatic variability. We highlight that a combination of experimental, observational and /or modeling studies have the potential to overcome important caveats of the respective individual approaches. PMID:23504722

Daily affect variability and context-specific alcohol consumption.

PubMed

Mohr, Cynthia D; Arpin, Sarah; McCabe, Cameron T

2015-11-01

Research explored the effects of variability in negative and positive affect on alcohol consumption, specifying daily fluctuation in affect as a critical form of emotion dysregulation. Using daily process methodology allows for a more objective calculation of affect variability relative to traditional self-reports. The present study models within-person negative and positive affect variabilities as predictors of context-specific consumption (i.e. solitary vs. social drinking), controlling for mean levels of affect. A community sample of moderate-to-heavy drinkers (n = 47; 49% women) from a US metropolitan area reported on affect and alcohol consumption thrice daily for 30 days via a handheld electronic interviewer. Within-person affect variability was calculated using daily standard deviations in positive and negative affect. Within person, greater negative and positive variabilities are related to greater daily solitary and social consumption. Across study days, mean levels of negative and positive affect variabilities related to greater social consumption between persons; yet, aggregated negative affect variability was related to less solitary consumption. Results affirm affect variability as a unique predictor of alcohol consumption, independent of mean affect levels. Yet, it is important to differentiate social context of consumption, as well as type of affect variability, particularly at the between-person level. These distinctions help clarify inconsistencies in the self-medication literature regarding associations between average levels of affect and consumption. Importantly, consistent within-person relationships for both variabilities support arguments that both negative and positive affect variabilities are detrimental and reflect an inability to regulate emotional experience. © 2015 Australasian Professional Society on Alcohol and other Drugs.

Long-term Variability of Beach Cusps

NASA Astrophysics Data System (ADS)

Pianca, C.; Holman, R. A.; Siegle, E.

2016-02-01

The most curious morphological features observed on beaches are the cusps. Due to their rhythmic spacing, beach cusps have attracted many observers and many, often contradictory, theories as to their form. Moreover, most of the research about beach cusps has focused on their formation. Few had available long time series to study such things as the variability of alongshore and cross-shore position and spacing on the cusp field, the presence, longevity and interactions between higher and lower sets of cusps, and the processes by which cusp fields extend, shrink or change length scale. The purpose of this work is to use long-term data sets of video images from two study sites, an intermediate (Duck, USA, 26 years) and a reflective beach (Massaguaçu, Brazil, 3 years), to investigate the temporal and spatial changes of cusps conditions. Time-evolving shoreline data were first extracted using an algorithm called ASLIM (Pianca et al 2015). Cusps were then identified based on the band-passed variability of time exposure image data about this shoreline as a function of elevation relative to MSL. The identified beaches cusps will be analyzed for cusp spacing, positions (upper or lower cusps), alongshore variability, merging events, percentage of cusp events, patterns of the events and time scales of variability. Finally, the relationship of these characteristics to environmental conditions (wave, tides, beach conditions) will be studied.

3D sorghum reconstructions from depth images identify QTL regulating shoot architecture

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

Mccormick, Ryan F.; Truong, Sandra K.; Mullet, John E.

Dissecting the genetic basis of complex traits is aided by frequent and nondestructive measurements. Advances in range imaging technologies enable the rapid acquisition of three-dimensional (3D) data from an imaged scene. A depth camera was used to acquire images of sorghum (Sorghum bicolor), an important grain, forage, and bioenergy crop, at multiple developmental time points from a greenhouse-grown recombinant inbred line population. A semiautomated software pipeline was developed and used to generate segmented, 3D plant reconstructions from the images. Automated measurements made from 3D plant reconstructions identified quantitative trait loci for standard measures of shoot architecture, such as shoot height,more » leaf angle, and leaf length, and for novel composite traits, such as shoot compactness. The phenotypic variability associated with some of the quantitative trait loci displayed differences in temporal prevalence; for example, alleles closely linked with the sorghum Dwarf3 gene, an auxin transporter and pleiotropic regulator of both leaf inclination angle and shoot height, influence leaf angle prior to an effect on shoot height. Furthermore, variability in composite phenotypes that measure overall shoot architecture, such as shoot compactness, is regulated by loci underlying component phenotypes like leaf angle. As such, depth imaging is an economical and rapid method to acquire shoot architecture phenotypes in agriculturally important plants like sorghum to study the genetic basis of complex traits.« less

3D sorghum reconstructions from depth images identify QTL regulating shoot architecture

DOE PAGES

Mccormick, Ryan F.; Truong, Sandra K.; Mullet, John E.

2016-08-15

Dissecting the genetic basis of complex traits is aided by frequent and nondestructive measurements. Advances in range imaging technologies enable the rapid acquisition of three-dimensional (3D) data from an imaged scene. A depth camera was used to acquire images of sorghum (Sorghum bicolor), an important grain, forage, and bioenergy crop, at multiple developmental time points from a greenhouse-grown recombinant inbred line population. A semiautomated software pipeline was developed and used to generate segmented, 3D plant reconstructions from the images. Automated measurements made from 3D plant reconstructions identified quantitative trait loci for standard measures of shoot architecture, such as shoot height,more » leaf angle, and leaf length, and for novel composite traits, such as shoot compactness. The phenotypic variability associated with some of the quantitative trait loci displayed differences in temporal prevalence; for example, alleles closely linked with the sorghum Dwarf3 gene, an auxin transporter and pleiotropic regulator of both leaf inclination angle and shoot height, influence leaf angle prior to an effect on shoot height. Furthermore, variability in composite phenotypes that measure overall shoot architecture, such as shoot compactness, is regulated by loci underlying component phenotypes like leaf angle. As such, depth imaging is an economical and rapid method to acquire shoot architecture phenotypes in agriculturally important plants like sorghum to study the genetic basis of complex traits.« less

Important considerations in lesion-symptom mapping: Illustrations from studies of word comprehension.

PubMed

Shahid, Hinna; Sebastian, Rajani; Schnur, Tatiana T; Hanayik, Taylor; Wright, Amy; Tippett, Donna C; Fridriksson, Julius; Rorden, Chris; Hillis, Argye E

2017-06-01

Lesion-symptom mapping is an important method of identifying networks of brain regions critical for functions. However, results might be influenced substantially by the imaging modality and timing of assessment. We tested the hypothesis that brain regions found to be associated with acute language deficits depend on (1) timing of behavioral measurement, (2) imaging sequences utilized to define the "lesion" (structural abnormality only or structural plus perfusion abnormality), and (3) power of the study. We studied 191 individuals with acute left hemisphere stroke with MRI and language testing to identify areas critical for spoken word comprehension. We use the data from this study to examine the potential impact of these three variables on lesion-symptom mapping. We found that only the combination of structural and perfusion imaging within 48 h of onset identified areas where more abnormal voxels was associated with more severe acute deficits, after controlling for lesion volume and multiple comparisons. The critical area identified with this methodology was the left posterior superior temporal gyrus, consistent with other methods that have identified an important role of this area in spoken word comprehension. Results have implications for interpretation of other lesion-symptom mapping studies, as well as for understanding areas critical for auditory word comprehension in the healthy brain. We propose that lesion-symptom mapping at the acute stage of stroke addresses a different sort of question about brain-behavior relationships than lesion-symptom mapping at the chronic stage, but that timing of behavioral measurement and imaging modalities should be considered in either case. Hum Brain Mapp 38:2990-3000, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Perceived importance of substance use prevention in juvenile justice: a multi-level analysis.

PubMed

Sales, Jessica M; Wasserman, Gail; Elkington, Katherine S; Lehman, Wayne; Gardner, Sheena; McReynolds, Larkin; Wiley, Tisha; Knudsen, Hannah

2018-05-15

Youth under juvenile justice (JJ) supervision are at high-risk of adverse outcomes from substance use, making prevention important. Few studies have examined prevention-related attitudes of JJ employees, yet such attitudes may be important for implementing prevention programs. Attitudes toward prevention may reflect individual characteristics and organizational contexts. Mixed effects regression was used to analyze data from 492 employees in 36 sites participating in the Juvenile Justice-Translational Research on Interventions for Adolescents in the Legal System (JJ-TRIALS) cooperative agreement. JJ employees' perceived importance of substance use prevention was measured. Staff-level variables included attitudes, job type, and demographic characteristics. Site-level variables focused on use of evidence-based screening tools, prevention programs, and drug testing. On average, JJ employees rated substance use prevention as highly important (mean = 45.9, out of 50). JJ employees generally agreed that preventing substance use was part of their agency's responsibility (mean = 3.8 on scale ranging from 1 to 5). At the site level, 72.2% used an evidence-based screening tool, 22.2% used one or more evidence-based prevention program, and 47.2% used drug testing. Reported importance of prevention was positively associated with site-level use of screening tools and drug testing as well as staff-level attitudes regarding prevention being consistent with the agency's mission. The associations between screening and prevention attitudes suggest that commitment to identifying youth needs may result in greater openness to preventing substance use. Future efforts to implement substance use prevention within JJ agencies charged with supervising youth in the community may benefit from highlighting the fit between prevention and the agency's mission.

The History of Variable Stars: A Fresh Look

NASA Astrophysics Data System (ADS)

Hatch, R. A.

2012-06-01

(Abstract only) For historians of astronomy, variable stars are important for a simple reason - stars change. But good evidence suggests this is a very modern idea. Over the millennia, our species has viewed stars as eternal and unchanging, forever fixed in time and space - indeed, the Celestial Dance was a celebration of order, reason, and stability. But everything changed in the period between Copernicus and Newton. According to tradition, two New Stars announced the birth of the New Science. Blazing across the celestial stage, Tycho's Star (1572) and Kepler's Star (1604) appeared dramatically - and just as unexpectedly - disappeared forever. But variable stars were different. Mira Ceti, the oldest, brightest, and most controversial variable star, was important because it appeared and disappeared again and again. Mira was important because it did not go away. The purpose of this essay is to take a fresh look at the history of variable stars. In re-thinking the traditional narrative, I begin with the first sightings of David Fabricius (1596) and his contemporaries - particularly Hevelius (1662) and Boulliau (1667) - to new traditions that unfolded from Newton and Maupertuis to Herschel (1780) and Pigott (1805). The essay concludes with important 19th-century developments, particularly by Argelander (1838), Pickering (1888), and Lockyer (1890). Across three centuries, variable stars prompted astronomers to re-think all the ways that stars were no longer "fixed." New strategies were needed. Astronomers needed to organize, to make continuous observations, to track changing magnitudes, and to explain stellar phases. Importantly - as Mira suggested from the outset - these challenges called for an army of observers with the discipline of Spartans. But recruiting that army required a strategy, a set of theories with shared expectations. Observation and theory worked hand-in-hand. In presenting new historical evidence from neglected printed sources and unpublished

THE TAIWANESE-AMERICAN OCCULTATION SURVEY PROJECT STELLAR VARIABILITY. II. DETECTION OF 15 VARIABLE STARS

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

Mondal, S.; Lin, C. C.; Chen, W. P.

2010-05-15

The Taiwanese-American Occultation Survey (TAOS) project has collected more than a billion photometric measurements since 2005 January. These sky survey data-covering timescales from a fraction of a second to a few hundred days-are a useful source to study stellar variability. A total of 167 star fields, mostly along the ecliptic plane, have been selected for photometric monitoring with the TAOS telescopes. This paper presents our initial analysis of a search for periodic variable stars from the time-series TAOS data on one particular TAOS field, No. 151 (R.A. = 17{sup h}30{sup m}6.{sup s}7, decl. = 27{sup 0}17'30'', J2000), which had beenmore » observed over 47 epochs in 2005. A total of 81 candidate variables are identified in the 3 deg{sup 2} field, with magnitudes in the range 8 < R < 16. On the basis of the periodicity and shape of the light curves, 29 variables, 15 of which were previously unknown, are classified as RR Lyrae, Cepheid, {delta} Scuti, SX Phonencis, semi-regular, and eclipsing binaries.« less

Pre-analytical and analytical factors influencing Alzheimer's disease cerebrospinal fluid biomarker variability.

PubMed

Fourier, Anthony; Portelius, Erik; Zetterberg, Henrik; Blennow, Kaj; Quadrio, Isabelle; Perret-Liaudet, Armand

2015-09-20

A panel of cerebrospinal fluid (CSF) biomarkers including total Tau (t-Tau), phosphorylated Tau protein at residue 181 (p-Tau) and β-amyloid peptides (Aβ42 and Aβ40), is frequently used as an aid in Alzheimer's disease (AD) diagnosis for young patients with cognitive impairment, for predicting prodromal AD in mild cognitive impairment (MCI) subjects, for AD discrimination in atypical clinical phenotypes and for inclusion/exclusion and stratification of patients in clinical trials. Due to variability in absolute levels between laboratories, there is no consensus on medical cut-off value for the CSF AD signature. Thus, for full implementation of this core AD biomarker panel in clinical routine, this issue has to be solved. Variability can be explained both by pre-analytical and analytical factors. For example, the plastic tubes used for CSF collection and storage, the lack of reference material and the variability of the analytical protocols were identified as important sources of variability. The aim of this review is to highlight these pre-analytical and analytical factors and describe efforts done to counteract them in order to establish cut-off values for core CSF AD biomarkers. This review will give the current state of recommendations. Copyright © 2015. Published by Elsevier B.V.

Climate variability controls on unsaturated water and chemical movement, High Plains aquifer, USA

USGS Publications Warehouse

Gurdak, J.J.; Hanson, R.T.; McMahon, P.B.; Bruce, B.W.; McCray, J.E.; Thyne, G.D.; Reedy, R.C.

2007-01-01

Responses in the vadose zone and groundwater to interannual, interdecadal, and multidecadal climate variability have important implications for groundwater resource sustainability, yet they are poorly documented and not well understood in most aquifers of the USA. This investigation systematically examines the role of interannual to multidecadal climate variability on groundwater levels, deep infiltration (3-23 m) events, and downward displacement (>1 m) of chloride and nitrate reservoirs in thick (15-50 m) vadose zones across the regionally extensive High Plains aquifer. Such vadose zone responses are unexpected across much of the aquifer given a priori that unsaturated total-potential profiles indicate upward water movement from the water table toward the root zone, mean annual potential evapotranspiration exceeds mean annual precipitation, and millennia-scale evapoconcentration results in substantial vadose zone chloride and nitrate reservoirs. Using singular spectrum analysis (SSA) to reconstruct precipitation and groundwater level time-series components, variability was identified in all time series as partially coincident with known climate cycles, such as the Pacific Decadal Oscillation (PDO) (10-25 yr) and the El Nin??o/Southern Oscillation (ENSO) (2-6 yr). Using these lag-correlated hydrologic time series, a new method is demonstrated to estimate climate-varying unsaturated water flux. The results suggest the importance of interannual to interdecadal climate variability on water-flux estimation in thick vadose zones and provide better understanding of the climate-induced transients responsible for the observed deep infiltration and chemical-mobilization events. Based on these results, we discuss implications for climate-related sustainability of the High Plains aquifer. ?? Soil Science Society of America.

A Spreadsheet-Based Visualized Mindtool for Improving Students' Learning Performance in Identifying Relationships between Numerical Variables

ERIC Educational Resources Information Center

Lai, Chiu-Lin; Hwang, Gwo-Jen

2015-01-01

In this study, a spreadsheet-based visualized Mindtool was developed for improving students' learning performance when finding relationships between numerical variables by engaging them in reasoning and decision-making activities. To evaluate the effectiveness of the proposed approach, an experiment was conducted on the "phenomena of climate…

Challenges in Identifying Patients with Type 2 Diabetes for Quality-Improvement Interventions in Primary Care Settings and the Importance of Valid Disease Registries.

PubMed

Wozniak, Lisa; Soprovich, Allison; Rees, Sandra; Johnson, Steven T; Majumdar, Sumit R; Johnson, Jeffrey A

2015-10-01

Patient registries are considered an important foundation of chronic disease management, and diabetes patient registries are associated with better processes and outcomes of care. The purpose of this article is to describe the development and use of registries in the Alberta's Caring for Diabetes (ABCD) project to identify and reach target populations for quality-improvement interventions in the primary care setting. We applied the reach, effectiveness, adoption, implementation and maintenance (RE-AIM) framework and expanded the definition of reach beyond the individual (i.e. patient) level to include the ability to identify target populations at an organizational level. To characterize reach and the implementation of registries, semistructured interviews were conducted with key informants, and a usual-care checklist was compiled for each participating Primary Care Network (PCN). Content analysis was used to analyze qualitative data. Using registries to identify and recruit participants for the ABCD interventions proved challenging. The quality of the registries depended on whether physicians granted PCN access to patient lists, the strategies used in development, the reliability of diagnostic information and the data elements collected. In addition, once a diabetes registry was developed, there was limited ability to update it. Proactive management of chronic diseases like diabetes requires the ability to reach targeted patients at the population level. We observed several challenges to the development and application of patient registries. Given the importance of valid registries, strong collaborations and novel strategies that involve policy-makers, PCNs and providers are needed to help find solutions to improve registry quality and resolve maintenance issues. Copyright © 2015 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.

Small RNA sequencing in cells and exosomes identifies eQTLs and 14q32 as a region of active export

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

Tsang, Emily K.; Abell, Nathan S.; Li, Xin

Exosomes are small extracellular vesicles that carry heterogeneous cargo, including RNA, between cells. Increasing evidence suggests that exosomes are important mediators of intercellular communication and biomarkers of disease. Despite this, the variability of exosomal RNA between individuals has not been well quantified. To assess this variability, we sequenced the small RNA of cells and exosomes from a 17-member family. Across individuals, we show that selective export of miRNAs occurs not only at the level of specific transcripts, but that a cluster of 74 mature miRNAs on chromosome 14q32 is massively exported in exosomes while mostly absent from cells. We alsomore » observe more interindividual variability between exosomal samples than between cellular ones and identify four miRNA expression quantitative trait loci shared between cells and exosomes. Lastly, our findings indicate that genomically colocated miRNAs can be exported together and highlight the variability in exosomal miRNA levels between individuals as relevant for exosome use as diagnostics.« less

Small RNA sequencing in cells and exosomes identifies eQTLs and 14q32 as a region of active export

DOE PAGES

Tsang, Emily K.; Abell, Nathan S.; Li, Xin; ...

2016-10-31

Exosomes are small extracellular vesicles that carry heterogeneous cargo, including RNA, between cells. Increasing evidence suggests that exosomes are important mediators of intercellular communication and biomarkers of disease. Despite this, the variability of exosomal RNA between individuals has not been well quantified. To assess this variability, we sequenced the small RNA of cells and exosomes from a 17-member family. Across individuals, we show that selective export of miRNAs occurs not only at the level of specific transcripts, but that a cluster of 74 mature miRNAs on chromosome 14q32 is massively exported in exosomes while mostly absent from cells. We alsomore » observe more interindividual variability between exosomal samples than between cellular ones and identify four miRNA expression quantitative trait loci shared between cells and exosomes. Lastly, our findings indicate that genomically colocated miRNAs can be exported together and highlight the variability in exosomal miRNA levels between individuals as relevant for exosome use as diagnostics.« less

Ionosphere variability during the 2009 SSW: Influence of the lunar semidiurnal tide and mechanisms producing electron density variability

NASA Astrophysics Data System (ADS)

Pedatella, N. M.; Liu, H.-L.; Sassi, F.; Lei, J.; Chau, J. L.; Zhang, X.

2014-05-01

To investigate ionosphere variability during the 2009 sudden stratosphere warming (SSW), we present simulation results that combine the Whole Atmosphere Community Climate Model Extended version and the thermosphere-ionosphere-mesosphere electrodynamics general circulation model (TIME-GCM). The simulations reveal notable enhancements in both the migrating semidiurnal solar (SW2) and lunar (M2) tides during the SSW. The SW2 and M2 amplitudes reach ˜50 m s-1 and ˜40 m s-1, respectively, in zonal wind at E region altitudes. The dramatic increase in the M2 at these altitudes influences the dynamo generation of electric fields, and the importance of the M2 on the ionosphere variability during the 2009 SSW is demonstrated by comparing simulations with and without the M2. TIME-GCM simulations that incorporate the M2 are found to be in good agreement with Jicamarca Incoherent Scatter Radar vertical plasma drifts and Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) observations of the maximum F region electron density. The agreement with observations is worse if the M2 is not included in the simulation, demonstrating that the lunar tide is an important contributor to the ionosphere variability during the 2009 SSW. We additionally investigate sources of the F region electron density variability during the SSW. The primary driver of the electron density variability is changes in electric fields. Changes in meridional neutral winds and thermosphere composition are found to also contribute to the electron density variability during the 2009 SSW. The electron density variability for the 2009 SSW is therefore not solely due to variability in electric fields as previously thought.

Interannual variability in the number of Northern Hemisphere Cut-off low systems.

NASA Astrophysics Data System (ADS)

Nieto, R.; Gimeno, L.; de La Torre, L.; Tesouro, M.; Añel, J. A.; Ribera, P.

2003-04-01

Cut-off low-pressure systems-COLS- are usually closed circulations at middle and upper troposphere developed from a deep trough in the westerlies. The importance of their study is due to both the convective severe events that can occur if they are over warm ocean and because they are important mechanisms of Stratosphere-troposphere exchange- STE-. However few is known about their interannual variability, due to the limited duration of the study (five years) of previous global climatologies. In this study we identify COLs systems in the Northern Hemisphere for a 41-year period (1958 to 1998) using an approach based in imposing the three main physical characteristics of the conceptual model of COL (a. closed circulation and minimum of geopotential, minimum of equivalent thickness, and two baroclinic zones, one in front of the low and the other behind the low). Data from NCAR-NCEP reanalysis were used. The aim of the study is to detect trends and to identify associations both with blocking events and major modes of climate variability. Results show that 1) in the Asian sector both less intense and more intense COLs had a significant positive trend whereas in the Pacific and the Atlantic sectors only less intense COLs had a significant positive trend, 2) Most of COLs were associated with blocking events, 3) During positive ENSO phases the number of less intense COLs in the Pacific were lower than during negative ENSO phases and 4) During positive Northern Annular Mode (NAM) phases the number of less intense COLs in the Atlantic were higher than during negative NAM phases.

Statistically extracted fundamental watershed variables for estimating the loads of total nitrogen in small streams

USGS Publications Warehouse

Kronholm, Scott C.; Capel, Paul D.; Terziotti, Silvia

2016-01-01

Accurate estimation of total nitrogen loads is essential for evaluating conditions in the aquatic environment. Extrapolation of estimates beyond measured streams will greatly expand our understanding of total nitrogen loading to streams. Recursive partitioning and random forest regression were used to assess 85 geospatial, environmental, and watershed variables across 636 small (<585 km2) watersheds to determine which variables are fundamentally important to the estimation of annual loads of total nitrogen. Initial analysis led to the splitting of watersheds into three groups based on predominant land use (agricultural, developed, and undeveloped). Nitrogen application, agricultural and developed land area, and impervious or developed land in the 100-m stream buffer were commonly extracted variables by both recursive partitioning and random forest regression. A series of multiple linear regression equations utilizing the extracted variables were created and applied to the watersheds. As few as three variables explained as much as 76 % of the variability in total nitrogen loads for watersheds with predominantly agricultural land use. Catchment-scale national maps were generated to visualize the total nitrogen loads and yields across the USA. The estimates provided by these models can inform water managers and help identify areas where more in-depth monitoring may be beneficial.

Continuation Power Flow with Variable-Step Variable-Order Nonlinear Predictor

NASA Astrophysics Data System (ADS)

Kojima, Takayuki; Mori, Hiroyuki

This paper proposes a new continuation power flow calculation method for drawing a P-V curve in power systems. The continuation power flow calculation successively evaluates power flow solutions through changing a specified value of the power flow calculation. In recent years, power system operators are quite concerned with voltage instability due to the appearance of deregulated and competitive power markets. The continuation power flow calculation plays an important role to understand the load characteristics in a sense of static voltage instability. In this paper, a new continuation power flow with a variable-step variable-order (VSVO) nonlinear predictor is proposed. The proposed method evaluates optimal predicted points confirming with the feature of P-V curves. The proposed method is successfully applied to IEEE 118-bus and IEEE 300-bus systems.

Modelling the regional variability of the probability of high trihalomethane occurrence in municipal drinking water.

PubMed

Cool, Geneviève; Lebel, Alexandre; Sadiq, Rehan; Rodriguez, Manuel J

2015-12-01

The regional variability of the probability of occurrence of high total trihalomethane (TTHM) levels was assessed using multilevel logistic regression models that incorporate environmental and infrastructure characteristics. The models were structured in a three-level hierarchical configuration: samples (first level), drinking water utilities (DWUs, second level) and natural regions, an ecological hierarchical division from the Quebec ecological framework of reference (third level). They considered six independent variables: precipitation, temperature, source type, seasons, treatment type and pH. The average probability of TTHM concentrations exceeding the targeted threshold was 18.1%. The probability was influenced by seasons, treatment type, precipitations and temperature. The variance at all levels was significant, showing that the probability of TTHM concentrations exceeding the threshold is most likely to be similar if located within the same DWU and within the same natural region. However, most of the variance initially attributed to natural regions was explained by treatment types and clarified by spatial aggregation on treatment types. Nevertheless, even after controlling for treatment type, there was still significant regional variability of the probability of TTHM concentrations exceeding the threshold. Regional variability was particularly important for DWUs using chlorination alone since they lack the appropriate treatment required to reduce the amount of natural organic matter (NOM) in source water prior to disinfection. Results presented herein could be of interest to authorities in identifying regions with specific needs regarding drinking water quality and for epidemiological studies identifying geographical variations in population exposure to disinfection by-products (DBPs).

Identifying linkages between land use, geomorphology, and aquatic habitat in a mixed-use watershed.

PubMed

McIlroy, Susan K; Montagne, Cliff; Jones, Clain A; McGlynn, Brian L

2008-11-01

The potential impacts of land use on large woody debris (LWD) were examined in Sourdough Creek Watershed, a rapidly growing area encompassing Bozeman, Montana, USA. We identified six land classes within a 250 m buffer extending on either side of Sourdough Creek and assessed aquatic habitat and geomorphologic variables within each class. All LWD pieces were counted, and we examined 14 other variables, including undercut bank, sinuosity, and substrate composition. LWD numbers were generally low and ranged from 0 to 8.2 pieces per 50 m of stream. Linear regression showed that LWD increased with distance from headwaters, riparian forest width, and sinuosity in four of the six land classes. Statistically significant differences between land classes for many aquatic habitat and geomorphologic variables indicated the impacts of different land uses on stream structure. We also found that practices such as active wood removal played a key role in LWD abundance. This finding suggests that managers should prioritize public education and outreach concerning the importance of in-stream wood, especially in mixed-use watersheds where wood is removed for either aesthetic reasons or to prevent stream flooding.

Interannual variability of ammonia concentrations over the United States: sources and implications

NASA Astrophysics Data System (ADS)

Schiferl, Luke D.; Heald, Colette L.; Van Damme, Martin; Clarisse, Lieven; Clerbaux, Cathy; Coheur, Pierre-François; Nowak, John B.; Neuman, J. Andrew; Herndon, Scott C.; Roscioli, Joseph R.; Eilerman, Scott J.

2016-09-01

The variability of atmospheric ammonia (NH3), emitted largely from agricultural sources, is an important factor when considering how inorganic fine particulate matter (PM2.5) concentrations and nitrogen cycling are changing over the United States. This study combines new observations of ammonia concentration from the surface, aboard aircraft, and retrieved by satellite to both evaluate the simulation of ammonia in a chemical transport model (GEOS-Chem) and identify which processes control the variability of these concentrations over a 5-year period (2008-2012). We find that the model generally underrepresents the ammonia concentration near large source regions (by 26 % at surface sites) and fails to reproduce the extent of interannual variability observed at the surface during the summer (JJA). Variability in the base simulation surface ammonia concentration is dominated by meteorology (64 %) as compared to reductions in SO2 and NOx emissions imposed by regulation (32 %) over this period. Introduction of year-to-year varying ammonia emissions based on animal population, fertilizer application, and meteorologically driven volatilization does not substantially improve the model comparison with observed ammonia concentrations, and these ammonia emissions changes have little effect on the simulated ammonia concentration variability compared to those caused by the variability of meteorology and acid-precursor emissions. There is also little effect on the PM2.5 concentration due to ammonia emissions variability in the summer when gas-phase changes are favored, but variability in wintertime emissions, as well as in early spring and late fall, will have a larger impact on PM2.5 formation. This work highlights the need for continued improvement in both satellite-based and in situ ammonia measurements to better constrain the magnitude and impacts of spatial and temporal variability in ammonia concentrations.

Temporal Variability of Observed and Simulated Hyperspectral Earth Reflectance

NASA Technical Reports Server (NTRS)

Roberts, Yolanda; Pilewskie, Peter; Kindel, Bruce; Feldman, Daniel; Collins, William D.

2012-01-01

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system designed to study Earth's climate variability with unprecedented absolute radiometric accuracy and SI traceability. Observation System Simulation Experiments (OSSEs) were developed using GCM output and MODTRAN to simulate CLARREO reflectance measurements during the 21st century as a design tool for the CLARREO hyperspectral shortwave imager. With OSSE simulations of hyperspectral reflectance, Feldman et al. [2011a,b] found that shortwave reflectance is able to detect changes in climate variables during the 21st century and improve time-to-detection compared to broadband measurements. The OSSE has been a powerful tool in the design of the CLARREO imager and for understanding the effect of climate change on the spectral variability of reflectance, but it is important to evaluate how well the OSSE simulates the Earth's present-day spectral variability. For this evaluation we have used hyperspectral reflectance measurements from the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), a shortwave spectrometer that was operational between March 2002 and April 2012. To study the spectral variability of SCIAMACHY-measured and OSSE-simulated reflectance, we used principal component analysis (PCA), a spectral decomposition technique that identifies dominant modes of variability in a multivariate data set. Using quantitative comparisons of the OSSE and SCIAMACHY PCs, we have quantified how well the OSSE captures the spectral variability of Earth?s climate system at the beginning of the 21st century relative to SCIAMACHY measurements. These results showed that the OSSE and SCIAMACHY data sets share over 99% of their total variance in 2004. Using the PCs and the temporally distributed reflectance spectra projected onto the PCs (PC scores), we can study the temporal variability of the observed and simulated reflectance spectra. Multivariate time

An environmental scan of academic pediatric emergency medicine at Canadian medical schools: Identifying variability across Canada.

PubMed

Artz, Jennifer D; Meckler, Garth; Argintaru, Niran; Lim, Roderick; Stiell, Ian G

2018-01-28

To complement our environmental scan of academic emergency medicine departments, we conducted a similar environmental scan of the academic pediatric emergency medicine programs offered by the Canadian medical schools. We developed an 88-question form, which was distributed to pediatric academic leaders at each medical school. The responses were validated via email to ensure that the questions were answered completely and consistently. Fourteen of the 17 Canadian medical schools have some type of pediatric emergency medicine academic program. None of the pediatric emergency medicine units have full departmental status, while nine are divisions, two are sections, and three have no status. Canadian academic pediatric emergency medicine is practised at 13 major teaching hospitals and one specialized pediatric emergency department. There are 394 pediatric emergency medicine faculty members, including 13 full professors and 64 associate professors. Eight sites regularly take pediatric undergraduate clinical clerks, and all 14 provide resident education. Fellowship training is offered at 10 sites, with five offering advanced pediatric emergency medicine fellowship training. Half of the sites have at least one physician with a Master's degree in education, totalling 18 faculty members across Canada. There are 31 clinical researchers with salary support at nine universities. Eleven sites have published peer-reviewed papers (n=423) in the past five years, ranging from two to 102 per site. Annual academic budgets range from $10,000 to $2,607,515. This comprehensive review of academic activities in pediatric emergency medicine across Canada identifies the variability across the country, including the recognition of sites above and below the national average, which may prompt change at individual sites. Sharing these academic practices may inspire sites to provide more support to teachers, educators, and researchers.

Variability in Institutional Screening Practices Related to Collegiate Student-Athlete Mental Health.

PubMed

Kroshus, Emily

2016-05-01

Universal screening for mental health concerns, as part of the preparticipation examination in collegiate sports medicine settings, can be an important and feasible strategy for facilitating early detection of mental health disorders. To assess whether sports medicine departments at National Collegiate Athletic Association (NCAA) member colleges have policies related to identifying student-athlete mental health problems, the nature of preparticipation examination screening related to mental health, and whether other departmental or institutional screening initiatives are in place. I also aimed to characterize the variability in screening by institutional characteristics. Cross-sectional study. College sports medicine departments. Team physicians and head athletic trainers at NCAA member colleges (n = 365, 30.3% response rate). Electronic survey of departmental mental health screening activities. A total of 39% of respondents indicated that their institution had a written plan related to identifying student-athletes with mental health concerns. Fewer than half reported that their sports medicine department administers a written or verbal screening instrument for symptoms of disordered eating (44.5%), depression (32.3%), or anxiety (30.7%). The strongest predictors of mental health screening were the presence of a written plan related to identifying student-athlete mental health concerns and the employment of a clinical psychologist. Additionally, Division I institutions and institutions with a greater ratio of athletic trainers to student-athletes tended to engage in more screening. The substantial among-institutions variability in mental health screening suggests that opportunities exist to make these practices more widespread. To address this variability, recent NCAA mental health best-practice guidelines suggested that institutions should screen for a range of mental health disorders and risk behaviors. However, at some institutions, staffing deficits may need to

Validation of the ICU-DaMa tool for automatically extracting variables for minimum dataset and quality indicators: The importance of data quality assessment.

PubMed

Sirgo, Gonzalo; Esteban, Federico; Gómez, Josep; Moreno, Gerard; Rodríguez, Alejandro; Blanch, Lluis; Guardiola, Juan José; Gracia, Rafael; De Haro, Lluis; Bodí, María

2018-04-01

Big data analytics promise insights into healthcare processes and management, improving outcomes while reducing costs. However, data quality is a major challenge for reliable results. Business process discovery techniques and an associated data model were used to develop data management tool, ICU-DaMa, for extracting variables essential for overseeing the quality of care in the intensive care unit (ICU). To determine the feasibility of using ICU-DaMa to automatically extract variables for the minimum dataset and ICU quality indicators from the clinical information system (CIS). The Wilcoxon signed-rank test and Fisher's exact test were used to compare the values extracted from the CIS with ICU-DaMa for 25 variables from all patients attended in a polyvalent ICU during a two-month period against the gold standard of values manually extracted by two trained physicians. Discrepancies with the gold standard were classified into plausibility, conformance, and completeness errors. Data from 149 patients were included. Although there were no significant differences between the automatic method and the manual method, we detected differences in values for five variables, including one plausibility error and two conformance and completeness errors. Plausibility: 1) Sex, ICU-DaMa incorrectly classified one male patient as female (error generated by the Hospital's Admissions Department). Conformance: 2) Reason for isolation, ICU-DaMa failed to detect a human error in which a professional misclassified a patient's isolation. 3) Brain death, ICU-DaMa failed to detect another human error in which a professional likely entered two mutually exclusive values related to the death of the patient (brain death and controlled donation after circulatory death). Completeness: 4) Destination at ICU discharge, ICU-DaMa incorrectly classified two patients due to a professional failing to fill out the patient discharge form when thepatients died. 5) Length of continuous renal replacement

Using variable homography to measure emergent fibers on textile fabrics

NASA Astrophysics Data System (ADS)

Xu, Jun; Cudel, Christophe; Kohler, Sophie; Fontaine, Stéphane; Haeberlé, Olivier; Klotz, Marie-Louise

2011-07-01

A fabric's smoothness is a key factor to determine the quality of textile finished products and has great influence on the functionality of industrial textiles and high-end textile products. With popularization of the 'zero defect' industrial concept, identifying and measuring defective material in the early stage of production is of great interest for the industry. In the current market, many systems are able to achieve automatic monitoring and control of fabric, paper, and nonwoven material during the entire production process, however online measurement of hairiness is still an open topic and highly desirable for industrial applications. In this paper we propose a computer vision approach, based on variable homography, which can be used to measure the emergent fiber's length on textile fabrics. The main challenges addressed in this paper are the application of variable homography to textile monitoring and measurement, as well as the accuracy of the estimated calculation. We propose that a fibrous structure can be considered as a two-layer structure and then show how variable homography can estimate the length of the fiber defects. Simulations are carried out to show the effectiveness of this method to measure the emergent fiber's length. The true lengths of selected fibers are measured precisely using a digital optical microscope, and then the same fibers are tested by our method. Our experimental results suggest that smoothness monitored by variable homography is an accurate and robust method for quality control of important industrially fabrics.

Prediction of fruit and vegetable intake: The importance of contextualizing motivation.

PubMed

Evans, Rachel; Kawabata, Masato; Thomas, Shirley

2015-09-01

Motivation is identified as a key antecedent of self-regulated behaviour, such as eating fruit and vegetables. However, inaccurate measurement of this construct may lead to poor prediction of behaviour and inflate the impact of post-motivational factors, such as planning, in models of health behaviour. This study explored the properties of a newly identified measure of motivation, termed behavioural resolve (Rhodes & Horne, 2013, Psychol. Sport Exerc., 14, 455-460), in relation to intention, planning, and fruit and vegetable intake (FVI). Prospective self-report survey. University students living in the United Kingdom completed two online surveys. The first assessed demographic and predictor variables (intention, behavioural resolve, action planning, and coping planning). The second, completed approximately 2 weeks later, measured average daily FVI and perceived experience of obstacles to FVI. At Time 1, there were 195 respondents, with 139 providing follow-up data. All predictor variables were significantly correlated with FVI. Two independent multiple hierarchical regression analyses revealed that both intention and behavioural resolve were significant predictors of FVI, but behavioural resolve explained greater FVI variance (40.1%) than intention (36.4%). Furthermore, action planning showed incremental predictive utility over intention, but not behavioural resolve, in predicting FVI. The results indicated that motivation is an important determinant of FVI for students, with behavioural resolve demonstrating advantages over intention as a measure of this domain and a predictor of FVI behaviour. © 2014 The British Psychological Society.

Analysis of contextual variables in the evaluation of child abuse in the pediatric emergency setting.

PubMed

Almeida, Ana Nunes de; Ramos, Vasco; Almeida, Helena Nunes de; Escobar, Carlos Gil; Garcia, Catarina

This article comprises a sample of abuse modalities observed in a pediatric emergency room of a public hospital in the Lisbon metropolitan area and a multifactorial characterization of physical and sexual violence. The objectives are: (1) to discuss the importance of social and family variables in the configuration of both types of violence; (2) to show how physical and sexual violence have subtypes and internal diversity. A statistical analysis was carried out in a database (1063 records of child abuse between 2004 and 2013). A form was applied to cases with suspected abuse, containing data on the child, family, abuse episode, abuser, medical history, and clinical observation. A factorial analysis of multiple correspondence was performed to identify patterns of association between social variables and physical and sexual violence, as well as their internal diversity. The prevalence of abuse in this pediatric emergency room was 0.6%. Physical violence predominated (69.4%), followed by sexual violence (39.3%). Exploratory profiles of these types of violence were constructed. Regarding physical violence, the gender of the abuser was the first differentiating dimension; the victim's gender and age range were the second one. In the case of sexual violence, the age of the abuser and co-residence with him/her comprised the first dimension; the victim's age and gender comprised the second dimension. Patterns of association between victims, family contexts, and abusers were identified. It is necessary to alert clinicians about the importance of social variables in the multiple facets of child abuse. Copyright © 2017 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

ICD-10 codes used to identify adverse drug events in administrative data: a systematic review.

PubMed

Hohl, Corinne M; Karpov, Andrei; Reddekopp, Lisa; Doyle-Waters, Mimi; Stausberg, Jürgen

2014-01-01

Adverse drug events, the unintended and harmful effects of medications, are important outcome measures in health services research. Yet no universally accepted set of International Classification of Diseases (ICD) revision 10 codes or coding algorithms exists to ensure their consistent identification in administrative data. Our objective was to synthesize a comprehensive set of ICD-10 codes used to identify adverse drug events. We developed a systematic search strategy and applied it to five electronic reference databases. We searched relevant medical journals, conference proceedings, electronic grey literature and bibliographies of relevant studies, and contacted content experts for unpublished studies. One author reviewed the titles and abstracts for inclusion and exclusion criteria. Two authors reviewed eligible full-text articles and abstracted data in duplicate. Data were synthesized in a qualitative manner. Of 4241 titles identified, 41 were included. We found a total of 827 ICD-10 codes that have been used in the medical literature to identify adverse drug events. The median number of codes used to search for adverse drug events was 190 (IQR 156-289) with a large degree of variability between studies in the numbers and types of codes used. Authors commonly used external injury (Y40.0-59.9) and disease manifestation codes. Only two papers reported on the sensitivity of their code set. Substantial variability exists in the methods used to identify adverse drug events in administrative data. Our work may serve as a point of reference for future research and consensus building in this area.

ICD-10 codes used to identify adverse drug events in administrative data: a systematic review

PubMed Central

Hohl, Corinne M; Karpov, Andrei; Reddekopp, Lisa; Stausberg, Jürgen

2014-01-01

Background Adverse drug events, the unintended and harmful effects of medications, are important outcome measures in health services research. Yet no universally accepted set of International Classification of Diseases (ICD) revision 10 codes or coding algorithms exists to ensure their consistent identification in administrative data. Our objective was to synthesize a comprehensive set of ICD-10 codes used to identify adverse drug events. Methods We developed a systematic search strategy and applied it to five electronic reference databases. We searched relevant medical journals, conference proceedings, electronic grey literature and bibliographies of relevant studies, and contacted content experts for unpublished studies. One author reviewed the titles and abstracts for inclusion and exclusion criteria. Two authors reviewed eligible full-text articles and abstracted data in duplicate. Data were synthesized in a qualitative manner. Results Of 4241 titles identified, 41 were included. We found a total of 827 ICD-10 codes that have been used in the medical literature to identify adverse drug events. The median number of codes used to search for adverse drug events was 190 (IQR 156–289) with a large degree of variability between studies in the numbers and types of codes used. Authors commonly used external injury (Y40.0–59.9) and disease manifestation codes. Only two papers reported on the sensitivity of their code set. Conclusions Substantial variability exists in the methods used to identify adverse drug events in administrative data. Our work may serve as a point of reference for future research and consensus building in this area. PMID:24222671

DNA Barcode for Identifying Folium Artemisiae Argyi from Counterfeits.

PubMed

Mei, Quanxi; Chen, Xiaolu; Xiang, Li; Liu, Yue; Su, Yanyan; Gao, Yuqiao; Dai, Weibo; Dong, Pengpeng; Chen, Shilin

2016-01-01

Folium Artemisiae Argyi is an important herb in traditional Chinese medicine. It is commonly used in moxibustion, medicine, etc. However, identifying Artemisia argyi is difficult because this herb exhibits similar morphological characteristics to closely related species and counterfeits. To verify the applicability of DNA barcoding, ITS2 and psbA-trnH were used to identify A. argyi from 15 closely related species and counterfeits. Results indicated that total DNA was easily extracted from all the samples and that both ITS2 and psbA-trnH fragments can be easily amplified. ITS2 was a more ideal barcode than psbA-trnH and ITS2+psbA-trnH to identify A. argyi from closely related species and counterfeits on the basis of sequence character, genetic distance, and tree methods. The sequence length was 225 bp for the 56 ITS2 sequences of A. argyi, and no variable site was detected. For the ITS2 sequences, A. capillaris, A. anomala, A. annua, A. igniaria, A. maximowicziana, A. princeps, Dendranthema vestitum, and D. indicum had single nucleotide polymorphisms (SNPs). The intraspecific Kimura 2-Parameter distance was zero, which is lower than the minimum interspecific distance (0.005). A. argyi, the closely related species, and counterfeits, except for Artemisia maximowicziana and Artemisia sieversiana, were separated into pairs of divergent clusters by using the neighbor joining, maximum parsimony, and maximum likelihood tree methods. Thus, the ITS2 sequence was an ideal barcode to identify A. argyi from closely related species and counterfeits to ensure the safe use of this plant.

Standardized principal components for vegetation variability monitoring across space and time

NASA Astrophysics Data System (ADS)

Mathew, T. R.; Vohora, V. K.

2016-08-01

Vegetation at any given location changes through time and in space. In what quantity it changes, where and when can help us in identifying sources of ecosystem stress, which is very useful for understanding changes in biodiversity and its effect on climate change. Such changes known for a region are important in prioritizing management. The present study considers the dynamics of savanna vegetation in Kruger National Park (KNP) through the use of temporal satellite remote sensing images. Spatial variability of vegetation is a key characteristic of savanna landscapes and its importance to biodiversity has been demonstrated by field-based studies. The data used for the study were sourced from the U.S. Agency for International Development where AVHRR derived Normalized Difference Vegetation Index (NDVI) images available at spatial resolutions of 8 km and at dekadal scales. The study area was extracted from these images for the time-period 1984-2002. Maximum value composites were derived for individual months resulting in an image dataset of 216 NDVI images. Vegetation dynamics across spatio-temporal domains were analyzed using standardized principal components analysis (SPCA) on the NDVI time-series. Each individual image variability in the time-series is considered. The outcome of this study demonstrated promising results - the variability of vegetation change in the area across space and time, and also indicated changes in landscape on 6 individual principal components (PCs) showing differences not only in magnitude, but also in pattern, of different selected eco-zones with constantly changing and evolving ecosystem.

Environmental Variables That Influence Patient Satisfaction: A Review of the Literature.

PubMed

MacAllister, Lorissa; Zimring, Craig; Ryherd, Erica

2016-10-01

Patient's perception of care-referred to as patient satisfaction-is of great interest in the healthcare industry, as it becomes more directly tied to the revenue of the health system providers. The perception of care has now become important in addition to the actual health outcome of the patient. The known influencers for the patient perception of care are the patient's own characteristics as well as the quality of service received. In patient surveys, the physical environment is noted as important for being clean and quiet but is not considered a critical part of patient satisfaction or other health outcomes. Patient perception of care is currently measured as patient satisfaction, a systematic collection of perceptions of social interactions from an individual person as well as their interaction with the environment. This exploration of the literature intends to explore the rigorous, statistically tested research conducted that has a spatial predictor variable and a health or behavior outcome, with the intent to begin to further test the relationships of these variables in the future studies. This literature review uses the patient satisfaction framework of components of influence and identifies at least 10 known spatial environmental variables that have been shown to have a direct connection to the health and behavior outcome of a patient. The results show that there are certain features of the spatial layout and environmental design in hospital or work settings that influence outcomes and should be noted in the future research. © The Author(s) 2016.

Identifying Challenges to the Integration of Computer-Based Surveillance Information Systems in a Large City Health Department: A Case Study.

PubMed

Jennings, Jacky M; Stover, Jeffrey A; Bair-Merritt, Megan H; Fichtenberg, Caroline; Munoz, Mary Grace; Maziad, Rafiq; Ketemepi, Sherry Johnson; Zenilman, Jonathan

2009-01-01

Integrated infectious disease surveillance information systems have the potential to provide important new surveillance capacities and business efficiencies for local health departments. We conducted a case study at a large city health department of the primary computer-based infectious disease surveillance information systems during a 10-year period to identify the major challenges for information integration across the systems. The assessment included key informant interviews and evaluations of the computer-based surveillance information systems used for acute communicable diseases, human immunodeficiency virus/acquired immunodeficiency syndrome, sexually transmitted diseases, and tuberculosis. Assessments were conducted in 1998 with a follow-up in 2008. Assessments specifically identified and described the primary computer-based surveillance information system, any duplicative information systems, and selected variables collected. Persistent challenges to information integration across the information systems included the existence of duplicative data systems, differences in the variables used to collect similar information, and differences in basic architecture. The assessments identified a number of challenges for information integration across the infectious disease surveillance information systems at this city health department. The results suggest that local disease control programs use computer-based surveillance information systems that were not designed for data integration. To the extent that integration provides important new surveillance capacities and business efficiencies, we recommend that patient-centric information systems be designed that provide all the epidemiologic, clinical, and research needs in one system. In addition, the systems should include a standard system of elements and fields across similar surveillance systems.

Development and validation of classifiers and variable subsets for predicting nursing home admission.

PubMed

Nuutinen, Mikko; Leskelä, Riikka-Leena; Suojalehto, Ella; Tirronen, Anniina; Komssi, Vesa

2017-04-13

In previous years a substantial number of studies have identified statistically important predictors of nursing home admission (NHA). However, as far as we know, the analyses have been done at the population-level. No prior research has analysed the prediction accuracy of a NHA model for individuals. This study is an analysis of 3056 longer-term home care customers in the city of Tampere, Finland. Data were collected from the records of social and health service usage and RAI-HC (Resident Assessment Instrument - Home Care) assessment system during January 2011 and September 2015. The aim was to find out the most efficient variable subsets to predict NHA for individuals and validate the accuracy. The variable subsets of predicting NHA were searched by sequential forward selection (SFS) method, a variable ranking metric and the classifiers of logistic regression (LR), support vector machine (SVM) and Gaussian naive Bayes (GNB). The validation of the results was guaranteed using randomly balanced data sets and cross-validation. The primary performance metrics for the classifiers were the prediction accuracy and AUC (average area under the curve). The LR and GNB classifiers achieved 78% accuracy for predicting NHA. The most important variables were RAI MAPLE (Method for Assigning Priority Levels), functional impairment (RAI IADL, Activities of Daily Living), cognitive impairment (RAI CPS, Cognitive Performance Scale), memory disorders (diagnoses G30-G32 and F00-F03) and the use of community-based health-service and prior hospital use (emergency visits and periods of care). The accuracy of the classifier for individuals was high enough to convince the officials of the city of Tampere to integrate the predictive model based on the findings of this study as a part of home care information system. Further work need to be done to evaluate variables that are modifiable and responsive to interventions.

Stochastic investigation of precipitation process for climatic variability identification

NASA Astrophysics Data System (ADS)

Sotiriadou, Alexia; Petsiou, Amalia; Feloni, Elisavet; Kastis, Paris; Iliopoulou, Theano; Markonis, Yannis; Tyralis, Hristos; Dimitriadis, Panayiotis; Koutsoyiannis, Demetris

2016-04-01

The precipitation process is important not only to hydrometeorology but also to renewable energy resources management. We use a dataset consisting of daily and hourly records around the globe to identify statistical variability with emphasis on the last period. Specifically, we investigate the occurrence of mean, maximum and minimum values and we estimate statistical properties such as marginal probability distribution function and the type of decay of the climacogram (i.e., mean process variance vs. scale). Acknowledgement: This research is conducted within the frame of the undergraduate course "Stochastic Methods in Water Resources" of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly.

Comparing domestic versus imported apples: a focus on energy use.

PubMed

Milà i Canals, Llorenç; Cowell, Sarah J; Sim, Sarah; Basson, Lauren

2007-07-01

The issue of whether food miles are a relevant indicator for the environmental impacts associated with foods has received significant attention in recent years. It is suggested here that issues other than the distance travelled need to be considered. The argument is presented by illustrating the case for the provision of apples. The effects of variability in primary energy requirements for apple cultivation and for other life cycle stages, seasonality (timing of consumption) and loss of produce during storage are studied in this paper, by comparing apples from different supplier countries for consumption in Europe. Data sources for primary energy use (PEU) of apple production are identified ranging from 0.4-3.8 MJ/kg apples for European and Southern American countries and 0.4-0.7 MJ/kg for New Zealand. This variability is related to different yields and producer management practices in the different countries. Storage loss may range from 5% to 40% for storage periods between 4 and 10 months, and this has a significant effect on the results (e.g. increasing the total PEU by 8-16% when stored for 5-9 months in Europe as compared with a no loss and no storage situation). The storage periods and related storage losses change markedly through the year for imported (i.e. non-European) versus European apples. The timing of consumption and related storage losses need to be included in the assessment, as this affects the order of preference for locally sourced versus imported apples. The variability in energy requirements in different life cycle stages, but particularly for the fruit production stage, is also significant in this comparative analysis. Overall, it seems that there are similarities in the total PEU ranges for European and New Zealand apples during the Southern Hemisphere's apple season (European spring and summer). However, during the European autumn and winter (Northern Hemisphere apple season) PEU values are generally higher for apples imported from the

The Catalina Surveys Southern periodic variable star catalogue

NASA Astrophysics Data System (ADS)

Drake, A. J.; Djorgovski, S. G.; Catelan, M.; Graham, M. J.; Mahabal, A. A.; Larson, S.; Christensen, E.; Torrealba, G.; Beshore, E.; McNaught, R. H.; Garradd, G.; Belokurov, V.; Koposov, S. E.

2017-08-01

Here, we present the results from our analysis of 6 yr of optical photometry taken by the Siding Spring Survey (SSS). This completes a search for periodic variable stars within the 30 000 deg2 of the sky covered by the Catalina Surveys. The current analysis covers 81 million sources with declinations between -20° and -75° with median magnitudes in the range 11 < V < 19.5. We find approximately 34 000 new periodic variable stars in addition to the ˜9000 RR Lyrae that we previously discovered in SSS data. This brings the total number of periodic variables identified in Catalina data to ˜110 000. The new SSS periodic variable stars mainly consist of eclipsing binaries, RR Lyrae, LPVs, RS CVn stars, δ Scutis, and Anomalous Cepheids. By cross-matching these variable stars with those from prior surveys, we find that ˜90 per cent of the sources are new discoveries and recover ˜95 per cent of the known periodic variables in the survey region. For the known sources, we find excellent agreement between our catalogue and prior values of luminosity, period, and amplitude. However, we find many variable stars that had previously been misclassified. Examining the distribution of RR Lyrae, we find a population associated with the Large Magellanic Cloud (LMC) that extends more than 20° from its centre confirming recent evidence for the existence of a very extended stellar halo in the LMC. By combining SSS photometry with Dark Energy Survey data, we identify additional LMC halo RR Lyrae, thus confirming the significance of the population.

Variability extraction and modeling for product variants.

PubMed

Linsbauer, Lukas; Lopez-Herrejon, Roberto Erick; Egyed, Alexander

2017-01-01

Fast-changing hardware and software technologies in addition to larger and more specialized customer bases demand software tailored to meet very diverse requirements. Software development approaches that aim at capturing this diversity on a single consolidated platform often require large upfront investments, e.g., time or budget. Alternatively, companies resort to developing one variant of a software product at a time by reusing as much as possible from already-existing product variants. However, identifying and extracting the parts to reuse is an error-prone and inefficient task compounded by the typically large number of product variants. Hence, more disciplined and systematic approaches are needed to cope with the complexity of developing and maintaining sets of product variants. Such approaches require detailed information about the product variants, the features they provide and their relations. In this paper, we present an approach to extract such variability information from product variants. It identifies traces from features and feature interactions to their implementation artifacts, and computes their dependencies. This work can be useful in many scenarios ranging from ad hoc development approaches such as clone-and-own to systematic reuse approaches such as software product lines. We applied our variability extraction approach to six case studies and provide a detailed evaluation. The results show that the extracted variability information is consistent with the variability in our six case study systems given by their variability models and available product variants.

Identification of speech transients using variable frame rate analysis and wavelet packets.

PubMed

Rasetshwane, Daniel M; Boston, J Robert; Li, Ching-Chung

2006-01-01

Speech transients are important cues for identifying and discriminating speech sounds. Yoo et al. and Tantibundhit et al. were successful in identifying speech transients and, emphasizing them, improving the intelligibility of speech in noise. However, their methods are computationally intensive and unsuitable for real-time applications. This paper presents a method to identify and emphasize speech transients that combines subband decomposition by the wavelet packet transform with variable frame rate (VFR) analysis and unvoiced consonant detection. The VFR analysis is applied to each wavelet packet to define a transitivity function that describes the extent to which the wavelet coefficients of that packet are changing. Unvoiced consonant detection is used to identify unvoiced consonant intervals and the transitivity function is amplified during these intervals. The wavelet coefficients are multiplied by the transitivity function for that packet, amplifying the coefficients localized at times when they are changing and attenuating coefficients at times when they are steady. Inverse transform of the modified wavelet packet coefficients produces a signal corresponding to speech transients similar to the transients identified by Yoo et al. and Tantibundhit et al. A preliminary implementation of the algorithm runs more efficiently.

The use of administrative health care databases to identify patients with rheumatoid arthritis

PubMed Central

Hanly, John G; Thompson, Kara; Skedgel, Chris

2015-01-01

Objective To validate and compare the decision rules to identify rheumatoid arthritis (RA) in administrative databases. Methods A study was performed using administrative health care data from a population of 1 million people who had access to universal health care. Information was available on hospital discharge abstracts and physician billings. RA cases in health administrative databases were matched 1:4 by age and sex to randomly selected controls without inflammatory arthritis. Seven case definitions were applied to identify RA cases in the health administrative data, and their performance was compared with the diagnosis by a rheumatologist. The validation study was conducted on a sample of individuals with administrative data who received a rheumatologist consultation at the Arthritis Center of Nova Scotia. Results We identified 535 RA cases and 2,140 non-RA, noninflammatory arthritis controls. Using the rheumatologist’s diagnosis as the gold standard, the overall accuracy of the case definitions for RA cases varied between 68.9% and 82.9% with a kappa statistic between 0.26 and 0.53. The sensitivity and specificity varied from 20.7% to 94.8% and 62.5% to 98.5%, respectively. In a reference population of 1 million, the estimated annual number of incident cases of RA was between 176 and 1,610 and the annual number of prevalent cases was between 1,384 and 5,722. Conclusion The accuracy of case definitions for the identification of RA cases from rheumatology clinics using administrative health care databases is variable when compared to a rheumatologist’s assessment. This should be considered when comparing results across studies. This variability may also be used as an advantage in different study designs, depending on the relative importance of sensitivity and specificity for identifying the population of interest to the research question. PMID:27790047

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