Investigating the Nexus of Climate, Energy, Water, and Land at Decision-Relevant Scales: The Platform for Regional Integrated Modeling and Analysis (PRIMA)

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

Kraucunas, Ian P.; Clarke, Leon E.; Dirks, James A.

2015-04-01

The Platform for Regional Integrated Modeling and Analysis (PRIMA) is an innovative modeling system developed at Pacific Northwest National Laboratory (PNNL) to simulate interactions among natural and human systems at scales relevant to regional decision making. PRIMA brings together state-of-the-art models of regional climate, hydrology, agriculture, socioeconomics, and energy systems using a flexible coupling approach. The platform can be customized to inform a variety of complex questions and decisions, such as the integrated evaluation of mitigation and adaptation options across a range of sectors. Research into stakeholder decision support needs underpins the platform's application to regional issues, including uncertainty characterization.more » Ongoing numerical experiments are yielding new insights into the interactions among human and natural systems on regional scales with an initial focus on the energy-land-water nexus in the upper U.S. Midwest. This paper focuses on PRIMA’s functional capabilities and describes some lessons learned to date about integrated regional modeling.« less

Spatial Analysis of China Province-level Perinatal Mortality

PubMed Central

XIANG, Kun; SONG, Deyong

2016-01-01

Background: Using spatial analysis tools to determine the spatial patterns of China province-level perinatal mortality and using spatial econometric model to examine the impacts of health care resources and different socio-economic factors on perinatal mortality. Methods: The Global Moran’s I index is used to examine whether the spatial autocorrelation exists in selected regions and Moran’s I scatter plot to examine the spatial clustering among regions. Spatial econometric models are used to investigate the spatial relationships between perinatal mortality and contributing factors. Results: The overall Moran’s I index indicates that perinatal mortality displays positive spatial autocorrelation. Moran’s I scatter plot analysis implies that there is a significant clustering of mortality in both high-rate regions and low-rate regions. The spatial econometric models analyses confirm the existence of a direct link between perinatal mortality and health care resources, socio-economic factors. Conclusions: Since a positive spatial autocorrelation has been detected in China province-level perinatal mortality, the upgrading of regional economic development and medical service level will affect the mortality not only in region itself but also its adjacent regions. PMID:27398334

Regional primitive equation modeling and analysis of the polymode data set

NASA Astrophysics Data System (ADS)

Spall, Michael A.

A regional, hybrid coordinate, primitive equation (PE) model is applied to a 60-day period of the POLYMODE data set. The initialization techniques and open boundary conditions introduced by Spall and Robinson are shown to produce stable, realistic, and reasonably accurate hindcasts for the 2-month data set. Comparisons with quasi-geostrophic (QG) modeling studies indicate that the PE model reproduced the jet formation that dominates the region more accurately than did the QG model. When the PE model used boundary conditions that were partially adjusted by the QG model, the resulting fields were very similar to the QG fields, indicating a rapid degradation of small-scale features near the boundaries in the QG calculation. A local term-by-term primitive equation energy and vorticity analysis package is also introduced. The full vorticity, horizontal divergence, kinetic energy, and available gravitational energy equations are solved diagnostically from the output of the regional PE model. Through the analysis of a time series of horizontal maps, the dominant processes in the flow are illustrated. The individual terms are also integrated over the region of jet formation to highlight the net balances as a function of time. The formation of the deep thermocline jet is shown to be due to horizontal advection through the boundary, baroclinic conversion in the deep thermocline and vertical pressure work, which exports the deep energy to the upper thermocline levels. It is concluded here that the PE model reproduces the observed jet formation better than the QG model because of the increased horizontal advection and stronger vertical pressure work. Although the PE model is shown to be superior to the QG model in this application, it is believed that both PE and QG models can play an important role in the regional study of mid-ocean mesoscale eddies.

The role of country-to-region assignments in global integrated modeling of energy, agriculture, land use, and climate

NASA Astrophysics Data System (ADS)

Kyle, P.; Patel, P.; Calvin, K. V.

2014-12-01

Global integrated assessment models used for understanding the linkages between the future energy, agriculture, and climate systems typically represent between 8 and 30 geopolitical macro-regions, balancing the benefits of geographic resolution with the costs of additional data collection, processing, analysis, and computing resources. As these models are continually being improved and updated in order to address new questions for the research and policy communities, it is worth examining the consequences of the country-to-region mapping schemes used for model results. This study presents an application of a data processing system built for the GCAM integrated assessment model that allows any country-to-region assignments, with a minimum of four geopolitical regions and a maximum of 185. We test ten different mapping schemes, including the specific mappings used in existing major integrated assessment models. We also explore the impacts of clustering nations into regions according to the similarity of the structure of each nation's energy and agricultural sectors, as indicated by multivariate analysis. Scenarios examined include a reference scenario, a low-emissions scenario, and scenarios with agricultural and buildings sector climate change impacts. We find that at the global level, the major output variables (primary energy, agricultural land use) are surprisingly similar regardless of regional assignments, but at finer geographic scales, differences are pronounced. We suggest that enhancing geographic resolution is advantageous for analysis of climate impacts on the buildings and agricultural sectors, due to the spatial heterogeneity of these drivers.

Studying the Representation Accuracy of the Earth's Gravity Field in the Polar Regions Based on the Global Geopotential Models

NASA Astrophysics Data System (ADS)

Koneshov, V. N.; Nepoklonov, V. B.

2018-05-01

The development of studies on estimating the accuracy of the Earth's modern global gravity models in terms of the spherical harmonics of the geopotential in the problematic regions of the world is discussed. The comparative analysis of the results of reconstructing quasi-geoid heights and gravity anomalies from the different models is carried out for two polar regions selected within a radius of 1000 km from the North and South poles. The analysis covers nine recently developed models, including six high-resolution models and three lower order models, including the Russian GAOP2012 model. It is shown that the modern models determine the quasi-geoid heights and gravity anomalies in the polar regions with errors of 5 to 10 to a few dozen cm and from 3 to 5 to a few dozen mGal, respectively, depending on the resolution. The accuracy of the models in the Arctic is several times higher than in the Antarctic. This is associated with the peculiarities of gravity anomalies in every particular region and with the fact that the polar part of the Antarctic has been comparatively less explored by the gravity methods than the polar Arctic.

Regional climate projections for the MENA-CORDEX domain: analysis of projected temperature and precipitation changes

NASA Astrophysics Data System (ADS)

Hänsler, Andreas; Weber, Torsten; Eggert, Bastian; Saeed, Fahad; Jacob, Daniela

2014-05-01

Within the CORDEX initiative a multi-model suite of regionalized climate change information will be made available for several regions of the world. The German Climate Service Center (CSC) is taking part in this initiative by applying the regional climate model REMO to downscale global climate projections of different coupled general circulation models (GCMs) for several CORDEX domains. Also for the MENA-CORDEX domain, a set of regional climate change projections has been established at the CSC by downscaling CMIP5 projections of the Max-Planck-Institute Earth System Model (MPI-ESM) for the scenarios RCP4.5 and RCP8.5 with the regional model REMO for the time period from 1950 to 2100 to a horizontal resolution of 0.44 degree. In this study we investigate projected changes in future climate conditions over the domain towards the end of the 21st century. Focus in the analysis is given to projected changes in the temperature and rainfall characteristics and their differences for the two scenarios will be highlighted.

Measurement error in time-series analysis: a simulation study comparing modelled and monitored data.

PubMed

Butland, Barbara K; Armstrong, Ben; Atkinson, Richard W; Wilkinson, Paul; Heal, Mathew R; Doherty, Ruth M; Vieno, Massimo

2013-11-13

Assessing health effects from background exposure to air pollution is often hampered by the sparseness of pollution monitoring networks. However, regional atmospheric chemistry-transport models (CTMs) can provide pollution data with national coverage at fine geographical and temporal resolution. We used statistical simulation to compare the impact on epidemiological time-series analysis of additive measurement error in sparse monitor data as opposed to geographically and temporally complete model data. Statistical simulations were based on a theoretical area of 4 regions each consisting of twenty-five 5 km × 5 km grid-squares. In the context of a 3-year Poisson regression time-series analysis of the association between mortality and a single pollutant, we compared the error impact of using daily grid-specific model data as opposed to daily regional average monitor data. We investigated how this comparison was affected if we changed the number of grids per region containing a monitor. To inform simulations, estimates (e.g. of pollutant means) were obtained from observed monitor data for 2003-2006 for national network sites across the UK and corresponding model data that were generated by the EMEP-WRF CTM. Average within-site correlations between observed monitor and model data were 0.73 and 0.76 for rural and urban daily maximum 8-hour ozone respectively, and 0.67 and 0.61 for rural and urban loge(daily 1-hour maximum NO2). When regional averages were based on 5 or 10 monitors per region, health effect estimates exhibited little bias. However, with only 1 monitor per region, the regression coefficient in our time-series analysis was attenuated by an estimated 6% for urban background ozone, 13% for rural ozone, 29% for urban background loge(NO2) and 38% for rural loge(NO2). For grid-specific model data the corresponding figures were 19%, 22%, 54% and 44% respectively, i.e. similar for rural loge(NO2) but more marked for urban loge(NO2). Even if correlations between model and monitor data appear reasonably strong, additive classical measurement error in model data may lead to appreciable bias in health effect estimates. As process-based air pollution models become more widely used in epidemiological time-series analysis, assessments of error impact that include statistical simulation may be useful.

Bayesian sensitivity analysis of bifurcating nonlinear models

NASA Astrophysics Data System (ADS)

Becker, W.; Worden, K.; Rowson, J.

2013-01-01

Sensitivity analysis allows one to investigate how changes in input parameters to a system affect the output. When computational expense is a concern, metamodels such as Gaussian processes can offer considerable computational savings over Monte Carlo methods, albeit at the expense of introducing a data modelling problem. In particular, Gaussian processes assume a smooth, non-bifurcating response surface. This work highlights a recent extension to Gaussian processes which uses a decision tree to partition the input space into homogeneous regions, and then fits separate Gaussian processes to each region. In this way, bifurcations can be modelled at region boundaries and different regions can have different covariance properties. To test this method, both the treed and standard methods were applied to the bifurcating response of a Duffing oscillator and a bifurcating FE model of a heart valve. It was found that the treed Gaussian process provides a practical way of performing uncertainty and sensitivity analysis on large, potentially-bifurcating models, which cannot be dealt with by using a single GP, although an open problem remains how to manage bifurcation boundaries that are not parallel to coordinate axes.

Regional-specific Stochastic Simulation of Spatially-distributed Ground-motion Time Histories using Wavelet Packet Analysis

NASA Astrophysics Data System (ADS)

Huang, D.; Wang, G.

2014-12-01

Stochastic simulation of spatially distributed ground-motion time histories is important for performance-based earthquake design of geographically distributed systems. In this study, we develop a novel technique to stochastically simulate regionalized ground-motion time histories using wavelet packet analysis. First, a transient acceleration time history is characterized by wavelet-packet parameters proposed by Yamamoto and Baker (2013). The wavelet-packet parameters fully characterize ground-motion time histories in terms of energy content, time- frequency-domain characteristics and time-frequency nonstationarity. This study further investigates the spatial cross-correlations of wavelet-packet parameters based on geostatistical analysis of 1500 regionalized ground motion data from eight well-recorded earthquakes in California, Mexico, Japan and Taiwan. The linear model of coregionalization (LMC) is used to develop a permissible spatial cross-correlation model for each parameter group. The geostatistical analysis of ground-motion data from different regions reveals significant dependence of the LMC structure on regional site conditions, which can be characterized by the correlation range of Vs30 in each region. In general, the spatial correlation and cross-correlation of wavelet-packet parameters are stronger if the site condition is more homogeneous. Using the regional-specific spatial cross-correlation model and cokriging technique, wavelet packet parameters at unmeasured locations can be best estimated, and regionalized ground-motion time histories can be synthesized. Case studies and blind tests demonstrated that the simulated ground motions generally agree well with the actual recorded data, if the influence of regional-site conditions is considered. The developed method has great potential to be used in computational-based seismic analysis and loss estimation in a regional scale.

The regionalization of national-scale SPARROW models for stream nutrients

USGS Publications Warehouse

Schwarz, Gregory E.; Alexander, Richard B.; Smith, Richard A.; Preston, Stephen D.

2011-01-01

This analysis modifies the parsimonious specification of recently published total nitrogen (TN) and total phosphorus (TP) national-scale SPAtially Referenced Regressions On Watershed attributes models to allow each model coefficient to vary geographically among three major river basins of the conterminous United States. Regionalization of the national models reduces the standard errors in the prediction of TN and TP loads, expressed as a percentage of the predicted load, by about 6 and 7%. We develop and apply a method for combining national-scale and regional-scale information to estimate a hybrid model that imposes cross-region constraints that limit regional variation in model coefficients, effectively reducing the number of free model parameters as compared to a collection of independent regional models. The hybrid TN and TP regional models have improved model fit relative to the respective national models, reducing the standard error in the prediction of loads, expressed as a percentage of load, by about 5 and 4%. Only 19% of the TN hybrid model coefficients and just 2% of the TP hybrid model coefficients show evidence of substantial regional specificity (more than ±100% deviation from the national model estimate). The hybrid models have much greater precision in the estimated coefficients than do the unconstrained regional models, demonstrating the efficacy of pooling information across regions to improve regional models.

Regional Scale Meteorological Analysis and Prediction Using GPS Occultation and EOS Data

NASA Technical Reports Server (NTRS)

Bromwich, David H.; Shum, C. K.; Zhao, Changyin; Kuo, Bill; Rocken, Chris

2004-01-01

The main objective of the research under this award is to improve regional meteorological analysis and prediction for traditionally data limited regions, particularly over the Southern Ocean and Antarctica, using the remote sensing observations from current and upcoming GPS radio occultation missions and the EOS instrument suite. The major components of this project are: 1.Develop and improve the methods for retrieving temperature, moisture, and pressure profiles from GPS radio occultation data and EOS radiometer data. 2. Develop and improve a regional scale data assimilation system (MM5 4DVAR). 3. Perform case studies involving data analysis and numerical modeling to investigate the impact of different data for regional meteorological analysis and the importance of data assimilation for regional meteorological simulation over the Antarctic region. 4. Apply the findings and improvements from the above studies to weather forecasting experiments. 5. In the third year of the award we made significant progress toward the remaining goals of the project. The work included carefully evaluating the performance of an atmospheric mesoscale model, the Polar MM5 in Antarctic applications and improving the upper boundary condition.

NCEP SST Analysis

Science.gov Websites

Branches Global Climate & Weather Modeling Mesoscale Modeling Marine Modeling and Analysis Contact EMC , state and local government Web resources and services. Real-time, global, sea surface temperature (RTG_SST_HR) analysis For a regional map, click the desired area in the global SST analysis and anomaly maps

STATISTICAL GROWTH MODELING OF LONGITUDINAL DT-MRI FOR REGIONAL CHARACTERIZATION OF EARLY BRAIN DEVELOPMENT.

PubMed

Sadeghi, Neda; Prastawa, Marcel; Fletcher, P Thomas; Gilmore, John H; Lin, Weili; Gerig, Guido

2012-01-01

A population growth model that represents the growth trajectories of individual subjects is critical to study and understand neurodevelopment. This paper presents a framework for jointly estimating and modeling individual and population growth trajectories, and determining significant regional differences in growth pattern characteristics applied to longitudinal neuroimaging data. We use non-linear mixed effect modeling where temporal change is modeled by the Gompertz function. The Gompertz function uses intuitive parameters related to delay, rate of change, and expected asymptotic value; all descriptive measures which can answer clinical questions related to growth. Our proposed framework combines nonlinear modeling of individual trajectories, population analysis, and testing for regional differences. We apply this framework to the study of early maturation in white matter regions as measured with diffusion tensor imaging (DTI). Regional differences between anatomical regions of interest that are known to mature differently are analyzed and quantified. Experiments with image data from a large ongoing clinical study show that our framework provides descriptive, quantitative information on growth trajectories that can be directly interpreted by clinicians. To our knowledge, this is the first longitudinal analysis of growth functions to explain the trajectory of early brain maturation as it is represented in DTI.

Phylogeny of sipunculan worms: A combined analysis of four gene regions and morphology.

PubMed

Schulze, Anja; Cutler, Edward B; Giribet, Gonzalo

2007-01-01

The intra-phyletic relationships of sipunculan worms were analyzed based on DNA sequence data from four gene regions and 58 morphological characters. Initially we analyzed the data under direct optimization using parsimony as optimality criterion. An implied alignment resulting from the direct optimization analysis was subsequently utilized to perform a Bayesian analysis with mixed models for the different data partitions. For this we applied a doublet model for the stem regions of the 18S rRNA. Both analyses support monophyly of Sipuncula and most of the same clades within the phylum. The analyses differ with respect to the relationships among the major groups but whereas the deep nodes in the direct optimization analysis generally show low jackknife support, they are supported by 100% posterior probability in the Bayesian analysis. Direct optimization has been useful for handling sequences of unequal length and generating conservative phylogenetic hypotheses whereas the Bayesian analysis under mixed models provided high resolution in the basal nodes of the tree.

Methods for estimating annual exceedance probability discharges for streams in Arkansas, based on data through water year 2013

USGS Publications Warehouse

Wagner, Daniel M.; Krieger, Joshua D.; Veilleux, Andrea G.

2016-08-04

In 2013, the U.S. Geological Survey initiated a study to update regional skew, annual exceedance probability discharges, and regional regression equations used to estimate annual exceedance probability discharges for ungaged locations on streams in the study area with the use of recent geospatial data, new analytical methods, and available annual peak-discharge data through the 2013 water year. An analysis of regional skew using Bayesian weighted least-squares/Bayesian generalized-least squares regression was performed for Arkansas, Louisiana, and parts of Missouri and Oklahoma. The newly developed constant regional skew of -0.17 was used in the computation of annual exceedance probability discharges for 281 streamgages used in the regional regression analysis. Based on analysis of covariance, four flood regions were identified for use in the generation of regional regression models. Thirty-nine basin characteristics were considered as potential explanatory variables, and ordinary least-squares regression techniques were used to determine the optimum combinations of basin characteristics for each of the four regions. Basin characteristics in candidate models were evaluated based on multicollinearity with other basin characteristics (variance inflation factor < 2.5) and statistical significance at the 95-percent confidence level (p ≤ 0.05). Generalized least-squares regression was used to develop the final regression models for each flood region. Average standard errors of prediction of the generalized least-squares models ranged from 32.76 to 59.53 percent, with the largest range in flood region D. Pseudo coefficients of determination of the generalized least-squares models ranged from 90.29 to 97.28 percent, with the largest range also in flood region D. The regional regression equations apply only to locations on streams in Arkansas where annual peak discharges are not substantially affected by regulation, diversion, channelization, backwater, or urbanization. The applicability and accuracy of the regional regression equations depend on the basin characteristics measured for an ungaged location on a stream being within range of those used to develop the equations.

Characterizing the anthropogenic signature in the LCLU dynamics in the Central Asia region

NASA Astrophysics Data System (ADS)

Tatarskii, V.; Sokolik, I. N.; de Beurs, K.; Shiklomanov, A. I.

2017-12-01

Humans have been changing the LCLU dynamics over time through the world. In the Central Asia region, these changes have been especially pronounced due to the political and economic transformation. We present a detailed analysis, focusing on identifying and quantifying the anthropogenic signature in the water and land use across the region. We have characterized the anthropogenic dust emission by combining the modeling and observations. The model is a fully coupled model called WRF-Chem-DuMo that takes explicitly into account the vegetation treatment in modeling the dust emission. We have reconstructed the anthropogenic dust sources in the region, such as the retreat of the Aral Sea, changes in agricultural fields, etc. In addition, we characterize the anthropogenic water use dynamics, including the changes in the water use for the agricultural production. Furthermore, we perform an analysis to identify the anthropogenic signature in the NDVI pattern. The NDVI were analyzed in conjunction with the meteorological fields that were simulated at the high special resolution using the WRF model. Meteorological fields of precipitation and temperature were used for the correlation analysis to separate the natural vs. anthropogenic changes. In this manner, we were able to identify the regions that have been affected by human activities. We will present the quantitative assessment of the anthropogenic changes. The diverse consequences for the economy of the region, as well as, the environment will be addressed.

Application of class-modelling techniques to infrared spectra for analysis of pork adulteration in beef jerkys.

PubMed

Kuswandi, Bambang; Putri, Fitra Karima; Gani, Agus Abdul; Ahmad, Musa

2015-12-01

The use of chemometrics to analyse infrared spectra to predict pork adulteration in the beef jerky (dendeng) was explored. In the first step, the analysis of pork in the beef jerky formulation was conducted by blending the beef jerky with pork at 5-80 % levels. Then, they were powdered and classified into training set and test set. The second step, the spectra of the two sets was recorded by Fourier Transform Infrared (FTIR) spectroscopy using atenuated total reflection (ATR) cell on the basis of spectral data at frequency region 4000-700 cm(-1). The spectra was categorised into four data sets, i.e. (a) spectra in the whole region as data set 1; (b) spectra in the fingerprint region (1500-600 cm(-1)) as data set 2; (c) spectra in the whole region with treatment as data set 3; and (d) spectra in the fingerprint region with treatment as data set 4. The third step, the chemometric analysis were employed using three class-modelling techniques (i.e. LDA, SIMCA, and SVM) toward the data sets. Finally, the best result of the models towards the data sets on the adulteration analysis of the samples were selected and the best model was compared with the ELISA method. From the chemometric results, the LDA model on the data set 1 was found to be the best model, since it could classify and predict 100 % accuracy of the sample tested. The LDA model was applied toward the real samples of the beef jerky marketed in Jember, and the results showed that the LDA model developed was in good agreement with the ELISA method.

Regional variations in mortality rates in England and Wales: an analysis using multi-level modelling.

PubMed

Langford, I H; Bentham, G

1996-03-01

Mortality rates in England and Wales display a persistent regional pattern indicating generally poorer health in the North and West. Some of this is simply a reflection of regional differences in the extent of social deprivation which is known to exert a profound influence on health. Part of the pattern may also be the result of regional differences in urbanization which also affect mortality rates. However, there may be important regional differences over and above these compositional effects. This study attempts to establish the magnitude of such independent regional differences in mortality rates by using the techniques of multi-level modelling. Standardized mortality rates (SMRs) for males and females under 65 for 1989-91 in local authority districts are grouped into categories using the ACORN classification scheme. The Townsend Index is included as a measure of social deprivation. Using a cross-classified multi-level model, it is shown that region accounts for approximately four times more variation in SMRs than is explained by the ACORN classification. Analysis of diagnostic residuals show a clear North-South divide in excess mortality when both regional and socio-economic classification of districts are modelled simultaneously, a possibility allowed for by the use of a multi-level model.

Selecting global climate models for regional climate change studies

PubMed Central

Pierce, David W.; Barnett, Tim P.; Santer, Benjamin D.; Gleckler, Peter J.

2009-01-01

Regional or local climate change modeling studies currently require starting with a global climate model, then downscaling to the region of interest. How should global models be chosen for such studies, and what effect do such choices have? This question is addressed in the context of a regional climate detection and attribution (D&A) study of January-February-March (JFM) temperature over the western U.S. Models are often selected for a regional D&A analysis based on the quality of the simulated regional climate. Accordingly, 42 performance metrics based on seasonal temperature and precipitation, the El Nino/Southern Oscillation (ENSO), and the Pacific Decadal Oscillation are constructed and applied to 21 global models. However, no strong relationship is found between the score of the models on the metrics and results of the D&A analysis. Instead, the importance of having ensembles of runs with enough realizations to reduce the effects of natural internal climate variability is emphasized. Also, the superiority of the multimodel ensemble average (MM) to any 1 individual model, already found in global studies examining the mean climate, is true in this regional study that includes measures of variability as well. Evidence is shown that this superiority is largely caused by the cancellation of offsetting errors in the individual global models. Results with both the MM and models picked randomly confirm the original D&A results of anthropogenically forced JFM temperature changes in the western U.S. Future projections of temperature do not depend on model performance until the 2080s, after which the better performing models show warmer temperatures. PMID:19439652

The analysis of factors of management of safety of critical information infrastructure with use of dynamic models

NASA Astrophysics Data System (ADS)

Trostyansky, S. N.; Kalach, A. V.; Lavlinsky, V. V.; Lankin, O. V.

2018-03-01

Based on the analysis of the dynamic model of panel data by region, including fire statistics for surveillance sites and statistics of a set of regional socio-economic indicators, as well as the time of rapid response of the state fire service to fires, the probability of fires in the surveillance sites and the risk of human death in The result of such fires from the values of the corresponding indicators for the previous year, a set of regional social-economics factors, as well as regional indicators time rapid response of the state fire service in the fire. The results obtained are consistent with the results of the application to the fire risks of the model of a rational offender. Estimation of the economic equivalent of human life from data on surveillance objects for Russia, calculated on the basis of the analysis of the presented dynamic model of fire risks, correctly agrees with the known literary data. The results obtained on the basis of the econometric approach to fire risks allow us to forecast fire risks at the supervisory sites in the regions of Russia and to develop management solutions to minimize such risks.

A kinematic model to assess spinal motion during walking.

PubMed

Konz, Regina J; Fatone, Stefania; Stine, Rebecca L; Ganju, Aruna; Gard, Steven A; Ondra, Stephen L

2006-11-15

A 3-dimensional multi-segment kinematic spine model was developed for noninvasive analysis of spinal motion during walking. Preliminary data from able-bodied ambulators were collected and analyzed using the model. Neither the spine's role during walking nor the effect of surgical spinal stabilization on gait is fully understood. Typically, gait analysis models disregard the spine entirely or regard it as a single rigid structure. Data on regional spinal movements, in conjunction with lower limb data, associated with walking are scarce. KinTrak software (Motion Analysis Corp., Santa Rosa, CA) was used to create a biomechanical model for analysis of 3-dimensional regional spinal movements. Measuring known angles from a mechanical model and comparing them to the calculated angles validated the kinematic model. Spine motion data were collected from 10 able-bodied adults walking at 5 self-selected speeds. These results were compared to data reported in the literature. The uniaxial angles measured on the mechanical model were within 5 degrees of the calculated kinematic model angles, and the coupled angles were within 2 degrees. Regional spine kinematics from able-bodied subjects calculated with this model compared well to data reported by other authors. A multi-segment kinematic spine model has been developed and validated for analysis of spinal motion during walking. By understanding the spine's role during ambulation and the cause-and-effect relationship between spine motion and lower limb motion, preoperative planning may be augmented to restore normal alignment and balance with minimal negative effects on walking.

Energy Systems Analysis Tools | Energy Analysis | NREL

Science.gov Websites

energy resources. REFlex NREL uses this dispatch model to evaluate renewable generation as a function of information. Regional Energy Deployment System (ReEDS) NREL uses this multi-regional, multi-time period, GIS

Transportation Impact Evaluation System

DOT National Transportation Integrated Search

1979-11-01

This report specifies a framework for spatial analysis and the general modelling steps required. It also suggests available urban and regional data sources, along with some typical existing urban and regional models. The goal is to develop a computer...

Development of Regional Supply Functions and a Least-Cost Model for Allocating Water Resources in Utah: A Parametric Linear Programming Approach.

DTIC Science & Technology

SYSTEMS ANALYSIS, * WATER SUPPLIES, MATHEMATICAL MODELS, OPTIMIZATION, ECONOMICS, LINEAR PROGRAMMING, HYDROLOGY, REGIONS, ALLOCATIONS, RESTRAINT, RIVERS, EVAPORATION, LAKES, UTAH, SALVAGE, MINES(EXCAVATIONS).

Analysis of high-resolution simulations for the Black Forest region from a point of view of tourism climatology - a comparison between two regional climate models (REMO and CLM)

NASA Astrophysics Data System (ADS)

Endler, Christina; Matzarakis, Andreas

2011-03-01

An analysis of climate simulations from a point of view of tourism climatology based on two regional climate models, namely REMO and CLM, was performed for a regional domain in the southwest of Germany, the Black Forest region, for two time frames, 1971-2000 that represents the twentieth century climate and 2021-2050 that represents the future climate. In that context, the Intergovernmental Panel on Climate Change (IPCC) scenarios A1B and B1 are used. The analysis focuses on human-biometeorological and applied climatologic issues, especially for tourism purposes - that means parameters belonging to thermal (physiologically equivalent temperature, PET), physical (precipitation, snow, wind), and aesthetic (fog, cloud cover) facets of climate in tourism. In general, both models reveal similar trends, but differ in their extent. The trend of thermal comfort is contradicting: it tends to decrease in REMO, while it shows a slight increase in CLM. Moreover, REMO reveals a wider range of future climate trends than CLM, especially for sunshine, dry days, and heat stress. Both models are driven by the same global coupled atmosphere-ocean model ECHAM5/MPI-OM. Because both models are not able to resolve meso- and micro-scale processes such as cloud microphysics, differences between model results and discrepancies in the development of even those parameters (e.g., cloud formation and cover) are due to different model parameterization and formulation. Climatic changes expected by 2050 are small compared to 2100, but may have major impacts on tourism as for example, snow cover and its duration are highly vulnerable to a warmer climate directly affecting tourism in winter. Beyond indirect impacts are of high relevance as they influence tourism as well. Thus, changes in climate, natural environment, demography, tourists' demands, among other things affect economy in general. The analysis of the CLM results and its comparison with the REMO results complete the analysis performed within the project Climate Trends and Sustainable Development of Tourism in Coastal and Low Mountain Range Regions (CAST) funded by the German Federal Ministry of Education and Research (BMBF).

Population-Based Analysis and Projections of Liver Supply Under Redistricting.

PubMed

Parikh, Neehar D; Marrero, Wesley J; Sonnenday, Christopher J; Lok, Anna S; Hutton, David W; Lavieri, Mariel S

2017-09-01

To reduce the geographic heterogeneity in liver transplant allocation, the United Network of Organ Sharing has proposed redistricting, which is impacted by both donor supply and liver transplantation demand. We aimed to determine the impact of demographic changes on the redistricting proposal and characterize causes behind geographic heterogeneity in donor supply. We analyzed adult donors from 2002 to 2014 from the United Network of Organ Sharing database and calculated regional liver donation and utilization stratified by age, race, and body mass index. We used US population data to make regional projections of available donors from 2016 to 2025, incorporating the proposed 8-region redistricting plan. We used donors/100 000 population age 18 to 84 years (D/100K) as a measure of equity. We calculated a coefficient of variation (standard deviation/mean) for each regional model. We performed an exploratory analysis where we used national rates of donation, utilization and both for each regional model. The overall projected D/100K will decrease from 2.53 to 2.49 from 2016 to 2025. The coefficient of variation in 2016 is expected to be 20.3% in the 11-region model and 13.2% in the 8-region model. We found that standardizing regional donation and utilization rates would reduce geographic heterogeneity to 4.9% in the 8-region model and 4.6% in the 11-region model. The 8-region allocation model will reduce geographic variation in donor supply to a significant extent; however, we project that geographic disparity will marginally increase over time. Though challenging, interventions to better standardize donation and utilization rates would be impactful in reducing geographic heterogeneity in organ supply.

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

NASA Astrophysics Data System (ADS)

Ganora, D.; Laio, F.

2016-07-01

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

Fully-coupled analysis of jet mixing problems. Part 1. Shock-capturing model, SCIPVIS

NASA Technical Reports Server (NTRS)

Dash, S. M.; Wolf, D. E.

1984-01-01

A computational model, SCIPVIS, is described which predicts the multiple cell shock structure in imperfectly expanded, turbulent, axisymmetric jets. The model spatially integrates the parabolized Navier-Stokes jet mixing equations using a shock-capturing approach in supersonic flow regions and a pressure-split approximation in subsonic flow regions. The regions are coupled using a viscous-characteristic procedure. Turbulence processes are represented via the solution of compressibility-corrected two-equation turbulence models. The formation of Mach discs in the jet and the interactive analysis of the wake-like mixing process occurring behind Mach discs is handled in a rigorous manner. Calculations are presented exhibiting the fundamental interactive processes occurring in supersonic jets and the model is assessed via comparisons with detailed laboratory data for a variety of under- and overexpanded jets.

Climate change impacts utilizing regional models for agriculture, hydrology and natural ecosystems

NASA Astrophysics Data System (ADS)

Kafatos, M.; Asrar, G. R.; El-Askary, H. M.; Hatzopoulos, N.; Kim, J.; Kim, S.; Medvigy, D.; Prasad, A. K.; Smith, E.; Stack, D. H.; Tremback, C.; Walko, R. L.

2012-12-01

Climate change impacts the entire Earth but with crucial and often catastrophic impacts at local and regional levels. Extreme phenomena such as fires, dust storms, droughts and other natural hazards present immediate risks and challenges. Such phenomena will become more extreme as climate change and anthropogenic activities accelerate in the future. We describe a major project funded by NIFA (Grant # 2011-67004-30224), under the joint NSF-DOE-USDA Earth System Models (EaSM) program, to investigate the impacts of climate variability and change on the agricultural and natural (i.e. rangeland) ecosystems in the Southwest USA using a combination of historical and present observations together with climate, and ecosystem models, both in hind-cast and forecast modes. The applicability of the methodology to other regions is relevant (for similar geographic regions as well as other parts of the world with different agriculture and ecosystems) and should advance the state of knowledge for regional impacts of climate change. A combination of multi-model global climate projections from the decadal predictability simulations, to downscale dynamically these projections using three regional climate models, combined with remote sensing MODIS and other data, in order to obtain high-resolution climate data that can be used with hydrological and ecosystem models for impacts analysis, is described in this presentation. Such analysis is needed to assess the future risks and potential impacts of projected changes on these natural and managed ecosystems. The results from our analysis can be used by scientists to assist extended communities to determine agricultural coping strategies, and is, therefore, of interest to wide communities of stakeholders. In future work we will be including surface hydrologic modeling and water resources, extend modeling to higher resolutions and include significantly more crops and geographical regions with different weather and climate conditions. Specifics of the importance of the scientific methodology e.g. RCM ensemble modeling (using OLAM, RAMS and WRF); combining RCM runs with agriculture modeling system (specifically APSIM); bringing different RCM setups to as close as possible common framework, etc., and important science results (e.g. the significance of Gulf of CA SST for precipitation over dry regions; the AR landfall impacts on precipitation; etc.) are described in our work. We emphasize that the methodology is significant in order to advance the state of the art climate change impacts at regional levels; and to implement our methodology for realistic impact analysis on the natural and managed (agriculture) ecosystems, beyond the SW US.

Bankfull discharge and channel characteristics of streams in New York State

USGS Publications Warehouse

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

2009-01-01

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

Spatial econometric analysis of factors influencing regional energy efficiency in China.

PubMed

Song, Malin; Chen, Yu; An, Qingxian

2018-05-01

Increased environmental pollution and energy consumption caused by the country's rapid development has raised considerable public concern, and has become the focus of the government and public. This study employs the super-efficiency slack-based model-data envelopment analysis (SBM-DEA) to measure the total factor energy efficiency of 30 provinces in China. The estimation model for the spatial interaction intensity of regional total factor energy efficiency is based on Wilson's maximum entropy model. The model is used to analyze the factors that affect the potential value of total factor energy efficiency using spatial dynamic panel data for 30 provinces during 2000-2014. The study found that there are differences and spatial correlations of energy efficiency among provinces and regions in China. The energy efficiency in the eastern, central, and western regions fluctuated significantly, and was mainly because of significant energy efficiency impacts on influences of industrial structure, energy intensity, and technological progress. This research is of great significance to China's energy efficiency and regional coordinated development.

Assessment of Managed Aquifer Recharge Site Suitability Using a GIS and Modeling.

PubMed

Russo, Tess A; Fisher, Andrew T; Lockwood, Brian S

2015-01-01

We completed a two-step regional analysis of a coastal groundwater basin to (1) assess regional suitability for managed aquifer recharge (MAR), and (2) quantify the relative impact of MAR activities on groundwater levels and sea water intrusion. The first step comprised an analysis of surface and subsurface hydrologic properties and conditions, using a geographic information system (GIS). Surface and subsurface data coverages were compiled, georeferenced, reclassified, and integrated (including novel approaches for combining related datasets) to derive a spatial distribution of MAR suitability values. In the second step, results from the GIS analysis were used with a regional groundwater model to assess the hydrologic impact of potential MAR placement and operating scenarios. For the region evaluated in this study, the Pajaro Valley Groundwater Basin, California, GIS results suggest that about 7% (15 km2) of the basin may be highly suitable for MAR. Modeling suggests that simulated MAR projects placed near the coast help to reduce sea water intrusion more rapidly, but these projects also result in increased groundwater flows to the ocean. In contrast, projects placed farther inland result in more long-term reduction in sea water intrusion and less groundwater flowing to the ocean. This work shows how combined GIS analysis and modeling can assist with regional water supply planning, including evaluation of options for enhancing groundwater resources. © 2014, National Ground Water Association.

A brain-region-based meta-analysis method utilizing the Apriori algorithm.

PubMed

Niu, Zhendong; Nie, Yaoxin; Zhou, Qian; Zhu, Linlin; Wei, Jieyao

2016-05-18

Brain network connectivity modeling is a crucial method for studying the brain's cognitive functions. Meta-analyses can unearth reliable results from individual studies. Meta-analytic connectivity modeling is a connectivity analysis method based on regions of interest (ROIs) which showed that meta-analyses could be used to discover brain network connectivity. In this paper, we propose a new meta-analysis method that can be used to find network connectivity models based on the Apriori algorithm, which has the potential to derive brain network connectivity models from activation information in the literature, without requiring ROIs. This method first extracts activation information from experimental studies that use cognitive tasks of the same category, and then maps the activation information to corresponding brain areas by using the automatic anatomical label atlas, after which the activation rate of these brain areas is calculated. Finally, using these brain areas, a potential brain network connectivity model is calculated based on the Apriori algorithm. The present study used this method to conduct a mining analysis on the citations in a language review article by Price (Neuroimage 62(2):816-847, 2012). The results showed that the obtained network connectivity model was consistent with that reported by Price. The proposed method is helpful to find brain network connectivity by mining the co-activation relationships among brain regions. Furthermore, results of the co-activation relationship analysis can be used as a priori knowledge for the corresponding dynamic causal modeling analysis, possibly achieving a significant dimension-reducing effect, thus increasing the efficiency of the dynamic causal modeling analysis.

Parameter Uncertainty Analysis Using Monte Carlo Simulations for a Regional-Scale Groundwater Model

NASA Astrophysics Data System (ADS)

Zhang, Y.; Pohlmann, K.

2016-12-01

Regional-scale grid-based groundwater models for flow and transport often contain multiple types of parameters that can intensify the challenge of parameter uncertainty analysis. We propose a Monte Carlo approach to systematically quantify the influence of various types of model parameters on groundwater flux and contaminant travel times. The Monte Carlo simulations were conducted based on the steady-state conversion of the original transient model, which was then combined with the PEST sensitivity analysis tool SENSAN and particle tracking software MODPATH. Results identified hydrogeologic units whose hydraulic conductivity can significantly affect groundwater flux, and thirteen out of 173 model parameters that can cause large variation in travel times for contaminant particles originating from given source zones.

SERA Scenarios of Early Market Fuel Cell Electric Vehicle Introductions: Modeling Framework, Regional Markets, and Station Clustering

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

Bush, B.; Melaina, M.; Penev, M.

This report describes the development and analysis of detailed temporal and spatial scenarios for early market hydrogen fueling infrastructure clustering and fuel cell electric vehicle rollout using the Scenario Evaluation, Regionalization and Analysis (SERA) model. The report provides an overview of the SERA scenario development framework and discusses the approach used to develop the nationwidescenario.

Regional impacts of oil and gas development on ozone formation in the western United States.

PubMed

Rodriguez, Marco A; Barna, Michael G; Moore, Tom

2009-09-01

The Intermountain West is currently experiencing increased growth in oil and gas production, which has the potential to affect the visibility and air quality of various Class I areas in the region. The following work presents an analysis of these impacts using the Comprehensive Air Quality Model with extensions (CAMx). CAMx is a state-of-the-science, "one-atmosphere" Eulerian photochemical dispersion model that has been widely used in the assessment of gaseous and particulate air pollution (ozone, fine [PM2.5], and coarse [PM10] particulate matter). Meteorology and emissions inventories developed by the Western Regional Air Partnership Regional Modeling Center for regional haze analysis and planning are used to establish an ozone baseline simulation for the year 2002. The predicted range of values for ozone in the national parks and other Class I areas in the western United States is then evaluated with available observations from the Clean Air Status and Trends Network (CASTNET). This evaluation demonstrates the model's suitability for subsequent planning, sensitivity, and emissions control strategy modeling. Once the ozone baseline simulation has been established, an analysis of the model results is performed to investigate the regional impacts of oil and gas development on the ozone concentrations that affect the air quality of Class I areas. Results indicate that the maximum 8-hr ozone enhancement from oil and gas (9.6 parts per billion [ppb]) could affect southwestern Colorado and northwestern New Mexico. Class I areas in this region that are likely to be impacted by increased ozone include Mesa Verde National Park and Weminuche Wilderness Area in Colorado and San Pedro Parks Wilderness Area, Bandelier Wilderness Area, Pecos Wilderness Area, and Wheeler Peak Wilderness Area in New Mexico.

Influence of Regional Difference in Bone Mineral Density on Hip Fracture Site in Elderly Females by Finite Element Analysis.

PubMed

Lin, Z L; Li, P F; Pang, Z H; Zheng, X H; Huang, F; Xu, H H; Li, Q L

2015-11-01

Hip fracture is a kind of osteoporotic fractures in elderly patients. Its important monitoring indicator is to measure bone mineral density (BMD) using DXA. The stress characteristics and material distribution in different parts of the bones can be well simulated by three-dimensional finite element analysis. Our previous studies have demonstrated a linear positive correlation between clinical BMD and the density of three-dimensional finite element model of the femur. However, the correlation between the density variation between intertrochanteric region and collum femoris region of the model and the fracture site has not been studied yet. The present study intends to investigate whether the regional difference in the density of three-dimensional finite element model of the femur can be used to predict hip fracture site in elderly females. The CT data of both hip joints were collected from 16 cases of elderly female patients with hip fractures. Mimics 15.01 software was used to reconstruct the model of proximal femur on the healthy side. Ten kinds of material properties were assigned. In Abaqus 6.12 software, the collum femoris region and intertrochanteric region were, respectively, drawn for calculating the corresponding regional density of the model, followed by prediction of hip fracture site and final comparison with factual fracture site. The intertrochanteric region/collum femoris region density was [(1.20 ± 0.02) × 10(6)] on the fracture site and [(1.22 ± 0.03) × 10(6)] on the non-fracture site, and the difference was statistically significant (P = 0.03). Among 16 established models of proximal femur on the healthy side, 14 models were consistent with the actual fracture sites, one model was inconsistent, and one model was unpredictable, with the coincidence rate of 87.5 %. The intertrochanteric region or collum femoris region with lower BMD is more prone to hip fracture of the type on the corresponding site.

HABITAT DISTRIBUTION MODELS FOR 37 VERTEBRATE SPECIES IN T HE MOJAVE DESERT ECOREGION OF NEVADA, ARIZONA, AND UTAH

EPA Science Inventory

Thirty-seven covered species in the Clark County Multi-Species Habitat Conservation Plan (MSHCP) were previously modeled through the Southwest Regional Gap Analysis Project (SWReGAP), using a deductive approach. To increase the applicability of such habitat models in the region ...

Surface Current Skill Assessment of Global and Regional forecast models.

NASA Astrophysics Data System (ADS)

Allen, A. A.

2016-02-01

The U.S. Coast Guard has been using SAROPS since January 2007 at all fifty of its operational centers to plan search and rescue missions. SAROPS relies on an Environmental Data Server (EDS) that integrates global, national, and regional ocean and meteorological observation and forecast data. The server manages spatial and temporal aggregation of hindcast, nowcast, and forecast data so the SAROPS controller has the best available data for search planning. The EDS harvests a wide range of global and regional forecasts and data, including NOAA NCEP's global HYCOM model (RTOFS), the U.S. Navy's Global HYCOM model, the 5 NOAA NOS Great Lakes models and a suite of other reginal forecasts from NOS and IOOS Regional Associations. The EDS also integrates surface drifter data as the U.S. Coast Guard regularly deploys Self-Locating Datum Marker Buoys (SLDMBs) during SAR cases and a significant set of drifter data has been collected and the archive continues to grow. This data is critically useful during real-time SAR planning, but also represents a valuable scientific dataset for analyzing surface currents. In 2014, a new initiative was started by the U.S. Coast Guard to evaluate the skill of the various models to support the decision making process during search and rescue planning. This analysis falls into 2 categories: historical analysis of drifter tracks and model predictions to provide skill assessment of models in different regions and real-time analysis of models and drifter tracks during a SAR incident. The EDS, using Liu and Wiesberg's (2014) autonomously determines surface skill measurements of the co-located models' simulated surface trajectories versus the actual drift of the SLDMBs (CODE/Davis style surface drifters GPS positioned at 30min intervals). Surface skill measurements are archived in a database and are user retrieval by lat/long/time cubes. This paper will focus on the comparison of models from in the period from 23 August to 21 September 2015. Surface Skill was determined for the following regions: California Coast, Gulf of Mexico, South and Mid Atlantic Bights. Skill was determined for the two version of the NCEP Global RTOFS, Navy's Global HYCOM model, and where appropriated the local regional models

The Regionalization of National-Scale SPARROW Models for Stream Nutrients

USGS Publications Warehouse

Schwarz, G.E.; Alexander, R.B.; Smith, R.A.; Preston, S.D.

2011-01-01

This analysis modifies the parsimonious specification of recently published total nitrogen (TN) and total phosphorus (TP) national-scale SPAtially Referenced Regressions On Watershed attributes models to allow each model coefficient to vary geographically among three major river basins of the conterminous United States. Regionalization of the national models reduces the standard errors in the prediction of TN and TP loads, expressed as a percentage of the predicted load, by about 6 and 7%. We develop and apply a method for combining national-scale and regional-scale information to estimate a hybrid model that imposes cross-region constraints that limit regional variation in model coefficients, effectively reducing the number of free model parameters as compared to a collection of independent regional models. The hybrid TN and TP regional models have improved model fit relative to the respective national models, reducing the standard error in the prediction of loads, expressed as a percentage of load, by about 5 and 4%. Only 19% of the TN hybrid model coefficients and just 2% of the TP hybrid model coefficients show evidence of substantial regional specificity (more than ??100% deviation from the national model estimate). The hybrid models have much greater precision in the estimated coefficients than do the unconstrained regional models, demonstrating the efficacy of pooling information across regions to improve regional models. ?? 2011 American Water Resources Association. This article is a U.S. Government work and is in the public domain in the USA.

SERA Scenarios of Early Market Fuel Cell Electric Vehicle Introductions: Modeling Framework, Regional Markets, and Station Clustering; NREL (National Renewable Energy Laboratory)

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

Melaina, M.

This presentation provides an overview of the Scenario Evaluation and Regionalization Analysis (SERA) model, describes the methodology for developing scenarios for hydrogen infrastructure development, outlines an example "Hydrogen Success" scenario, and discusses detailed scenario metrics for a particular case study region, the Northeast Corridor.

Analysis of the Effect of Interior Nudging on Temperature and Precipitation Distributions of Multi-year Regional Climate Simulations

NASA Astrophysics Data System (ADS)

Nolte, C. G.; Otte, T. L.; Bowden, J. H.; Otte, M. J.

2010-12-01

There is disagreement in the regional climate modeling community as to the appropriateness of the use of internal nudging. Some investigators argue that the regional model should be minimally constrained and allowed to respond to regional-scale forcing, while others have noted that in the absence of interior nudging, significant large-scale discrepancies develop between the regional model solution and the driving coarse-scale fields. These discrepancies lead to reduced confidence in the ability of regional climate models to dynamically downscale global climate model simulations under climate change scenarios, and detract from the usability of the regional simulations for impact assessments. The advantages and limitations of interior nudging schemes for regional climate modeling are investigated in this study. Multi-year simulations using the WRF model driven by reanalysis data over the continental United States at 36km resolution are conducted using spectral nudging, grid point nudging, and for a base case without interior nudging. The means, distributions, and inter-annual variability of temperature and precipitation will be evaluated in comparison to regional analyses.

Predicting groundwater redox status on a regional scale using linear discriminant analysis.

PubMed

Close, M E; Abraham, P; Humphries, B; Lilburne, L; Cuthill, T; Wilson, S

2016-08-01

Reducing conditions are necessary for denitrification, thus the groundwater redox status can be used to identify subsurface zones where potentially significant nitrate reduction can occur. Groundwater chemistry in two contrasting regions of New Zealand was classified with respect to redox status and related to mappable factors, such as geology, topography and soil characteristics using discriminant analysis. Redox assignment was carried out for water sampled from 568 and 2223 wells in the Waikato and Canterbury regions, respectively. For the Waikato region 64% of wells sampled indicated oxic conditions in the water; 18% indicated reduced conditions and 18% had attributes indicating both reducing and oxic conditions termed "mixed". In Canterbury 84% of wells indicated oxic conditions; 10% were mixed; and only 5% indicated reduced conditions. The analysis was performed over three different well depths, <25m, 25 to 100 and >100m. For both regions, the percentage of oxidised groundwater decreased with increasing well depth. Linear discriminant analysis was used to develop models to differentiate between the three redox states. Models were derived for each depth and region using 67% of the data, and then subsequently validated on the remaining 33%. The average agreement between predicted and measured redox status was 63% and 70% for the Waikato and Canterbury regions, respectively. The models were incorporated into GIS and the prediction of redox status was extended over the whole region, excluding mountainous land. This knowledge improves spatial prediction of reduced groundwater zones, and therefore, when combined with groundwater flow paths, improves estimates of denitrification. Copyright © 2016 Elsevier B.V. All rights reserved.

JAVA CLASSES FOR NONPROCEDURAL VARIOGRAM MONITORING

EPA Science Inventory

A set of Java classes was written for variogram modeling to support research for US EPA's Regional Vulnerability Assessment Program (ReVA). The modeling objectives of this research program are to use conceptual programming tools for numerical analysis for regional risk assessm...

The Ohio River Basin energy facility siting model. Volume 1: Methodology

NASA Astrophysics Data System (ADS)

Fowler, G. L.; Bailey, R. E.; Gordon, S. I.; Jansen, S. D.; Randolph, J. C.; Jones, W. W.

1981-04-01

The siting model developed for ORBES is specifically designed for regional policy analysis. The region includes 423 counties in an area that consists of all of Kentucky and substantial portions of Illinois, Indiana, Ohio, Pennsylvania, and West Virginia.

Modelling near field regional uplift patterns in West Greenland/Disko Bay with plane-Earth finite element models.

NASA Astrophysics Data System (ADS)

Meldgaard, Asger; Nielsen, Lars; Iaffaldano, Giampiero

2017-04-01

Relative sea level data, primarily obtained through isolation basin analysis in western Greenland and on Disko Island, indicates asynchronous rates of uplift during the Early Holocene with larger rates of uplift in southern Disko Bay compared to the northern part of the bay. Similar short-wavelength variations can be inferred from the Holocene marine limit as observations on the north and south side of Disko Island differ by as much as 60 m. While global isostatic adjustment models are needed to account for far field contributions to the relative sea level and for the calculation of accurate ocean functions, they are generally not suited for a detailed analysis of the short-wavelength uplift patterns observed close to present ice margins. This is in part due to the excessive computational cost required for sufficient resolution, and because these models generally ignore regional lateral heterogeneities in mantle and lithosphere rheology. To mitigate this problem, we perform sensitivity tests to investigate the effects of near field loading on a regional plane-Earth finite element model of the lithosphere and mantle of the Disko Bay area, where the global isostatic uplift chronology is well documented. By loading the model area through detailed regional ocean function and ice models, and by including a high resolution topography model of the area, we seek to assess the isostatic rebound generated by surface processes with wavelengths similar to those of the observed rebound signal. We also investigate possible effects of varying lithosphere and mantle rheology, which may play an important role in explaining the rebound signal. We use the abundance of relative sea level curves obtained in the region primarily through isolation basin analysis on Disko Island to constrain the parameters of the Earth model.

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Data integrity systems for organ contours in radiation therapy planning.

PubMed

Shah, Veeraj P; Lakshminarayanan, Pranav; Moore, Joseph; Tran, Phuoc T; Quon, Harry; Deville, Curtiland; McNutt, Todd R

2018-06-12

The purpose of this research is to develop effective data integrity models for contoured anatomy in a radiotherapy workflow for both real-time and retrospective analysis. Within this study, two classes of contour integrity models were developed: data driven models and contiguousness models. The data driven models aim to highlight contours which deviate from a gross set of contours from similar disease sites and encompass the following regions of interest (ROI): bladder, femoral heads, spinal cord, and rectum. The contiguousness models, which individually analyze the geometry of contours to detect possible errors, are applied across many different ROI's and are divided into two metrics: Extent and Region Growing over volume. After analysis, we found that 70% of detected bladder contours were verified as suspicious. The spinal cord and rectum models verified that 73% and 80% of contours were suspicious respectively. The contiguousness models were the most accurate models and the Region Growing model was the most accurate submodel. 100% of the detected noncontiguous contours were verified as suspicious, but in the cases of spinal cord, femoral heads, bladder, and rectum, the Region Growing model detected additional two to five suspicious contours that the Extent model failed to detect. When conducting a blind review to detect false negatives, it was found that all the data driven models failed to detect all suspicious contours. The Region Growing contiguousness model produced zero false negatives in all regions of interest other than prostate. With regards to runtime, the contiguousness via extent model took an average of 0.2 s per contour. On the other hand, the region growing method had a longer runtime which was dependent on the number of voxels in the contour. Both contiguousness models have potential for real-time use in clinical radiotherapy while the data driven models are better suited for retrospective use. © 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

EVALUATING THE PERFORMANCE OF REGIONAL-SCALE PHOTOCHEMICAL MODELING SYSTEMS: PART I--METEOROLOGICAL PREDICTIONS. (R825260)

EPA Science Inventory

In this study, the concept of scale analysis is applied to evaluate two state-of-science meteorological models, namely MM5 and RAMS3b, currently being used to drive regional-scale air quality models. To this end, seasonal time series of observations and predictions for temperatur...

ANALYSIS OF MERCURY IN VERMONT AND NEW HAMPSHIRE LAKES: EVALUATION OF THE REGIONAL MERCURY CYCLING MODEL

EPA Science Inventory

An evaluation of the Regional Mercury Cycling Model (R-MCM, a steady-state fate and transport model used to simulate mercury concentrations in lakes) is presented based on its application to a series of 91 lakes in Vermont and New Hampshire. Visual and statistical analyses are pr...

Geodetic Imaging and Tsunami Modeling of the 2017 Coupled Landslide-Tsunami Event in Karrat Fjord, West Greenland.

NASA Astrophysics Data System (ADS)

Barba, M.; Willis, M. J.; Tiampo, K. F.; Lynett, P. J.; Mätzler, E.; Thorsøe, K.; Higman, B. M.; Thompson, J. A.; Morin, P. J.

2017-12-01

We use a combination of geodetic imaging techniques and modelling efforts to examine the June 2017 Karrat Fjord, West Greenland, landslide and tsunami event. Our efforts include analysis of pre-cursor motions extracted from Sentinal SAR interferometry that we improved with high-resolution Digital Surface Models derived from commercial imagery and geo-coded Structure from Motion analyses. We produce well constrained estimates of landslide volume through DSM differencing by improving the ArcticDEM coverage of the region, and provide modeled tsunami run-up estimates at villages around the region, constrained with in-situ observations provided by the Greenlandic authorities. Estimates of run-up at unoccupied coasts are derived using a blend of high resolution imagery and elevation models. We further detail post-failure slope stability for areas of interest around the Karrat Fjord region. Warming trends in the region from model and satellite analysis are combined with optical imagery to ascertain whether the influence of melting permafrost and the formation of small springs on a slight bench on the mountainside that eventually failed can be used as indicators of future events.

Empirical Study on Total Factor Productive Energy Efficiency in Beijing-Tianjin-Hebei Region-Analysis based on Malmquist Index and Window Model

NASA Astrophysics Data System (ADS)

Xu, Qiang; Ding, Shuai; An, Jingwen

2017-12-01

This paper studies the energy efficiency of Beijing-Tianjin-Hebei region and to finds out the trend of energy efficiency in order to improve the economic development quality of Beijing-Tianjin-Hebei region. Based on Malmquist index and window analysis model, this paper estimates the total factor energy efficiency in Beijing-Tianjin-Hebei region empirically by using panel data in this region from 1991 to 2014, and provides the corresponding political recommendations. The empirical result shows that, the total factor energy efficiency in Beijing-Tianjin-Hebei region increased from 1991 to 2014, mainly relies on advances in energy technology or innovation, and obvious regional differences in energy efficiency to exist. Throughout the window period of 24 years, the regional differences of energy efficiency in Beijing-Tianjin-Hebei region shrank. There has been significant convergent trend in energy efficiency after 2000, mainly depends on the diffusion and spillover of energy technologies.

A preliminary cost-effectiveness analysis of hepatitis E vaccination among pregnant women in epidemic regions.

PubMed

Zhao, Yueyuan; Zhang, Xuefeng; Zhu, Fengcai; Jin, Hui; Wang, Bei

2016-08-02

Objective To estimate the cost-effectiveness of hepatitis E vaccination among pregnant women in epidemic regions. Methods A decision tree model was constructed to evaluate the cost-effectiveness of 3 hepatitis E virus vaccination strategies from societal perspectives. The model parameters were estimated on the basis of published studies and experts' experience. Sensitivity analysis was used to evaluate the uncertainties of the model. Results Vaccination was more economically effective on the basis of the incremental cost-effectiveness ratio (ICER< 3 times China's per capital gross domestic product/quality-adjusted life years); moreover, screening and vaccination had higher QALYs and lower costs compared with universal vaccination. No parameters significantly impacted ICER in one-way sensitivity analysis, and probabilistic sensitivity analysis also showed screening and vaccination to be the dominant strategy. Conclusion Screening and vaccination is the most economical strategy for pregnant women in epidemic regions; however, further studies are necessary to confirm the efficacy and safety of the hepatitis E vaccines.

Rapid analysis of glucose, fructose, sucrose, and maltose in honeys from different geographic regions using fourier transform infrared spectroscopy and multivariate analysis.

PubMed

Wang, Jun; Kliks, Michael M; Jun, Soojin; Jackson, Mel; Li, Qing X

2010-03-01

Quantitative analysis of glucose, fructose, sucrose, and maltose in different geographic origin honey samples in the world using the Fourier transform infrared (FTIR) spectroscopy and chemometrics such as partial least squares (PLS) and principal component regression was studied. The calibration series consisted of 45 standard mixtures, which were made up of glucose, fructose, sucrose, and maltose. There were distinct peak variations of all sugar mixtures in the spectral "fingerprint" region between 1500 and 800 cm(-1). The calibration model was successfully validated using 7 synthetic blend sets of sugars. The PLS 2nd-derivative model showed the highest degree of prediction accuracy with a highest R(2) value of 0.999. Along with the canonical variate analysis, the calibration model further validated by high-performance liquid chromatography measurements for commercial honey samples demonstrates that FTIR can qualitatively and quantitatively determine the presence of glucose, fructose, sucrose, and maltose in multiple regional honey samples.

Analysis of the sensitivity properties of a model of vector-borne bubonic plague.

PubMed

Buzby, Megan; Neckels, David; Antolin, Michael F; Estep, Donald

2008-09-06

Model sensitivity is a key to evaluation of mathematical models in ecology and evolution, especially in complex models with numerous parameters. In this paper, we use some recently developed methods for sensitivity analysis to study the parameter sensitivity of a model of vector-borne bubonic plague in a rodent population proposed by Keeling & Gilligan. The new sensitivity tools are based on a variational analysis involving the adjoint equation. The new approach provides a relatively inexpensive way to obtain derivative information about model output with respect to parameters. We use this approach to determine the sensitivity of a quantity of interest (the force of infection from rats and their fleas to humans) to various model parameters, determine a region over which linearization at a specific parameter reference point is valid, develop a global picture of the output surface, and search for maxima and minima in a given region in the parameter space.

The influence of regional deprivation index on personal happiness using multilevel analysis

PubMed Central

Kim, Kil Hun; Chun, Jin-Ho; Sohn, Hae Sook

2015-01-01

OBJECTIVES: The objective of the present study was to identify the factors that influence the happiness index of community residents, by considering personal and regional aspects, and to use as evidence of efforts for improvement of the happiness index. METHODS: The study was conducted based on information from 16,270 participants who met the data requirement among those who participated in the 2011 South Gyeongsang Community Health Survey. Of the factors that can influence the happiness index, socioeconomic characteristics, health behavior, morbidity, and healthcare use, social contact, and participation in social activities were classified as personal factors; for regional factors, data from the 2010 census were used to extrapolate the regional deprivation indices at the submunicipal-level (eup, myeon, and dong) in South Gyeongsang Province. The happiness index for each characteristic was compared to that for others via t-test and ANOVA, and multilevel analysis was performed, using four models: a basic model for identification of only random effects, model 1 for identification of personal factors, model 2 for identification of regional factors, and model 3 for simultaneous consideration of both personal and regional factors. RESULTS: The mean happiness index was 63.2 points (64.6 points in males and 62.0 points in females), while the mean deprivation index was -1.58 points. In the multilevel analysis, the regional-level variance ratio of the basic model was 10.8%, confirming interregional differences. At the personal level, higher happiness indices were seen in groups consisting of males with high educational level, high income, high degree of physical activity, sufficient sleep, active social contact, and participation in social activities; whereas lower happiness indices were seen in people who frequently skipped breakfast, had unmet healthcare needs, and had accompanying diseases, as well as those with higher deprivation index. CONCLUSIONS: The study confirmed that the happiness index of community residents was influenced by not only personal aspects but also various regional characteristics. To increase the happiness index, interests at both personal and regional levels, as well as community emphasis on creating social rapport and engaging in selective efforts, are needed in vulnerable regions with relatively high deprivation index. PMID:26725223

The influence of regional deprivation index on personal happiness using multilevel analysis.

PubMed

Kim, Kil Hun; Chun, Jin-Ho; Sohn, Hae Sook

2015-01-01

The objective of the present study was to identify the factors that influence the happiness index of community residents, by considering personal and regional aspects, and to use as evidence of efforts for improvement of the happiness index. The study was conducted based on information from 16,270 participants who met the data requirement among those who participated in the 2011 South Gyeongsang Community Health Survey. Of the factors that can influence the happiness index, socioeconomic characteristics, health behavior, morbidity, and healthcare use, social contact, and participation in social activities were classified as personal factors; for regional factors, data from the 2010 census were used to extrapolate the regional deprivation indices at the submunicipal-level (eup, myeon, and dong) in South Gyeongsang Province. The happiness index for each characteristic was compared to that for others via t-test and ANOVA, and multilevel analysis was performed, using four models: a basic model for identification of only random effects, model 1 for identification of personal factors, model 2 for identification of regional factors, and model 3 for simultaneous consideration of both personal and regional factors. The mean happiness index was 63.2 points (64.6 points in males and 62.0 points in females), while the mean deprivation index was -1.58 points. In the multilevel analysis, the regional-level variance ratio of the basic model was 10.8%, confirming interregional differences. At the personal level, higher happiness indices were seen in groups consisting of males with high educational level, high income, high degree of physical activity, sufficient sleep, active social contact, and participation in social activities; whereas lower happiness indices were seen in people who frequently skipped breakfast, had unmet healthcare needs, and had accompanying diseases, as well as those with higher deprivation index. The study confirmed that the happiness index of community residents was influenced by not only personal aspects but also various regional characteristics. To increase the happiness index, interests at both personal and regional levels, as well as community emphasis on creating social rapport and engaging in selective efforts, are needed in vulnerable regions with relatively high deprivation index.

Importance of Foliar Nitrogen Concentration to Predict Forest Productivity in the Mid-Atlantic Region

Treesearch

Yude Pan; John Hom; Jennifer Jenkins; Richard Birdsey

2004-01-01

To assess what difference it might make to include spatially defined estimates of foliar nitrogen in the regional application of a forest ecosystem model (PnET-II), we composed model predictions of wood production from extensive ground-based forest inventory analysis data across the Mid-Atlantic region. Spatial variation in foliar N concentration was assigned based on...

A Phylogenetic and Phenotypic Analysis of Salmonella enterica Serovar Weltevreden, an Emerging Agent of Diarrheal Disease in Tropical Regions

PubMed Central

Makendi, Carine; Page, Andrew J.; Wren, Brendan W.; Le Thi Phuong, Tu; Clare, Simon; Hale, Christine; Goulding, David; Klemm, Elizabeth J.; Pickard, Derek; Okoro, Chinyere; Hunt, Martin; Thompson, Corinne N.; Phu Huong Lan, Nguyen; Tran Do Hoang, Nhu; Thwaites, Guy E.; Le Hello, Simon; Brisabois, Anne; Weill, François-Xavier; Baker, Stephen; Dougan, Gordon

2016-01-01

Salmonella enterica serovar Weltevreden (S. Weltevreden) is an emerging cause of diarrheal and invasive disease in humans residing in tropical regions. Despite the regional and international emergence of this Salmonella serovar, relatively little is known about its genetic diversity, genomics or virulence potential in model systems. Here we used whole genome sequencing and bioinformatics analyses to define the phylogenetic structure of a diverse global selection of S. Weltevreden. Phylogenetic analysis of more than 100 isolates demonstrated that the population of S. Weltevreden can be segregated into two main phylogenetic clusters, one associated predominantly with continental Southeast Asia and the other more internationally dispersed. Subcluster analysis suggested the local evolution of S. Weltevreden within specific geographical regions. Four of the isolates were sequenced using long read sequencing to produce high quality reference genomes. Phenotypic analysis in Hep-2 cells and in a murine infection model indicated that S. Weltevreden were significantly attenuated in these models compared to the classical S. Typhimurium reference strain SL1344. Our work outlines novel insights into this important emerging pathogen and provides a baseline understanding for future research studies. PMID:26867150

An analytical model for highly seperated flow on airfoils at low speeds

NASA Technical Reports Server (NTRS)

Zunnalt, G. W.; Naik, S. N.

1977-01-01

A computer program was developed to solve the low speed flow around airfoils with highly separated flow. A new flow model included all of the major physical features in the separated region. Flow visualization tests also were made which gave substantiation to the validity of the model. The computation involves the matching of the potential flow, boundary layer and flows in the separated regions. Head's entrainment theory was used for boundary layer calculations and Korst's jet mixing analysis was used in the separated regions. A free stagnation point aft of the airfoil and a standing vortex in the separated region were modelled and computed.

A comparative study on the stress distribution around dental implants in three arch form models for replacing six implants using finite element analysis.

PubMed

Zarei, Maryam; Jahangirnezhad, Mahmoud; Yousefimanesh, Hojatollah; Robati, Maryam; Robati, Hossein

2018-01-01

Dental implant is a method to replacement of missing teeth. It is important for replacing the missed anterior teeth. In vitro method is a safe method for evaluation of stress distribution. Finite element analysis as an in vitro method evaluated stress distribution around replacement of six maxillary anterior teeth implants in three models of maxillary arch. In this in vitro study, using ABAQUS software (Simulia Corporation, Vélizy-Villacoublay, France), implant simulation was performed for reconstruction of six maxillary anterior teeth in three models. Two implants were placed on both sides of the canine tooth region (A model); two implants on both sides of the canine tooth region and another on one side of the central incisor region (B model); and two implants on both sides of the canine tooth region and two implants in the central incisor area (C model). All implants evaluated in three arch forms (tapered, ovoid, and square). Data were analyzed by finite analysis software. Von Mises stress by increasing of implant number was reduced. In a comparison of A model in each maxillary arch, the stress created in the cortical and cancellous bones in the square arch was less than ovoid and tapered arches. The stress created in implants and cortical and cancellous bones in C model was less than A and B models. The C model (four-implant) reduced the stress distribution in cortical and cancellous bones, but this pattern must be evaluated according to arch form and cost benefit of patients.

Cage Regional Energy Budgets from the GLAS 4TH Order Model

NASA Technical Reports Server (NTRS)

Herman, G. F.; Alexder, M. A.; Shubert, S. D.

1984-01-01

The status and future plans of a study to (1) assess the accuracy of regional energy balance calculations obtained from the 4th-order model, (2) determine the impact of satellite data on the calculations, and (3) determine their utility for ocean energy transport studies are discussed. An equation is presented which models the vertically-integrated, time and areally-averaged total energy content of a region of the atmosphere extending from the surface to the top of the atmosphere. All of the terms of the equation were evaluated using early versions of the GLAS FGGE IIIb analysis, and analysis with satellite data deleted. Results show that the budget is dominated by the surface fluxes, net radiation, and horizontal atmospoheric divergence.

[Global Atmospheric Chemistry/Transport Modeling and Data-Analysis

NASA Technical Reports Server (NTRS)

Prinn, Ronald G.

1999-01-01

This grant supported a global atmospheric chemistry/transport modeling and data- analysis project devoted to: (a) development, testing, and refining of inverse methods for determining regional and global transient source and sink strengths for trace gases; (b) utilization of these inverse methods which use either the Model for Atmospheric Chemistry and Transport (MATCH) which is based on analyzed observed winds or back- trajectories calculated from these same winds for determining regional and global source and sink strengths for long-lived trace gases important in ozone depletion and the greenhouse effect; (c) determination of global (and perhaps regional) average hydroxyl radical concentrations using inverse methods with multiple "titrating" gases; and (d) computation of the lifetimes and spatially resolved destruction rates of trace gases using 3D models. Important ultimate goals included determination of regional source strengths of important biogenic/anthropogenic trace gases and also of halocarbons restricted by the Montreal Protocol and its follow-on agreements, and hydrohalocarbons now used as alternatives to the above restricted halocarbons.

The magnetotelluric phase tensor analysis of the Sembalun-Propok area, West Nusa Tenggara, Indonesia

NASA Astrophysics Data System (ADS)

Febriani, F.; Widarto, D. S.; Gaffar, E.; Nasution, A.; Grandis, H.

2017-04-01

The subsurface structure of the Sembalun-Propok area, NTB, Indonesia, has been investigated using magnetotelluric method (MT). To obtain the information of the dimensionality of the regional structure and determine the regional strike of the study area, the phase tensor analysis has been performed in this study. The results show that most of the skew angle values (β) are distributed within ± 5°. It indicates that the regional structure of the study area can be assumed as two dimensional. In addition, to determine the regional strike of the study area, we also calculated the major axes of the phase tensor. The result presents that the regional strike of the study area is about N330°E. According to the results of the phase tensor analysis, we rotated the impedance tensor to N330°E and performed 2-D inversion modeling. The result presents that the substructure model suits with the geological background of the study area.

EVALUATING THE PERFORMANCE OF REGIONAL-SCALE PHOTOCHEMICAL MODELING SYSTEMS: PART II--OZONE PREDICTIONS. (R825260)

EPA Science Inventory

In this paper, the concept of scale analysis is applied to evaluate ozone predictions from two regional-scale air quality models. To this end, seasonal time series of observations and predictions from the RAMS3b/UAM-V and MM5/MAQSIP (SMRAQ) modeling systems for ozone were spectra...

Spatio-Temporal Analysis of Trends and periodicities of regional drought projections in India

NASA Astrophysics Data System (ADS)

Gupta, Vivek; Jain, Manoj Kumar

2017-04-01

Climate change is believed to be altering the hydrologic cycle of different regions worldwide. This may alter the occurrence and distribution of extreme events such as droughts and floods. India is one of the most drought affected country, it is therefore important to understand spatiotemporal variation of droughts in future due to climate change. In this paper, we have analyzed the spatiotemporal projections of droughts over India for 21st century using Global Climate Model (GCM) precipitation projections of ESM2G model under two Representative Concentration Pathways (RCP) namely, RCP 4.5 and RCP 8.5. K-means Clustering algorithm has been exploited to obtain homogeneous precipitation region in India for regional drought analysis. Further, temporal analysis of projected annual minimum SPI for year 2006 to 2100 has been performed for different homogeneous regions obtained using cluster analysis. Trend analysis of annual minimum SPI series has also been performed using Mann-Kendall and Sen's slope method. Furthermore, periodicity in SPI series have been examined using wavelet periodogram analysis. Findings of this paper suggest that major drought events for Northeastern and Southern India are likely to occur in second half of the 21st century while for all other parts of India, most of the major drought events are expected in first half of the 21st century. Also, wavelet periodicity analysis indicates inter-annual periodicities of projected droughts between 3 to 9.5 years in different regions of India.

Atrial Electrogram Fractionation Distribution before and after Pulmonary Vein Isolation in Human Persistent Atrial Fibrillation-A Retrospective Multivariate Statistical Analysis.

PubMed

Almeida, Tiago P; Chu, Gavin S; Li, Xin; Dastagir, Nawshin; Tuan, Jiun H; Stafford, Peter J; Schlindwein, Fernando S; Ng, G André

2017-01-01

Purpose: Complex fractionated atrial electrograms (CFAE)-guided ablation after pulmonary vein isolation (PVI) has been used for persistent atrial fibrillation (persAF) therapy. This strategy has shown suboptimal outcomes due to, among other factors, undetected changes in the atrial tissue following PVI. In the present work, we investigate CFAE distribution before and after PVI in patients with persAF using a multivariate statistical model. Methods: 207 pairs of atrial electrograms (AEGs) were collected before and after PVI respectively, from corresponding LA regions in 18 persAF patients. Twelve attributes were measured from the AEGs, before and after PVI. Statistical models based on multivariate analysis of variance (MANOVA) and linear discriminant analysis (LDA) have been used to characterize the atrial regions and AEGs. Results: PVI significantly reduced CFAEs in the LA (70 vs. 40%; P < 0.0001). Four types of LA regions were identified, based on the AEGs characteristics: (i) fractionated before PVI that remained fractionated after PVI (31% of the collected points); (ii) fractionated that converted to normal (39%); (iii) normal prior to PVI that became fractionated (9%) and; (iv) normal that remained normal (21%). Individually, the attributes failed to distinguish these LA regions, but multivariate statistical models were effective in their discrimination ( P < 0.0001). Conclusion: Our results have unveiled that there are LA regions resistant to PVI, while others are affected by it. Although, traditional methods were unable to identify these different regions, the proposed multivariate statistical model discriminated LA regions resistant to PVI from those affected by it without prior ablation information.

Information flow in an atmospheric model and data assimilation

NASA Astrophysics Data System (ADS)

Yoon, Young-noh

2011-12-01

Weather forecasting consists of two processes, model integration and analysis (data assimilation). During the model integration, the state estimate produced by the analysis evolves to the next cycle time according to the atmospheric model to become the background estimate. The analysis then produces a new state estimate by combining the background state estimate with new observations, and the cycle repeats. In an ensemble Kalman filter, the probability distribution of the state estimate is represented by an ensemble of sample states, and the covariance matrix is calculated using the ensemble of sample states. We perform numerical experiments on toy atmospheric models introduced by Lorenz in 2005 to study the information flow in an atmospheric model in conjunction with ensemble Kalman filtering for data assimilation. This dissertation consists of two parts. The first part of this dissertation is about the propagation of information and the use of localization in ensemble Kalman filtering. If we can perform data assimilation locally by considering the observations and the state variables only near each grid point, then we can reduce the number of ensemble members necessary to cover the probability distribution of the state estimate, reducing the computational cost for the data assimilation and the model integration. Several localized versions of the ensemble Kalman filter have been proposed. Although tests applying such schemes have proven them to be extremely promising, a full basic understanding of the rationale and limitations of localization is currently lacking. We address these issues and elucidate the role played by chaotic wave dynamics in the propagation of information and the resulting impact on forecasts. The second part of this dissertation is about ensemble regional data assimilation using joint states. Assuming that we have a global model and a regional model of higher accuracy defined in a subregion inside the global region, we propose a data assimilation scheme that produces the analyses for the global and the regional model simultaneously, considering forecast information from both models. We show that our new data assimilation scheme produces better results both in the subregion and the global region than the data assimilation scheme that produces the analyses for the global and the regional model separately.

Regional model simulation of summer rainfall over the Philippines: Effect of choice of driving fields and ocean flux schemes

NASA Astrophysics Data System (ADS)

Francisco, R. V.; Argete, J.; Giorgi, F.; Pal, J.; Bi, X.; Gutowski, W. J.

2006-09-01

The latest version of the Abdus Salam International Centre for Theoretical Physics (ICTP) regional model RegCM is used to investigate summer monsoon precipitation over the Philippine archipelago and surrounding ocean waters, a region where regional climate models have not been applied before. The sensitivity of simulated precipitation to driving lateral boundary conditions (NCEP and ERA40 reanalyses) and ocean surface flux scheme (BATS and Zeng) is assessed for 5 monsoon seasons. The ability of the RegCM to simulate the spatial patterns and magnitude of monsoon precipitation is demonstrated, both in response to the prominent large scale circulations over the region and to the local forcing by the physiographical features of the Philippine islands. This provides encouraging indications concerning the development of a regional climate modeling system for the Philippine region. On the other hand, the model shows a substantial sensitivity to the analysis fields used for lateral boundary conditions as well as the ocean surface flux schemes. The use of ERA40 lateral boundary fields consistently yields greater precipitation amounts compared to the use of NCEP fields. Similarly, the BATS scheme consistently produces more precipitation compared to the Zeng scheme. As a result, different combinations of lateral boundary fields and surface ocean flux schemes provide a good simulation of precipitation amounts and spatial structure over the region. The response of simulated precipitation to using different forcing analysis fields is of the same order of magnitude as the response to using different surface flux parameterizations in the model. As a result it is difficult to unambiguously establish which of the model configurations is best performing.

GIS-Based Suitability Model for Assessment of Forest Biomass Energy Potential in a Region of Portugal

NASA Astrophysics Data System (ADS)

Quinta-Nova, Luis; Fernandez, Paulo; Pedro, Nuno

2017-12-01

This work focuses on developed a decision support system based on multicriteria spatial analysis to assess the potential for generation of biomass residues from forestry sources in a region of Portugal (Beira Baixa). A set of environmental, economic and social criteria was defined, evaluated and weighted in the context of Saaty’s analytic hierarchies. The best alternatives were obtained after applying Analytic Hierarchy Process (AHP). The model was applied to the central region of Portugal where forest and agriculture are the most representative land uses. Finally, sensitivity analysis of the set of factors and their associated weights was performed to test the robustness of the model. The proposed evaluation model provides a valuable reference for decision makers in establishing a standardized means of selecting the optimal location for new biomass plants.

The interpretation of simultaneous soft X-ray spectroscopic and imaging observations of an active region. [in solar corona

NASA Technical Reports Server (NTRS)

Davis, J. M.; Gerassimenko, M.; Krieger, A. S.; Vaiana, G. S.

1975-01-01

Simultaneous soft X-ray spectroscopic and broad-band imaging observations of an active region have been analyzed together to determine the parameters which describe the coronal plasma. From the spectroscopic data, models of temperature-emission measure-elemental abundance have been constructed which provide acceptable statistical fits. By folding these possible models through the imaging analysis, models which are not self-consistent can be rejected. In this way, only the oxygen, neon, and iron abundances of Pottasch (1967), combined with either an isothermal or exponential temperature-emission-measure model, are consistent with both sets of data. Contour maps of electron temperature and density for the active region have been constructed from the imaging data. The implications of the analysis for the determination of coronal abundances and for future satellite experiments are discussed.

Potentiality Prediction of Electric Power Replacement Based on Power Market Development Strategy

NASA Astrophysics Data System (ADS)

Miao, Bo; Yang, Shuo; Liu, Qiang; Lin, Jingyi; Zhao, Le; Liu, Chang; Li, Bin

2017-05-01

The application of electric power replacement plays an important role in promoting the development of energy conservation and emission reduction in our country. To exploit the potentiality of regional electric power replacement, the regional GDP (gross domestic product) and energy consumption are taken as potentiality evaluation indicators. The principal component factors are extracted with PCA (principal component analysis), and the integral potentiality analysis is made to the potentiality of electric power replacement in the national various regions; a region is taken as a research object, and the potentiality of electric power replacement is defined and quantified. The analytical model for the potentiality of multi-scenario electric power replacement is developed, and prediction is made to the energy consumption with the grey prediction model. The relevant theoretical research is utilized to realize prediction analysis on the potentiality amount of multi-scenario electric power replacement.

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

PubMed

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

2015-07-01

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

Experimental testing and constitutive modeling of the mechanical properties of the swine skin tissue.

PubMed

Łagan, Sylwia D; Liber-Kneć, Aneta

2017-01-01

The aim of the study was an estimation of the possibility of using hyperelastic material models to fit experimental data obtained in the tensile test for the swine skin tissue. The uniaxial tensile tests of samples taken from the abdomen and back of a pig was carried out. The mechanical properties of the skin such as the mean Young's modulus, the mean maximum stress and the mean maximum elongation were calculated. The experimental data have been used to identify the parameters in specific strain-energy functions given in seven constitutive models of hyperelastic materials: neo-Hookean, Mooney-Rivlin, Ogden, Yeoh, Martins, Humphrey and Veronda-Westmann. An analysis of errors in fitting of theoretical and experimental data was done. Comparison of load -displacement curves for the back and abdomen regions of skin taken showed a different scope of both the mean maximum loading forces and the mean maximum elongation. Samples which have been prepared from the abdominal area had lower values of the mean maximum load compared to samples from the spine area. The reverse trend was observed during the analysis of the values of elongation. An analysis of the accuracy of model fitting to the experimental data showed that, the least accurate were the model of neo- -Hookean, model of Mooney-Rivlin for the abdominal region and model of Veronda-Westmann for the spine region. An analysis of seven hyperelastic material models showed good correlations between the experimental and the theoretical data for five models.

Global/local stress analysis of composite panels

NASA Technical Reports Server (NTRS)

Ransom, Jonathan B.; Knight, Norman F., Jr.

1989-01-01

A method for performing a global/local stress analysis is described, and its capabilities are demonstrated. The method employs spline interpolation functions which satisfy the linear plate bending equation to determine displacements and rotations from a global model which are used as boundary conditions for the local model. Then, the local model is analyzed independent of the global model of the structure. This approach can be used to determine local, detailed stress states for specific structural regions using independent, refined local models which exploit information from less-refined global models. The method presented is not restricted to having a priori knowledge of the location of the regions requiring local detailed stress analysis. This approach also reduces the computational effort necessary to obtain the detailed stress state. Criteria for applying the method are developed. The effectiveness of the method is demonstrated using a classical stress concentration problem and a graphite-epoxy blade-stiffened panel with a discontinuous stiffener.

Global/local stress analysis of composite structures. M.S. Thesis

NASA Technical Reports Server (NTRS)

Ransom, Jonathan B.

1989-01-01

A method for performing a global/local stress analysis is described and its capabilities are demonstrated. The method employs spline interpolation functions which satisfy the linear plate bending equation to determine displacements and rotations from a global model which are used as boundary conditions for the local model. Then, the local model is analyzed independent of the global model of the structure. This approach can be used to determine local, detailed stress states for specific structural regions using independent, refined local models which exploit information from less-refined global models. The method presented is not restricted to having a priori knowledge of the location of the regions requiring local detailed stress analysis. This approach also reduces the computational effort necessary to obtain the detailed stress state. Criteria for applying the method are developed. The effectiveness of the method is demonstrated using a classical stress concentration problem and a graphite-epoxy blade-stiffened panel with a discontinuous stiffener.

Application of Markov chain Monte Carlo analysis to biomathematical modeling of respirable dust in US and UK coal miners

PubMed Central

Sweeney, Lisa M.; Parker, Ann; Haber, Lynne T.; Tran, C. Lang; Kuempel, Eileen D.

2015-01-01

A biomathematical model was previously developed to describe the long-term clearance and retention of particles in the lungs of coal miners. The model structure was evaluated and parameters were estimated in two data sets, one from the United States and one from the United Kingdom. The three-compartment model structure consists of deposition of inhaled particles in the alveolar region, competing processes of either clearance from the alveolar region or translocation to the lung interstitial region, and very slow, irreversible sequestration of interstitialized material in the lung-associated lymph nodes. Point estimates of model parameter values were estimated separately for the two data sets. In the current effort, Bayesian population analysis using Markov chain Monte Carlo simulation was used to recalibrate the model while improving assessments of parameter variability and uncertainty. When model parameters were calibrated simultaneously to the two data sets, agreement between the derived parameters for the two groups was very good, and the central tendency values were similar to those derived from the deterministic approach. These findings are relevant to the proposed update of the ICRP human respiratory tract model with revisions to the alveolar-interstitial region based on this long-term particle clearance and retention model. PMID:23454101

Application of turbulence modeling to predict surface heat transfer in stagnation flow region of circular cylinder

NASA Technical Reports Server (NTRS)

Wang, Chi R.; Yeh, Frederick C.

1987-01-01

A theoretical analysis and numerical calculations for the turbulent flow field and for the effect of free-stream turbulence on the surface heat transfer rate of a stagnation flow are presented. The emphasis is on the modeling of turbulence and its augmentation of surface heat transfer rate. The flow field considered is the region near the forward stagnation point of a circular cylinder in a uniform turbulent mean flow. The free stream is steady and incompressible with a Reynolds number of the order of 10 to the 5th power and turbulence intensity of less than 5 percent. For this analysis, the flow field is divided into three regions: (1) a uniform free-stream region where the turbulence is homogeneous and isotropic; (2) an external viscid flow region where the turbulence is distorted by the variation of the mean flow velocity; and, (3) an anisotropic turbulent boundary layer region over the cylinder surface. The turbulence modeling techniques used are the kappa-epsilon two-equation model in the external flow region and the time-averaged turbulence transport equation in the boundary layer region. The turbulence double correlations, the mean velocity, and the mean temperature within the boundary layer are solved numerically from the transport equations. The surface heat transfer rate is calculated as functions of the free-stream turbulence longitudinal microlength scale, the turbulence intensity, and the Reynolds number.

Regional Sustainable Development Analysis Based on Information Entropy—Sichuan Province as an Example

PubMed Central

Liang, Xuedong; Si, Dongyang; Zhang, Xinli

2017-01-01

According to the implementation of a scientific development perspective, sustainable development needs to consider regional development, economic and social development, and the harmonious development of society and nature, but regional sustainable development is often difficult to quantify. Through an analysis of the structure and functions of a regional system, this paper establishes an evaluation index system, which includes an economic subsystem, an ecological environmental subsystem and a social subsystem, to study regional sustainable development capacity. A sustainable development capacity measure model for Sichuan Province was established by applying the information entropy calculation principle and the Brusselator principle. Each subsystem and entropy change in a calendar year in Sichuan Province were analyzed to evaluate Sichuan Province’s sustainable development capacity. It was found that the established model could effectively show actual changes in sustainable development levels through the entropy change reaction system, at the same time this model could clearly demonstrate how those forty-six indicators from the three subsystems impact on the regional sustainable development, which could make up for the lack of sustainable development research. PMID:29027982

Regional Sustainable Development Analysis Based on Information Entropy-Sichuan Province as an Example.

PubMed

Liang, Xuedong; Si, Dongyang; Zhang, Xinli

2017-10-13

According to the implementation of a scientific development perspective, sustainable development needs to consider regional development, economic and social development, and the harmonious development of society and nature, but regional sustainable development is often difficult to quantify. Through an analysis of the structure and functions of a regional system, this paper establishes an evaluation index system, which includes an economic subsystem, an ecological environmental subsystem and a social subsystem, to study regional sustainable development capacity. A sustainable development capacity measure model for Sichuan Province was established by applying the information entropy calculation principle and the Brusselator principle. Each subsystem and entropy change in a calendar year in Sichuan Province were analyzed to evaluate Sichuan Province's sustainable development capacity. It was found that the established model could effectively show actual changes in sustainable development levels through the entropy change reaction system, at the same time this model could clearly demonstrate how those forty-six indicators from the three subsystems impact on the regional sustainable development, which could make up for the lack of sustainable development research.

A Modernized National Spatial Reference System in 2022: Focus on the Caribbean Terrestrial Reference Frame

NASA Astrophysics Data System (ADS)

Roman, D. R.

2017-12-01

In 2022, the National Geodetic Survey will replace all three NAD 83 reference frames the four new terrestrial reference frames. Each frame will be named after a tectonic plate (North American, Pacific, Caribbean and Mariana) and each will be related to the IGS frame through three Euler Pole parameters (EPPs). This talk will focus on practical application in the Caribbean region. A working group is being re-established for development of the North American region and will likely also result in analysis of the Pacific region as well. Both of these regions are adequately covered with existing CORS sites to model the EPPs. The Mariana region currently lacks sufficient coverage, but a separate project is underway to collect additional information to help in defining EPPs for that region at a later date. The Caribbean region has existing robust coverage through UNAVCO's COCONet and other data sets, but these require further analysis. This discussion will focus on practical examination of Caribbean sites to establish candidates for determining the Caribbean frame EPPs as well as an examination of any remaining velocities that might inform a model of the remaining velocities within that frame (Intra-Frame Velocity Model). NGS has a vested interest in defining such a model to meet obligations to U.S. citizens in Puerto Rico and the U.S. Virgin Islands. Beyond this, NGS aims to collaborate with other countries in the region through efforts with SIRGAS and UN-GGIM-Americas for a more acceptable regional model to serve everyone's needs.

Evidence for an anterior-posterior differentiation in the human hippocampal formation revealed by meta-analytic parcellation of fMRI coordinate maps: focus on the subiculum.

PubMed

Chase, Henry W; Clos, Mareike; Dibble, Sofia; Fox, Peter; Grace, Anthony A; Phillips, Mary L; Eickhoff, Simon B

2015-06-01

Previous studies, predominantly in experimental animals, have suggested the presence of a differentiation of function across the hippocampal formation. In rodents, ventral regions are thought to be involved in emotional behavior while dorsal regions mediate cognitive or spatial processes. Using a combination of modeling the co-occurrence of significant activations across thousands of neuroimaging experiments and subsequent data-driven clustering of these data we were able to provide evidence of distinct subregions within a region corresponding to the human subiculum, a critical hub within the hippocampal formation. This connectivity-based model consists of a bilateral anterior region, as well as separate posterior and intermediate regions on each hemisphere. Functional connectivity assessed both by meta-analytic and resting fMRI approaches revealed that more anterior regions were more strongly connected to the default mode network, and more posterior regions were more strongly connected to 'task positive' regions. In addition, our analysis revealed that the anterior subregion was functionally connected to the ventral striatum, midbrain and amygdala, a circuit that is central to models of stress and motivated behavior. Analysis of a behavioral taxonomy provided evidence for a role for each subregion in mnemonic processing, as well as implication of the anterior subregion in emotional and visual processing and the right posterior subregion in reward processing. These findings lend support to models which posit anterior-posterior differentiation of function within the human hippocampal formation and complement other early steps toward a comparative (cross-species) model of the region. Copyright © 2015 Elsevier Inc. All rights reserved.

Uncertainty in Ecohydrological Modeling in an Arid Region Determined with Bayesian Methods

PubMed Central

Yang, Junjun; He, Zhibin; Du, Jun; Chen, Longfei; Zhu, Xi

2016-01-01

In arid regions, water resources are a key forcing factor in ecosystem circulation, and soil moisture is the critical link that constrains plant and animal life on the soil surface and underground. Simulation of soil moisture in arid ecosystems is inherently difficult due to high variability. We assessed the applicability of the process-oriented CoupModel for forecasting of soil water relations in arid regions. We used vertical soil moisture profiling for model calibration. We determined that model-structural uncertainty constituted the largest error; the model did not capture the extremes of low soil moisture in the desert-oasis ecotone (DOE), particularly below 40 cm soil depth. Our results showed that total uncertainty in soil moisture prediction was improved when input and output data, parameter value array, and structure errors were characterized explicitly. Bayesian analysis was applied with prior information to reduce uncertainty. The need to provide independent descriptions of uncertainty analysis (UA) in the input and output data was demonstrated. Application of soil moisture simulation in arid regions will be useful for dune-stabilization and revegetation efforts in the DOE. PMID:26963523

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

NASA Astrophysics Data System (ADS)

Zhang, Ying; Moges, Semu; Block, Paul

2018-01-01

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

Localized Multi-Model Extremes Metrics for the Fourth National Climate Assessment

NASA Astrophysics Data System (ADS)

Thompson, T. R.; Kunkel, K.; Stevens, L. E.; Easterling, D. R.; Biard, J.; Sun, L.

2017-12-01

We have performed localized analysis of scenario-based datasets for the Fourth National Climate Assessment (NCA4). These datasets include CMIP5-based Localized Constructed Analogs (LOCA) downscaled simulations at daily temporal resolution and 1/16th-degree spatial resolution. Over 45 temperature and precipitation extremes metrics have been processed using LOCA data, including threshold, percentile, and degree-days calculations. The localized analysis calculates trends in the temperature and precipitation extremes metrics for relatively small regions such as counties, metropolitan areas, climate zones, administrative areas, or economic zones. For NCA4, we are currently addressing metropolitan areas as defined by U.S. Census Bureau Metropolitan Statistical Areas. Such localized analysis provides essential information for adaptation planning at scales relevant to local planning agencies and businesses. Nearly 30 such regions have been analyzed to date. Each locale is defined by a closed polygon that is used to extract LOCA-based extremes metrics specific to the area. For each metric, single-model data at each LOCA grid location are first averaged over several 30-year historical and future periods. Then, for each metric, the spatial average across the region is calculated using model weights based on both model independence and reproducibility of current climate conditions. The range of single-model results is also captured on the same localized basis, and then combined with the weighted ensemble average for each region and each metric. For example, Boston-area cooling degree days and maximum daily temperature is shown below for RCP8.5 (red) and RCP4.5 (blue) scenarios. We also discuss inter-regional comparison of these metrics, as well as their relevance to risk analysis for adaptation planning.

Regional surface soil heat flux estimate from multiple remote sensing data in a temperate and semiarid basin

NASA Astrophysics Data System (ADS)

Li, Nana; Jia, Li; Lu, Jing; Menenti, Massimo; Zhou, Jie

2017-01-01

The regional surface soil heat flux (G0) estimation is very important for the large-scale land surface process modeling. However, most of the regional G0 estimation methods are based on the empirical relationship between G0 and the net radiation flux. A physical model based on harmonic analysis was improved (referred to as "HM model") and applied over the Heihe River Basin northwest China with multiple remote sensing data, e.g., FY-2C, AMSR-E, and MODIS, and soil map data. The sensitivity analysis of the model was studied as well. The results show that the improved model describes the variation of G0 well. Land surface temperature (LST) and thermal inertia (Γ) are the two key input variables to the HM model. Compared with in situ G0, there are some differences, mainly due to the differences between remote-sensed LST and the in situ LST. The sensitivity analysis shows that the errors from -7 to -0.5 K in LST amplitude and from -300 to 300 J m-2 K-1 s-0.5 in Γ will cause about 20% errors, which are acceptable for G0 estimation.

Modeling and Analysis of Global and Regional Climate Change in Relation to Atmospheric Hydrologic Processes

NASA Technical Reports Server (NTRS)

Johnson, Donald R.

2001-01-01

This research was directed to the development and application of global isentropic modeling and analysis capabilities to describe hydrologic processes and energy exchange in the climate system, and discern regional climate change. An additional objective was to investigate the accuracy and theoretical limits of global climate predictability which are imposed by the inherent limitations of simulating trace constituent transport and the hydrologic processes of condensation, precipitation and cloud life cycles.

GCIP water and energy budget synthesis (WEBS)

USGS Publications Warehouse

Roads, J.; Lawford, R.; Bainto, E.; Berbery, E.; Chen, S.; Fekete, B.; Gallo, K.; Grundstein, A.; Higgins, W.; Kanamitsu, M.; Krajewski, W.; Lakshmi, V.; Leathers, D.; Lettenmaier, D.; Luo, L.; Maurer, E.; Meyers, T.; Miller, D.; Mitchell, Ken; Mote, T.; Pinker, R.; Reichler, T.; Robinson, D.; Robock, A.; Smith, J.; Srinivasan, G.; Verdin, K.; Vinnikov, K.; Vonder, Haar T.; Vorosmarty, C.; Williams, S.; Yarosh, E.

2003-01-01

As part of the World Climate Research Program's (WCRPs) Global Energy and Water-Cycle Experiment (GEWEX) Continental-scale International Project (GCIP), a preliminary water and energy budget synthesis (WEBS) was developed for the period 1996-1999 fromthe "best available" observations and models. Besides this summary paper, a companion CD-ROM with more extensive discussion, figures, tables, and raw data is available to the interested researcher from the GEWEX project office, the GAPP project office, or the first author. An updated online version of the CD-ROM is also available at http://ecpc.ucsd.edu/gcip/webs.htm/. Observations cannot adequately characterize or "close" budgets since too many fundamental processes are missing. Models that properly represent the many complicated atmospheric and near-surface interactions are also required. This preliminary synthesis therefore included a representative global general circulation model, regional climate model, and a macroscale hydrologic model as well as a global reanalysis and a regional analysis. By the qualitative agreement among the models and available observations, it did appear that we now qualitatively understand water and energy budgets of the Mississippi River Basin. However, there is still much quantitative uncertainty. In that regard, there did appear to be a clear advantage to using a regional analysis over a global analysis or a regional simulation over a global simulation to describe the Mississippi River Basin water and energy budgets. There also appeared to be some advantage to using a macroscale hydrologic model for at least the surface water budgets. Copyright 2003 by the American Geophysical Union.

Discrete time modeling and stability analysis of TCP Vegas

NASA Astrophysics Data System (ADS)

You, Byungyong; Koo, Kyungmo; Lee, Jin S.

2007-12-01

This paper presents an analysis method for TCP Vegas network model with single link and single source. Some papers showed global stability of several network models, but those models are not a dual problem where dynamics both exist in sources and links such as TCP Vegas. Other papers studied TCP Vegas as a dual problem, but it did not fully derive an asymptotic stability region. Therefore we analyze TCP Vegas with Jury's criterion which is necessary and sufficient condition. So we use state space model in discrete time and by using Jury's criterion, we could find an asymptotic stability region of TCP Vegas network model. This result is verified by ns-2 simulation. And by comparing with other results, we could know our method performed well.

Regional Climate Change across North America in 2030 Projected from RCP6.0

NASA Astrophysics Data System (ADS)

Otte, T.; Nolte, C. G.; Faluvegi, G.; Shindell, D. T.

2012-12-01

Projecting climate change scenarios to local scales is important for understanding and mitigating the effects of climate change on society and the environment. Many of the general circulation models (GCMs) that are participating in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) do not fully resolve regional-scale processes and therefore cannot capture local changes in temperature and precipitation extremes. We seek to project the GCM's large-scale climate change signal to the local scale using a regional climate model (RCM) by applying dynamical downscaling techniques. The RCM will be used to better understand the local changes of temperature and precipitation extremes that may result from a changing climate. In this research, downscaling techniques that we developed with historical data are now applied to GCM fields. Results from downscaling NASA/GISS ModelE2 simulations of the IPCC AR5 Representative Concentration Pathway (RCP) scenario 6.0 will be shown. The Weather Research and Forecasting (WRF) model has been used as the RCM to downscale decadal time slices for ca. 2000 and ca. 2030 over North America and illustrate potential changes in regional climate that are projected by ModelE2 and WRF under RCP6.0. The analysis focuses on regional climate fields that most strongly influence the interactions between climate change and air quality. In particular, an analysis of extreme temperature and precipitation events will be presented.

The assessment of vulnerability to natural disasters in China by using the DEA method

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

Wei Yiming; Fan Ying; Lu Cong

2004-05-01

China has been greatly affected by natural disasters, so that it is of great importance to analyze the impact of natural disasters on national economy. Usually, the frequency of disasters or absolute loss inflicted by disasters is the first priority to be considered, while the capability of regions to overcome disasters is ignored. The concept of vulnerability is used to measure the capability to overcome disasters in different regions with distinctive economies. Traditional methods for vulnerability analysis calculate sub-indices based on disaster frequency, loss, the economic impact and the population of each region, and then add the sub-indices to getmore » a composite index for regional vulnerability. But those methods are sensitive to the weights selected for sub-indices when multi-indexes are added up to get an index of total vulnerability. The analytic results are less convincing because of the subjectivity of different weighting methods. A data envelopment analysis (DEA)-based model for analysis of regional vulnerability to natural disasters is presented here to improve upon the traditional method. This paper systematically describes the DEA method to evaluate the relative severity of disasters in each region. A model for regional vulnerability analysis is developed, based on the annual governmental statistics from 1989 to 2000. The regional vulnerabilities in China's mainland are illustrated as a case study, and a new method for the classification of regional vulnerability to natural disasters in China is proposed.« less

Analysis and modeling of the seasonal South China Sea temperature cycle using remote sensing

NASA Astrophysics Data System (ADS)

Twigt, Daniel J.; de Goede, Erik D.; Schrama, Ernst J. O.; Gerritsen, Herman

2007-10-01

The present paper describes the analysis and modeling of the South China Sea (SCS) temperature cycle on a seasonal scale. It investigates the possibility to model this cycle in a consistent way while not taking into account tidal forcing and associated tidal mixing and exchange. This is motivated by the possibility to significantly increase the model’s computational efficiency when neglecting tides. The goal is to develop a flexible and efficient tool for seasonal scenario analysis and to generate transport boundary forcing for local models. Given the significant spatial extent of the SCS basin and the focus on seasonal time scales, synoptic remote sensing is an ideal tool in this analysis. Remote sensing is used to assess the seasonal temperature cycle to identify the relevant driving forces and is a valuable source of input data for modeling. Model simulations are performed using a three-dimensional baroclinic-reduced depth model, driven by monthly mean sea surface anomaly boundary forcing, monthly mean lateral temperature, and salinity forcing obtained from the World Ocean Atlas 2001 climatology, six hourly meteorological forcing from the European Center for Medium range Weather Forecasting ERA-40 dataset, and remotely sensed sea surface temperature (SST) data. A sensitivity analysis of model forcing and coefficients is performed. The model results are quantitatively assessed against climatological temperature profiles using a goodness-of-fit norm. In the deep regions, the model results are in good agreement with this validation data. In the shallow regions, discrepancies are found. To improve the agreement there, we apply a SST nudging method at the free water surface. This considerably improves the model’s vertical temperature representation in the shallow regions. Based on the model validation against climatological in situ and SST data, we conclude that the seasonal temperature cycle for the deep SCS basin can be represented to a good degree. For shallow regions, the absence of tidal mixing and exchange has a clear impact on the model’s temperature representation. This effect on the large-scale temperature cycle can be compensated to a good degree by SST nudging for diagnostic applications.

Evaluation of CMIP5 Ability to Reproduce 20th Century Regional Trends in Surface Air Temperature and Precipitation over CONUS

NASA Astrophysics Data System (ADS)

Lee, J.; Waliser, D. E.; Lee, H.; Loikith, P. C.; Kunkel, K.

2017-12-01

Monitoring temporal changes in key climate variables, such as surface air temperature and precipitation, is an integral part of the ongoing efforts of the United States National Climate Assessment (NCA). Climate models participating in CMIP5 provide future trends for four different emissions scenarios. In order to have confidence in the future projections of surface air temperature and precipitation, it is crucial to evaluate the ability of CMIP5 models to reproduce observed trends for three different time periods (1895-1939, 1940-1979, and 1980-2005). Towards this goal, trends in surface air temperature and precipitation obtained from the NOAA nClimGrid 5 km gridded station observation-based product are compared during all three time periods to the 206 CMIP5 historical simulations from 48 unique GCMs and their multi-model ensemble (MME) for NCA-defined climate regions during summer (JJA) and winter (DJF). This evaluation quantitatively examines the biases of simulated trends of the spatially averaged temperature and precipitation in the NCA climate regions. The CMIP5 MME reproduces historical surface air temperature trends for JJA for all time period and all regions, except the Northern Great Plains from 1895-1939 and Southeast during 1980-2005. Likewise, for DJF, the MME reproduces historical surface air temperature trends across all time periods over all regions except the Southeast from 1895-1939 and the Midwest during 1940-1979. The Regional Climate Model Evaluation System (RCMES), an analysis tool which supports the NCA by providing access to data and tools for regional climate model validation, facilitates the comparisons between the models and observation. The RCMES Toolkit is designed to assist in the analysis of climate variables and the procedure of the evaluation of climate projection models to support the decision-making processes. This tool is used in conjunction with the above analysis and results will be presented to demonstrate its capability to access observation and model datasets, calculate evaluation metrics, and visualize the results. Several other examples of the RCMES capabilities can be found at https://rcmes.jpl.nasa.gov.

THE SOUTHWEST REGIONAL GAP PROJECT: A DATABASE MODEL FOR REGIONAL LANDSCAPE ASSESSMENT, RESOURCE PLANNING, AND VULNERABILITY ANALYSIS

EPA Science Inventory

The Gap Analysis Program (GAP) is a national interagency program that maps the distribution of plant communities and selected animal species and compares these distributions with land stewardship to identify biotic elements at potential risk of endangerment. Acquisition of primar...

AQMEII3 evaluation of regional NA/EU simulations and analysis of scale, boundary conditions and emissions error-dependence

EPA Science Inventory

Through the comparison of several regional-scale chemistry transport modelling systems that simulate meteorology and air quality over the European and American continents, this study aims at i) apportioning the error to the responsible processes using time-scale analysis, ii) hel...

Evaluating Economic Impacts of Expanded Global Wood Energy Consumption with the USFPM/GFPM Model

Treesearch

Peter J. Ince; Andrew Kramp; Kenneth E. Skog

2012-01-01

A U.S. forest sector market module was developed within the general Global Forest Products Model. The U.S. module tracks regional timber markets, timber harvests by species group, and timber product outputs in greater detail than does the global model. This hybrid approach provides detailed regional market analysis for the United States although retaining the...

Space-time modeling of timber prices

Treesearch

Mo Zhou; Joseph Buongriorno

2006-01-01

A space-time econometric model was developed for pine sawtimber timber prices of 21 geographically contiguous regions in the southern United States. The correlations between prices in neighboring regions helped predict future prices. The impulse response analysis showed that although southern pine sawtimber markets were not globally integrated, local supply and demand...

THE OHIO RIVER BASIN ENERGY FACILITY SITING MODEL. VOLUME II: SITES AND ON-LINE DATES

EPA Science Inventory

The report was prepared as part of the Ohio River Basin Energy Study (ORBES), a multidisciplinary policy research program. The siting model developed for ORBES is specifically designed for regional policy analysis. The region includes 423 counties in an area that consists of all ...

Influence of Boundary Conditions on Regional Air Quality Simulations—Analysis of AQMEII Phase 3 Results

EPA Science Inventory

Chemical boundary conditions are a key input to regional-scale photochemical models. In this study, performed during the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3), we perform annual simulations over North America with chemical boundary con...

A framework for process-based assessment of regional climate model experiments: applied to projections of southern African precipitation

NASA Astrophysics Data System (ADS)

James, Rachel; Washington, Richard; Jones, Richard

2015-04-01

There is a demand from adaptation planners for regional climate change projections, particularly the finer resolution data delivered by regional models. However, climate models are subject to important uncertainties, and their projections diverge substantially, particularly for precipitation. So how should decision makers know which futures to consider and which to disregard? Model evaluation is clearly a priority. The majority of studies seeking to assess the validity of projections are based on comparison of the models' twentieth century climatologies with observations or reanalysis. Whilst this work is very important, examination of the modelled mean state it is not sufficient to assess the credibility of modelled changes. Direct investigation of the mechanisms for change is also vital. In this study, a framework for process-based analysis of projections is presented, whereby circulation changes accompanying future responses are examined, and then compared to atmospheric dynamics during historical years in models and reanalyses. This framework has previously been applied to investigate a drying signal in West Africa, and will here be used to examine projected precipitation change in southern Africa. An ensemble of five global and regional model experiments will be employed, consisting of five perturbed versions of HadCM3 and five corresponding runs of HadRM3P (PRECIS), run over the CORDEX Africa domain. The global and regional model runs show contrasting future responses: there is a strong drying in the global models over southern Africa during the rainy season, but the regional models show drying over Madagascar and the south west Indian Ocean. Circulation changes associated with these projections will be presented as a first step towards understanding the mechanisms for change and the reasons for difference between the global and regional models. The interannual variability will also be examined and compared to reanalysis to explore how well the models represent the dipole between southern Africa and Madagascar in the twentieth century simulations. This analysis could shed light on the credibility of the projected changes, and the relative trustworthiness of the global and regional models. This research makes a valuable contribution to the understanding of mechanisms for change in southern Africa. It also has wider relevance for regional climate model studies, in highlighting the need to evaluate models on a case by case basis, and providing a framework for assessment which could be applied to other models and other regions.

Shear-lag analysis about an internally-dropped ply

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

Vizzini, A.J.

1995-12-31

The region around a terminated ply is modeled as several elastic layers separated by shear regions. A shear-lag analysis is then performed allowing for the thickness of the elastic and shear layers to vary. Boundary conditions, away for the ply drop, are based on the deflections determined by a finite element model. The interlaminar stresses are compared against those generated by the finite element model for tapered laminates under pure extension, pure bending, and extension-bending coupling. The shear-lag analysis predicts the interlaminar shear at and near the ply drop for pure extension and in cases involving bending if the deflectionsmore » due to bending are removed. The interlaminar shear stress and force equilibrium are used to determine the interlaminar normal stress. The trends in the interlaminar normal stress shown by the finite element model are partially captured by the shear-lag analysis. This simple analysis indicates that the mechanism for load transfer about a ply drop is primarily due to shear transfer through the resin rich areas.« less

Revisiting regional flood frequency analysis in Slovakia: the region-of-influence method vs. traditional regional approaches

NASA Astrophysics Data System (ADS)

Gaál, Ladislav; Kohnová, Silvia; Szolgay, Ján.

2010-05-01

During the last 10-15 years, the Slovak hydrologists and water resources managers have been devoting considerable efforts to develop statistical tools for modelling probabilities of flood occurrence in a regional context. Initially, these models followed concepts to regional flood frequency analysis that were based on fixed regions, later the Hosking and Wallis's (HW; 1997) theory was adopted and modified. Nevertheless, it turned out to be that delineating homogeneous regions using these approaches is not a straightforward task, mostly due to the complex orography of the country. In this poster we aim at revisiting flood frequency analyses so far accomplished for Slovakia by adopting one of the pooling approaches, i.e. the region-of-influence (ROI) approach (Burn, 1990). In the ROI approach, unique pooling groups of similar sites are defined for each site under study. The similarity of sites is defined through Euclidean distance in the space of site attributes that had also proved applicability in former cluster analyses: catchment area, afforested area, hydrogeological catchment index and the mean annual precipitation. The homogeneity of the proposed pooling groups is evaluated by the built-in homogeneity test by Lu and Stedinger (1992). Two alternatives of the ROI approach are examined: in the first one the target size of the pooling groups is adjusted to the target return period T of the estimated flood quantiles, while in the other one, the target size is fixed, regardless of the target T. The statistical models of the ROI approach are inter-compared by the conventional regionalization approach based on the HW methodology where the parameters of flood frequency distributions were derived by means of L-moment statistics and a regional formula for the estimation of the index flood was derived by multiple regression methods using physiographic and climatic catchment characteristics. The inter-comparison of different frequency models is evaluated by means of the root mean square error of data from Monte Carlo simulations. The analysis is based on the annual peak discharges from 168 small and mid-sized catchments from Slovakia. The study is supported by the Grant Agency of AS CR under project B300420801; the Slovak Research and Development Agency under the contract No. APVV-0443-07 and the Slovak VEGA Grant Agency under the project No. 1/0103/10. Burn, D.H., 1990: Evaluation of regional flood frequency analysis with a region of influence approach. Water Resources Research, 26(10), 2257-2265. Hosking, J.R.M., Wallis, J.R., 1997: Regional frequency analysis: an approach based on L-moments. Cambridge University Press, Cambridge. Lu, L.-H., Stedinger, J.R., 1992: Sampling variance of normalized GEV/PWM quantile estimators and a regional homogeneity test. Journal of Hydrology, 138(1-2), 223-245.

Analysis of Regional Effects on Market Segment Production

DTIC Science & Technology

2016-06-01

REGIONAL EFFECTS ON MARKET SEGMENT PRODUCTION by James D. Moffitt June 2016 Thesis Advisor: Lyn R. Whitaker Co-Advisor: Jonathan K. Alt...REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE ANALYSIS OF REGIONAL EFFECTS ON MARKET SEGMENT PRODUCTION 5. FUNDING NUMBERS 6...accessions in Potential Rating Index Zip Code Market New Evolution (PRIZM NE) market segments. This model will aid USAREC G2 analysts involved in

Application of uncertainty and sensitivity analysis to the air quality SHERPA modelling tool

NASA Astrophysics Data System (ADS)

Pisoni, E.; Albrecht, D.; Mara, T. A.; Rosati, R.; Tarantola, S.; Thunis, P.

2018-06-01

Air quality has significantly improved in Europe over the past few decades. Nonetheless we still find high concentrations in measurements mainly in specific regions or cities. This dimensional shift, from EU-wide to hot-spot exceedances, calls for a novel approach to regional air quality management (to complement EU-wide existing policies). The SHERPA (Screening for High Emission Reduction Potentials on Air quality) modelling tool was developed in this context. It provides an additional tool to be used in support to regional/local decision makers responsible for the design of air quality plans. It is therefore important to evaluate the quality of the SHERPA model, and its behavior in the face of various kinds of uncertainty. Uncertainty and sensitivity analysis techniques can be used for this purpose. They both reveal the links between assumptions and forecasts, help in-model simplification and may highlight unexpected relationships between inputs and outputs. Thus, a policy steered SHERPA module - predicting air quality improvement linked to emission reduction scenarios - was evaluated by means of (1) uncertainty analysis (UA) to quantify uncertainty in the model output, and (2) by sensitivity analysis (SA) to identify the most influential input sources of this uncertainty. The results of this study provide relevant information about the key variables driving the SHERPA output uncertainty, and advise policy-makers and modellers where to place their efforts for an improved decision-making process.

Renewable Energy Deployment in Colorado and the West: A Modeling Sensitivity and GIS Analysis

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

Barrows, Clayton; Mai, Trieu; Haase, Scott

2016-03-01

The Resource Planning Model is a capacity expansion model designed for a regional power system, such as a utility service territory, state, or balancing authority. We apply a geospatial analysis to Resource Planning Model renewable energy capacity expansion results to understand the likelihood of renewable development on various lands within Colorado.

Mapping the total electron content over Malaysia using Spherical Cap Harmonic Analysis

NASA Astrophysics Data System (ADS)

Bahari, S.; Abdullah, M.; Bouya, Z.; Musa, T. A.

2017-12-01

The ionosphere over Malaysia is unique because of her location which is in close proximity to the geomagnetic equator and is in the equatorial regions. In this region, the magnetic field is horizontally oriented from south to north and field aligned direction is in the meridional plane (ExB) which becomes the source of equatorial ionospheric anomaly occurrence such as plasma bubble, fountain effects and others. Until today, there is no model that has been developed over Malaysia to study the ionosphere. Due to that, the main objective of this paper is to develop a new technique for mapping the total electron content (TEC) from GPS measurements. Data by myRTKnet network of GPS receiver over Malaysia were used in this study. A new methodology, based on modified spherical cap harmonic analysis (SCHA), was developed to estimate diurnal vertical TEC over the region using GPS observations. The SCHA model is based on longitudinal expansion in Fourier series and fractional Legendre co-latitudinal functions over a spherical cap-like region. The TEC map with spatial resolution of 0.15 ° x 0.15 ° in latitude and longitude with the time resolution of 30 seconds are derived. TEC maps from the SCHA model were compared with the global ionospheric map and other regional models. Result shows that during low solar activity, SCHA model had a better mapping with the accuracy of less than 1 TECU compared to other regional models.

A diameter growth model for single-stem growth forms for the interior west forest inventory and analysis’s region

Treesearch

Michael T. Thompson

2015-01-01

The Interior West Forest Inventory and Analysis Unit (IWFIA) will soon transition from a regional system to a national FIA system for compiling estimates of forest growth, removals, and mortality. The national system requires regional diameter-growth models to estimate diameters on trees in situations where the initial or terminal diameter is not known at the beginning...

Dynamics analysis of the fast-slow hydro-turbine governing system with different time-scale coupling

NASA Astrophysics Data System (ADS)

Zhang, Hao; Chen, Diyi; Wu, Changzhi; Wang, Xiangyu

2018-01-01

Multi-time scales modeling of hydro-turbine governing system is crucial in precise modeling of hydropower plant and provides support for the stability analysis of the system. Considering the inertia and response time of the hydraulic servo system, the hydro-turbine governing system is transformed into the fast-slow hydro-turbine governing system. The effects of the time-scale on the dynamical behavior of the system are analyzed and the fast-slow dynamical behaviors of the system are investigated with different time-scale. Furthermore, the theoretical analysis of the stable regions is presented. The influences of the time-scale on the stable region are analyzed by simulation. The simulation results prove the correctness of the theoretical analysis. More importantly, the methods and results of this paper provide a perspective to multi-time scales modeling of hydro-turbine governing system and contribute to the optimization analysis and control of the system.

An analysis of simulated and observed storm characteristics

NASA Astrophysics Data System (ADS)

Benestad, R. E.

2010-09-01

A calculus-based cyclone identification (CCI) method has been applied to the most recent re-analysis (ERAINT) from the European Centre for Medium-range Weather Forecasts and results from regional climate model (RCM) simulations. The storm frequency for events with central pressure below a threshold value of 960-990hPa were examined, and the gradient wind from the simulated storm systems were compared with corresponding estimates from the re-analysis. The analysis also yielded estimates for the spatial extent of the storm systems, which was also included in the regional climate model cyclone evaluation. A comparison is presented between a number of RCMs and the ERAINT re-analysis in terms of their description of the gradient winds, number of cyclones, and spatial extent. Furthermore, a comparison between geostrophic wind estimated though triangules of interpolated or station measurements of SLP is presented. Wind still represents one of the more challenging variables to model realistically.

Regional Lung Ventilation Analysis Using Temporally Resolved Magnetic Resonance Imaging.

PubMed

Kolb, Christoph; Wetscherek, Andreas; Buzan, Maria Teodora; Werner, René; Rank, Christopher M; Kachelrie, Marc; Kreuter, Michael; Dinkel, Julien; Heuel, Claus Peter; Maier-Hein, Klaus

We propose a computer-aided method for regional ventilation analysis and observation of lung diseases in temporally resolved magnetic resonance imaging (4D MRI). A shape model-based segmentation and registration workflow was used to create an atlas-derived reference system in which regional tissue motion can be quantified and multimodal image data can be compared regionally. Model-based temporal registration of the lung surfaces in 4D MRI data was compared with the registration of 4D computed tomography (CT) images. A ventilation analysis was performed on 4D MR images of patients with lung fibrosis; 4D MR ventilation maps were compared with corresponding diagnostic 3D CT images of the patients and 4D CT maps of subjects without impaired lung function (serving as reference). Comparison between the computed patient-specific 4D MR regional ventilation maps and diagnostic CT images shows good correlation in conspicuous regions. Comparison to 4D CT-derived ventilation maps supports the plausibility of the 4D MR maps. Dynamic MRI-based flow-volume loops and spirograms further visualize the free-breathing behavior. The proposed methods allow for 4D MR-based regional analysis of tissue dynamics and ventilation in spontaneous breathing and comparison of patient data. The proposed atlas-based reference coordinate system provides an automated manner of annotating and comparing multimodal lung image data.

Photo- and electroproduction of K+Λ with a unitarity-restored isobar model

NASA Astrophysics Data System (ADS)

Skoupil, D.; Bydžovský, P.

2018-02-01

Exploiting the isobar model, kaon photo- and electroproduction on the proton in the resonance region comes under scrutiny. An upgrade of our previous model, comprising higher-spin nucleon and hyperon exchanges in the consistent formalism, was accomplished by implementing energy-dependent widths of nucleon resonances, which leads to a different choice of hadron form factor with much softer values of cutoff parameter for the resonant part. For a reliable description of electroproduction, the necessity of including longitudinal couplings of nucleon resonances to virtual photons was revealed. We present a new model whose free parameters were adjusted to photo- and electroproduction data and which provides a reliable overall description of experimental data in all kinematic regions. The majority of nucleon resonances chosen in this analysis coincide with those selected in our previous analysis and also in the Bayesian analysis with the Regge-plus-resonance model as the states contributing to this process with the highest probability.

Local soil effects on the Ground Motion Prediction model for the Racha region in Georgia

NASA Astrophysics Data System (ADS)

Jorjiashvili, N.; Shengelia, I.; Otinashvili, M.; Tvaliashvili, A.

2016-12-01

The Caucasus is a region of numerous natural hazards and ensuing disasters. Analysis of the losses due to past disasters indicates those most catastrophic in the region have historically been due to strong earthquakes. Estimation of expected ground motion is a fundamental earthquake hazard assessment. The most commonly used parameter for attenuation relation is the peak ground acceleration because this parameter gives useful information for Seismic Hazard Assessment that was selected for the analysis. One of the most important topics that have a significant influence on earthquake records is the site ground conditions that are the main issue of the study because the same earthquake recorded at the same distance may cause different damage according to ground conditions. In the study earthquake records were selected for the Racha region in Georgia which has the highest seismic activity in the region. Next, new GMP models are obtained based on new digital data recorded in the same area. After removing the site effect the earthquake records on the rock site were obtained. Thus, two GMP models were obtained: one for the ground surface and the other for the rock site. At the end, comparison was done for the both models in order to analyze the influence of the local soil conditions on the GMP model.

A New Trans-Disciplinary Approach to Regional Integrated Assessment of Climate Impact and Adaptation in Agricultural Systems (Invited)

NASA Astrophysics Data System (ADS)

Antle, J. M.; Valdivia, R. O.; Jones, J.; Rosenzweig, C.; Ruane, A. C.

2013-12-01

This presentation provides an overview of the new methods developed by researchers in the Agricultural Model Inter-comparison and Improvement Project (AgMIP) for regional climate impact assessment and analysis of adaptation in agricultural systems. This approach represents a departure from approaches in the literature in several dimensions. First, the approach is based on the analysis of agricultural systems (not individual crops) and is inherently trans-disciplinary: it is based on a deep collaboration among a team of climate scientists, agricultural scientists and economists to design and implement regional integrated assessments of agricultural systems. Second, in contrast to previous approaches that have imposed future climate on models based on current socio-economic conditions, this approach combines bio-physical and economic models with a new type of pathway analysis (Representative Agricultural Pathways) to parameterize models consistent with a plausible future world in which climate change would be occurring. Third, adaptation packages for the agricultural systems in a region are designed by the research team with a level of detail that is useful to decision makers, such as research administrators and donors, who are making agricultural R&D investment decisions. The approach is illustrated with examples from AgMIP's projects currently being carried out in Africa and South Asia.

Reference Models for Multi-Layer Tissue Structures

DTIC Science & Technology

2016-09-01

simulation,  finite   element  analysis 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON USAMRMC...Physiologically realistic, fully specimen-specific, nonlinear reference models. Tasks. Finite element analysis of non-linear mechanics of cadaver...models. Tasks. Finite element analysis of non-linear mechanics of multi-layer tissue regions of human subjects. Deliverables. Partially subject- and

Process for computing geometric perturbations for probabilistic analysis

DOEpatents

Fitch, Simeon H. K. [Charlottesville, VA; Riha, David S [San Antonio, TX; Thacker, Ben H [San Antonio, TX

2012-04-10

A method for computing geometric perturbations for probabilistic analysis. The probabilistic analysis is based on finite element modeling, in which uncertainties in the modeled system are represented by changes in the nominal geometry of the model, referred to as "perturbations". These changes are accomplished using displacement vectors, which are computed for each node of a region of interest and are based on mean-value coordinate calculations.

Sensitivity Analysis of QSAR Models for Assessing Novel Military Compounds

DTIC Science & Technology

2009-01-01

ER D C TR -0 9 -3 Strategic Environmental Research and Development Program Sensitivity Analysis of QSAR Models for Assessing Novel...Environmental Research and Development Program ERDC TR-09-3 January 2009 Sensitivity Analysis of QSAR Models for Assessing Novel Military Compound...Jay L. Clausen Cold Regions Research and Engineering Laboratory U.S. Army Engineer Research and Development Center 72 Lyme Road Hanover, NH

Benefits of explicit urban parameterization in regional climate modeling to study climate and city interactions

NASA Astrophysics Data System (ADS)

Daniel, M.; Lemonsu, Aude; Déqué, M.; Somot, S.; Alias, A.; Masson, V.

2018-06-01

Most climate models do not explicitly model urban areas and at best describe them as rock covers. Nonetheless, the very high resolutions reached now by the regional climate models may justify and require a more realistic parameterization of surface exchanges between urban canopy and atmosphere. To quantify the potential impact of urbanization on the regional climate, and evaluate the benefits of a detailed urban canopy model compared with a simpler approach, a sensitivity study was carried out over France at a 12-km horizontal resolution with the ALADIN-Climate regional model for 1980-2009 time period. Different descriptions of land use and urban modeling were compared, corresponding to an explicit modeling of cities with the urban canopy model TEB, a conventional and simpler approach representing urban areas as rocks, and a vegetated experiment for which cities are replaced by natural covers. A general evaluation of ALADIN-Climate was first done, that showed an overestimation of the incoming solar radiation but satisfying results in terms of precipitation and near-surface temperatures. The sensitivity analysis then highlighted that urban areas had a significant impact on modeled near-surface temperature. A further analysis on a few large French cities indicated that over the 30 years of simulation they all induced a warming effect both at daytime and nighttime with values up to + 1.5 °C for the city of Paris. The urban model also led to a regional warming extending beyond the urban areas boundaries. Finally, the comparison to temperature observations available for Paris area highlighted that the detailed urban canopy model improved the modeling of the urban heat island compared with a simpler approach.

Spatio-Temporal Simulation and Analysis of Regional Ecological Security Based on Lstm

NASA Astrophysics Data System (ADS)

Gong, C.; Qi, L.; Heming, L.; Karimian, H.; Yuqin, M.

2017-10-01

Region is a complicated system, where human, nature and society interact and influence. Quantitative modeling and simulation of ecology in the region are the key to realize the strategy of regional sustainable development. Traditional machine learning methods have made some achievements in the modeling of regional ecosystems, but it is difficult to determine the learning characteristics and to realize spatio-temporal simulation. Deep learning does not need prior identification of training characteristics, have excellent feature learning ability, can improve the accuracy of model prediction, so the use of deep learning model has a significant advantage. Therefore, we use net primary productivity (NPP), atmospheric optical depth (AOD), moderate-resolution imaging spectrometer (MODIS), Normalized Difference Vegetation Index (NDVI), landcover and population data, and use LSTM to do spatio-temporal simulation. We conduct spatial analysis and driving force analysis. The conclusions are as follows: the ecological deficit of northwestern Henan and urban communities such as Zhengzhou is higher. The reason of former lies in the weak land productivity of the Loess Plateau, the irrational crop cultivation mode. The latter lies in the high consumption of resources in the large urban agglomeration; The positive trend of Henan ecological development from 2013 is mainly due to the effective environmental protection policy in the 12th five-year plan; The main driver of the sustained ecological deficit growth of Henan in 2004-2013 is high-speed urbanization, increasing population and goods consumption. This article provides relevant basic scientific support and reference for the regional ecological scientific management and construction.

Molecular dynamics simulation of propagating cracks

NASA Technical Reports Server (NTRS)

Mullins, M.

1982-01-01

Steady state crack propagation is investigated numerically using a model consisting of 236 free atoms in two (010) planes of bcc alpha iron. The continuum region is modeled using the finite element method with 175 nodes and 288 elements. The model shows clear (010) plane fracture to the edge of the discrete region at moderate loads. Analysis of the results obtained indicates that models of this type can provide realistic simulation of steady state crack propagation.

Combining tower mixing ratio and community model data to estimate regional-scale net ecosystem carbon exchange by boundary layer inversion over four flux towers in the United States

Treesearch

Xueri Dang; Chun-Ta Lai; David Y. Hollinger; Andrew J. Schauer; Jingfeng Xiao; J. William Munger; Clenton Owensby; James R. Ehleringer

2011-01-01

We evaluated an idealized boundary layer (BL) model with simple parameterizations using vertical transport information from community model outputs (NCAR/NCEP Reanalysis and ECMWF Interim Analysis) to estimate regional-scale net CO2 fluxes from 2002 to 2007 at three forest and one grassland flux sites in the United States. The BL modeling...

Linkage and related analyses of Barrett's esophagus and its associated adenocarcinomas.

PubMed

Sun, Xiangqing; Elston, Robert; Falk, Gary W; Grady, William M; Faulx, Ashley; Mittal, Sumeet K; Canto, Marcia I; Shaheen, Nicholas J; Wang, Jean S; Iyer, Prasad G; Abrams, Julian A; Willis, Joseph E; Guda, Kishore; Markowitz, Sanford; Barnholtz-Sloan, Jill S; Chandar, Apoorva; Brock, Wendy; Chak, Amitabh

2016-07-01

Familial aggregation and segregation analysis studies have provided evidence of a genetic basis for esophageal adenocarcinoma (EAC) and its premalignant precursor, Barrett's esophagus (BE). We aim to demonstrate the utility of linkage analysis to identify the genomic regions that might contain the genetic variants that predispose individuals to this complex trait (BE and EAC). We genotyped 144 individuals in 42 multiplex pedigrees chosen from 1000 singly ascertained BE/EAC pedigrees, and performed both model-based and model-free linkage analyses, using S.A.G.E. and other software. Segregation models were fitted, from the data on both the 42 pedigrees and the 1000 pedigrees, to determine parameters for performing model-based linkage analysis. Model-based and model-free linkage analyses were conducted in two sets of pedigrees: the 42 pedigrees and a subset of 18 pedigrees with female affected members that are expected to be more genetically homogeneous. Genome-wide associations were also tested in these families. Linkage analyses on the 42 pedigrees identified several regions consistently suggestive of linkage by different linkage analysis methods on chromosomes 2q31, 12q23, and 4p14. A linkage on 15q26 is the only consistent linkage region identified in the 18 female-affected pedigrees, in which the linkage signal is higher than in the 42 pedigrees. Other tentative linkage signals are also reported. Our linkage study of BE/EAC pedigrees identified linkage regions on chromosomes 2, 4, 12, and 15, with some reported associations located within our linkage peaks. Our linkage results can help prioritize association tests to delineate the genetic determinants underlying susceptibility to BE and EAC.

A modern regional geological analysis of Venezuela - lessons from a major new world oil province on exploration in mature areas

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

Daly, M.; Audemard, F.; Valdes, G.

1993-09-01

Venezuela has produced some 44 billion bbl of oil since the early part of the century. As such, it represents one of the world's major oil producers and a mature petroleum province. However, major tracts of Venezuela's sedimentary basins remain underexplored and large discoveries are still being made in new and old reservoir systems. A regional geological analysis of Venezuela, focusing on basin evolution and sequence stratigraphy and incorporating data from the three national oil companies, is presented. The analysis presents a regionally consistent tectonostratigraphic model capable of explaining the evolution of the Mesozoic and Cenozoic basins of Venezuela andmore » placing the major reservoir facies in their regional tectonic and sequence stratigraphic context. Four regional cross sections describe the stratigraphic and structural model. The model recognizes a Jurassic rifting event and inversion, succeeded by an Early Cretaceous passive margin. In western Venezuela, the Early Cretaceous passive subsidence is enhanced locally by extension related to the Colombian active margin. Venezuela experienced a major change in the Campanian with the initial collision of the Caribbean arc, recorded by foreland structuring and widespread stratigraphic changes. From the Campanian onward, the tectonostratigraphic evolution can be modeled in terms of a progressive southeast-directed arc-continent collision and the migration of the associated foredeep and rift basins. Within the tectonic framework, the major sequence stratigraphic units are identified and the reservoir distribution interpreted. This model provides a strong predictive tool to extrapolate reservoir systems into Venezuela's underexplored areas and to readdress its traditional areas.« less

Applicability of Monte Carlo cross validation technique for model development and validation using generalised least squares regression

NASA Astrophysics Data System (ADS)

Haddad, Khaled; Rahman, Ataur; A Zaman, Mohammad; Shrestha, Surendra

2013-03-01

SummaryIn regional hydrologic regression analysis, model selection and validation are regarded as important steps. Here, the model selection is usually based on some measurements of goodness-of-fit between the model prediction and observed data. In Regional Flood Frequency Analysis (RFFA), leave-one-out (LOO) validation or a fixed percentage leave out validation (e.g., 10%) is commonly adopted to assess the predictive ability of regression-based prediction equations. This paper develops a Monte Carlo Cross Validation (MCCV) technique (which has widely been adopted in Chemometrics and Econometrics) in RFFA using Generalised Least Squares Regression (GLSR) and compares it with the most commonly adopted LOO validation approach. The study uses simulated and regional flood data from the state of New South Wales in Australia. It is found that when developing hydrologic regression models, application of the MCCV is likely to result in a more parsimonious model than the LOO. It has also been found that the MCCV can provide a more realistic estimate of a model's predictive ability when compared with the LOO.

A study of a steering system algorithm for pleasure boats based on stability analysis of a human-machine system model

NASA Astrophysics Data System (ADS)

Ikeda, Fujio; Toyama, Shigehiro; Ishiduki, Souta; Seta, Hiroaki

2016-09-01

Maritime accidents of small ships continue to increase in number. One of the major factors is poor manoeuvrability of the Manual Hydraulic Steering Mechanism (MHSM) in common use. The manoeuvrability can be improved by using the Electronic Control Steering Mechanism (ECSM). This paper conducts stability analyses of a pleasure boat controlled by human models in view of path following on a target course, in order to establish design guidelines for the ECSM. First, to analyse the stability region, the research derives the linear approximated model in a planar global coordinate system. Then, several human models are assumed to develop closed-loop human-machine controlled systems. These human models include basic proportional, derivative, integral and time-delay actions. The stability analysis simulations for those human-machine systems are carried out. The results show that the stability region tends to spread as a ship's velocity increases in the case of the basic proportional human model. The derivative action and time-delay action of human models are effective in spreading the stability region in their respective ranges of frontal gazing points.

Epistasis analysis for quantitative traits by functional regression model.

PubMed

Zhang, Futao; Boerwinkle, Eric; Xiong, Momiao

2014-06-01

The critical barrier in interaction analysis for rare variants is that most traditional statistical methods for testing interactions were originally designed for testing the interaction between common variants and are difficult to apply to rare variants because of their prohibitive computational time and poor ability. The great challenges for successful detection of interactions with next-generation sequencing (NGS) data are (1) lack of methods for interaction analysis with rare variants, (2) severe multiple testing, and (3) time-consuming computations. To meet these challenges, we shift the paradigm of interaction analysis between two loci to interaction analysis between two sets of loci or genomic regions and collectively test interactions between all possible pairs of SNPs within two genomic regions. In other words, we take a genome region as a basic unit of interaction analysis and use high-dimensional data reduction and functional data analysis techniques to develop a novel functional regression model to collectively test interactions between all possible pairs of single nucleotide polymorphisms (SNPs) within two genome regions. By intensive simulations, we demonstrate that the functional regression models for interaction analysis of the quantitative trait have the correct type 1 error rates and a much better ability to detect interactions than the current pairwise interaction analysis. The proposed method was applied to exome sequence data from the NHLBI's Exome Sequencing Project (ESP) and CHARGE-S study. We discovered 27 pairs of genes showing significant interactions after applying the Bonferroni correction (P-values < 4.58 × 10(-10)) in the ESP, and 11 were replicated in the CHARGE-S study. © 2014 Zhang et al.; Published by Cold Spring Harbor Laboratory Press.

Appendix F : finite element analysis of end region.

DOT National Transportation Integrated Search

2013-03-01

FE (finite element) modeling was conducted to 1) provide a better understanding of the : elastic behavior of the end region prior to cracking and 2) to evaluate the effects of bearing pad : stiffness and width on end region elastic stresses. The FEA ...

78 FR 29314 - Approval and Promulgation of State Implementation Plans; State of Utah; Interstate Transport of...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-20

...) SIP submissions an adequate technical analysis to support their conclusions regarding interstate... acceptable modeling technical analyses are available, but EPA does not believe that modeling is required if... regional scale technical analysis, and Utah will point to that analysis in order to conclude that there are...

A numerical analysis of high-temperature heat pipe startup from the frozen state

NASA Technical Reports Server (NTRS)

Cao, Y.; Faghri, A.

1993-01-01

Continuum and rarefied vapor flows co-exist along the heat pipe length for most of the startup period. A two-region model is proposed in which the vapor flow in the continuum region is modeled by the compressible Navier-Stokes equations, and the vapor flow in the rarefied region is simulated by a self-diffusion model. The two vapor regions are linked with appropriate boundary conditions, and heat pipe wail, wick, and vapor flow are solved as a conjugate problem. The numerical solutions for the entire heat pipe startup process from the frozen state are compared with the corresponding experimental data with good agreement.

Modeling motor connectivity using TMS/PET and structural equation modeling

PubMed Central

Laird, Angela R.; Robbins, Jacob M.; Li, Karl; Price, Larry R.; Cykowski, Matthew D.; Narayana, Shalini; Laird, Robert W.; Franklin, Crystal; Fox, Peter T.

2010-01-01

Structural equation modeling (SEM) was applied to positron emission tomographic (PET) images acquired during transcranial magnetic stimulation (TMS) of the primary motor cortex (M1hand). TMS was applied across a range of intensities, and responses both at the stimulation site and remotely connected brain regions covaried with stimulus intensity. Regions of interest (ROIs) were identified through an activation likelihood estimation (ALE) meta-analysis of TMS studies. That these ROIs represented the network engaged by motor planning and execution was confirmed by an ALE meta-analysis of finger movement studies. Rather than postulate connections in the form of an a priori model (confirmatory approach), effective connectivity models were developed using a model-generating strategy based on improving tentatively specified models. This strategy exploited the experimentally-imposed causal relations: (1) that response variations were caused by stimulation variations, (2) that stimulation was unidirectionally applied to the M1hand region, and (3) that remote effects must be caused, either directly or indirectly, by the M1hand excitation. The path model thus derived exhibited an exceptional level of goodness (χ2=22.150, df = 38, P = 0.981, TLI=1.0). The regions and connections derived were in good agreement with the known anatomy of the human and primate motor system. The model-generating SEM strategy thus proved highly effective and successfully identified a complex set of causal relationships of motor connectivity. PMID:18387823

77 FR 21896 - Approval and Promulgation of Air Quality Implementation Plans; State of Nevada; Regional Haze...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-12

... proposed approval, including specific comments on NDEP's modeling and cost analysis of the RGGS BART Determination for NO X . See Modeling for the Reid Gardner Generating Station: Visibility Impacts in Class I... independent modeling analysis to evaluate the incremental visibility improvement attributable to the NO X...

RADSS: an integration of GIS, spatial statistics, and network service for regional data mining

NASA Astrophysics Data System (ADS)

Hu, Haitang; Bao, Shuming; Lin, Hui; Zhu, Qing

2005-10-01

Regional data mining, which aims at the discovery of knowledge about spatial patterns, clusters or association between regions, has widely applications nowadays in social science, such as sociology, economics, epidemiology, crime, and so on. Many applications in the regional or other social sciences are more concerned with the spatial relationship, rather than the precise geographical location. Based on the spatial continuity rule derived from Tobler's first law of geography: observations at two sites tend to be more similar to each other if the sites are close together than if far apart, spatial statistics, as an important means for spatial data mining, allow the users to extract the interesting and useful information like spatial pattern, spatial structure, spatial association, spatial outlier and spatial interaction, from the vast amount of spatial data or non-spatial data. Therefore, by integrating with the spatial statistical methods, the geographical information systems will become more powerful in gaining further insights into the nature of spatial structure of regional system, and help the researchers to be more careful when selecting appropriate models. However, the lack of such tools holds back the application of spatial data analysis techniques and development of new methods and models (e.g., spatio-temporal models). Herein, we make an attempt to develop such an integrated software and apply it into the complex system analysis for the Poyang Lake Basin. This paper presents a framework for integrating GIS, spatial statistics and network service in regional data mining, as well as their implementation. After discussing the spatial statistics methods involved in regional complex system analysis, we introduce RADSS (Regional Analysis and Decision Support System), our new regional data mining tool, by integrating GIS, spatial statistics and network service. RADSS includes the functions of spatial data visualization, exploratory spatial data analysis, and spatial statistics. The tool also includes some fundamental spatial and non-spatial database in regional population and environment, which can be updated by external database via CD or network. Utilizing this data mining and exploratory analytical tool, the users can easily and quickly analyse the huge mount of the interrelated regional data, and better understand the spatial patterns and trends of the regional development, so as to make a credible and scientific decision. Moreover, it can be used as an educational tool for spatial data analysis and environmental studies. In this paper, we also present a case study on Poyang Lake Basin as an application of the tool and spatial data mining in complex environmental studies. At last, several concluding remarks are discussed.

Bifurcations in a discrete time model composed of Beverton-Holt function and Ricker function.

PubMed

Shang, Jin; Li, Bingtuan; Barnard, Michael R

2015-05-01

We provide rigorous analysis for a discrete-time model composed of the Ricker function and Beverton-Holt function. This model was proposed by Lewis and Li [Bull. Math. Biol. 74 (2012) 2383-2402] in the study of a population in which reproduction occurs at a discrete instant of time whereas death and competition take place continuously during the season. We show analytically that there exists a period-doubling bifurcation curve in the model. The bifurcation curve divides the parameter space into the region of stability and the region of instability. We demonstrate through numerical bifurcation diagrams that the regions of periodic cycles are intermixed with the regions of chaos. We also study the global stability of the model. Copyright © 2015 Elsevier Inc. All rights reserved.

Management Models and Cost Analysis for Regional Special Education Programs.

ERIC Educational Resources Information Center

Connors, Eugene T.

The implementation of the Education for All Handicapped Children Act (PL 94-142) has placed an enormous financial burden on local districts. In order to create special education programs that combine cost effectiveness and high quality, a regional model has been developed. The Therapeutic Residential Experience for Emotional Stability (TREES) in…

SENSITIVITY ANALYSIS AND PRELIMINARY EVALUATION OF RELMAP (REGIONAL LAGRANGIAN MODEL OF AIR POLLUTION) INVOLVING FINE AND COURSE PARTICULATE MATTER

EPA Science Inventory

In response to the new, size-discriminate federal standards for Inhalable Particulate Matter, the Regional Lagrangian Model of Air Pollution (RELMAP) has been modified to include simple, linear parameterizations. As an initial step in the possible refinement, RELMAP has been subj...

Optimizing a Drone Network to Deliver Automated External Defibrillators.

PubMed

Boutilier, Justin J; Brooks, Steven C; Janmohamed, Alyf; Byers, Adam; Buick, Jason E; Zhan, Cathy; Schoellig, Angela P; Cheskes, Sheldon; Morrison, Laurie J; Chan, Timothy C Y

2017-06-20

Public access defibrillation programs can improve survival after out-of-hospital cardiac arrest, but automated external defibrillators (AEDs) are rarely available for bystander use at the scene. Drones are an emerging technology that can deliver an AED to the scene of an out-of-hospital cardiac arrest for bystander use. We hypothesize that a drone network designed with the aid of a mathematical model combining both optimization and queuing can reduce the time to AED arrival. We applied our model to 53 702 out-of-hospital cardiac arrests that occurred in the 8 regions of the Toronto Regional RescuNET between January 1, 2006, and December 31, 2014. Our primary analysis quantified the drone network size required to deliver an AED 1, 2, or 3 minutes faster than historical median 911 response times for each region independently. A secondary analysis quantified the reduction in drone resources required if RescuNET was treated as a large coordinated region. The region-specific analysis determined that 81 bases and 100 drones would be required to deliver an AED ahead of median 911 response times by 3 minutes. In the most urban region, the 90th percentile of the AED arrival time was reduced by 6 minutes and 43 seconds relative to historical 911 response times in the region. In the most rural region, the 90th percentile was reduced by 10 minutes and 34 seconds. A single coordinated drone network across all regions required 39.5% fewer bases and 30.0% fewer drones to achieve similar AED delivery times. An optimized drone network designed with the aid of a novel mathematical model can substantially reduce the AED delivery time to an out-of-hospital cardiac arrest event. © 2017 American Heart Association, Inc.

Uncertainty analysis in 3D global models: Aerosol representation in MOZART-4

NASA Astrophysics Data System (ADS)

Gasore, J.; Prinn, R. G.

2012-12-01

The Probabilistic Collocation Method (PCM) has been proven to be an efficient general method of uncertainty analysis in atmospheric models (Tatang et al 1997, Cohen&Prinn 2011). However, its application has been mainly limited to urban- and regional-scale models and chemical source-sink models, because of the drastic increase in computational cost when the dimension of uncertain parameters increases. Moreover, the high-dimensional output of global models has to be reduced to allow a computationally reasonable number of polynomials to be generated. This dimensional reduction has been mainly achieved by grouping the model grids into a few regions based on prior knowledge and expectations; urban versus rural for instance. As the model output is used to estimate the coefficients of the polynomial chaos expansion (PCE), the arbitrariness in the regional aggregation can generate problems in estimating uncertainties. To address these issues in a complex model, we apply the probabilistic collocation method of uncertainty analysis to the aerosol representation in MOZART-4, which is a 3D global chemical transport model (Emmons et al., 2010). Thereafter, we deterministically delineate the model output surface into regions of homogeneous response using the method of Principal Component Analysis. This allows the quantification of the uncertainty associated with the dimensional reduction. Because only a bulk mass is calculated online in Mozart-4, a lognormal number distribution is assumed with a priori fixed scale and location parameters, to calculate the surface area for heterogeneous reactions involving tropospheric oxidants. We have applied the PCM to the six parameters of the lognormal number distributions of Black Carbon, Organic Carbon and Sulfate. We have carried out a Monte-Carlo sampling from the probability density functions of the six uncertain parameters, using the reduced PCE model. The global mean concentration of major tropospheric oxidants did not show a significant variation in response to the variation in input parameters. However, a substantial variation at regional and temporal scale has been found. Tatang M. A., Pan W., Prinn R G., McRae G. J., An efficient method for parametric uncertainty analysis of numerical geophysical models, J. Gephys. Res., 102, 21925-21932, 1997. Cohen, J.B., and R.G. Prinn, Development of a fast, urban chemistry metamodel for inclusion in global models,Atmos. Chem. Phys., 11, 7629-7656, doi:10.5194/acp-11-7629-2011, 2011. Emmons L. K., Walters S., Hess P. G., Lamarque J. -F., P_ster G. G., Fillmore D., Granier C., Guenther A., Kinnison D., Laepple T., Orlando J., Tie X., Tyndall G., Wiedinmyer C., Baughcum S. L., Kloster J. S., Description and evaluation of the Model for Ozone and Related chemical Tracers, version 4 (MOZART-4). Geosci. Model Dev., 3, 4367, 2010.

Updating Indiana Annual Forest Inventory and Analysis Plot Data Using Eastern Broadleaf Forest Diameter Growth Models

Treesearch

Veronica C. Lessard

2001-01-01

The Forest Inventory and Analysis (FIA) program of the North Central Research Station (NCRS), USDA Forest Service, has developed nonlinear, individual-tree, distance-independent annual diameter growth models. The models are calibrated for species groups and formulated as the product of an average diameter growth component and a modifier component. The regional models...

River catchment rainfall series analysis using additive Holt-Winters method

NASA Astrophysics Data System (ADS)

Puah, Yan Jun; Huang, Yuk Feng; Chua, Kuan Chin; Lee, Teang Shui

2016-03-01

Climate change is receiving more attention from researchers as the frequency of occurrence of severe natural disasters is getting higher. Tropical countries like Malaysia have no distinct four seasons; rainfall has become the popular parameter to assess climate change. Conventional ways that determine rainfall trends can only provide a general result in single direction for the whole study period. In this study, rainfall series were modelled using additive Holt-Winters method to examine the rainfall pattern in Langat River Basin, Malaysia. Nine homogeneous series of more than 25 years data and less than 10% missing data were selected. Goodness of fit of the forecasted models was measured. It was found that seasonal rainfall model forecasts are generally better than the monthly rainfall model forecasts. Three stations in the western region exhibited increasing trend. Rainfall in southern region showed fluctuation. Increasing trends were discovered at stations in the south-eastern region except the seasonal analysis at station 45253. Decreasing trend was found at station 2818110 in the east, while increasing trend was shown at station 44320 that represents the north-eastern region. The accuracies of both rainfall model forecasts were tested using the recorded data of years 2010-2012. Most of the forecasts are acceptable.

Interim analysis report : model deployment of a regional, multi-modal 511 traveler information system

DOT National Transportation Integrated Search

2004-02-17

This document presents the results of the analysis of baseline, or "pre-enhancement," data describing the operation of the existing 511 telephone traveler information system operated by the Arizona Department of Transportation (ADOT). The model deplo...

Analysis of time series for postal shipments in Regional VII East Java Indonesia

NASA Astrophysics Data System (ADS)

Kusrini, DE; Ulama, B. S. S.; Aridinanti, L.

2018-03-01

The change of number delivery goods through PT. Pos Regional VII East Java Indonesia indicates that the trend of increasing and decreasing the delivery of documents and non-documents in PT. Pos Regional VII East Java Indonesia is strongly influenced by conditions outside of PT. Pos Regional VII East Java Indonesia so that the prediction the number of document and non-documents requires a model that can accommodate it. Based on the time series plot monthly data fluctuations occur from 2013-2016 then the model is done using ARIMA or seasonal ARIMA and selected the best model based on the smallest AIC value. The results of data analysis about the number of shipments on each product sent through the Sub-Regional Postal Office VII East Java indicates that there are 5 post offices of 26 post offices entering the territory. The largest number of shipments is available on the PPB (Paket Pos Biasa is regular package shipment/non-document ) and SKH (Surat Kilat Khusus is Special Express Mail/document) products. The time series model generated is largely a Random walk model meaning that the number of shipment in the future is influenced by random effects that are difficult to predict. Some are AR and MA models, except for Express shipment products with Malang post office destination which has seasonal ARIMA model on lag 6 and 12. This means that the number of items in the following month is affected by the number of items in the previous 6 months.

Thermal environment analysis and energy conservation research of rural residence in cold regions of China based on BIM platform

NASA Astrophysics Data System (ADS)

Dong, J. Y.; Cheng, W.; Ma, C. P.; Xin, L. S.; Tan, Y. T.

2017-06-01

In order to study the issue of rural residential energy consumption in cold regions of China, modeled an architecture prototype based on BIM platform according to the affecting factors of rural residential thermal environment, and imported the virtual model which contains building information into energy analysis tools and chose the appropriate building orientation. By analyzing the energy consumption of the residential buildings with different enclosure structure forms, we designed the optimal energy-saving residence form. There is a certain application value of this method for researching the energy consumption and energy-saving design for the rural residence in cold regions of China.

Spatial analysis of relative humidity during ungauged periods in a mountainous region

NASA Astrophysics Data System (ADS)

Um, Myoung-Jin; Kim, Yeonjoo

2017-08-01

Although atmospheric humidity influences environmental and agricultural conditions, thereby influencing plant growth, human health, and air pollution, efforts to develop spatial maps of atmospheric humidity using statistical approaches have thus far been limited. This study therefore aims to develop statistical approaches for inferring the spatial distribution of relative humidity (RH) for a mountainous island, for which data are not uniformly available across the region. A multiple regression analysis based on various mathematical models was used to identify the optimal model for estimating monthly RH by incorporating not only temperature but also location and elevation. Based on the regression analysis, we extended the monthly RH data from weather stations to cover the ungauged periods when no RH observations were available. Then, two different types of station-based data, the observational data and the data extended via the regression model, were used to form grid-based data with a resolution of 100 m. The grid-based data that used the extended station-based data captured the increasing RH trend along an elevation gradient. Furthermore, annual RH values averaged over the regions were examined. Decreasing temporal trends were found in most cases, with magnitudes varying based on the season and region.

ADVANCEMENTS IN SOURCE-TO-DOSE ANALYSIS OF POPULATION EXPOSURES TO OZONE

EPA Science Inventory

The current study takes advantage of the observations from regional air quality monitoring networks, the data from the NE-OPS (North East Oxidant and Particulate Study) Project in the Philadelphia region, and regional photochemical air quality model predictions to obtain and co...

Estimation of the contribution of exports to the provincial economy: an analysis based on China's multi-regional input-output tables.

PubMed

Wu, Sanmang; Li, Shantong; Lei, Yalin

2016-01-01

This paper developed an estimation model for the contribution of exports to a country's regional economy based on the Chenery-Moses model and conducted an empirical analysis using China's multi-regional input-output tables for 1997, 2002, and 2007. The results indicated that China's national exports make significantly different contributions to the provincial economy in various regions, with the greatest contribution being observed in the eastern region and the smallest in the central region. The provinces are also subjected to significantly different export spillover effects. The boosting effect for the eastern provinces is primarily generated from local exports, whereas the western provinces primarily benefit from the export spillover effect from the eastern provinces. The eastern provinces, such as Guangdong, Zhejiang, Jiangsu, and Shanghai, are the primary sources of export spillover effects, and Guangdong is the largest source of export spillover effects for almost all of the provinces in China.

Regional ionospheric model for improvement of navigation position with EGNOS

NASA Astrophysics Data System (ADS)

Swiatek, Anna; Tomasik, Lukasz; Jaworski, Leszek

The problem of insufficient accuracy of EGNOS correction for the territory of Poland, located at the edge of EGNOS range is well known. The EEI PECS project (EGNOS EUPOS Integration) assumed improving the EGNOS correction by using the GPS observations from Polish ASG-EUPOS stations. A ionospheric delay parameter is a part of EGNOS correction. The comparative analysis of TEC values obtained from EGNOS and regional permanent GNSS stations showed the systematic shift. The TEC from EGNOS correction is underestimated related to computed regional TEC value. The new-‘improved’ corrections computed based on regional model were substituted for the EGNOS correction for suitable message. Dynamic measurements managed using the Mobile GPS Laboratory (MGL), showed the improvement of navigation position with TEC regional model.

Modelling probabilities of heavy precipitation by regional approaches

NASA Astrophysics Data System (ADS)

Gaal, L.; Kysely, J.

2009-09-01

Extreme precipitation events are associated with large negative consequences for human society, mainly as they may trigger floods and landslides. The recent series of flash floods in central Europe (affecting several isolated areas) on June 24-28, 2009, the worst one over several decades in the Czech Republic as to the number of persons killed and the extent of damage to buildings and infrastructure, is an example. Estimates of growth curves and design values (corresponding e.g. to 50-yr and 100-yr return periods) of precipitation amounts, together with their uncertainty, are important in hydrological modelling and other applications. The interest in high quantiles of precipitation distributions is also related to possible climate change effects, as climate model simulations tend to project increased severity of precipitation extremes in a warmer climate. The present study compares - in terms of Monte Carlo simulation experiments - several methods to modelling probabilities of precipitation extremes that make use of ‘regional approaches’: the estimation of distributions of extremes takes into account data in a ‘region’ (‘pooling group’), in which one may assume that the distributions at individual sites are identical apart from a site-specific scaling factor (the condition is referred to as ‘regional homogeneity’). In other words, all data in a region - often weighted in some way - are taken into account when estimating the probability distribution of extremes at a given site. The advantage is that sampling variations in the estimates of model parameters and high quantiles are to a large extent reduced compared to the single-site analysis. We focus on the ‘region-of-influence’ (ROI) method which is based on the identification of unique pooling groups (forming the database for the estimation) for each site under study. The similarity of sites is evaluated in terms of a set of site attributes related to the distributions of extremes. The issue of the size of the region is linked with a built-in test on regional homogeneity of data. Once a pooling group is delineated, weights based on a dissimilarity measure are assigned to individual sites involved in a pooling group, and all (weighted) data are employed in the estimation of model parameters and high quantiles at a given location. The ROI method is compared with the Hosking-Wallis (HW) regional frequency analysis, which is based on delineating fixed regions (instead of flexible pooling groups) and assigning unit weights to all sites in a region. The comparison of the performance of the individual regional models makes use of data on annual maxima of 1-day precipitation amounts at 209 stations covering the Czech Republic, with altitudes ranging from 150 to 1490 m a.s.l. We conclude that the ROI methodology is superior to the HW analysis, particularly for very high quantiles (100-yr return values). Another advantage of the ROI approach is that subjective decisions - unavoidable when fixed regions in the HW analysis are formed - may efficiently be suppressed, and almost all settings of the ROI method may be justified by results of the simulation experiments. The differences between (any) regional method and single-site analysis are very pronounced and suggest that the at-site estimation is highly unreliable. The ROI method is then applied to estimate high quantiles of precipitation amounts at individual sites. The estimates and their uncertainty are compared with those from a single-site analysis. We focus on the eastern part of the Czech Republic, i.e. an area with complex orography and a particularly pronounced role of Mediterranean cyclones in producing precipitation extremes. The design values are compared with precipitation amounts recorded during the recent heavy precipitation events, including the one associated with the flash flood on June 24, 2009. We also show that the ROI methodology may easily be transferred to the analysis of precipitation extremes in climate model outputs. It efficiently reduces (random) variations in the estimates of parameters of the extreme value distributions in individual gridboxes that result from large spatial variability of heavy precipitation, and represents a straightforward tool for ‘weighting’ data from neighbouring gridboxes within the estimation procedure. The study is supported by the Grant Agency of AS CR under project B300420801.

Effective connectivities of cortical regions for top-down face processing: A Dynamic Causal Modeling study

PubMed Central

Li, Jun; Liu, Jiangang; Liang, Jimin; Zhang, Hongchuan; Zhao, Jizheng; Rieth, Cory A.; Huber, David E.; Li, Wu; Shi, Guangming; Ai, Lin; Tian, Jie; Lee, Kang

2013-01-01

To study top-down face processing, the present study used an experimental paradigm in which participants detected non-existent faces in pure noise images. Conventional BOLD signal analysis identified three regions involved in this illusory face detection. These regions included the left orbitofrontal cortex (OFC) in addition to the right fusiform face area (FFA) and right occipital face area (OFA), both of which were previously known to be involved in both top-down and bottom-up processing of faces. We used Dynamic Causal Modeling (DCM) and Bayesian model selection to further analyze the data, revealing both intrinsic and modulatory effective connectivities among these three cortical regions. Specifically, our results support the claim that the orbitofrontal cortex plays a crucial role in the top-down processing of faces by regulating the activities of the occipital face area, and the occipital face area in turn detects the illusory face features in the visual stimuli and then provides this information to the fusiform face area for further analysis. PMID:20423709

Precipitation recycling as a mechanism for ecoclimatological stability through local and non-local interactions

NASA Astrophysics Data System (ADS)

Dominguez, Francina

This study is the first to analyze the mechanisms that drive precipitation recycling variability at the daily to intraseasonal timescale. A new Dynamic Precipitation Recycling model is developed which, unlike previous models, includes the moisture storage term in the equation of conservation of atmospheric moisture. As shown using scaling analysis, the moisture storage term is non-negligible at small time scales, so the new model enables us to analyze precipitation recycling variability at shorter timescales than traditional models. The daily to intraseasonal analysis enables us to uncover key relationships between recycling and the moisture and energy fluxes. In the second phase of this work, a spatiotemporal analysis of daily precipitation recycling is performed over two regions of North America: the Midwestern United States, and the North American Monsoon System (NAMS) region. These regions were chosen because they present contrasting land-atmosphere interactions. Different physical mechanisms drive precipitation recycling in each region. In the Midwestern United States, evapotranspiration is not significantly affected by soil moisture anomalies, and there is a high recycling ratio during periods of reduced total precipitation. The reason is that, during periods of drier atmospheric conditions, transpiration will continue to provide moisture to the overlying atmosphere and contribute to total rainfall. Consequently, precipitation recycling variability in not driven by changes in evapotranspiration. Precipitable water, sensible heat and moisture fluxes are the main drivers of recycling variability in the Midwest. However, the drier soil moisture conditions over the NAMS region limit evapotranspiration, which will drive recycling variability. In this region, evapotranspiration becomes an important contribution to precipitation after Monsoon onset when total precipitation and evapotranspiration are highest. The precipitation recycling process in the NAMS region relocates moisture from regions of high evapotranspiration like the seasonally dry tropical forests of Mexico to drier regions downwind. During long monsoons, when soil moisture is abundant for a prolonged period of time, precipitation recycling significantly contributes to precipitation during periods of reduced total rainfall. In both the moisture abundant Midwestern region and the drier NAMS region, precipitation recycling plays an important role in maintaining a favorable hydroclimatological environment for vegetation.

A regional scale modeling framework combining biogeochemical model with life cycle and economic analysis for integrated assessment of cropping systems.

PubMed

Tabatabaie, Seyed Mohammad Hossein; Bolte, John P; Murthy, Ganti S

2018-06-01

The goal of this study was to integrate a crop model, DNDC (DeNitrification-DeComposition), with life cycle assessment (LCA) and economic analysis models using a GIS-based integrated platform, ENVISION. The integrated model enables LCA practitioners to conduct integrated economic analysis and LCA on a regional scale while capturing the variability of soil emissions due to variation in regional factors during production of crops and biofuel feedstocks. In order to evaluate the integrated model, the corn-soybean cropping system in Eagle Creek Watershed, Indiana was studied and the integrated model was used to first model the soil emissions and then conduct the LCA as well as economic analysis. The results showed that the variation in soil emissions due to variation in weather is high causing some locations to be carbon sink in some years and source of CO 2 in other years. In order to test the model under different scenarios, two tillage scenarios were defined: 1) conventional tillage (CT) and 2) no tillage (NT) and analyzed with the model. The overall GHG emissions for the corn-soybean cropping system was simulated and results showed that the NT scenario resulted in lower soil GHG emissions compared to CT scenario. Moreover, global warming potential (GWP) of corn ethanol from well to pump varied between 57 and 92gCO 2 -eq./MJ while GWP under the NT system was lower than that of the CT system. The cost break-even point was calculated as $3612.5/ha in a two year corn-soybean cropping system and the results showed that under low and medium prices for corn and soybean most of the farms did not meet the break-even point. Copyright © 2017 Elsevier B.V. All rights reserved.

Nonlinear system controller design based on domain of attaction: An application to CELSS analysis and control

NASA Technical Reports Server (NTRS)

Babcock, P. S., IV

1986-01-01

Nonlinear system controller design based on the domain of attraction is presented. This is particularly suited to investigating Closed Ecological Life Support Systems (CELSS) models. In particular, the dynamic consequences of changes in the waste storage capacity and system mass, and how information is used for control in CELSS models are examined. The models' high dimensionality and nonlinear state equations make them difficult to analyze by any other technique. The domain of attraction is the region in initial conditions that tend toward an attractor and it is delineated by randomly selecting initial conditions from the region of state space being investigated. Error analysis is done by repeating the domain simulations with independent samples. A refinement of this region is the domain of performance which is the region of initial conditions meeting a performance criteria. In nonlinear systems, local stability does not insure stability over a larger region. The domain of attraction marks out this stability region; hence, it can be considered a measure of a nonlinear system's ability to recovery from state perturbations. Considering random perturbations, the minimum radius of the domain is a measure of the magnitude of perturbations for which recovery is guaranteed. Design of both linear and nonlinear controllers are shown. Three CELSS models, with 9 to 30 state variable, are presented. Measures of the domain of attraction are used to show the global behavior of these models under a variety of design and controller scenarios.

Robust network data envelopment analysis approach to evaluate the efficiency of regional electricity power networks under uncertainty.

PubMed

Fathollah Bayati, Mohsen; Sadjadi, Seyed Jafar

2017-01-01

In this paper, new Network Data Envelopment Analysis (NDEA) models are developed to evaluate the efficiency of regional electricity power networks. The primary objective of this paper is to consider perturbation in data and develop new NDEA models based on the adaptation of robust optimization methodology. Furthermore, in this paper, the efficiency of the entire networks of electricity power, involving generation, transmission and distribution stages is measured. While DEA has been widely used to evaluate the efficiency of the components of electricity power networks during the past two decades, there is no study to evaluate the efficiency of the electricity power networks as a whole. The proposed models are applied to evaluate the efficiency of 16 regional electricity power networks in Iran and the effect of data uncertainty is also investigated. The results are compared with the traditional network DEA and parametric SFA methods. Validity and verification of the proposed models are also investigated. The preliminary results indicate that the proposed models were more reliable than the traditional Network DEA model.

Robust network data envelopment analysis approach to evaluate the efficiency of regional electricity power networks under uncertainty

PubMed Central

Sadjadi, Seyed Jafar

2017-01-01

In this paper, new Network Data Envelopment Analysis (NDEA) models are developed to evaluate the efficiency of regional electricity power networks. The primary objective of this paper is to consider perturbation in data and develop new NDEA models based on the adaptation of robust optimization methodology. Furthermore, in this paper, the efficiency of the entire networks of electricity power, involving generation, transmission and distribution stages is measured. While DEA has been widely used to evaluate the efficiency of the components of electricity power networks during the past two decades, there is no study to evaluate the efficiency of the electricity power networks as a whole. The proposed models are applied to evaluate the efficiency of 16 regional electricity power networks in Iran and the effect of data uncertainty is also investigated. The results are compared with the traditional network DEA and parametric SFA methods. Validity and verification of the proposed models are also investigated. The preliminary results indicate that the proposed models were more reliable than the traditional Network DEA model. PMID:28953900

Region Spherical Harmonic Magnetic Modeling from Near-Surface and Satellite-Altitude Anomlaies

NASA Technical Reports Server (NTRS)

Kim, Hyung Rae; von Frese, Ralph R. B.; Taylor, Patrick T.

2013-01-01

The compiled near-surface data and satellite crustal magnetic measured data are modeled with a regionally concentrated spherical harmonic presentation technique over Australia and Antarctica. Global crustal magnetic anomaly studies have used a spherical harmonic analysis to represent the Earth's magnetic crustal field. This global approach, however is best applied where the data are uniformly distributed over the entire Earth. Satellite observations generally meet this requirement, but unequally distributed data cannot be easily adapted in global modeling. Even for the satellite observations, due to the errors spread over the globe, data smoothing is inevitable in the global spherical harmonic presentations. In addition, global high-resolution modeling requires a great number of global spherical harmonic coefficients for the regional presentation of crustal magnetic anomalies, whereas a lesser number of localized spherical coefficients will satisfy. We compared methods in both global and regional approaches and for a case where the errors were propagated outside the region of interest. For observations from the upcoming Swarm constellation, the regional modeling will allow the production a lesser number of spherical coefficients that are relevant to the region of interest

Semi-Automated Trajectory Analysis of Deep Ballistic Penetrating Brain Injury

PubMed Central

Folio, Les; Solomon, Jeffrey; Biassou, Nadia; Fischer, Tatjana; Dworzak, Jenny; Raymont, Vanessa; Sinaii, Ninet; Wassermann, Eric M.; Grafman, Jordan

2016-01-01

Background Penetrating head injuries (PHIs) are common in combat operations and most have visible wound paths on computed tomography (CT). Objective We assess agreement between an automated trajectory analysis-based assessment of brain injury and manual tracings of encephalomalacia on CT. Methods We analyzed 80 head CTs with ballistic PHI from the Institutional Review Board approved Vietnam head injury registry. Anatomic reports were generated from spatial coordinates of projectile entrance and terminal fragment location. These were compared to manual tracings of the regions of encephalomalacia. Dice’s similarity coefficients, kappa, sensitivities, and specificities were calculated to assess agreement. Times required for case analysis were also compared. Results Results show high specificity of anatomic regions identified on CT with semiautomated anatomical estimates and manual tracings of tissue damage. Radiologist’s and medical students’ anatomic region reports were similar (Kappa 0.8, t-test p < 0.001). Region of probable injury modeling of involved brain structures was sensitive (0.7) and specific (0.9) compared with manually traced structures. Semiautomated analysis was 9-fold faster than manual tracings. Conclusion Our region of probable injury spatial model approximates anatomical regions of encephalomalacia from ballistic PHI with time-saving over manual methods. Results show potential for automated anatomical reporting as an adjunct to current practice of radiologist/neurosurgical review of brain injury by penetrating projectiles. PMID:23707123

A new framework for estimating return levels using regional frequency analysis

NASA Astrophysics Data System (ADS)

Winter, Hugo; Bernardara, Pietro; Clegg, Georgina

2017-04-01

We propose a new framework for incorporating more spatial and temporal information into the estimation of extreme return levels. Currently, most studies use extreme value models applied to data from a single site; an approach which is inefficient statistically and leads to return level estimates that are less physically realistic. We aim to highlight the benefits that could be obtained by using methodology based upon regional frequency analysis as opposed to classic single site extreme value analysis. This motivates a shift in thinking, which permits the evaluation of local and regional effects and makes use of the wide variety of data that are now available on high temporal and spatial resolutions. The recent winter storms over the UK during the winters of 2013-14 and 2015-16, which have caused wide-ranging disruption and damaged important infrastructure, provide the main motivation for the current work. One of the most impactful natural hazards is flooding, which is often initiated by extreme precipitation. In this presentation, we focus on extreme rainfall, but shall discuss other meteorological variables alongside potentially damaging hazard combinations. To understand the risks posed by extreme precipitation, we need reliable statistical models which can be used to estimate quantities such as the T-year return level, i.e. the level which is expected to be exceeded once every T-years. Extreme value theory provides the main collection of statistical models that can be used to estimate the risks posed by extreme precipitation events. Broadly, at a single site, a statistical model is fitted to exceedances of a high threshold and the model is used to extrapolate to levels beyond the range of the observed data. However, when we have data at many sites over a spatial domain, fitting a separate model for each separate site makes little sense and it would be better if we could incorporate all this information to improve the reliability of return level estimates. Here, we use the regional frequency analysis approach to define homogeneous regions which are affected by the same storms. Extreme value models are then fitted to the data pooled from across a region. We find that this approach leads to more spatially consistent return level estimates with reduced uncertainty bounds.

Computational Tools for Probing Interactions in Multiple Linear Regression, Multilevel Modeling, and Latent Curve Analysis

ERIC Educational Resources Information Center

Preacher, Kristopher J.; Curran, Patrick J.; Bauer, Daniel J.

2006-01-01

Simple slopes, regions of significance, and confidence bands are commonly used to evaluate interactions in multiple linear regression (MLR) models, and the use of these techniques has recently been extended to multilevel or hierarchical linear modeling (HLM) and latent curve analysis (LCA). However, conducting these tests and plotting the…

Neutron lifetimes behavior analysis considering the two-region kinetic model in the IPEN/MB-01 reactor

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

Gonnelli, Eduardo; Diniz, Ricardo

2014-11-11

This is a complementary work about the behavior analysis of the neutron lifetimes that was developed in the IPEN/MB-01 nuclear reactor facility. The macroscopic neutron noise technique was experimentally employed using pulse mode detectors for two stages of control rods insertion, where a total of twenty levels of subcriticality have been carried out. It was also considered that the neutron reflector density was treated as an additional group of delayed neutrons, being a sophisticated approach in the two-region kinetic theoretical model.

Analysis of High School German Textbooks through Rasch Measurement Model

ERIC Educational Resources Information Center

Batdi, Veli; Elaldi, Senel

2016-01-01

The purpose of the present study is to analyze German teacher trainers' views on high school German textbooks through the Rasch measurement model. A survey research design was employed and study group consisted of a total of 21 teacher trainers, three from each region and selected randomly from provinces which are located in seven regions and…

SE Great Basin Play Fairway Analysis

DOE Data Explorer

Adam Brandt

2015-11-15

This submission includes a Na/K geothermometer probability greater than 200 deg C map, as well as two play fairway analysis (PFA) models. The probability map acts as a composite risk segment for the PFA models. The PFA models differ in their application of magnetotelluric conductors as composite risk segments. These PFA models map out the geothermal potential in the region of SE Great Basin, Utah.

Experiences in evaluating regional air quality models

NASA Astrophysics Data System (ADS)

Liu, Mei-Kao; Greenfield, Stanley M.

Any area of the world concerned with the health and welfare of its people and the viability of its ecological system must eventually address the question of the control of air pollution. This is true in developed countries as well as countries that are undergoing a considerable degree of industrialization. The control or limitation of the emissions of a pollutant can be very costly. To avoid ineffective or unnecessary control, the nature of the problem must be fully understood and the relationship between source emissions and ambient concentrations must be established. Mathematical models, while admittedly containing large uncertainties, can be used to examine alternatives of emission restrictions for achieving safe ambient concentrations. The focus of this paper is to summarize our experiences with modeling regional air quality in the United States and Western Europe. The following modeling experiences have been used: future SO 2 and sulfate distributions and projected acidic deposition as related to coal development in the northern Great Plains in the U.S.; analysis of regional ozone and sulfate episodes in the northeastern U.S.; analysis of the regional ozone problem in western Europe in support of alternative emission control strategies; analysis of distributions of toxic chemicals in the Southeast Ohio River Valley in support of the design of a monitoring network human exposure. Collectively, these prior modeling analyses can be invaluable in examining a similar problem in other parts of the world as well, such as the Pacific rim in Asia.

Modifications to the modular three-dimensional finite-difference ground-water flow model used for the Columbia Plateau Regional Aquifer-System Analysis, Washington, Oregon, and Idaho

USGS Publications Warehouse

Hansen, A.J.

1993-01-01

The report documents modifications to the U.S. Geological Survey's modular three-dimensional finite-difference ground-water flow model used for a regional aquifer-system analysis of the Columbia Plateau. The report, which describes the concepts and mathematical basis for the modifications, is intended for potential users who are familiar with the original modular model. The modifications permit flow from a layer to any adjacent layer, allow the model to retain a cell of a layer that has been cut completely through by a canyon, and allow placing ground-water flow barriers on only specified branch conductances; a special version of the modified model uses a convergent grid. The report describes the data-input items that this modified model must read.

Parameter dimensionality reduction of a conceptual model for streamflow prediction in Canadian, snowmelt dominated ungauged basins

NASA Astrophysics Data System (ADS)

Arsenault, Richard; Poissant, Dominique; Brissette, François

2015-11-01

This paper evaluated the effects of parametric reduction of a hydrological model on five regionalization methods and 267 catchments in the province of Quebec, Canada. The Sobol' variance-based sensitivity analysis was used to rank the model parameters by their influence on the model results and sequential parameter fixing was performed. The reduction in parameter correlations improved parameter identifiability, however this improvement was found to be minimal and was not transposed in the regionalization mode. It was shown that 11 of the HSAMI models' 23 parameters could be fixed with little or no loss in regionalization skill. The main conclusions were that (1) the conceptual lumped models used in this study did not represent physical processes sufficiently well to warrant parameter reduction for physics-based regionalization methods for the Canadian basins examined and (2) catchment descriptors did not adequately represent the relevant hydrological processes, namely snow accumulation and melt.

TRAC-PD2 posttest analysis of the CCTF Evaluation-Model Test C1-19 (Run 38). [PWR

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

Motley, F.

The results of a Transient Reactor Analysis Code posttest analysis of the Cylindral Core Test Facility Evaluation-Model Test agree very well with the results of the experiment. The good agreement obtained verifies the multidimensional analysis capability of the TRAC code. Because of the steep radial power profile, the importance of using fine noding in the core region was demonstrated (as compared with poorer results obtained from an earlier pretest prediction that used a coarsely noded model).

NASA Langley developments in response calculations needed for failure and life prediction

NASA Technical Reports Server (NTRS)

Housner, Jerrold M.

1993-01-01

NASA Langley developments in response calculations needed for failure and life predictions are discussed. Topics covered include: structural failure analysis in concurrent engineering; accuracy of independent regional modeling demonstrated on classical example; functional interface method accurately joins incompatible finite element models; interface method for insertion of local detail modeling extended to curve pressurized fuselage window panel; interface concept for joining structural regions; motivation for coupled 2D-3D analysis; compression panel with discontinuous stiffener coupled 2D-3D model and axial surface strains at the middle of the hat stiffener; use of adaptive refinement with multiple methods; adaptive mesh refinement; and studies on quantity effect of bow-type initial imperfections on reliability of stiffened panels.

A modeling analysis program for the JPL table mountain Io sodium cloud data

NASA Technical Reports Server (NTRS)

Smyth, W. H.; Goldberg, B. A.

1984-01-01

A detailed review of 110 of the 263 Region B/C images of the 1981 data set is undertaken and a preliminary assessment of 39 images of the 1976-79 data set is presented. The basic spatial characteristics of these images are discussed. Modeling analysis of these images after further data processing will provide useful information about Io and the planetary magnetosphere. Plans for data processing and modeling analysis are outlined. Results of very preliminary modeling activities are presented.

Analysis of the disturbed electric field effects in the sporadic E-layers at equatorial and low latitude regions

NASA Astrophysics Data System (ADS)

Araujo Resende, Laysa Cristina; Moro, Juliano; Denardini, Clezio Marcos; Carrasco, Alexander J.; Batista, Paulo; Chen, Sony Su; Batista, Inez S.; Andrioli, Vania Fatima

2016-07-01

In the present work we analyze the disturbed electric field effects in the sporadic E-layers at equatorial regions, Jicamarca (11.57°S, 76.52°O, I: -2°) and São Luís (2°S, 44° O, I: -2.3°), and at low latitude regions, Fortaleza (3.9°S, 38.45°O, I: -9°) and Cachoeira Paulista (22.42°S, 45°O, I: -15°). We have conducted a deep analysis to investigate these effects using a theoretical model for the ionospheric E region, called MIRE. This model is able to simulate the Es layers taking into account the E region winds and electric fields. It calculates the densities for the main molecular (NO^{+}, O_{2}^{+}, N_{2}^{+}) and metallic ions (Fe^{+}, Mg^{+}) by solving the continuity and momentum equations for each species. The main purpose of this analysis is to verify the disturbed electric fields role in the occurrence or disruption of Es layers through simulations. The analysis show that the Es layer formation and dynamics can be influenced by the prompt penetration electric fields that occur during magnetic disturbances. Therefore, the simulations present interesting results that helps to improve the understanding of Es layer behavior during the disturbed periods.

Underground Test Area Subproject Phase I Data Analysis Task. Volume VII - Tritium Transport Model Documentation Package

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

None

Volume VII of the documentation for the Phase I Data Analysis Task performed in support of the current Regional Flow Model, Transport Model, and Risk Assessment for the Nevada Test Site Underground Test Area Subproject contains the tritium transport model documentation. Because of the size and complexity of the model area, a considerable quantity of data was collected and analyzed in support of the modeling efforts. The data analysis task was consequently broken into eight subtasks, and descriptions of each subtask's activities are contained in one of the eight volumes that comprise the Phase I Data Analysis Documentation.

[Multilevel analysis of the technical efficiency of hospitals in the Spanish National Health System by property and type of management].

PubMed

Pérez-Romero, Carmen; Ortega-Díaz, M Isabel; Ocaña-Riola, Ricardo; Martín-Martín, José Jesús

2018-05-11

To analyze technical efficiency by type of property and management of general hospitals in the Spanish National Health System (2010-2012) and identify hospital and regional explanatory variables. 230 hospitals were analyzed combining data envelopment analysis and fixed effects multilevel linear models. Data envelopment analysis measured overall, technical and scale efficiency, and the analysis of explanatory factors was performed using multilevel models. The average rate of overall technical efficiency of hospitals without legal personality is lower than hospitals with legal personality (0.691 and 0.876 in 2012). There is a significant variability in efficiency under variable returns (TE) by direct, indirect and mixed forms of management. The 29% of the variability in TE es attributable to the Region. Legal personality increased the TE of the hospitals by 11.14 points. On the other hand, most of the forms of management (different to those of the traditional hospitals) increased TE in varying percentages. At regional level, according to the model considered, insularity and average annual income per household are explanatory variables of TE. Having legal personality favours technical efficiency. The regulatory and management framework of hospitals, more than public or private ownership, seem to explain technical efficiency. Regional characteristics explain the variability in TE. Copyright © 2018 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Phenolic Analysis and Theoretic Design for Chinese Commercial Wines' Authentication.

PubMed

Li, Si-Yu; Zhu, Bao-Qing; Reeves, Malcolm J; Duan, Chang-Qing

2018-01-01

To develop a robust tool for Chinese commercial wines' varietal, regional, and vintage authentication, phenolic compounds in 121 Chinese commercial dry red wines were detected and quantified by using high-performance liquid chromatography triple-quadrupole mass spectrometry (HPLC-QqQ-MS/MS), and differentiation abilities of principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were compared. Better than PCA and PLS-DA, OPLS-DA models used to differentiate wines according to their varieties (Cabernet Sauvignon or other varieties), regions (east or west Cabernet Sauvignon wines), and vintages (young or old Cabernet Sauvignon wines) were ideally established. The S-plot provided in OPLS-DA models showed the key phenolic compounds which were both statistically and biochemically significant in sample differentiation. Besides, the potential of the OPLS-DA models in deeper sample differentiating of more detailed regional and vintage information of wines was proved optimistic. On the basis of our results, a promising theoretic design for wine authentication was further proposed for the first time, which might be helpful in practical authentication of more commercial wines. The phenolic data of 121 Chinese commercial dry red wines was processed with different statistical tools for varietal, regional, and vintage differentiation. A promising theoretical design was summarized, which might be helpful for wine authentication in practical situation. © 2017 Institute of Food Technologists®.

Aerosol Source Attributions and Source-Receptor Relationships Across the Northern Hemisphere

NASA Technical Reports Server (NTRS)

Bian, Huisheng; Chin, Mian; Kucsera, Tom; Pan, Xiaohua; Darmenov, Anton; Colarco, Peter; Torres, Omar; Shults, Michael

2014-01-01

Emissions and long-range transport of air pollution pose major concerns on air quality and climate change. To better assess the impact of intercontinental transport of air pollution on regional and global air quality, ecosystems, and near-term climate change, the UN Task Force on Hemispheric Transport of Air Pollution (HTAP) is organizing a phase II activity (HTAP2) that includes global and regional model experiments and data analysis, focusing on ozone and aerosols. This study presents the initial results of HTAP2 global aerosol modeling experiments. We will (a) evaluate the model results with surface and aircraft measurements, (b) examine the relative contributions of regional emission and extra-regional source on surface PM concentrations and column aerosol optical depth (AOD) over several NH pollution and dust source regions and the Arctic, and (c) quantify the source-receptor relationships in the pollution regions that reflect the sensitivity of regional aerosol amount to the regional and extra-regional emission reductions.

Effect of Mesoscale and Multiscale Modeling on the Performance of Kevlar Woven Fabric Subjected to Ballistic Impact: A Numerical Study

NASA Astrophysics Data System (ADS)

Jia, Xin; Huang, Zhengxiang; Zu, Xudong; Gu, Xiaohui; Xiao, Qiangqiang

2013-12-01

In this study, an optimal finite element model of Kevlar woven fabric that is more computational efficient compared with existing models was developed to simulate ballistic impact onto fabric. Kevlar woven fabric was modeled to yarn level architecture by using the hybrid elements analysis (HEA), which uses solid elements in modeling the yarns at the impact region and uses shell elements in modeling the yarns away from the impact region. Three HEA configurations were constructed, in which the solid element region was set as about one, two, and three times that of the projectile's diameter with impact velocities of 30 m/s (non-perforation case) and 200 m/s (perforation case) to determine the optimal ratio between the solid element region and the shell element region. To further reduce computational time and to maintain the necessary accuracy, three multiscale models were presented also. These multiscale models combine the local region with the yarn level architecture by using the HEA approach and the global region with homogenous level architecture. The effect of the varying ratios of the local and global area on the ballistic performance of fabric was discussed. The deformation and damage mechanisms of fabric were analyzed and compared among numerical models. Simulation results indicate that the multiscale model based on HEA accurately reproduces the baseline results and obviously decreases computational time.

An innovative expression model of human health risk based on the quantitative analysis of soil metals sources contribution in different spatial scales.

PubMed

Zhang, Yimei; Li, Shuai; Wang, Fei; Chen, Zhuang; Chen, Jie; Wang, Liqun

2018-09-01

Toxicity of heavy metals from industrialization poses critical concern, and analysis of sources associated with potential human health risks is of unique significance. Assessing human health risk of pollution sources (factored health risk) concurrently in the whole and the sub region can provide more instructive information to protect specific potential victims. In this research, we establish a new expression model of human health risk based on quantitative analysis of sources contribution in different spatial scales. The larger scale grids and their spatial codes are used to initially identify the level of pollution risk, the type of pollution source and the sensitive population at high risk. The smaller scale grids and their spatial codes are used to identify the contribution of various sources of pollution to each sub region (larger grid) and to assess the health risks posed by each source for each sub region. The results of case study show that, for children (sensitive populations, taking school and residential area as major region of activity), the major pollution source is from the abandoned lead-acid battery plant (ALP), traffic emission and agricultural activity. The new models and results of this research present effective spatial information and useful model for quantifying the hazards of source categories and human health a t complex industrial system in the future. Copyright © 2018 Elsevier Ltd. All rights reserved.

Validation of the measure automobile emissions model : a statistical analysis

DOT National Transportation Integrated Search

2000-09-01

The Mobile Emissions Assessment System for Urban and Regional Evaluation (MEASURE) model provides an external validation capability for hot stabilized option; the model is one of several new modal emissions models designed to predict hot stabilized e...

Lagrangian Turbulence and Transport in Semi-Enclosed Basins and Coastal Regions

DTIC Science & Technology

2008-09-30

P.M. Poulain, R. Signell, J. Chiggiato , S. Carniel, 2008: Variational analysis of drifter positions and model outputs for the reconstruction of... Chiggiato , S. Carniel, 2008: Variational analysis of drifter positions and model outputs for the reconstruction of surface currents in the Central

A Unified Analysis of Structured Sonar-terrain Data using Bayesian Functional Mixed Models.

PubMed

Zhu, Hongxiao; Caspers, Philip; Morris, Jeffrey S; Wu, Xiaowei; Müller, Rolf

2018-01-01

Sonar emits pulses of sound and uses the reflected echoes to gain information about target objects. It offers a low cost, complementary sensing modality for small robotic platforms. While existing analytical approaches often assume independence across echoes, real sonar data can have more complicated structures due to device setup or experimental design. In this paper, we consider sonar echo data collected from multiple terrain substrates with a dual-channel sonar head. Our goals are to identify the differential sonar responses to terrains and study the effectiveness of this dual-channel design in discriminating targets. We describe a unified analytical framework that achieves these goals rigorously, simultaneously, and automatically. The analysis was done by treating the echo envelope signals as functional responses and the terrain/channel information as covariates in a functional regression setting. We adopt functional mixed models that facilitate the estimation of terrain and channel effects while capturing the complex hierarchical structure in data. This unified analytical framework incorporates both Gaussian models and robust models. We fit the models using a full Bayesian approach, which enables us to perform multiple inferential tasks under the same modeling framework, including selecting models, estimating the effects of interest, identifying significant local regions, discriminating terrain types, and describing the discriminatory power of local regions. Our analysis of the sonar-terrain data identifies time regions that reflect differential sonar responses to terrains. The discriminant analysis suggests that a multi- or dual-channel design achieves target identification performance comparable with or better than a single-channel design.

A Unified Analysis of Structured Sonar-terrain Data using Bayesian Functional Mixed Models

PubMed Central

Zhu, Hongxiao; Caspers, Philip; Morris, Jeffrey S.; Wu, Xiaowei; Müller, Rolf

2017-01-01

Sonar emits pulses of sound and uses the reflected echoes to gain information about target objects. It offers a low cost, complementary sensing modality for small robotic platforms. While existing analytical approaches often assume independence across echoes, real sonar data can have more complicated structures due to device setup or experimental design. In this paper, we consider sonar echo data collected from multiple terrain substrates with a dual-channel sonar head. Our goals are to identify the differential sonar responses to terrains and study the effectiveness of this dual-channel design in discriminating targets. We describe a unified analytical framework that achieves these goals rigorously, simultaneously, and automatically. The analysis was done by treating the echo envelope signals as functional responses and the terrain/channel information as covariates in a functional regression setting. We adopt functional mixed models that facilitate the estimation of terrain and channel effects while capturing the complex hierarchical structure in data. This unified analytical framework incorporates both Gaussian models and robust models. We fit the models using a full Bayesian approach, which enables us to perform multiple inferential tasks under the same modeling framework, including selecting models, estimating the effects of interest, identifying significant local regions, discriminating terrain types, and describing the discriminatory power of local regions. Our analysis of the sonar-terrain data identifies time regions that reflect differential sonar responses to terrains. The discriminant analysis suggests that a multi- or dual-channel design achieves target identification performance comparable with or better than a single-channel design. PMID:29749977

[The rule of lymphatic formation in rabbit VX2 supraglottic carcinoma model with lymph node metastasis].

PubMed

Zhang, Pin; Ji, Wenyue; Zhang, Xiangbo

2012-02-01

Establishment of transplanted model of VX2 supraglottic carcinoma in rabbits and investigation the rule of lymphatic vessels formation. After establishment of VX2 tumor-bearing rabbits, the carcinoma tissues were transplanted into the operculum laryngis submucosa in sixty New-Zealand white rabbits to establish transplanted tumor model. Vascular endothelial growth factor-3 (VEGFR-3) label staining was performed to observe lymphatic vessels. Number density, volume density of lymphatics periphery region of carcinoma, normal region and centre region were measured using computer image analysis system. There was no lymphatic vessels in carcinomatous centre region,but the lymphatic vessels number density, volume density in periphery region was much more than normal region. Their cavities were dilated. The discrepancy had statistical significance (P<0.01). The rule of lymphatic formation in rabbit VX2 supraglottic carcinoma model mimesis rule of lymphatic formation anthropo- supraglottic carcinoma. Lymphatic multiplication and dilation at periphery region of carcinoma is associated with lymph node metastasis. Evaluation of it at periphery region of carcinoma may be useful in predicting lymph node metastasis in patients with supraglottic carcinoma. This conclusion provides theoretical basis for utility of the anti-tumor medicines which inhibit lymphatic formation in animal model.

REGIONAL VULNERABILITY ASSESSMENT (REVA) IMPROVING ENVIRONMENTAL DECISION MAKING THROUGH CLIENT PARTNERSHIPS

EPA Science Inventory

The Regional Vulnerability Assessment (ReV A) Program is an applied research program t,1at is focusing on using spatial information and model results to support environmental decision-making at regional- down to local-scales. Re VA has developed analysis and assessment methods to...

Use of NARCCAP data to characterize regional climate uncertainty in the impact of global climate change on large river fish population: Missouri River sturgeon example

NASA Astrophysics Data System (ADS)

Anderson, C. J.; Wildhaber, M. L.; Wikle, C. K.; Moran, E. H.; Franz, K. J.; Dey, R.

2012-12-01

Climate change operates over a broad range of spatial and temporal scales. Understanding the effects of change on ecosystems requires accounting for the propagation of information and uncertainty across these scales. For example, to understand potential climate change effects on fish populations in riverine ecosystems, climate conditions predicted by course-resolution atmosphere-ocean global climate models must first be translated to the regional climate scale. In turn, this regional information is used to force watershed models, which are used to force river condition models, which impact the population response. A critical challenge in such a multiscale modeling environment is to quantify sources of uncertainty given the highly nonlinear nature of interactions between climate variables and the individual organism. We use a hierarchical modeling approach for accommodating uncertainty in multiscale ecological impact studies. This framework allows for uncertainty due to system models, model parameter settings, and stochastic parameterizations. This approach is a hybrid between physical (deterministic) downscaling and statistical downscaling, recognizing that there is uncertainty in both. We use NARCCAP data to determine confidence the capability of climate models to simulate relevant processes and to quantify regional climate variability within the context of the hierarchical model of uncertainty quantification. By confidence, we mean the ability of the regional climate model to replicate observed mechanisms. We use the NCEP-driven simulations for this analysis. This provides a base from which regional change can be categorized as either a modification of previously observed mechanisms or emergence of new processes. The management implications for these categories of change are significantly different in that procedures to address impacts from existing processes may already be known and need adjustment; whereas, an emergent processes may require new management strategies. The results from hierarchical analysis of uncertainty are used to study the relative change in weights of the endangered Missouri River pallid sturgeon (Scaphirhynchus albus) under a 21st century climate scenario.

Developing a high-resolution regional atmospheric reanalysis for Australia

NASA Astrophysics Data System (ADS)

White, Christopher; Fox-Hughes, Paul; Su, Chun-Hsu; Jakob, Dörte; Kociuba, Greg; Eisenberg, Nathan; Steinle, Peter; Harris, Rebecca; Corney, Stuart; Love, Peter; Remenyi, Tomas; Chladil, Mark; Bally, John; Bindoff, Nathan

2017-04-01

A dynamically consistent, long-term atmospheric reanalysis can be used to support high-quality assessments of environmental risk and likelihood of extreme events. Most reanalyses are presently based on coarse-scale global systems that are not suitable for regional assessments in fire risk, water and natural resources, amongst others. The Australian Bureau of Meteorology is currently working to close this gap by producing a high-resolution reanalysis over the Australian and New Zealand region to construct a sequence of atmospheric conditions at sub-hourly intervals over the past 25 years from 1990. The Australia reanalysis consists of a convective-scale analysis nested within a 12 km regional-scale reanalysis, which is bounded by a coarse-scale ERA-Interim reanalysis that provides the required boundary and initial conditions. We use an unchanging atmospheric modelling suite based on the UERRA system used at the UK Met Office and the more recent version of the Bureau of Meteorology's operational numerical prediction model used in ACCESS-R (Australian Community Climate and Earth-System Simulator-Regional system). An advanced (4-dimensional variational) data assimilation scheme is used to optimally combine model physics with multiple observations from aircrafts, sondes, surface observations and satellites to create a best estimate of state of the atmosphere over a 6-hour moving window. This analysis is in turn used to drive a higher-resolution (1.5 km) downscaling model over selected subdomains within Australia, currently eastern New South Wales and Tasmania, with the capability to support this anywhere in the Australia-New Zealand domain. The temporal resolution of the gridded analysis fields for both the regional and higher-resolution subdomains are generally one hour, with many fields such as 10 m winds and 2 m temperatures available every 10 minutes. The reanalysis also produces many other variables that include wind, temperature, moisture, pressure, cloud cover, precipitation, evaporation, soil water, and energy fluxes. In this presentation, we report on the implementation of the Australia regional reanalysis and results from first stages of the project, with a focus on the Tasmanian subdomain. An initial benchmarking 1.5 km data set - referred to as the 'Initial Analysis' - has been constructed over the subdomains consisting of regridded and harmonised analysis and short-term forecast fields from the operational ACCESS-C model using the past 5 years (2011-2015) of archived data. Evaluation of the Initial Analysis against surface observations from automatic weather stations indicate changes in model skills over time that may be attributed to changes in NWP and assimilation systems, and model cycling frequency. Preliminary evaluations of the reanalysis across Tasmania and its inter-comparisons with the Initial Analysis and the ERA-Interim reanalysis products will be presented, including some features across the Tasmanian subdomain such as means and extremes of analysed weather variables. Finally, we describe a number of applications across Tasmania of the reanalysis of immediate interest to meteorologists, fire and landscape managers and other members of the emergency management community, including the use of the data to create post-processed fields such as soil dryness, tornados and fire danger indices for forest fire danger risk assessment, including a climatology of Continuous Haines Index.

Two-step sensitivity testing of parametrized and regionalized life cycle assessments: methodology and case study.

PubMed

Mutel, Christopher L; de Baan, Laura; Hellweg, Stefanie

2013-06-04

Comprehensive sensitivity analysis is a significant tool to interpret and improve life cycle assessment (LCA) models, but is rarely performed. Sensitivity analysis will increase in importance as inventory databases become regionalized, increasing the number of system parameters, and parametrized, adding complexity through variables and nonlinear formulas. We propose and implement a new two-step approach to sensitivity analysis. First, we identify parameters with high global sensitivities for further examination and analysis with a screening step, the method of elementary effects. Second, the more computationally intensive contribution to variance test is used to quantify the relative importance of these parameters. The two-step sensitivity test is illustrated on a regionalized, nonlinear case study of the biodiversity impacts from land use of cocoa production, including a worldwide cocoa products trade model. Our simplified trade model can be used for transformable commodities where one is assessing market shares that vary over time. In the case study, the highly uncertain characterization factors for the Ivory Coast and Ghana contributed more than 50% of variance for almost all countries and years examined. The two-step sensitivity test allows for the interpretation, understanding, and improvement of large, complex, and nonlinear LCA systems.

Anomalous Structure of Oceanic Lithosphere in the North Atlantic and Arctic Oceans: A Preliminary Analysis Based on Bathymetry, Gravity and Crustal Structure

NASA Astrophysics Data System (ADS)

Barantsrva, O.

2014-12-01

We present a preliminary analysis of the crustal and upper mantle structure for off-shore regions in the North Atlantic and Arctic oceans. These regions have anomalous oceanic lithosphere: the upper mantle of the North Atlantic ocean is affected by the Iceland plume, while the Arctic ocean has some of the slowest spreading rates. Our specific goal is to constrain the density structure of the upper mantle in order to understand the links between the deep lithosphere dynamics, ocean spreading, ocean floor bathymetry, heat flow and structure of the oceanic lithosphere in the regions where classical models of evolution of the oceanic lithosphere may not be valid. The major focus is on the oceanic lithosphere, but the Arctic shelves with a sufficient data coverage are also included into the analysis. Out major interest is the density structure of the upper mantle, and the analysis is based on the interpretation of GOCE satellite gravity data. To separate gravity anomalies caused by subcrustal anomalous masses, the gravitational effect of water, crust and the deep mantle is removed from the observed gravity field. For bathymetry we use the global NOAA database ETOPO1. The crustal correction to gravity is based on two crustal models: (1) global model CRUST1.0 (Laske, 2013) and, for a comparison, (2) a regional seismic model EUNAseis (Artemieva and Thybo, 2013). The crustal density structure required for the crustal correction is constrained from Vp data. Previous studies have shown that a large range of density values corresponds to any Vp value. To overcome this problem and to reduce uncertainty associated with the velocity-density conversion, we account for regional tectonic variations in the Northern Atlantics as constrained by numerous published seismic profiles and potential-field models across the Norwegian off-shore crust (e.g. Breivik et al., 2005, 2007), and apply different Vp-density conversions for different parts of the region. We present preliminary results, which we use to examine factors that control variations in bathymetry, sedimentary and crustal thicknesses in these anomalous oceanic domains.

Satellite Sounder Data Assimilation for Improving Alaska Region Weather Forecast

NASA Technical Reports Server (NTRS)

Zhu, Jiang; Stevens, E.; Zavodsky, B. T.; Zhang, X.; Heinrichs, T.; Broderson, D.

2014-01-01

Data assimilation has been demonstrated very useful in improving both global and regional numerical weather prediction. Alaska has very coarser surface observation sites. On the other hand, it gets much more satellite overpass than lower 48 states. How to utilize satellite data to improve numerical prediction is one of hot topics among weather forecast community in Alaska. The Geographic Information Network of Alaska (GINA) at University of Alaska is conducting study on satellite data assimilation for WRF model. AIRS/CRIS sounder profile data are used to assimilate the initial condition for the customized regional WRF model (GINA-WRF model). Normalized standard deviation, RMSE, and correlation statistic analysis methods are applied to analyze one case of 48 hours forecasts and one month of 24-hour forecasts in order to evaluate the improvement of regional numerical model from Data assimilation. The final goal of the research is to provide improved real-time short-time forecast for Alaska regions.

Inventory and comparative evaluation of seabed mapping, classification and modeling activities in the Northwest Atlantic, USA to support regional ocean planning

NASA Astrophysics Data System (ADS)

Shumchenia, Emily J.; Guarinello, Marisa L.; Carey, Drew A.; Lipsky, Andrew; Greene, Jennifer; Mayer, Larry; Nixon, Matthew E.; Weber, John

2015-06-01

Efforts are in motion globally to address coastal and marine management needs through spatial planning and concomitant seabed habitat mapping. Contrasting strategies are often evident in these processes among local, regional, national and international scientific approaches and policy needs. In answer to such contrasts among its member states, the United States Northeast Regional Ocean Council formed a Habitat Working Group to conduct a regional inventory and comparative evaluation of seabed characterization, classification, and modeling activities in New England. The goals of this effort were to advance regional understanding of ocean habitats and identify opportunities for collaboration. Working closely with the Habitat Working Group, we organized and led the inventory and comparative analysis with a focus on providing processes and tools that can be used by scientists and managers, updated and adapted for future use, and applied in other ocean management regions throughout the world. Visual schematics were a critical component of the comparative analysis and aided discussion among scientists and managers. Regional consensus was reached on a common habitat classification scheme (U.S. Coastal and Marine Ecological Classification Standard) for regional seabed maps. Results and schematics were presented at a region-wide workshop where further steps were taken to initiate collaboration among projects. The workshop culminated in an agreement on a set of future seabed mapping goals for the region. The work presented here may serve as an example to other ocean planning regions in the U.S., Europe or elsewhere seeking to integrate a variety of seabed characterization, classification and modeling activities.

Diagnostic evaluation of distributed physically based model at the REW scale (THREW) using rainfall-runoff event analysis

NASA Astrophysics Data System (ADS)

Tian, F.; Sivapalan, M.; Li, H.; Hu, H.

2007-12-01

The importance of diagnostic analysis of hydrological models is increasingly recognized by the scientific community (M. Sivapalan, et al., 2003; H. V. Gupta, et al., 2007). Model diagnosis refers to model structures and parameters being identified not only by statistical comparison of system state variables and outputs but also by process understanding in a specific watershed. Process understanding can be gained by the analysis of observational data and model results at the specific watershed as well as through regionalization. Although remote sensing technology can provide valuable data about the inputs, state variables, and outputs of the hydrological system, observational rainfall-runoff data still constitute the most accurate, reliable, direct, and thus a basic component of hydrology related database. One critical question in model diagnostic analysis is, therefore, what signature characteristic can we extract from rainfall and runoff data. To this date only a few studies have focused on this question, such as Merz et al. (2006) and Lana-Renault et al. (2007), still none of these studies related event analysis with model diagnosis in an explicit, rigorous, and systematic manner. Our work focuses on the identification of the dominant runoff generation mechanisms from event analysis of rainfall-runoff data, including correlation analysis and analysis of timing pattern. The correlation analysis involves the identification of the complex relationship among rainfall depth, intensity, runoff coefficient, and antecedent conditions, and the timing pattern analysis aims to identify the clustering pattern of runoff events in relation to the patterns of rainfall events. Our diagnostic analysis illustrates the changing pattern of runoff generation mechanisms in the DMIP2 test watersheds located in Oklahoma region, which is also well recognized by numerical simulations based on TsingHua Representative Elementary Watershed (THREW) model. The result suggests the usefulness of rainfall-runoff event analysis for model development as well as model diagnostics.

Symmetry analysis for hyperbolic equilibria using a TB/dengue fever model

NASA Astrophysics Data System (ADS)

Massoukou, R. Y. M.'Pika; Govinder, K. S.

2016-08-01

We investigate the interplay between Lie symmetry analysis and dynamical systems analysis. As an example, we take a toy model describing the spread of TB and dengue fever. We first undertake a comprehensive dynamical systems analysis including a discussion about local stability. For those regions in which such analyzes cannot be translated to global behavior, we undertake a Lie symmetry analysis. It is shown that the Lie analysis can be useful in providing information for systems where the (local) dynamical systems analysis breaks down.

Multi-region statistical shape model for cochlear implantation

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

The analysis of GEOS-3 altimeter data in the Tasman and Coral seas

NASA Technical Reports Server (NTRS)

Mather, R. S.

1977-01-01

A technique was developed for preprocessing GEOS-3 altimetry data to establish a model of the regional sea surface. The algorithms developed models for a 35,000,000 sq km area with an internal precision of + or - 1 m. There were discrepancies between the sea surface model so obtained and GEM6 based geoid profiles with wavelengths of approximately 2500 km and amplitudes of up to 5 m in this region. The amplitudes were smaller when compared with GEM10-based geoid determinations. However, the comparison of 14 pairs of overlapping passes in the region indicated altimeter resolution of the + or - 25 cm level if the wavelength corresponding to the Nyquist frequency were 30 km. The spectral analysis of such comparisons indicated the existence of significant signal strength in the discrepancies after least squares fitting, with wavelengths in excess of 200 km.

Modeling seasonal leptospirosis transmission and its association with rainfall and temperature in Thailand using time-series and ARIMAX analyses.

PubMed

Chadsuthi, Sudarat; Modchang, Charin; Lenbury, Yongwimon; Iamsirithaworn, Sopon; Triampo, Wannapong

2012-07-01

To study the number of leptospirosis cases in relations to the seasonal pattern, and its association with climate factors. Time series analysis was used to study the time variations in the number of leptospirosis cases. The Autoregressive Integrated Moving Average (ARIMA) model was used in data curve fitting and predicting the next leptospirosis cases. We found that the amount of rainfall was correlated to leptospirosis cases in both regions of interest, namely the northern and northeastern region of Thailand, while the temperature played a role in the northeastern region only. The use of multivariate ARIMA (ARIMAX) model showed that factoring in rainfall (with an 8 months lag) yields the best model for the northern region while the model, which factors in rainfall (with a 10 months lag) and temperature (with an 8 months lag) was the best for the northeastern region. The models are able to show the trend in leptospirosis cases and closely fit the recorded data in both regions. The models can also be used to predict the next seasonal peak quite accurately. Copyright © 2012 Hainan Medical College. Published by Elsevier B.V. All rights reserved.

An Experimental and Numerical Comparison of the Rupture Locations of an Abdominal Aortic Aneurysm

PubMed Central

Doyle, Barry J.; Corbett, Timothy J.; Callanan, Anthony; Walsh, Michael T.; Vorp, David A.; McGloughlin, Timothy M.

2009-01-01

Purpose: To identify the rupture locations of idealized physical models of abdominal aortic aneurysm (AAA) using an in-vitro setup and to compare the findings to those predicted numerically. Methods: Five idealized AAAs were manufactured using Sylgard 184 silicone rubber, which had been mechanically characterized from tensile tests, tear tests, and finite element analysis. The models were then inflated to the point of rupture and recorded using a high-speed camera. Numerical modeling attempted to confirm these rupture locations. Regional variations in wall thickness of the silicone models was also quantified and applied to numerical models. Results: Four of the 5 models tested ruptured at inflection points in the proximal and distal regions of the aneurysm sac and not at regions of maximum diameter. These findings agree with high stress regions computed numerically. Wall stress appears to be independent of wall thickness, with high stress occurring at regions of inflection regardless of wall thickness variations. Conclusion: According to these experimental and numerical findings, AAAs experience higher stresses at regions of inflection compared to regions of maximum diameter. Ruptures of the idealized silicone models occurred predominantly at the inflection points, as numerically predicted. Regions of inflection can be easily identified from basic 3-dimensional reconstruction; as ruptures appear to occur at inflection points, these findings may provide a useful insight into the clinical significance of inflection regions. This approach will be applied to patient-specific models in a future study. PMID:19642790

Cluster analysis applied to localized dispersion curves in East Asia: the limits of surface wave resolution

NASA Astrophysics Data System (ADS)

Witek, M.; van der Lee, S.; Kang, T. S.; Chang, S. J.; Ning, J.; Ning, S.

2017-12-01

We have measured Rayleigh wave group velocity dispersion curves from one year of station-pair cross-correlations of continuous vertical-component broadband data from 1082 seismic stations in regional networks across China, Korea, Taiwan, and Japan for the year 2011. We use the measurements to map local dispersion anomalies for periods in the range 6-40 s. We combined our ambient noise data set with the earthquake group velocity data set of Ma et al. (2014), and then applied agglomerative hierarchical clustering to the localized dispersion curves. We find that the dispersion curves naturally organize themselves into distinct tectonic regions. For our distribution of interstation distances, only 8 distinct regions need to be defined. Additional clusters reduce the overall data misfit by increasingly smaller amounts. The size and number of clusters needed to suitably predict the data may give an indication of the resolving power of the data set. The regions that emerge from the cluster analysis include Tibet, the Sea of Japan, the South China Block and the Korean peninsula, the Ordos and Yangtze cratons, and Mesozoic rift basins such as the Songliao, Bohai Bay and Ulleung basins. We also performed a traditional inversion for 3D S-velocity structure, and the resulting model fits the data as well as the 8-cluster model, while both models fit the earthquake data and ambient noise data better than the LITHO1.0 model of Pasyanos et al. (2014). Our 3D model of the crust and upper mantle confirms many of the features seen in previous studies of the region, most notably the lithospheric thinning going from west to east and low velocity zones in the crust on the Tibetan periphery. We conclude that cluster analysis is able to greatly reduce the dimensionality of surface wave dispersion data, in the sense that a data set of over half a million dispersion curves is sufficiently predicted by appropriately averaging over a relatively small set of distinct tectonic regions. The resulting clustered model objectively quantifies the more intuitive ways in which we usually tend to interpret tomographic models.

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

PubMed

Choi, Hyungyun; Kim, Ho

2017-01-01

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

[Effect of near infrared spectrum on the precision of PLS model for oil yield from oil shale].

PubMed

Wang, Zhi-Hong; Liu, Jie; Chen, Xiao-Chao; Sun, Yu-Yang; Yu, Yang; Lin, Jun

2012-10-01

It is impossible to use present measurement methods for the oil yield of oil shale to realize in-situ detection and these methods unable to meet the requirements of the oil shale resources exploration and exploitation. But in-situ oil yield analysis of oil shale can be achieved by the portable near infrared spectroscopy technique. There are different correlativities of NIR spectrum data formats and contents of sample components, and the different absorption specialities of sample components shows in different NIR spectral regions. So with the proportioning samples, the PLS modeling experiments were done by 3 formats (reflectance, absorbance and K-M function) and 4 regions of modeling spectrum, and the effect of NIR spectral format and region to the precision of PLS model for oil yield from oil shale was studied. The results show that the best data format is reflectance and the best modeling region is combination spectral range by PLS model method and proportioning samples. Therefore, the appropriate data format and the proper characteristic spectral region can increase the precision of PLS model for oil yield form oil shale.

Automated antibody structure prediction using Accelrys tools: Results and best practices

PubMed Central

Fasnacht, Marc; Butenhof, Ken; Goupil-Lamy, Anne; Hernandez-Guzman, Francisco; Huang, Hongwei; Yan, Lisa

2014-01-01

We describe the methodology and results from our participation in the second Antibody Modeling Assessment experiment. During the experiment we predicted the structure of eleven unpublished antibody Fv fragments. Our prediction methods centered on template-based modeling; potential templates were selected from an antibody database based on their sequence similarity to the target in the framework regions. Depending on the quality of the templates, we constructed models of the antibody framework regions either using a single, chimeric or multiple template approach. The hypervariable loop regions in the initial models were rebuilt by grafting the corresponding regions from suitable templates onto the model. For the H3 loop region, we further refined models using ab initio methods. The final models were subjected to constrained energy minimization to resolve severe local structural problems. The analysis of the models submitted show that Accelrys tools allow for the construction of quite accurate models for the framework and the canonical CDR regions, with RMSDs to the X-ray structure on average below 1 Å for most of these regions. The results show that accurate prediction of the H3 hypervariable loops remains a challenge. Furthermore, model quality assessment of the submitted models show that the models are of quite high quality, with local geometry assessment scores similar to that of the target X-ray structures. Proteins 2014; 82:1583–1598. © 2014 The Authors. Proteins published by Wiley Periodicals, Inc. PMID:24833271

Machine learning algorithms for modeling groundwater level changes in agricultural regions of the U.S.

DOE PAGES

Sahoo, S.; Russo, T. A.; Elliott, J.; ...

2017-05-13

Climate, groundwater extraction, and surface water flows have complex nonlinear relationships with groundwater level in agricultural regions. To better understand the relative importance of each driver and predict groundwater level change, we develop a new ensemble modeling framework based on spectral analysis, machine learning, and uncertainty analysis, as an alternative to complex and computationally expensive physical models. We apply and evaluate this new approach in the context of two aquifer systems supporting agricultural production in the United States: the High Plains aquifer (HPA) and the Mississippi River Valley alluvial aquifer (MRVA). We select input data sets by using a combinationmore » of mutual information, genetic algorithms, and lag analysis, and then use the selected data sets in a Multilayer Perceptron network architecture to simulate seasonal groundwater level change. As expected, model results suggest that irrigation demand has the highest influence on groundwater level change for a majority of the wells. The subset of groundwater observations not used in model training or cross-validation correlates strongly (R > 0.8) with model results for 88 and 83% of the wells in the HPA and MRVA, respectively. In both aquifer systems, the error in the modeled cumulative groundwater level change during testing (2003-2012) was less than 2 m over a majority of the area. Here, we conclude that our modeling framework can serve as an alternative approach to simulating groundwater level change and water availability, especially in regions where subsurface properties are unknown.« less

Machine learning algorithms for modeling groundwater level changes in agricultural regions of the U.S.

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

Sahoo, S.; Russo, T. A.; Elliott, J.

Climate, groundwater extraction, and surface water flows have complex nonlinear relationships with groundwater level in agricultural regions. To better understand the relative importance of each driver and predict groundwater level change, we develop a new ensemble modeling framework based on spectral analysis, machine learning, and uncertainty analysis, as an alternative to complex and computationally expensive physical models. We apply and evaluate this new approach in the context of two aquifer systems supporting agricultural production in the United States: the High Plains aquifer (HPA) and the Mississippi River Valley alluvial aquifer (MRVA). We select input data sets by using a combinationmore » of mutual information, genetic algorithms, and lag analysis, and then use the selected data sets in a Multilayer Perceptron network architecture to simulate seasonal groundwater level change. As expected, model results suggest that irrigation demand has the highest influence on groundwater level change for a majority of the wells. The subset of groundwater observations not used in model training or cross-validation correlates strongly (R > 0.8) with model results for 88 and 83% of the wells in the HPA and MRVA, respectively. In both aquifer systems, the error in the modeled cumulative groundwater level change during testing (2003-2012) was less than 2 m over a majority of the area. Here, we conclude that our modeling framework can serve as an alternative approach to simulating groundwater level change and water availability, especially in regions where subsurface properties are unknown.« less

Evaluation of the Analysis Influence on Transport in Reanalysis Regional Water Cycles

NASA Technical Reports Server (NTRS)

Bosilovich, M. G.; Chen, J.; Robertson, F. R.

2011-01-01

Regional water cycles of reanalyses do not follow theoretical assumptions applicable to pure simulated budgets. The data analysis changes the wind, temperature and moisture, perturbing the theoretical balance. Of course, the analysis is correcting the model forecast error, so that the state fields should be more aligned with observations. Recently, it has been reported that the moisture convergence over continental regions, even those with significant quantities of radiosonde profiles present, can produce long term values not consistent with theoretical bounds. Specifically, long averages over continents produce some regions of moisture divergence. This implies that the observational analysis leads to a source of water in the region. One such region is the Unite States Great Plains, which many radiosonde and lidar wind observations are assimilated. We will utilize a new ancillary data set from the MERRA reanalysis called the Gridded Innovations and Observations (GIO) which provides the assimilated observations on MERRA's native grid allowing more thorough consideration of their impact on regional and global climatology. Included with the GIO data are the observation minus forecast (OmF) and observation minus analysis (OmA). Using OmF and OmA, we can identify the bias of the analysis against each observing system and gain a better understanding of the observations that are controlling the regional analysis. In this study we will focus on the wind and moisture assimilation.

The Third Phase of AQMEII: Evaluation Strategy and Multi-Model Performance Analysis

EPA Science Inventory

AQMEII (Air Quality Model Evaluation International Initiative) is an extraordinary effort promoting policy-relevant research on regional air quality model evaluation across the European and North American atmospheric modelling communities, providing the ideal platform for advanci...

Spatial Microsimulation for Rural Policy Analysis in Ireland: The Implications of CAP Reforms for the National Spatial Strategy

ERIC Educational Resources Information Center

Ballas, D.; Clarke, G. P.; Wiemers, E.

2006-01-01

Microsimulation attempts to describe economic and social events by modelling the behaviour of individual agents. These models have proved useful in evaluating the impact of policy changes at the micro level. Spatial microsimulation models contain geographic information and allow for a regional or local approach to policy analysis. This paper…

Analysis of Title IIB Mathematics and Science Partnerships in the Northwest Region. Issues & Answers. REL 2007-No. 008

ERIC Educational Resources Information Center

Gummer, Edith; Stepanek, Jennifer

2007-01-01

This report describes the first year of the funded professional development activities in the Title IIB Math and Science Partnership (MSP) projects in the Northwest Region and the evaluation models. The analysis is structured around the factors of professional development associated with changes in teacher knowledge and practice. This study is…

Tube Bulge Process : Theoretical Analysis and Finite Element Simulations

NASA Astrophysics Data System (ADS)

Velasco, Raphael; Boudeau, Nathalie

2007-05-01

This paper is focused on the determination of mechanics characteristics for tubular materials, using tube bulge process. A comparative study is made between two different models: theoretical model and finite element analysis. The theoretical model is completely developed, based first on a geometrical analysis of the tube profile during bulging, which is assumed to strain in arc of circles. Strain and stress analysis complete the theoretical model, which allows to evaluate tube thickness and state of stress, at any point of the free bulge region. Free bulging of a 304L stainless steel is simulated using Ls-Dyna 970. To validate FE simulations approach, a comparison between theoretical and finite elements models is led on several parameters such as: thickness variation at the free bulge region pole with bulge height, tube thickness variation with z axial coordinate, and von Mises stress variation with plastic strain. Finally, the influence of geometrical parameters deviations on flow stress curve is observed using analytical model: deviations of the tube outer diameter, its initial thickness and the bulge height measurement are taken into account to obtain a resulting error on plastic strain and von Mises stress.

From ecological test site to geographic information system: lessons for the 1980's

USGS Publications Warehouse

Alexander, Robert H.

1981-01-01

Geographic information systems were common elements in two kinds of interdisciplinary regional demonstration projects in the 1970's. Ecological test sits attempted to provide for more efficient remote-sensing data delivery for regional environmental management. Regional environmental systems analysis attempted to formally describe and model the interacting regional social and environmental processes, including the resource-use decision making process. Lessons for the 1980's are drawn from recent evaluations and assessments of these programs, focusing on cost, rates of system development and technology transfer, program coordination, integrative analysis capability, and the involvement of system users and decision makers.

Turbulence modeling and surface heat transfer in a stagnation flow region

NASA Technical Reports Server (NTRS)

Wang, C. R.; Yeh, F. C.

1987-01-01

Analysis for the turbulent flow field and the effect of freestream turbulence on the surface heat transfer rate of a stagnation flow is presented. The emphasis is on modeling and its augmentation of surface heat transfer rate. The flow field considered is the region near the forward stagnation point of a circular cylinder in a uniform turbulent mean flow.

Software for calculating vegetation disturbance and recovery by using the equivalent clearcut area model.

Treesearch

Alan A. Ager; Caty Clifton

2005-01-01

The use of cumulative watershed effects models is mandated as part of interagency consultation over projects that might affect habitat for salmonids federally listed as threatened or endangered. Cumulative effects analysis is also required by a number of national forest plans in the Pacific Northwest Region (Region 6). Cumulative watershed effects in many cases are...

The Impact Snow Albedo Feedback over Mountain Regions as Examined through High-Resolution Regional Climate Change Experiments over the Rocky Mountains

NASA Astrophysics Data System (ADS)

Letcher, Theodore

As the climate warms, the snow albedo feedback (SAF) will play a substantial role in shaping the climate response of mid-latitude mountain regions with transient snow cover. One such region is the Rocky Mountains of the western United States where large snow packs accumulate during the winter and persist throughout the spring. In this dissertation, the Weather Research and Forecast model (WRF) configured as a regional climate model is used to investigate the role of the SAF in determining the regional climate response to forced anthropogenic climate change. The regional effects of climate change are investigated by using the pseudo global warming (PGW) framework, which is an experimental configuration in a which a mean climate perturbation is added to the boundary forcing of a regional model, thus preserving the large-scale circulation entering the region through the model boundaries and isolating the mesoscale climate response. Using this framework, the impact of the SAF on the regional energetics and atmospheric dynamics is examined and quantified. Linear feedback analysis is used to quantify the strength of the SAF over the Headwaters region of the Colorado Rockies for a series of high-resolution PGW experiments. This technique is used to test sensitivity of the feedback strength to model resolution and land surface model. Over the Colorado Rockies, and integrated over the entire spring season, the SAF strength is largely insensitive to model resolution, however there are more substantial differences on the sub-seasonal (monthly) timescale. In contrast, the SAF strength over this region is very sensitive to choice of land surface model. These simulations are also used to investigate how spatial and diurnal variability in warming caused by the SAF influences the dynamics of thermally driven mountain-breeze circulations. It is shown that, the SAF causes stronger daytime mountain-breeze circulations by increasing the warming on the mountains slopes thus enhancing the thermal contrast between the mountain slopes and the surrounding lowlands which drives these wind systems. This analysis is extended to investigate the impacts that the SAF has on the large-scale mountain-plain circulation that develops east of the Rockies over the Great Plains. To help isolate the SAF, a more idealized regional climate experiment which isolates the SAF is performed. It was found that SAF may influence thermally driven atmospheric dynamics up-to 200km east of the Mountains where the SAF originates, suggesting broader regional impacts of the SAF which may not be well resolved by coarser resolution global climate models. The implications of these changes on pollution transport and moist convection are also explored using these simulations.

Impacts of agricultural land use on biological integrity: A causal analysis

USGS Publications Warehouse

Riseng, C.M.; Wiley, M.J.; Black, R.W.; Munn, M.D.

2011-01-01

Agricultural land use has often been linked to nutrient enrichment, habitat degradation, hydrologic alteration, and loss of biotic integrity in streams. The U.S. Geological Survey's National Water Quality Assessment Program sampled 226 stream sites located in eight agriculture-dominated study units across the United States to investigate the geographic variability and causes of agricultural impacts on stream biotic integrity. In this analysis we used structural equation modeling (SEM) to develop a national and set of regional causal models linking agricultural land use to measured instream conditions. We then examined the direct, indirect, and total effects of agriculture on biotic integrity as it acted through multiple water quality and habitat pathways. In our nation-wide model, cropland affected benthic communities by both altering structural habitats and by imposing water quality-related stresses. Regionspecific modeling demonstrated that geographic context altered the relative importance of causal pathways through which agricultural activities affected stream biotic integrity. Cropland had strong negative total effects on the invertebrate community in the national, Midwest, and Western models, but a very weak effect in the Eastern Coastal Plain model. In theWestern Arid and Eastern Coastal Plain study regions, cropland impacts were transmitted primarily through dissolved water quality contaminants, but in the Midwestern region, they were transmitted primarily through particulate components of water quality. Habitat effects were important in the Western Arid model, but negligible in the Midwest and Eastern Coastal Plain models. The relative effects of riparian forested wetlands also varied regionally, having positive effects on biotic integrity in the Eastern Coastal Plain andWestern Arid region models, but no statistically significant effect in the Midwest. These differences in response to cropland and riparian cover suggest that best management practices and planning for the mitigation of agricultural land use impacts on stream ecosystems should be regionally focused. ?? 2011 by the Ecological Society of America.

Transport and Chemical Production of Ozone in the East Asian Pacific Rim Region: -Modeling Study Based on Observation-

NASA Astrophysics Data System (ADS)

Akimoto, H.; Li, J.; Wang, Z.; Yamaji, K.; Pochanart, P.; Ohara, T.; Uno, I.; Gao, C.; Wang, X.; Tanimoto, H.; Kurokawa, J.

2007-12-01

Form satellite observational data, east-central China covering the North China Plain (NCP) and Yanzi Delta (YZD) has been identified as the most widely spread source area of air pollutants in the East Asian Pacific region. In order to quantify transport and chemical production of ozone in this region, both of observational and modeling studies in both of source and outflow region are necessary. In the present study, we investigated the budgets of ozone over East Asia by using regional chemical transport models (NAQPMS and CMAQ) based on observations at newly founded three mountain sites (Mt. Tai, Hua and Huang) in east-central China, and several sites from EANET and regional WMO/GAW. The observations show that a striking pattern of two sharp high ozone peaks in May-June and September-October at the three mountain sites. The budget analysis by the model confirms that maximum of net photochemical ozone production reaches 31.8, 15.1 and 11.4 ppb/day at Mt. Tai, Hua and Huang, respectively. The net chemical production dominates the formation of ozone maximum at Mt. Tai and Hua in June, and the importing transport also plays a comparable importance at Mt. Huang. In the outflow region at Oki, Japan, transport of ozone produced by East Asian emissions accounts up to 21 ppb in summer but less than 3 ppb in winter agreeing with the model analysis. The contribution of ozone due to East Asian emission is the largest (53.6%) in July-August, and somewhat smaller in May-June (34.0%) and September-October (30.7%) on the transect between Japan and the Asian continent.

Statistical Analysis of the Impacts of Regional Transportation on the Air Quality in Beijing

NASA Astrophysics Data System (ADS)

Huang, Zhongwen; Zhang, Huiling; Tong, Lei; Xiao, Hang

2016-04-01

From October to December 2015, Beijing-Tianjin-Hebei (BTH) region had experienced several severe haze events. In order to assess the effects of the regional transportation on the air quality in Beijing, the air monitoring data (PM2.5, SO2, NO2 and CO) from that period published by Chinese National Environmental Monitoring Center (CNEMC) was collected and analyzed with various statistical models. The cities within BTH area were clustered into three groups according to the geographical conditions, while the air pollutant concentrations of cities within a group sharing similar variation trends. The Granger causality test results indicate that significant causal relationships exist between the air pollutant data of Beijing and its surrounding cities (Baoding, Chengde, Tianjin and Zhangjiakou) for the reference period. Then, linear regression models were constructed to capture the interdependency among the multiple time series. It shows that the observed air pollutant concentrations in Beijing were well consistent with the model-fitted results. More importantly, further analysis suggests that the air pollutants in Beijing were strongly affected by regional transportation, as the local sources only contributed 17.88%, 27.12%, 14.63% and 31.36% of PM2.5, SO2, NO2 and CO concentrations, respectively. And the major foreign source for Beijing was from Southwest (Baoding) direction, account for more than 42% of all these air pollutants. Thus, by combining various statistical models, it may not only be able to quickly predict the air qualities of any cities on a regional scale, but also to evaluate the local and regional source contributions for a particular city. Key words: regional transportation, air pollution, Granger causality test, statistical models

Differentially Methylated Region-Representational Difference Analysis (DMR-RDA): A Powerful Method to Identify DMRs in Uncharacterized Genomes.

PubMed

Sasheva, Pavlina; Grossniklaus, Ueli

2017-01-01

Over the last years, it has become increasingly clear that environmental influences can affect the epigenomic landscape and that some epigenetic variants can have heritable, phenotypic effects. While there are a variety of methods to perform genome-wide analyses of DNA methylation in model organisms, this is still a challenging task for non-model organisms without a reference genome. Differentially methylated region-representational difference analysis (DMR-RDA) is a sensitive and powerful PCR-based technique that isolates DNA fragments that are differentially methylated between two otherwise identical genomes. The technique does not require special equipment and is independent of prior knowledge about the genome. It is even applicable to genomes that have high complexity and a large size, being the method of choice for the analysis of plant non-model systems.

MOVES2010a regional level sensitivity analysis

DOT National Transportation Integrated Search

2012-12-10

This document discusses the sensitivity of various input parameter effects on emission rates using the US Environmental Protection Agencys (EPAs) MOVES2010a model at the regional level. Pollutants included in the study are carbon monoxide (CO),...

[A process of aquatic ecological function regionalization: The dual tree framework and conceptual model].

PubMed

Guo, Shu Hai; Wu, Bo

2017-12-01

Aquatic ecological regionalization and aquatic ecological function regionalization are the basis of water environmental management of a river basin and rational utilization of an aquatic ecosystem, and have been studied in China for more than ten years. Regarding the common problems in this field, the relationship between aquatic ecological regionalization and aquatic ecological function regionalization was discussed in this study by systematic analysis of the aquatic ecological zoning and the types of aquatic ecological function. Based on the dual tree structure, we put forward the RFCH process and the diamond conceptual model. Taking Liaohe River basin as an example and referring to the results of existing regionalization studies, we classified the aquatic ecological function regions based on three-class aquatic ecological regionalization. This study provided a process framework for aquatic ecological function regionalization of a river basin.

Regionalization Study of Satellite based Hydrological Model (SHM) in Hydrologically Homogeneous River Basins of India

NASA Astrophysics Data System (ADS)

Kumari, Babita; Paul, Pranesh Kumar; Singh, Rajendra; Mishra, Ashok; Gupta, Praveen Kumar; Singh, Raghvendra P.

2017-04-01

A new semi-distributed conceptual hydrological model, namely Satellite based Hydrological Model (SHM), has been developed under 'PRACRITI-2' program of Space Application Centre (SAC), Ahmedabad for sustainable water resources management of India by using data from Indian Remote Sensing satellites. Entire India is divided into 5km x 5km grid cells and properties at the center of the cells are assumed to represent the property of the cells. SHM contains five modules namely surface water, forest, snow, groundwater and routing. Two empirical equations (SCS-CN and Hargreaves) and water balance method have been used in the surface water module; the forest module is based on the calculations of water balancing & dynamics of subsurface. 2-D Boussinesq equation is used for groundwater modelling which is solved using implicit finite-difference. The routing module follows a distributed routing approach which requires flow path and network with the key point of travel time estimation. The aim of this study is to evaluate the performance of SHM using regionalization technique which also checks the usefulness of a model in data scarce condition or for ungauged basins. However, homogeneity analysis is pre-requisite to regionalization. Similarity index (Φ) and hierarchical agglomerative cluster analysis are adopted to test the homogeneity in terms of physical attributes of three basins namely Brahmani (39,033 km km^2)), Baitarani (10,982 km km^2)) and Kangsabati (9,660 km km^2)) with respect to Subarnarekha (29,196 km km^2)) basin. The results of both homogeneity analysis show that Brahmani basin is the most homogeneous with respect to Subarnarekha river basin in terms of physical characteristics (land use land cover classes, soiltype and elevation). The calibration and validation of model parameters of Brahmani basin is in progress which are to be transferred into the SHM set up of Subarnarekha basin and results are to be compared with the results of calibrated and validated parameter set up of SHM of Subarnarekha basin to test the applicability of SHM in hydrologically homogeneous regions of India. Keywords: SHM, regionalization, homogeneity, donor catchment, similarity index, cluster analysis

Impacts of spectral nudging on the simulated surface air temperature in summer compared with the selection of shortwave radiation and land surface model physics parameterization in a high-resolution regional atmospheric model

NASA Astrophysics Data System (ADS)

Park, Jun; Hwang, Seung-On

2017-11-01

The impact of a spectral nudging technique for the dynamical downscaling of the summer surface air temperature in a high-resolution regional atmospheric model is assessed. The performance of this technique is measured by comparing 16 analysis-driven simulation sets of physical parameterization combinations of two shortwave radiation and four land surface model schemes of the model, which are known to be crucial for the simulation of the surface air temperature. It is found that the application of spectral nudging to the outermost domain has a greater impact on the regional climate than any combination of shortwave radiation and land surface model physics schemes. The optimal choice of two model physics parameterizations is helpful for obtaining more realistic spatiotemporal distributions of land surface variables such as the surface air temperature, precipitation, and surface fluxes. However, employing spectral nudging adds more value to the results; the improvement is greater than using sophisticated shortwave radiation and land surface model physical parameterizations. This result indicates that spectral nudging applied to the outermost domain provides a more accurate lateral boundary condition to the innermost domain when forced by analysis data by securing the consistency with large-scale forcing over a regional domain. This consequently indirectly helps two physical parameterizations to produce small-scale features closer to the observed values, leading to a better representation of the surface air temperature in a high-resolution downscaled climate.

Hyperspectral analysis of soil organic matter in coal mining regions using wavelets, correlations, and partial least squares regression.

PubMed

Lin, Lixin; Wang, Yunjia; Teng, Jiyao; Wang, Xuchen

2016-02-01

Hyperspectral estimation of soil organic matter (SOM) in coal mining regions is an important tool for enhancing fertilization in soil restoration programs. The correlation--partial least squares regression (PLSR) method effectively solves the information loss problem of correlation--multiple linear stepwise regression, but results of the correlation analysis must be optimized to improve precision. This study considers the relationship between spectral reflectance and SOM based on spectral reflectance curves of soil samples collected from coal mining regions. Based on the major absorption troughs in the 400-1006 nm spectral range, PLSR analysis was performed using 289 independent bands of the second derivative (SDR) with three levels and measured SOM values. A wavelet-correlation-PLSR (W-C-PLSR) model was then constructed. By amplifying useful information that was previously obscured by noise, the W-C-PLSR model was optimal for estimating SOM content, with smaller prediction errors in both calibration (R(2) = 0.970, root mean square error (RMSEC) = 3.10, and mean relative error (MREC) = 8.75) and validation (RMSEV = 5.85 and MREV = 14.32) analyses, as compared with other models. Results indicate that W-C-PLSR has great potential to estimate SOM in coal mining regions.

A generalized estimating equations approach for resting-state functional MRI group analysis.

PubMed

D'Angelo, Gina M; Lazar, Nicole A; Eddy, William F; Morris, John C; Sheline, Yvette I

2011-01-01

An Alzheimer's fMRI study has motivated us to evaluate inter-regional correlations between groups. The overall objective is to assess inter-regional correlations at a resting-state with no stimulus or task. We propose using a generalized estimating equation (GEE) transition model and a GEE marginal model to model the within-subject correlation for each region. Residuals calculated from the GEE models are used to correlate brain regions and assess between group differences. The standard pooling approach of group averages of the Fisher-z transformation assuming temporal independence is a typical approach used to compare group correlations. The GEE approaches and standard Fisher-z pooling approach are demonstrated with an Alzheimer's disease (AD) connectivity study in a population of AD subjects and healthy control subjects. We also compare these methods using simulation studies and show that the transition model may have better statistical properties.

Spatial analysis of instream nitrogen loads and factors controlling nitrogen delivery to streams in the southeastern United States using spatially referenced regression on watershed attributes (SPARROW) and regional classification frameworks

USGS Publications Warehouse

Hoos, A.B.; McMahon, G.

2009-01-01

Understanding how nitrogen transport across the landscape varies with landscape characteristics is important for developing sound nitrogen management policies. We used a spatially referenced regression analysis (SPARROW) to examine landscape characteristics influencing delivery of nitrogen from sources in a watershed to stream channels. Modelled landscape delivery ratio varies widely (by a factor of 4) among watersheds in the southeastern United States - higher in the western part (Tennessee, Alabama, and Mississippi) than in the eastern part, and the average value for the region is lower compared to other parts of the nation. When we model landscape delivery ratio as a continuous function of local-scale landscape characteristics, we estimate a spatial pattern that varies as a function of soil and climate characteristics but exhibits spatial structure in residuals (observed load minus predicted load). The spatial pattern of modelled landscape delivery ratio and the spatial pattern of residuals coincide spatially with Level III ecoregions and also with hydrologic landscape regions. Subsequent incorporation into the model of these frameworks as regional scale variables improves estimation of landscape delivery ratio, evidenced by reduced spatial bias in residuals, and suggests that cross-scale processes affect nitrogen attenuation on the landscape. The model-fitted coefficient values are logically consistent with the hypothesis that broad-scale classifications of hydrologic response help to explain differential rates of nitrogen attenuation, controlling for local-scale landscape characteristics. Negative model coefficients for hydrologic landscape regions where the primary flow path is shallow ground water suggest that a lower fraction of nitrogen mass will be delivered to streams; this relation is reversed for regions where the primary flow path is overland flow.

Spatial analysis of instream nitrogen loads and factors controlling nitrogen delivery to streams in the southeastern United States using spatially referenced regression on watershed attributes (SPARROW) and regional classification frameworks

USGS Publications Warehouse

Hoos, Anne B.; McMahon, Gerard

2009-01-01

Understanding how nitrogen transport across the landscape varies with landscape characteristics is important for developing sound nitrogen management policies. We used a spatially referenced regression analysis (SPARROW) to examine landscape characteristics influencing delivery of nitrogen from sources in a watershed to stream channels. Modelled landscape delivery ratio varies widely (by a factor of 4) among watersheds in the southeastern United States—higher in the western part (Tennessee, Alabama, and Mississippi) than in the eastern part, and the average value for the region is lower compared to other parts of the nation. When we model landscape delivery ratio as a continuous function of local-scale landscape characteristics, we estimate a spatial pattern that varies as a function of soil and climate characteristics but exhibits spatial structure in residuals (observed load minus predicted load). The spatial pattern of modelled landscape delivery ratio and the spatial pattern of residuals coincide spatially with Level III ecoregions and also with hydrologic landscape regions. Subsequent incorporation into the model of these frameworks as regional scale variables improves estimation of landscape delivery ratio, evidenced by reduced spatial bias in residuals, and suggests that cross-scale processes affect nitrogen attenuation on the landscape. The model-fitted coefficient values are logically consistent with the hypothesis that broad-scale classifications of hydrologic response help to explain differential rates of nitrogen attenuation, controlling for local-scale landscape characteristics. Negative model coefficients for hydrologic landscape regions where the primary flow path is shallow ground water suggest that a lower fraction of nitrogen mass will be delivered to streams; this relation is reversed for regions where the primary flow path is overland flow.

Analysis of Unit-Level Changes in Operations with Increased SPP Wind from EPRI/LCG Balancing Study

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

Hadley, Stanton W

2012-01-01

Wind power development in the United States is outpacing previous estimates for many regions, particularly those with good wind resources. The pace of wind power deployment may soon outstrip regional capabilities to provide transmission and integration services to achieve the most economic power system operation. Conversely, regions such as the Southeastern United States do not have good wind resources and will have difficulty meeting proposed federal Renewable Portfolio Standards with local supply. There is a growing need to explore innovative solutions for collaborating between regions to achieve the least cost solution for meeting such a renewable energy mandate. The Departmentmore » of Energy funded the project 'Integrating Midwest Wind Energy into Southeast Electricity Markets' to be led by EPRI in coordination with the main authorities for the regions: SPP, Entergy, TVA, Southern Company and OPC. EPRI utilized several subcontractors for the project including LCG, the developers of the model UPLAN. The study aims to evaluate the operating cost benefits of coordination of scheduling and balancing for Southwest Power Pool (SPP) wind transfers to Southeastern Electric Reliability Council (SERC) Balancing Authorities (BAs). The primary objective of this project is to analyze the benefits of regional cooperation for integrating mid-western wind energy into southeast electricity markets. Scenarios were defined, modeled and investigated to address production variability and uncertainty and the associated balancing of large quantities of wind power in SPP and delivery to energy markets in the southern regions of the SERC. DOE funded Oak Ridge National Laboratory to provide additional support to the project, including a review of results and any side analysis that may provide additional insight. This report is a unit-by-unit analysis of changes in operations due to the different scenarios used in the overall study. It focuses on the change in capacity factors and the number of start-ups required for each unit since those criteria summarize key aspects of plant operations, how often are they called upon and how much do they operate. The primary analysis of the overall project is based on security-constrained unit commitment (SCUC) and economic dispatch (SCED) simulations of the SPP-SERC regions as modeled for the year 2022. The SCUC/SCED models utilized for the project were developed through extensive consultation with the project utility partners, to ensure the various regions and operational practices are represented as best as possible in the model. SPP, Entergy, Oglethorpe Power Company (OPC), Southern Company, and the Tennessee Valley Authority (TVA) actively participated in the project providing input data for the models and review of simulation results and conclusions. While other SERC utility systems are modeled, the listed SERC utilities were explicitly included as active participants in the project due to the size of their load and relative proximity to SPP for importing wind energy.« less

Diffuse nutrient losses and the impact factors determining their regional differences in four catchments from North to South China

NASA Astrophysics Data System (ADS)

Zhang, Yongyong; Zhou, Yujian; Shao, Quanxi; Liu, Hongbin; Lei, Qiuliang; Zhai, Xiaoyan; Wang, Xuelei

2016-12-01

Diffuse nutrient loss mechanism is complicated and shows remarkably regional differences due to spatial heterogeneities of underlying surface conditions, climate and agricultural practices. Moreover, current available observations are still hard to support the identification of impact factors due to different time or space steps. In this study, an integrated water system model (HEQM) was adopted to obtain the simulated loads of diffuse components (carriers: runoff and sediment; nutrient: total nitrogen (TN) and total phosphorous (TP)) with synchronous scales. Multivariable statistical analysis approaches (Analysis of Similarity and redundancy analysis) were used to assess the regional differences, and to identify impact factors as well as their contributions. Four catchments were selected as our study areas, i.e., Xiahui and Zhangjiafen Catchments of Miyun Basin in North China, Yuliang and Tunxi Catchments of Xin'anjiang Basin in South China. Results showed that the model performances of monthly processes were very good for runoff and good for sediment, TN and TP. The annual average coefficients of all the diffuse components in Xin'anjiang Basin were much greater than those in Miyun Basin, and showed significantly regional differences. All the selected impact factors interpreted 72.87-82.16% of the regional differences of carriers, and 62.72-71.62% of those of nutrient coefficients, respectively. For individual impact factor categories, the critical category was geography, followed by land-use/cover, carriers, climate, as well as soil and agricultural practices in Miyun Basin, or agricultural practices and soil in Xin'anjiang Basin. For individual factors, the critical factors were locations for the carrier regional differences, and carriers or chemical fertilizer for the nutrient regional differences. This study is expected to promote further applications of integrated water system model and multivariable statistical analysis in the diffuse nutrient studies, and provide a scientific support for the diffuse pollution control and management in China.

Biomass burning losses of carbon estimated from ecosystem modeling and satellite data analysis for the Brazilian Amazon region

NASA Astrophysics Data System (ADS)

Potter, Christopher; Brooks Genovese, Vanessa; Klooster, Steven; Bobo, Matthew; Torregrosa, Alicia

To produce a new daily record of gross carbon emissions from biomass burning events and post-burning decomposition fluxes in the states of the Brazilian Legal Amazon (Instituto Brasileiro de Geografia e Estatistica (IBGE), 1991. Anuario Estatistico do Brasil, Vol. 51. Rio de Janeiro, Brazil pp. 1-1024). We have used vegetation greenness estimates from satellite images as inputs to a terrestrial ecosystem production model. This carbon allocation model generates new estimates of regional aboveground vegetation biomass at 8-km resolution. The modeled biomass product is then combined for the first time with fire pixel counts from the advanced very high-resolution radiometer (AVHRR) to overlay regional burning activities in the Amazon. Results from our analysis indicate that carbon emission estimates from annual region-wide sources of deforestation and biomass burning in the early 1990s are apparently three to five times higher than reported in previous studies for the Brazilian Legal Amazon (Houghton et al., 2000. Nature 403, 301-304; Fearnside, 1997. Climatic Change 35, 321-360), i.e., studies which implied that the Legal Amazon region tends toward a net-zero annual source of terrestrial carbon. In contrast, our analysis implies that the total source fluxes over the entire Legal Amazon region range from 0.2 to 1.2 Pg C yr -1, depending strongly on annual rainfall patterns. The reasons for our higher burning emission estimates are (1) use of combustion fractions typically measured during Amazon forest burning events for computing carbon losses, (2) more detailed geographic distribution of vegetation biomass and daily fire activity for the region, and (3) inclusion of fire effects in extensive areas of the Legal Amazon covered by open woodland, secondary forests, savanna, and pasture vegetation. The total area of rainforest estimated annually to be deforested did not differ substantially among the previous analyses cited and our own.

South Asia river-flow projections and their implications for water resources

NASA Astrophysics Data System (ADS)

Mathison, C.; Wiltshire, A. J.; Falloon, P.; Challinor, A. J.

2015-12-01

South Asia is a region with a large and rising population, a high dependence on water intense industries, such as agriculture and a highly variable climate. In recent years, fears over the changing Asian summer monsoon (ASM) and rapidly retreating glaciers together with increasing demands for water resources have caused concern over the reliability of water resources and the potential impact on intensely irrigated crops in this region. Despite these concerns, there is a lack of climate simulations with a high enough resolution to capture the complex orography, and water resource analysis is limited by a lack of observations of the water cycle for the region. In this paper we present the first 25 km resolution regional climate projections of river flow for the South Asia region. Two global climate models (GCMs), which represent the ASM reasonably well are downscaled (1960-2100) using a regional climate model (RCM). In the absence of robust observations, ERA-Interim reanalysis is also downscaled providing a constrained estimate of the water balance for the region for comparison against the GCMs (1990-2006). The RCM river flow is routed using a river-routing model to allow analysis of present-day and future river flows through comparison with available river gauge observations. We examine how useful these simulations are for understanding potential changes in water resources for the South Asia region. In general the downscaled GCMs capture the seasonality of the river flows but overestimate the maximum river flows compared to the observations probably due to a positive rainfall bias and a lack of abstraction in the model. The simulations suggest an increasing trend in annual mean river flows for some of the river gauges in this analysis, in some cases almost doubling by the end of the century. The future maximum river-flow rates still occur during the ASM period, with a magnitude in some cases, greater than the present-day natural variability. Increases in river flow could mean additional water resources for irrigation, the largest usage of water in this region, but has implications in terms of inundation risk. These projected increases could be more than countered by changes in demand due to depleted groundwater, increases in domestic use or expansion of water intense industries. Including missing hydrological processes in the model would make these projections more robust but could also change the sign of the projections.

Benefit-cost evaluation of an intra-regional air service in the Bay area

NASA Technical Reports Server (NTRS)

Haefner, L. E.

1977-01-01

Utilization of an iterative statistical model is presented to evaluate combinations of commuter airport sites and surface transportation facilities in confunction with service by a given commuter aircraft type in light of Bay Area regional growth alternatives and peak and off-peak regional travel patterns. The model evaluates such transportation options with respect to criteria of airline profitability, public acceptance, and public and private nonuser costs. It incorporates information modal split, peak and off-peak use of the air commuter fleet, terminal and airport cost, development costs and uses of land in proximity to the airport sites, regional population shifts, and induced zonal shifts in travel demand. The model is multimodal in its analytical capability, and performs exhaustive sensitivity analysis.

A Data Assimilation System For Operational Weather Forecast In Galicia Region (nw Spain)

NASA Astrophysics Data System (ADS)

Balseiro, C. F.; Souto, M. J.; Pérez-Muñuzuri, V.; Brewster, K.; Xue, M.

Regional weather forecast models, such as the Advanced Regional Prediction System (ARPS), over complex environments with varying local influences require an accurate meteorological analysis that should include all local meteorological measurements available. In this work, the ARPS Data Analysis System (ADAS) (Xue et al. 2001) is applied as a three-dimensional weather analysis tool to include surface station and rawinsonde data with the NCEP AVN forecasts as the analysis background. Currently in ADAS, a set of five meteorological variables are considered during the analysis: horizontal grid-relative wind components, pressure, potential temperature and spe- cific humidity. The analysis is used for high resolution numerical weather prediction for the Galicia region. The analysis method used in ADAS is based on the successive corrective scheme of Bratseth (1986), which asymptotically approaches the result of a statistical (optimal) interpolation, but at lower computational cost. As in the optimal interpolation scheme, the Bratseth interpolation method can take into account the rel- ative error between background and observational data, therefore they are relatively insensitive to large variations in data density and can integrate data of mixed accuracy. This method can be applied economically in an operational setting, providing signifi- cant improvement over the background model forecast as well as any analysis without high-resolution local observations. A one-way nesting is applied for weather forecast in Galicia region, and the use of this assimilation system in both domains shows better results not only in initial conditions but also in all forecast periods. Bratseth, A.M. (1986): "Statistical interpolation by means of successive corrections." Tellus, 38A, 439-447. Souto, M. J., Balseiro, C. F., Pérez-Muñuzuri, V., Xue, M. Brewster, K., (2001): "Im- pact of cloud analysis on numerical weather prediction in the galician region of Spain". Submitted to Journal of Applied Meteorology. Xue, M., Wang. D., Gao, J., Brewster, K, Droegemeier, K. K., (2001): "The Advanced Regional Prediction System (ARPS), storm-scale numerical weather prediction and data assimilation". Meteor. Atmos Physics. Accepted

Low Density Lipoprotein and Non-Newtonian Oscillating Flow Biomechanical Parameters for Normal Human Aorta.

PubMed

Soulis, Johannes V; Fytanidis, Dimitrios K; Lampri, Olga P; Giannoglou, George D

2016-04-01

The temporal variation of the hemodynamic mechanical parameters during cardiac pulse wave is considered as an important atherogenic factor. Applying non-Newtonian blood molecular viscosity simulation is crucial for hemodynamic analysis. Understanding low density lipoprotein (LDL) distribution in relation to flow parameters will possibly spot the prone to atherosclerosis aorta regions. The biomechanical parameters tested were averaged wall shear stress (AWSS), oscillatory shear index (OSI) and relative residence time (RRT) in relation to the LDL concentration. Four non-Newtonian molecular viscosity models and the Newtonian one were tested for the normal human aorta under oscillating flow. The analysis was performed via computational fluid dynamic. Tested viscosity blood flow models for the biomechanical parameters yield a consistent aorta pattern. High OSI and low AWSS develop at the concave aorta regions. This is most noticeable in downstream flow region of the left subclavian artery and at concave ascending aorta. Concave aorta regions exhibit high RRT and elevated LDL. For the concave aorta site, the peak LDL value is 35.0% higher than its entrance value. For the convex site, it is 18.0%. High LDL endothelium regions located at the aorta concave site are well predicted with high RRT. We are in favor of using the non-Newtonian power law model for analysis. It satisfactorily approximates the molecular viscosity, WSS, OSI, RRT and LDL distribution. Concave regions are mostly prone to atherosclerosis. The flow biomechanical factor RRT is a relatively useful tool for identifying the localization of the atheromatic plaques of the normal human aorta.

Utilization of an Enhanced Canonical Correlation Analysis (ECCA) to Predict Daily Precipitation and Temperature in a Semi-Arid Environment

NASA Astrophysics Data System (ADS)

Lopez, S. R.; Hogue, T. S.

2011-12-01

Global climate models (GCMs) are primarily used to generate historical and future large-scale circulation patterns at a coarse resolution (typical order of 50,000 km2) and fail to capture climate variability at the ground level due to localized surface influences (i.e topography, marine, layer, land cover, etc). Their inability to accurately resolve these processes has led to the development of numerous 'downscaling' techniques. The goal of this study is to enhance statistical downscaling of daily precipitation and temperature for regions with heterogeneous land cover and topography. Our analysis was divided into two periods, historical (1961-2000) and contemporary (1980-2000), and tested using sixteen predictand combinations from four GCMs (GFDL CM2.0, GFDL CM2.1, CNRM-CM3 and MRI-CGCM2 3.2a. The Southern California area was separated into five county regions: Santa Barbara, Ventura, Los Angeles, Orange and San Diego. Principle component analysis (PCA) was performed on ground-based observations in order to (1) reduce the number of redundant gauges and minimize dimensionality and (2) cluster gauges that behave statistically similarly for post-analysis. Post-PCA analysis included extensive testing of predictor-predictand relationships using an enhanced canonical correlation analysis (ECCA). The ECCA includes obtaining the optimal predictand sets for all models within each spatial domain (county) as governed by daily and monthly overall statistics. Results show all models maintain mean annual and monthly behavior within each county and daily statistics are improved. The level of improvement highly depends on the vegetation extent within each county and the land-to-ocean ratio within the GCM spatial grid. The utilization of the entire historical period also leads to better statistical representation of observed daily precipitation. The validated ECCA technique is being applied to future climate scenarios distributed by the IPCC in order to provide forcing data for regional hydrologic models and assess future water resources in the Southern California region.

Historical and future drought in Bangladesh using copula-based bivariate regional frequency analysis

NASA Astrophysics Data System (ADS)

Mortuza, Md Rubayet; Moges, Edom; Demissie, Yonas; Li, Hong-Yi

2018-02-01

The study aims at regional and probabilistic evaluation of bivariate drought characteristics to assess both the past and future drought duration and severity in Bangladesh. The procedures involve applying (1) standardized precipitation index to identify drought duration and severity, (2) regional frequency analysis to determine the appropriate marginal distributions for both duration and severity, (3) copula model to estimate the joint probability distribution of drought duration and severity, and (4) precipitation projections from multiple climate models to assess future drought trends. Since drought duration and severity in Bangladesh are often strongly correlated and do not follow same marginal distributions, the joint and conditional return periods of droughts are characterized using the copula-based joint distribution. The country is divided into three homogeneous regions using Fuzzy clustering and multivariate discordancy and homogeneity measures. For given severity and duration values, the joint return periods for a drought to exceed both values are on average 45% larger, while to exceed either value are 40% less than the return periods from the univariate frequency analysis, which treats drought duration and severity independently. These suggest that compared to the bivariate drought frequency analysis, the standard univariate frequency analysis under/overestimate the frequency and severity of droughts depending on how their duration and severity are related. Overall, more frequent and severe droughts are observed in the west side of the country. Future drought trend based on four climate models and two scenarios showed the possibility of less frequent drought in the future (2020-2100) than in the past (1961-2010).

Spatial analysis of future East Asian seasonal temperature using two regional climate model simulations

NASA Astrophysics Data System (ADS)

Kim, Yura; Jun, Mikyoung; Min, Seung-Ki; Suh, Myoung-Seok; Kang, Hyun-Suk

2016-05-01

CORDEX-East Asia, a branch of the coordinated regional climate downscaling experiment (CORDEX) initiative, provides high-resolution climate simulations for the domain covering East Asia. This study analyzes temperature data from regional climate models (RCMs) participating in the CORDEX - East Asia region, accounting for the spatial dependence structure of the data. In particular, we assess similarities and dissimilarities of the outputs from two RCMs, HadGEM3-RA and RegCM4, over the region and over time. A Bayesian functional analysis of variance (ANOVA) approach is used to simultaneously model the temperature patterns from the two RCMs for the current and future climate. We exploit nonstationary spatial models to handle the spatial dependence structure of the temperature variable, which depends heavily on latitude and altitude. For a seasonal comparison, we examine changes in the winter temperature in addition to the summer temperature data. We find that the temperature increase projected by RegCM4 tends to be smaller than the projection of HadGEM3-RA for summers, and that the future warming projected by HadGEM3-RA tends to be weaker for winters. Also, the results show that there will be a warming of 1-3°C over the region in 45 years. More specifically, the warming pattern clearly depends on the latitude, with greater temperature increases in higher latitude areas, which implies that warming may be more severe in the northern part of the domain.

[Mobile Health Units: An Analysis of Concepts and Implementation Requirements in Rural Regions.

PubMed

Hämel, K; Kutzner, J; Vorderwülbecke, J

2017-12-01

Access to health services in rural regions represents a challenge. The development of care models that respond to health service shortages and pay particular attention to the increasing health care needs of the elderly is an important concern. A model that has been implemented in other countries is that of mobile health units. But until now, there is no overview of their possible objectives, functions and implementation requirements. This paper is based on a literature analysis and an internet research on mobile health units in rural regions. Mobile health units aim to avoid regional undersupply and address particularly vulnerable population groups. In the literature, mobile health units are described with a focus on specific illnesses, as well as those that provide comprehensive, partly multi-professional primary care that is close to patients' homes. The implementation of mobile health units is demanding; the key challenges are (a) alignment to the needs of the regional population, (b) user-oriented access and promotion of awareness and acceptance of mobile health units by the local population, and (c) network building within existing care structures to ensure continuity of care for patients. To fulfill these requirements, a community-oriented program development and implementation is important. Mobile health units could represent an interesting model for the provision of health care in rural regions in Germany. International experiences are an important starting point and should be taken into account for the further development of models in Germany. © Georg Thieme Verlag KG Stuttgart · New York.

Causal functional contributions and interactions in the attention network of the brain: an objective multi-perturbation analysis.

PubMed

Zavaglia, Melissa; Hilgetag, Claus C

2016-06-01

Spatial attention is a prime example for the distributed network functions of the brain. Lesion studies in animal models have been used to investigate intact attentional mechanisms as well as perspectives for rehabilitation in the injured brain. Here, we systematically analyzed behavioral data from cooling deactivation and permanent lesion experiments in the cat, where unilateral deactivation of the posterior parietal cortex (in the vicinity of the posterior middle suprasylvian cortex, pMS) or the superior colliculus (SC) cause a severe neglect in the contralateral hemifield. Counterintuitively, additional deactivation of structures in the opposite hemisphere reverses the deficit. Using such lesion data, we employed a game-theoretical approach, multi-perturbation Shapley value analysis (MSA), for inferring functional contributions and network interactions of bilateral pMS and SC from behavioral performance in visual attention studies. The approach provides an objective theoretical strategy for lesion inferences and allows a unique quantitative characterization of regional functional contributions and interactions on the basis of multi-perturbations. The quantitative analysis demonstrated that right posterior parietal cortex and superior colliculus made the strongest positive contributions to left-field orienting, while left brain regions had negative contributions, implying that their perturbation may reverse the effects of contralateral lesions or improve normal function. An analysis of functional modulations and interactions among the regions revealed redundant interactions (implying functional overlap) between regions within each hemisphere, and synergistic interactions between bilateral regions. To assess the reliability of the MSA method in the face of variable and incomplete input data, we performed a sensitivity analysis, investigating how much the contribution values of the four regions depended on the performance of specific configurations and on the prediction of unknown performances. The results suggest that the MSA approach is sensitive to categorical, but insensitive to gradual changes in the input data. Finally, we created a basic network model that was based on the known anatomical interactions among cortical-tectal regions and reproduced the experimentally observed behavior in visual orienting. We discuss the structural organization of the network model relative to the causal modulations identified by MSA, to aid a mechanistic understanding of the attention network of the brain.

Global ozone and air quality: a multi-model assessment of risks to human health and crops

NASA Astrophysics Data System (ADS)

Ellingsen, K.; Gauss, M.; van Dingenen, R.; Dentener, F. J.; Emberson, L.; Fiore, A. M.; Schultz, M. G.; Stevenson, D. S.; Ashmore, M. R.; Atherton, C. S.; Bergmann, D. J.; Bey, I.; Butler, T.; Drevet, J.; Eskes, H.; Hauglustaine, D. A.; Isaksen, I. S. A.; Horowitz, L. W.; Krol, M.; Lamarque, J. F.; Lawrence, M. G.; van Noije, T.; Pyle, J.; Rast, S.; Rodriguez, J.; Savage, N.; Strahan, S.; Sudo, K.; Szopa, S.; Wild, O.

2008-02-01

Within ACCENT, a European Network of Excellence, eighteen atmospheric models from the U.S., Europe, and Japan calculated present (2000) and future (2030) concentrations of ozone at the Earth's surface with hourly temporal resolution. Comparison of model results with surface ozone measurements in 14 world regions indicates that levels and seasonality of surface ozone in North America and Europe are characterized well by global models, with annual average biases typically within 5-10 nmol/mol. However, comparison with rather sparse observations over some regions suggest that most models overestimate annual ozone by 15-20 nmol/mol in some locations. Two scenarios from the International Institute for Applied Systems Analysis (IIASA) and one from the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC SRES) have been implemented in the models. This study focuses on changes in near-surface ozone and their effects on human health and vegetation. Different indices and air quality standards are used to characterise air quality. We show that often the calculated changes in the different indices are closely inter-related. Indices using lower thresholds are more consistent between the models, and are recommended for global model analysis. Our analysis indicates that currently about two-thirds of the regions considered do not meet health air quality standards, whereas only 2-4 regions remain below the threshold. Calculated air quality exceedances show moderate deterioration by 2030 if current emissions legislation is followed and slight improvements if current emissions reduction technology is used optimally. For the "business as usual" scenario severe air quality problems are predicted. We show that model simulations of air quality indices are particularly sensitive to how well ozone is represented, and improved accuracy is needed for future projections. Additional measurements are needed to allow a more quantitative assessment of the risks to human health and vegetation from changing levels of surface ozone.

Simulating Nationwide Pandemics: Applying the Multi-scale Epidemiologic Simulation and Analysis System to Human Infectious Diseases

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

Dombroski, M; Melius, C; Edmunds, T

2008-09-24

This study uses the Multi-scale Epidemiologic Simulation and Analysis (MESA) system developed for foreign animal diseases to assess consequences of nationwide human infectious disease outbreaks. A literature review identified the state of the art in both small-scale regional models and large-scale nationwide models and characterized key aspects of a nationwide epidemiological model. The MESA system offers computational advantages over existing epidemiological models and enables a broader array of stochastic analyses of model runs to be conducted because of those computational advantages. However, it has only been demonstrated on foreign animal diseases. This paper applied the MESA modeling methodology to humanmore » epidemiology. The methodology divided 2000 US Census data at the census tract level into school-bound children, work-bound workers, elderly, and stay at home individuals. The model simulated mixing among these groups by incorporating schools, workplaces, households, and long-distance travel via airports. A baseline scenario with fixed input parameters was run for a nationwide influenza outbreak using relatively simple social distancing countermeasures. Analysis from the baseline scenario showed one of three possible results: (1) the outbreak burned itself out before it had a chance to spread regionally, (2) the outbreak spread regionally and lasted a relatively long time, although constrained geography enabled it to eventually be contained without affecting a disproportionately large number of people, or (3) the outbreak spread through air travel and lasted a long time with unconstrained geography, becoming a nationwide pandemic. These results are consistent with empirical influenza outbreak data. The results showed that simply scaling up a regional small-scale model is unlikely to account for all the complex variables and their interactions involved in a nationwide outbreak. There are several limitations of the methodology that should be explored in future work including validating the model against reliable historical disease data, improving contact rates, spread methods, and disease parameters through discussions with epidemiological experts, and incorporating realistic behavioral assumptions.« less

Infrastructure Analysis Tools: A Focus on Cash Flow Analysis (Presentation)

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

Melaina, M.; Penev, M.

2012-09-01

NREL has developed and maintains a variety of infrastructure analysis models for the U.S. Department of Energy. Business case analysis has recently been added to this tool set. This presentation focuses on cash flow analysis. Cash flows depend upon infrastructure costs, optimized spatially and temporally, and assumptions about financing and revenue. NREL has incorporated detailed metrics on financing and incentives into the models. Next steps in modeling include continuing to collect feedback on regional/local infrastructure development activities and 'roadmap' dynamics, and incorporating consumer preference assumptions on infrastructure to provide direct feedback between vehicles and station rollout.

Statistical Field Estimation for Complex Coastal Regions and Archipelagos (PREPRINT)

DTIC Science & Technology

2011-04-09

and study the computational properties of these schemes. Specifically, we extend a multiscale Objective Analysis (OA) approach to complex coastal...computational properties of these schemes. Specifically, we extend a multiscale Objective Analysis (OA) approach to complex coastal regions and... multiscale free-surface code builds on the primitive-equation model of the Harvard Ocean Predic- tion System (HOPS, Haley et al. (2009)). Additionally

Development of lichen response indexes using a regional gradient modeling approach for large-scale monitoring of forests

Treesearch

Susan Will-Wolf; Peter Neitlich

2010-01-01

Development of a regional lichen gradient model from community data is a powerful tool to derive lichen indexes of response to environmental factors for large-scale and long-term monitoring of forest ecosystems. The Forest Inventory and Analysis (FIA) Program of the U.S. Department of Agriculture Forest Service includes lichens in its national inventory of forests of...

DYNARIP: A technique for regional forest inventory projection and policy analysis

Treesearch

William A. Bechtold

1984-01-01

DYNARIP is a policy-oriented model capable of tracking all of the treatments and disturbances experienced by the forest resources of an entire State or regional area. It can also isolate the impact of any one of the 27 man-caused or natural disturbances (including natural succession and forest land-base changes). The model is driven by empirical rates of change as...

Mathematical modelling of respiratory syncytial virus (RSV): vaccination strategies and budget applications.

PubMed

Acedo, L; Díez-Domingo, J; Moraño, J-A; Villanueva, R-J

2010-06-01

We propose an age-structured mathematical model for respiratory syncytial virus in which children aged <1 year are especially considered. Real data on hospitalized children in the Spanish region of Valencia were used in order to determine some seasonal parameters of the model. Weekly predictions of the number of children aged <1 year that will be hospitalized in the following years in Valencia are presented using this model. Results are applied to estimate the regional cost of paediatric hospitalizations and to perform a cost-effectiveness analysis of possible vaccination strategies.

WASP8 Workshop June 2018

EPA Pesticide Factsheets

US EPA Region 4 and the National Water Quality Modeling Work Group is proud to sponsor a 5-day workshop on water quality principles/modeling using the Water Quality Analysis Simulation Program (WASP).

Empirical research on coordination evaluation and sustainable development mechanism of regional logistics and new-type urbanization: a panel data analysis from 2000 to 2015 for Liaoning Province in China.

PubMed

Sun, Qiang

2017-06-01

As the largest developing country in the world, China has witnessed fast-paced urbanization over the past three decades with rapid economic growth. In fact, urbanization has been not only shown to promote economic growth and improve the livelihood of people but also can increase demands of regional logistics. Therefore, a better understanding of the relationship between urbanization and regional logistics is important for China's future sustainable development. The development of urban residential area and heterogeneous, modern society as well regional logistics are running two abreast. The regional logistics can promote the development of new-type urbanization jointly by promoting industrial concentration and logistics demand, enhancing the residents' quality of life and improving the infrastructure and logistics technology. In this paper, the index system and evaluation model for evaluating the development of regional logistics and the new-type urbanization are constructed. Further, the econometric analysis is utilized such as correlation analysis, co-integration test, and error correction model to explore relationships of the new-type urbanization development and regional logistics development in Liaoning Province. The results showed that there was a long-term stable equilibrium relationship between the new-type urbanization and regional logistics. The findings have important implications for Chinese policymakers that on the path towards a sustainable urbanization and regional reverse, this must be taken into consideration. The paper concludes providing some strategies that might be helpful to the policymakers in formulating development policies for sustainable urbanization.

Natural and human-induced terrestrial water storage change: A global analysis using hydrological models and GRACE

NASA Astrophysics Data System (ADS)

Felfelani, Farshid; Wada, Yoshihide; Longuevergne, Laurent; Pokhrel, Yadu N.

2017-10-01

Hydrological models and the data derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission have been widely used to study the variations in terrestrial water storage (TWS) over large regions. However, both GRACE products and model results suffer from inherent uncertainties, calling for the need to make a combined use of GRACE and models to examine the variations in total TWS and their individual components, especially in relation to natural and human-induced changes in the terrestrial water cycle. In this study, we use the results from two state-of-the-art hydrological models and different GRACE spherical harmonic products to examine the variations in TWS and its individual components, and to attribute the changes to natural and human-induced factors over large global river basins. Analysis of the spatial patterns of the long-term trend in TWS from the two models and GRACE suggests that both models capture the GRACE-measured direction of change, but differ from GRACE as well as each other in terms of the magnitude over different regions. A detailed analysis of the seasonal cycle of TWS variations over 30 river basins shows notable differences not only between models and GRACE but also among different GRACE products and between the two models. Further, it is found that while one model performs well in highly-managed river basins, it fails to reproduce the GRACE-observed signal in snow-dominated regions, and vice versa. The isolation of natural and human-induced changes in TWS in some of the managed basins reveals a consistently declining TWS trend during 2002-2010, however; significant differences are again obvious both between GRACE and models and among different GRACE products and models. Results from the decomposition of the TWS signal into the general trend and seasonality indicate that both models do not adequately capture both the trend and seasonality in the managed or snow-dominated basins implying that the TWS variations from a single model cannot be reliably used for all global regions. It is also found that the uncertainties arising from climate forcing datasets can introduce significant additional uncertainties, making direct comparison of model results and GRACE products even more difficult. Our results highlight the need to further improve the representation of human land-water management and snow processes in large-scale models to enable a reliable use of models and GRACE to study the changes in freshwater systems in all global regions.

Uncertainties in Earthquake Loss Analysis: A Case Study From Southern California

NASA Astrophysics Data System (ADS)

Mahdyiar, M.; Guin, J.

2005-12-01

Probabilistic earthquake hazard and loss analyses play important roles in many areas of risk management, including earthquake related public policy and insurance ratemaking. Rigorous loss estimation for portfolios of properties is difficult since there are various types of uncertainties in all aspects of modeling and analysis. It is the objective of this study to investigate the sensitivity of earthquake loss estimation to uncertainties in regional seismicity, earthquake source parameters, ground motions, and sites' spatial correlation on typical property portfolios in Southern California. Southern California is an attractive region for such a study because it has a large population concentration exposed to significant levels of seismic hazard. During the last decade, there have been several comprehensive studies of most regional faults and seismogenic sources. There have also been detailed studies on regional ground motion attenuations and regional and local site responses to ground motions. This information has been used by engineering seismologists to conduct regional seismic hazard and risk analysis on a routine basis. However, one of the more difficult tasks in such studies is the proper incorporation of uncertainties in the analysis. From the hazard side, there are uncertainties in the magnitudes, rates and mechanisms of the seismic sources and local site conditions and ground motion site amplifications. From the vulnerability side, there are considerable uncertainties in estimating the state of damage of buildings under different earthquake ground motions. From an analytical side, there are challenges in capturing the spatial correlation of ground motions and building damage, and integrating thousands of loss distribution curves with different degrees of correlation. In this paper we propose to address some of these issues by conducting loss analyses of a typical small portfolio in southern California, taking into consideration various source and ground motion uncertainties. The approach is designed to integrate loss distribution functions with different degrees of correlation for portfolio analysis. The analysis is based on USGS 2002 regional seismicity model.

PET brain kinetics studies of 11C-ITMM and 11C-ITDM,radioprobes for metabotropic glutamate receptor type 1, in a nonhuman primate

PubMed Central

Yamasaki, Tomoteru; Maeda, Jun; Fujinaga, Masayuki; Nagai, Yuji; Hatori, Akiko; Yui, Joji; Xie, Lin; Nengaki, Nobuki; Zhang, Ming-Rong

2014-01-01

The metabotropic glutamate receptor type 1 (mGluR1) is a novel target protein for the development of new drugs against central nervous system disorders. Recently, we have developed 11C-labeled PET probes 11C-ITMM and 11C-ITDM, which demonstrate similar profiles, for imaging of mGluR1. In the present study, we compared 11C-ITMM and 11C-ITDM PET imaging and quantitative analysis in the monkey brain. Respective PET images showed similar distribution of uptake in the cerebellum, thalamus, and cingulate cortex. Slightly higher uptake was detected with 11C-ITDM than with 11C-ITMM. For the kinetic analysis using the two-tissue compartment model (2-TCM), the distribution volume (VT) in the cerebellum, an mGluR1-rich region in the brain, was 2.5 mL∙cm-3 for 11C-ITMM and 3.6 mL∙cm-3 for 11C-ITDM. By contrast, the VT in the pons, a region with negligible mGluR1 expression, was similarly low for both radiopharmaceuticals. Based on these results, we performed noninvasive PET quantitative analysis with general reference tissue models using the time-activity curve of the pons as a reference region. We confirmed the relationship and differences between the reference tissue models and 2-TCM using correlational scatter plots and Bland-Altman plots analyses. Although the scattergrams of both radiopharmaceuticals showed over- or underestimations of reference tissue model-based the binding potentials against 2-TCM, there were no significant differences between the two kinetic analysis models. In conclusion, we first demonstrated the potentials of 11C-ITMM and 11C-ITDM for noninvasive PET quantitative analysis using reference tissue models. In addition, our findings suggest that 11C-ITDM may be superior to 11C-ITMM as a PET probe for imaging of mGluR1, because regional VT values in PET with 11C-ITDM were higher than those of 11C-ITMM. Clinical studies of 11C-ITDM in humans will be necessary in the future. PMID:24795840

PET brain kinetics studies of (11)C-ITMM and (11)C-ITDM,radioprobes for metabotropic glutamate receptor type 1, in a nonhuman primate.

PubMed

Yamasaki, Tomoteru; Maeda, Jun; Fujinaga, Masayuki; Nagai, Yuji; Hatori, Akiko; Yui, Joji; Xie, Lin; Nengaki, Nobuki; Zhang, Ming-Rong

2014-01-01

The metabotropic glutamate receptor type 1 (mGluR1) is a novel target protein for the development of new drugs against central nervous system disorders. Recently, we have developed (11)C-labeled PET probes (11)C-ITMM and (11)C-ITDM, which demonstrate similar profiles, for imaging of mGluR1. In the present study, we compared (11)C-ITMM and (11)C-ITDM PET imaging and quantitative analysis in the monkey brain. Respective PET images showed similar distribution of uptake in the cerebellum, thalamus, and cingulate cortex. Slightly higher uptake was detected with (11)C-ITDM than with (11)C-ITMM. For the kinetic analysis using the two-tissue compartment model (2-TCM), the distribution volume (VT) in the cerebellum, an mGluR1-rich region in the brain, was 2.5 mL∙cm(-3) for (11)C-ITMM and 3.6 mL∙cm(-3) for (11)C-ITDM. By contrast, the VT in the pons, a region with negligible mGluR1 expression, was similarly low for both radiopharmaceuticals. Based on these results, we performed noninvasive PET quantitative analysis with general reference tissue models using the time-activity curve of the pons as a reference region. We confirmed the relationship and differences between the reference tissue models and 2-TCM using correlational scatter plots and Bland-Altman plots analyses. Although the scattergrams of both radiopharmaceuticals showed over- or underestimations of reference tissue model-based the binding potentials against 2-TCM, there were no significant differences between the two kinetic analysis models. In conclusion, we first demonstrated the potentials of (11)C-ITMM and (11)C-ITDM for noninvasive PET quantitative analysis using reference tissue models. In addition, our findings suggest that (11)C-ITDM may be superior to (11)C-ITMM as a PET probe for imaging of mGluR1, because regional VT values in PET with (11)C-ITDM were higher than those of (11)C-ITMM. Clinical studies of (11)C-ITDM in humans will be necessary in the future.

High-risk regions and outbreak modelling of tularemia in humans.

PubMed

Desvars-Larrive, A; Liu, X; Hjertqvist, M; Sjöstedt, A; Johansson, A; Rydén, P

2017-02-01

Sweden reports large and variable numbers of human tularemia cases, but the high-risk regions are anecdotally defined and factors explaining annual variations are poorly understood. Here, high-risk regions were identified by spatial cluster analysis on disease surveillance data for 1984-2012. Negative binomial regression with five previously validated predictors (including predicted mosquito abundance and predictors based on local weather data) was used to model the annual number of tularemia cases within the high-risk regions. Seven high-risk regions were identified with annual incidences of 3·8-44 cases/100 000 inhabitants, accounting for 56·4% of the tularemia cases but only 9·3% of Sweden's population. For all high-risk regions, most cases occurred between July and September. The regression models explained the annual variation of tularemia cases within most high-risk regions and discriminated between years with and without outbreaks. In conclusion, tularemia in Sweden is concentrated in a few high-risk regions and shows high annual and seasonal variations. We present reproducible methods for identifying tularemia high-risk regions and modelling tularemia cases within these regions. The results may help health authorities to target populations at risk and lay the foundation for developing an early warning system for outbreaks.

Using High Resolution Regional Climate Models to Quantify the Snow Albedo Feedback in a Region of Complex Terrain

NASA Astrophysics Data System (ADS)

Letcher, T.; Minder, J. R.

2015-12-01

High resolution regional climate models are used to characterize and quantify the snow albedo feedback (SAF) over the complex terrain of the Colorado Headwaters region. Three pairs of 7-year control and pseudo global warming simulations (with horizontal grid spacings of 4, 12, and 36 km) are used to study how the SAF modifies the regional climate response to a large-scale thermodynamic perturbation. The SAF substantially enhances warming within the Headwaters domain, locally as much as 5 °C in regions of snow loss. The SAF also increases the inter-annual variability of the springtime warming within Headwaters domain under the perturbed climate. Linear feedback analysis is used quantify the strength of the SAF. The SAF attains a maximum value of 4 W m-2 K-1 during April when snow loss coincides with strong incoming solar radiation. On sub-seasonal timescales, simulations at 4 km and 12 km horizontal grid-spacing show good agreement in the strength and timing of the SAF, whereas a 36km simulation shows greater discrepancies that are tired to differences in snow accumulation and ablation caused by smoother terrain. An analysis of the regional energy budget shows that transport by atmospheric motion acts as a negative feedback to regional warming, damping the effects of the SAF. On the mesoscale, this transport causes non-local warming in locations with no snow. The methods presented here can be used generally to quantify the role of the SAF in other regional climate modeling experiments.

Improving emissions inventories in Mexico through systematic analysis of model performance along C-130 and DC-8 flight tracks during MILAGRO

NASA Astrophysics Data System (ADS)

Mena-Carrasco, M.; Carmichael, G. R.; Campbell, J. E.; Tang, Y.; Chai, T.

2007-05-01

During the MILAGRO campaign in March 2006 the University of Iowa provided regional air quality forecasting for scientific flight planning for the C-130 and DC-8. Model performance showed positive bias of ozone prediction (~15ppbv), associated to overpredictions in precursor concentrations (~2.15 ppbv NOy and ~1ppmv ARO1). Model bias showed a distinct geographical pattern in which the higher values were in and near Mexico City. Newer runs in which NOx and VOC emissions were decreased improved ozone prediction, decreasing bias and increasing model correlation, at the same time reducing regional bias over Mexico. This work will evaluate model performance using the newly published Mexico National Emissions Inventory, and the introduction of data assimilation to recover emissions scaling factors to optimize model performance. Finally the results of sensitivity runs showing the regional impact of Mexico City emissions on ozone concentrations will be shown, along with the influence of Mexico City aerosol concentrations on regional photochemistry.

Assessment of the performance of CORDEX-South Asia experiments for monsoonal precipitation over the Himalayan region during present climate: part I

NASA Astrophysics Data System (ADS)

Ghimire, S.; Choudhary, A.; Dimri, A. P.

2018-04-01

Analysis of regional climate simulations to evaluate the ability of 11 Coordinated Regional Climate Downscaling Experiment in South Asia experiments (CORDEX-South Asia) along with their ensemble to produce precipitation from June to September (JJAS) over the Himalayan region have been carried out. These suite of 11 combinations come from 6 regional climate models (RCMs) driven with 10 initial and boundary conditions from different global climate models and are collectively referred here as 11 CORDEX South Asia experiments. All the RCMs use a similar domain and are having similar spatial resolution of 0.44° ( 50 km). The set of experiments are considered to study precipitation sensitivity associated with the Indian summer monsoon (ISM) over the study region. This effort is made as ISM plays a vital role in summertime precipitation over the Himalayan region which acts as driver for the sustenance of habitat, population, crop, glacier, hydrology etc. In addition, so far the summer monsoon precipitation climatology over the Himalayan region has not been studied with the help of CORDEX data. Thus this study is initiated to evaluate the ability of the experiments and their ensemble in reproducing the characteristics of summer monsoon precipitation over Himalayan region, for the present climate (1970-2005). The precipitation climatology, annual precipitation cycles and interannual variabilities from each simulation have been assessed against the gridded observational dataset: Asian Precipitation-Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources for the given time period. Further, after the selection of the better performing experiment the frequency distribution of precipitation was also studied. In this study, an approach has also been made to study the degree of agreement among individual experiments as a way to quantify the uncertainty among them. The experiments though show a wide variation among themselves and individually over time and space in simulating precipitation distribution over the study region, but noticeably along the foothills of the Himalayas all the simulations show dry precipitation bias against the corresponding observation. In addition, as we move towards higher elevation regions these experiments in general show wet bias. The experiment driven by EC-EARTH global climate model and downscaled using Rossby Center regional Atmospheric model version 4 developed by Swedish Meteorological and Hydrological Institute (SMHI-RCA4) simulate precipitation closely in correspondence with the observation. The ensemble outperforms the result of individual experiments. Correspondingly, different kinds of statistical analysis like spatial and temporal correlation, Taylor diagram, frequency distribution and scatter plot have been performed to compare the model output with observation and to explain the associated resemblance, robustness and dynamics statistically. Through the bias and ensemble spread analysis, an estimation of the uncertainty of the model fields and the degree of agreement among them has also been carried out in this study. Overview of the study suggests that these experiments facilitate precipitation evolution and structure over the Himalayan region with certain degree of uncertainty.

Development of Advanced Modeling Tools for Hotpot Analysis of Transportation Emissions

DOT National Transportation Integrated Search

2009-07-29

Hot-spot analysis, also known as project-level analysis, assesses impacts of transportation emissions on local air pollution of carbon monoxide (CO), air toxics and particulate matter (PM). It is required for regional transportation plans (RTP), tran...

Impact of a variational objective analysis scheme on a regional area numerical model: The Italian Air Force Weather Service experience

NASA Astrophysics Data System (ADS)

Bonavita, M.; Torrisi, L.

2005-03-01

A new data assimilation system has been designed and implemented at the National Center for Aeronautic Meteorology and Climatology of the Italian Air Force (CNMCA) in order to improve its operational numerical weather prediction capabilities and provide more accurate guidance to operational forecasters. The system, which is undergoing testing before operational use, is based on an “observation space” version of the 3D-VAR method for the objective analysis component, and on the High Resolution Regional Model (HRM) of the Deutscher Wetterdienst (DWD) for the prognostic component. Notable features of the system include a completely parallel (MPI+OMP) implementation of the solution of analysis equations by a preconditioned conjugate gradient descent method; correlation functions in spherical geometry with thermal wind constraint between mass and wind field; derivation of the objective analysis parameters from a statistical analysis of the innovation increments.

Influence of Land Cover Heterogeneity, Land-Use Change and Management on the Regional Carbon Cycle in the Upper Midwest USA as Evaluated by High-Density Observations and a Dynamic Ecosystem Model

NASA Astrophysics Data System (ADS)

Desai, A. R.; Bolstad, P. V.; Moorcroft, P. R.; Davis, K. J.

2005-12-01

The interplay between land use change, forest management and land cover variability complicates the ability to characterize regional scale (10-1000 km) exchange of carbon dioxide between the land surface and atmosphere in heterogeneous landscapes. An attempt was made to observe and model these factors and their influence on the regional carbon cycle across the upper Midwest USA. A high density of eddy-covariance carbon flux, micrometeorology, carbon dioxide mixing ratio, stand-scale biometry and canopy component flux observations have been occurring in this area as part of the Chequamegon Ecosystem-Atmosphere Study. Observations limited to sampling only dominant stands and coarse-resolution biogeochemical models limited to biome-scale parameterization neither accurately capture the variability of carbon fluxes measured by the network of eddy covariance towers nor match the regional-scale carbon flux inferred from very tall tower eddy covariance measurements and multi-site upscaling. Analysis of plot level biometric data, U.S. Forest Service Forest Inventory Analysis data and high-resolution land cover data around the tall tower revealed significant variations in vegetation type, stand age, canopy stocking and structure. Wetlands, clearcuts and recent natural disturbances occur in characteristic small non-uniformly distributed patches that aggregate to form more than 30% of the landscape. The Ecosystem Demography model, a dynamic ecosystem model that incorporates vegetation heterogeneity, canopy structure, stand age, disturbance, land use change and forest management, was parameterized with regional biometric data and meteorology, historical records of land management and high-resolution satellite land cover maps. The model will be used to examine the significance of past land use change, natural disturbance history and current forest management in explaining landscape structure and regional carbon fluxes observed in the region today.

Regional tectonic analysis of Venus equatorial highlands and comparison with Earth-based Magellan radar images

NASA Technical Reports Server (NTRS)

Williams, David R.; Wetherill, George

1993-01-01

Research on regional tectonic analysis of Venus equatorial highlands and comparison with earth-based and Magellan radar images is presented. Over the past two years, the tectonic analysis of Venus performed centered on global properties of the planet, in order to understand fundamental aspects of the dynamics of the mantle and lithosphere of Venus. These include studies pertaining to the original constitutive and thermal character of the planet, as well as the evolution of Venus through time, and the present day tectonics. Parameterized convection models of the Earth and Venus were developed. The parameterized convection code was reformulated to model Venus with an initially hydrous mantle to determine how the cold-trap could affect the evolution of the planet.

IMPACT OF TRMM PRECIPITATION ON CPTEC’S RPSAS ANALYSIS

NASA Astrophysics Data System (ADS)

Herdies, D. L.; Bastarz, C. F.; Fernandez, J. P.

2009-12-01

In this work a data assimilation study was performed to assess the impact of estimated precipitation from TRMM (Tropical Rainfall Measuring Mission) on the CPTEC (Centro de Previsão de Tempo e Estudos Climáticos at Brasil) RPSAS (Regional Physical-space Statistical Analysis System) analyses and the Eta model forecast over the region of La Plata Basin, during a case o MCC (Mesoscale Convective Complex) occurred between 22th and 23th January 2003. The data assimilation system RPSAS and the mesoscale regional Eta model (both with 20km of spatial resolution) were run together with and without the TRMM precipitation. Is this study the assimilation of precipitation is basically a nudging process and is performed during the first guess stage by the Eta model, like in the NCEP (National Centers for Environmental Predictions) EDAS (Eta Data Assimilation System) precipitation data assimilation. During this process the model adjusts the precipitation by comparing, at which grid point and at which time step, the model precipitation against the TRMM precipitation. Doing this some adjustments are made on the latent heat vertical profile, water vapor mixing ratio and relative humidity, by considering the Betts-Miller-Janjic convective parameterization. On the next step, the RPSAS produces an analysis which covers most of the South America and the adjacent oceans. From this analysis the Eta model produces 6h, 12h, 18h and 24h forecast. Data collected from the SALLJEX (South America Low Level Jet EXperiment) was used to compare the forecasts of the model and the CPTEC 40km Regional Reanalysis was used to compare with the RPSAS analyses. Some preliminary results show that the precipitation assimilation improves the first hours of the forecast (typically 6h). The variables verified were the zonal and meridional wind, geopotential height and the precipitation. The convective precipitation fields were improved, mainly over the 6h forecast. This is an important improvement because the first guess field will serve as an analysis of the next forecast window. Also were noticed that the mean error for those variables was reduced (principally for the zonal wind). This reveals that with an improved first guess field, the model was able to detect the MCC occurred in the north of Argentina, due to the improved representation of the winds fields (direction and intensity), pressure and the surface variables.

Asia-MIP: Multi Model-data Synthesis of Terrestrial Carbon Cycles in Asia

NASA Astrophysics Data System (ADS)

Ichii, K.; Kondo, M.; Ito, A.; Kang, M.; Sasai, T.; SATO, H.; Ueyama, M.; Kobayashi, H.; Saigusa, N.; Kim, J.

2013-12-01

Asia, which is characterized by monsoon climate and intense human activities, is one of the prominent understudied regions in terms of terrestrial carbon budgets and mechanisms of carbon exchange. To better understand terrestrial carbon cycle in Asia, we initiated multi-model and data intercomparison project in Asia (Asia-MIP). We analyzed outputs from multiple approaches: satellite-based observations (AVHRR and MODIS) and related products, empirically upscaled estimations (Support Vector Regression) using eddy-covariance observation network in Asia (AsiaFlux, CarboEastAsia, FLUXNET), ~10 terrestrial biosphere models (e.g. BEAMS, Biome-BGC, LPJ, SEIB-DGVM, TRIFFID, VISIT models), and atmospheric inversion analysis (e.g. TransCom models). We focused on the two difference temporal coverage: long-term (30 years; 1982-2011) and decadal (10 years; 2001-2010; data intensive period) scales. The regions of covering Siberia, Far East Asia, East Asia, Southeast Asia and South Asia (60-80E, 10S-80N), was analyzed in this study for assessing the magnitudes, interannual variability, and key driving factors of carbon cycles. We will report the progress of synthesis effort to quantify terrestrial carbon budget in Asia. First, we analyzed the recent trends in Gross Primary Productivities (GPP) using satellite-based observation (AVHRR) and multiple terrestrial biosphere models. We found both model outputs and satellite-based observation consistently show an increasing trend in GPP in most of the regions in Asia. Mechanisms of the GPP increase were analyzed using models, and changes in temperature and precipitation play dominant roles in GPP increase in boreal and temperate regions, whereas changes in atmospheric CO2 and precipitation are important in tropical regions. However, their relative contributions were different. Second, in the decadal analysis (2001-2010), we found that the negative GPP and carbon uptake anomalies in 2003 summer in Far East Asia is one of the largest anomalies with high consistency among methods from 2001 to 2010 period. The model analysis showed that these anomalies were produced by different climate factors among the models. Therefore, we conclude that inconsistency of model sensitivity to meteorological anomalies is an important issue to be improved in future. Acknowledgement The study is financially supported by the Environment Research and Technology Development Fund (RFa-1201) of the Ministry of the Environment of Japan and JSPS KAKENHI Grant Number 25281003.

A strategy to study regional hydrology and terrestrial ecosystem processes using satellite remote sensing, ground-based data and computer modeling

NASA Technical Reports Server (NTRS)

Vorosmarty, C.; Grace, A.; Moore, B.; Choudhury, B.; Willmott, C. J.

1990-01-01

A strategy is presented for integrating scanning multichannel microwave radiometer data from the Nimbus-7 satellite with meteorological station records and computer simulations of land surface hydrology, terrestrial nutrient cycling, and trace gas emission. Analysis of the observations together with radiative transfer analysis shows that in the tropics the temporal and spatial variations of the polarization difference are determined primarily by the structure and phenology of vegetation and seasonal inundations of major rivers and wetlands. It is concluded that the proposed surface hydrology model, along with climatological records, and, potentially, 37-GHz data for phenology, will provide inputs to a terrestrial ecosystem model that predicts regional net primary production and CO2 gas exchange.

Improved Impact of Atmospheric Infrared Sounder (AIRS) Radiance Assimilation in Numerical Weather Prediction

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; Chou, Shih-Hung; Jedlovec, Gary

2012-01-01

Improvements to global and regional numerical weather prediction (NWP) have been demonstrated through assimilation of data from NASA s Atmospheric Infrared Sounder (AIRS). Current operational data assimilation systems use AIRS radiances, but impact on regional forecasts has been much smaller than for global forecasts. Retrieved profiles from AIRS contain much of the information that is contained in the radiances and may be able to reveal reasons for this reduced impact. Assimilating AIRS retrieved profiles in an identical analysis configuration to the radiances, tracking the quantity and quality of the assimilated data in each technique, and examining analysis increments and forecast impact from each data type can yield clues as to the reasons for the reduced impact. By doing this with regional scale models individual synoptic features (and the impact of AIRS on these features) can be more easily tracked. This project examines the assimilation of hyperspectral sounder data used in operational numerical weather prediction by comparing operational techniques used for AIRS radiances and research techniques used for AIRS retrieved profiles. Parallel versions of a configuration of the Weather Research and Forecasting (WRF) model with Gridpoint Statistical Interpolation (GSI) that mimics the analysis methodology, domain, and observational datasets for the regional North American Mesoscale (NAM) model run at the National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) are run to examine the impact of each type of AIRS data set. The first configuration will assimilate the AIRS radiance data along with other conventional and satellite data using techniques implemented within the operational system; the second configuration will assimilate AIRS retrieved profiles instead of AIRS radiances in the same manner. Preliminary results of this study will be presented and focus on the analysis impact of the radiances and profiles for selected cases.

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

PubMed

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

2016-01-01

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

An analysis of the DuPage County Regional Office of Education physics exam

NASA Astrophysics Data System (ADS)

Muehsler, Hans

In 2009, the DuPage County Regional Office of Education (ROE) tasked volunteer physics teachers with creating a basic skills physics exam reflecting what the participants valued and shared in common across curricula. Mechanics, electricity & magnetism (E&M), and wave phenomena emerged as the primary constructs. The resulting exam was intended for first-exposure physics students. The most recently completed version was psychometrically assessed for unidimensionality within the constructs using a robust WLS structural equation model and for reliability. An item analysis using a 3-PL IRT model was performed on the mechanics items and a 2-PL IRT model was performed on the E&M and waves items; a distractor analysis was also performed on all items. Lastly, differential item functioning (DIF) and differential test functioning (DTF) analyses, using the Mantel-Haenszel procedure, were performed using gender, ethnicity, year in school, ELL, physics level, and math level as groupings.

Spatial modeling of cutaneous leishmaniasis in the Andean region of Colombia.

PubMed

Pérez-Flórez, Mauricio; Ocampo, Clara Beatriz; Valderrama-Ardila, Carlos; Alexander, Neal

2016-06-27

The objective of this research was to identify environmental risk factors for cutaneous leishmaniasis (CL) in Colombia and map high-risk municipalities. The study area was the Colombian Andean region, comprising 715 rural and urban municipalities. We used 10 years of CL surveillance: 2000-2009. We used spatial-temporal analysis - conditional autoregressive Poisson random effects modelling - in a Bayesian framework to model the dependence of municipality-level incidence on land use, climate, elevation and population density. Bivariable spatial analysis identified rainforests, forests and secondary vegetation, temperature, and annual precipitation as positively associated with CL incidence. By contrast, livestock agroecosystems and temperature seasonality were negatively associated. Multivariable analysis identified land use - rainforests and agro-livestock - and climate - temperature, rainfall and temperature seasonality - as best predictors of CL. We conclude that climate and land use can be used to identify areas at high risk of CL and that this approach is potentially applicable elsewhere in Latin America.

Defining an Analytic Framework to Evaluate Quantitative MRI Markers of Traumatic Axonal Injury: Preliminary Results in a Mouse Closed Head Injury Model

PubMed Central

Sadeghi, N.; Namjoshi, D.; Irfanoglu, M. O.; Wellington, C.; Diaz-Arrastia, R.

2017-01-01

Diffuse axonal injury (DAI) is a hallmark of traumatic brain injury (TBI) pathology. Recently, the Closed Head Injury Model of Engineered Rotational Acceleration (CHIMERA) was developed to generate an experimental model of DAI in a mouse. The characterization of DAI using diffusion tensor magnetic resonance imaging (MRI; diffusion tensor imaging, DTI) may provide a useful set of outcome measures for preclinical and clinical studies. The objective of this study was to identify the complex neurobiological underpinnings of DTI features following DAI using a comprehensive and quantitative evaluation of DTI and histopathology in the CHIMERA mouse model. A consistent neuroanatomical pattern of pathology in specific white matter tracts was identified across ex vivo DTI maps and photomicrographs of histology. These observations were confirmed by voxelwise and regional analysis of DTI maps, demonstrating reduced fractional anisotropy (FA) in distinct regions such as the optic tract. Similar regions were identified by quantitative histology and exhibited axonal damage as well as robust gliosis. Additional analysis using a machine-learning algorithm was performed to identify regions and metrics important for injury classification in a manner free from potential user bias. This analysis found that diffusion metrics were able to identify injured brains almost with the same degree of accuracy as the histology metrics. Good agreement between regions detected as abnormal by histology and MRI was also found. The findings of this work elucidate the complexity of cellular changes that give rise to imaging abnormalities and provide a comprehensive and quantitative evaluation of the relative importance of DTI and histological measures to detect brain injury. PMID:28966972

Direct comparison of low- and mid-frequency Raman spectroscopy for quantitative solid-state pharmaceutical analysis.

PubMed

Lipiäinen, Tiina; Fraser-Miller, Sara J; Gordon, Keith C; Strachan, Clare J

2018-02-05

This study considers the potential of low-frequency (terahertz) Raman spectroscopy in the quantitative analysis of ternary mixtures of solid-state forms. Direct comparison between low-frequency and mid-frequency spectral regions for quantitative analysis of crystal form mixtures, without confounding sampling and instrumental variations, is reported for the first time. Piroxicam was used as a model drug, and the low-frequency spectra of piroxicam forms β, α2 and monohydrate are presented for the first time. These forms show clear spectral differences in both the low- and mid-frequency regions. Both spectral regions provided quantitative models suitable for predicting the mixture compositions using partial least squares regression (PLSR), but the low-frequency data gave better models, based on lower errors of prediction (2.7, 3.1 and 3.2% root-mean-square errors of prediction [RMSEP] values for the β, α2 and monohydrate forms, respectively) than the mid-frequency data (6.3, 5.4 and 4.8%, for the β, α2 and monohydrate forms, respectively). The better performance of low-frequency Raman analysis was attributed to larger spectral differences between the solid-state forms, combined with a higher signal-to-noise ratio. Copyright © 2017 Elsevier B.V. All rights reserved.

Detecting robust signals of interannual variability of gross primary productivity in Asia from multiple terrestrial carbon cycle models and long-term satellite-based vegetation data

NASA Astrophysics Data System (ADS)

Ichii, K.; Kondo, M.; Ueyama, M.; Kato, T.; Ito, A.; Sasai, T.; Sato, H.; Kobayashi, H.; Saigusa, N.

2014-12-01

Long term record of satellite-based terrestrial vegetation are important to evaluate terrestrial carbon cycle models. In this study, we demonstrate how multiple satellite observation can be used for evaluating past changes in gross primary productivity (GPP) and detecting robust anomalies in terrestrial carbon cycle in Asia through our model-data synthesis analysis, Asia-MIP. We focused on the two different temporal coverages: long-term (30 years; 1982-2011) and decadal (10 years; 2001-2011; data intensive period) scales. We used a NOAA/AVHRR NDVI record for long-term analysis and multiple satellite data and products (e.g. Terra-MODIS, SPOT-VEGETATION) as historical satellite data, and multiple terrestrial carbon cycle models (e.g. BEAMS, Biome-BGC, ORCHIDEE, SEIB-DGVM, and VISIT). As a results of long-term (30 years) trend analysis, satellite-based time-series data showed that approximately 40% of the area has experienced a significant increase in the NDVI, while only a few areas have experienced a significant decreasing trend over the last 30 years. The increases in the NDVI were dominant in the sub-continental regions of Siberia, East Asia, and India. Simulations using the terrestrial biosphere models also showed significant increases in GPP, similar to the results for the NDVI, in boreal and temperate regions. A modeled sensitivity analysis showed that the increases in GPP are explained by increased temperature and precipitation in Siberia. Precipitation, solar radiation, CO2fertilization and land cover changes are important factors in the tropical regions. However, the relative contributions of each factor to GPP changes are different among the models. Year-to-year variations of terrestrial GPP were overall consistently captured by the satellite data and terrestrial carbon cycle models if the anomalies are large (e.g. 2003 summer GPP anomalies in East Asia and 2002 spring GPP anomalies in mid to high latitudes). The behind mechanisms can be consistently explained by the models if the anomalies are caused in the low temperature regions (e.g. spring in Northern Asia). However, water-driven or radiation-driven GPP anomalies lacks consistent explanation among models. Therefore, terrestrial carbon cycle models require improvement of the sensitivity of climate anomalies to carbon cycles.

A Poisson process approximation for generalized K-5 confidence regions

NASA Technical Reports Server (NTRS)

Arsham, H.; Miller, D. R.

1982-01-01

One-sided confidence regions for continuous cumulative distribution functions are constructed using empirical cumulative distribution functions and the generalized Kolmogorov-Smirnov distance. The band width of such regions becomes narrower in the right or left tail of the distribution. To avoid tedious computation of confidence levels and critical values, an approximation based on the Poisson process is introduced. This aproximation provides a conservative confidence region; moreover, the approximation error decreases monotonically to 0 as sample size increases. Critical values necessary for implementation are given. Applications are made to the areas of risk analysis, investment modeling, reliability assessment, and analysis of fault tolerant systems.

Ozone Temporal Variability in the Subarctic Region: Comparison of Satellite Measurements with Numerical Simulations

NASA Astrophysics Data System (ADS)

Shved, G. M.; Virolainen, Ya. A.; Timofeyev, Yu. M.; Ermolenko, S. I.; Smyshlyaev, S. P.; Motsakov, M. A.; Kirner, O.

2018-01-01

Fourier and wavelet spectra of time series for the ozone column abundance in the atmospheric 0-25 and 25-60 km layers are analyzed from SBUV satellite observations and from numerical simulations based on the RSHU and EMAC models. The analysis uses datasets for three subarctic locations (St. Petersburg, Harestua, and Kiruna) for 2000-2014. The Fourier and wavelet spectra show periodicities in the range from 10 days to 10 years and from 1 day to 2 years, respectively. The comparison of the spectra shows overall agreement between the observational and modeled datasets. However, the analysis has revealed differences both between the measurements and the models and between the models themselves. The differences primarily concern the Rossby wave period region and the 11-year and semiannual periodicities. Possible reasons are given for the differences between the models and the measurements.

Outer satellite atmospheres: Their nature and planetary interactions

NASA Technical Reports Server (NTRS)

Smyth, W. H.; Combi, M. R.

1982-01-01

Significant progress is reported in early modeling analysis of observed sodium cloud images with our new model which includes the oscillating Io plasma torus ionization sink. Both the general w-D morphology of the region B cloud as well as the large spatial gradient seen between the region A and B clouds are found to be consistent with an isotropic flux of sodium atoms from Io. Model analysis of the spatially extended high velocity directional features provided substantial evidence for a magnetospheric wind driven gas escape mechanism from Io. In our efforts to define the source(s) of hydrogen atoms in the Saturn system, major steps were taken in order to understand the role of Titan. We have completed the comparison of the Voyager UVS data with previous Titan model results, as well as the update of the old model computer code to handle the spatially varying ionization sink for H atoms.

Examination of land use models, emphasizing UrbanSim, TELUM, and suitability analysis

DOT National Transportation Integrated Search

2008-08-31

This work provides integrated transportation land use modeling guidance to practitioners in Texas regions of all sizes. The research team synthesized existing land use modeling experiences from MPOs across the country, examined the compatibility of T...

Regional Higher Education Reform Initiatives in Africa: A Comparative Analysis with the Bologna Process

ERIC Educational Resources Information Center

Woldegiorgis, Emnet Tadesse; Jonck, Petronella; Goujon, Anne

2015-01-01

Europe's Bologna Process has been identified as a pioneering approach in regional cooperation with respect to the area of higher education. To address the challenges of African higher education, policymakers are recommending regional cooperation that uses the Bologna Process as a model. Based on these recommendations, the African Union Commission…

MMAB Sea Ice Analysis Page

Science.gov Websites

. Consequently we produce two sorts of field. One is suitable for use by models, the global field. And the other color bar gif of the Alaska Region map Previous Alaska Region Maps NCEP MMAB Interactive Sea Ice Image Generation Animation Alaska Region Sea of Okhotsk and Sea of Japan - current figure concentration color bar

A Skew-t space-varying regression model for the spectral analysis of resting state brain activity.

PubMed

Ismail, Salimah; Sun, Wenqi; Nathoo, Farouk S; Babul, Arif; Moiseev, Alexader; Beg, Mirza Faisal; Virji-Babul, Naznin

2013-08-01

It is known that in many neurological disorders such as Down syndrome, main brain rhythms shift their frequencies slightly, and characterizing the spatial distribution of these shifts is of interest. This article reports on the development of a Skew-t mixed model for the spatial analysis of resting state brain activity in healthy controls and individuals with Down syndrome. Time series of oscillatory brain activity are recorded using magnetoencephalography, and spectral summaries are examined at multiple sensor locations across the scalp. We focus on the mean frequency of the power spectral density, and use space-varying regression to examine associations with age, gender and Down syndrome across several scalp regions. Spatial smoothing priors are incorporated based on a multivariate Markov random field, and the markedly non-Gaussian nature of the spectral response variable is accommodated by the use of a Skew-t distribution. A range of models representing different assumptions on the association structure and response distribution are examined, and we conduct model selection using the deviance information criterion. (1) Our analysis suggests region-specific differences between healthy controls and individuals with Down syndrome, particularly in the left and right temporal regions, and produces smoothed maps indicating the scalp topography of the estimated differences.

Japanese MAGSAT team

NASA Technical Reports Server (NTRS)

Fukushima, N.; Maeda, H.; Yukutake, T.; Tanaka, M.; Miyazaki, Y.; Oshima, S.; Ogawa, K.; Kawamura, M.; Uyeda, S.; Kobayashi, K.

1982-01-01

Construction of a model of the regional magnetic field and investigation of the local magnetic anomalies and their origin were approaches used in attempts to study the crustal structure near Japan and its Antarctic bases. Spatial properties of the regional magnetic field and comparison of the regional model with that derived from MAGSAT data are discussed. Possible causes of the magnetic anomalies, and results of aeromagnetic surveys incorporating gravity and seismic data are explored. Ionospheric and magnetospheric contributions to geomagnetic variations, field-aligned currents, magnetic geomagnetic pulsations, and hydromagnetic waves by analysis of MAGSAT data are also examined.

Meta-analysis of real-time fMRI neurofeedback studies using individual participant data: How is brain regulation mediated?

PubMed

Emmert, Kirsten; Kopel, Rotem; Sulzer, James; Brühl, Annette B; Berman, Brian D; Linden, David E J; Horovitz, Silvina G; Breimhorst, Markus; Caria, Andrea; Frank, Sabine; Johnston, Stephen; Long, Zhiying; Paret, Christian; Robineau, Fabien; Veit, Ralf; Bartsch, Andreas; Beckmann, Christian F; Van De Ville, Dimitri; Haller, Sven

2016-01-01

An increasing number of studies using real-time fMRI neurofeedback have demonstrated that successful regulation of neural activity is possible in various brain regions. Since these studies focused on the regulated region(s), little is known about the target-independent mechanisms associated with neurofeedback-guided control of brain activation, i.e. the regulating network. While the specificity of the activation during self-regulation is an important factor, no study has effectively determined the network involved in self-regulation in general. In an effort to detect regions that are responsible for the act of brain regulation, we performed a post-hoc analysis of data involving different target regions based on studies from different research groups. We included twelve suitable studies that examined nine different target regions amounting to a total of 175 subjects and 899 neurofeedback runs. Data analysis included a standard first- (single subject, extracting main paradigm) and second-level (single subject, all runs) general linear model (GLM) analysis of all participants taking into account the individual timing. Subsequently, at the third level, a random effects model GLM included all subjects of all studies, resulting in an overall mixed effects model. Since four of the twelve studies had a reduced field of view (FoV), we repeated the same analysis in a subsample of eight studies that had a well-overlapping FoV to obtain a more global picture of self-regulation. The GLM analysis revealed that the anterior insula as well as the basal ganglia, notably the striatum, were consistently active during the regulation of brain activation across the studies. The anterior insula has been implicated in interoceptive awareness of the body and cognitive control. Basal ganglia are involved in procedural learning, visuomotor integration and other higher cognitive processes including motivation. The larger FoV analysis yielded additional activations in the anterior cingulate cortex, the dorsolateral and ventrolateral prefrontal cortex, the temporo-parietal area and the visual association areas including the temporo-occipital junction. In conclusion, we demonstrate that several key regions, such as the anterior insula and the basal ganglia, are consistently activated during self-regulation in real-time fMRI neurofeedback independent of the targeted region-of-interest. Our results imply that if the real-time fMRI neurofeedback studies target regions of this regulation network, such as the anterior insula, care should be given whether activation changes are related to successful regulation, or related to the regulation process per se. Furthermore, future research is needed to determine how activation within this regulation network is related to neurofeedback success. Copyright © 2015 Elsevier Inc. All rights reserved.

Regionalized rainfall-runoff model to estimate low flow indices

NASA Astrophysics Data System (ADS)

Garcia, Florine; Folton, Nathalie; Oudin, Ludovic

2016-04-01

Estimating low flow indices is of paramount importance to manage water resources and risk assessments. These indices are derived from river discharges which are measured at gauged stations. However, the lack of observations at ungauged sites bring the necessity of developing methods to estimate these low flow indices from observed discharges in neighboring catchments and from catchment characteristics. Different estimation methods exist. Regression or geostatistical methods performed on the low flow indices are the most common types of methods. Another less common method consists in regionalizing rainfall-runoff model parameters, from catchment characteristics or by spatial proximity, to estimate low flow indices from simulated hydrographs. Irstea developed GR2M-LoiEau, a conceptual monthly rainfall-runoff model, combined with a regionalized model of snow storage and melt. GR2M-LoiEau relies on only two parameters, which are regionalized and mapped throughout France. This model allows to cartography monthly reference low flow indices. The inputs data come from SAFRAN, the distributed mesoscale atmospheric analysis system, which provides daily solid and liquid precipitation and temperature data from everywhere in the French territory. To exploit fully these data and to estimate daily low flow indices, a new version of GR-LoiEau has been developed at a daily time step. The aim of this work is to develop and regionalize a GR-LoiEau model that can provide any daily, monthly or annual estimations of low flow indices, yet keeping only a few parameters, which is a major advantage to regionalize them. This work includes two parts. On the one hand, a daily conceptual rainfall-runoff model is developed with only three parameters in order to simulate daily and monthly low flow indices, mean annual runoff and seasonality. On the other hand, different regionalization methods, based on spatial proximity and similarity, are tested to estimate the model parameters and to simulate low flow indices in ungauged sites. The analysis is carried out on 691 French catchments that are representative of various hydro-meteorological behaviors. The results are validated with a cross-validation procedure and are compared with the ones obtained with GR4J, a conceptual rainfall-runoff model, which already provides daily estimations, but involves four parameters that cannot easily be regionalized.

Skill and predictability in multimodel ensemble forecasts for Northern Hemisphere regions with dominant winter precipitation

NASA Astrophysics Data System (ADS)

Ehsan, Muhammad Azhar; Tippett, Michael K.; Almazroui, Mansour; Ismail, Muhammad; Yousef, Ahmed; Kucharski, Fred; Omar, Mohamed; Hussein, Mahmoud; Alkhalaf, Abdulrahman A.

2017-05-01

Northern Hemisphere winter precipitation reforecasts from the European Centre for Medium Range Weather Forecast System-4 and six of the models in the North American Multi-Model Ensemble are evaluated, focusing on two regions (Region-A: 20°N-45°N, 10°E-65°E and Region-B: 20°N-55°N, 205°E-255°E) where winter precipitation is a dominant fraction of the annual total and where precipitation from mid-latitude storms is important. Predictability and skill (deterministic and probabilistic) are assessed for 1983-2013 by the multimodel composite (MME) of seven prediction models. The MME climatological mean and variability over the two regions is comparable to observation with some regional differences. The statistically significant decreasing trend observed in Region-B precipitation is captured well by the MME and most of the individual models. El Niño Southern Oscillation is a source of forecast skill, and the correlation coefficient between the Niño3.4 index and precipitation over region A and B is 0.46 and 0.35, statistically significant at the 95 % level. The MME reforecasts weakly reproduce the observed teleconnection. Signal, noise and signal to noise ratio analysis show that the signal variance over two regions is very small as compared to noise variance which tends to reduce the prediction skill. The MME ranked probability skill score is higher than that of individual models, showing the advantage of a multimodel ensemble. Observed Region-A rainfall anomalies are strongly associated with the North Atlantic Oscillation, but none of the models reproduce this relation, which may explain the low skill over Region-A. The superior quality of multimodel ensemble compared with individual models is mainly due to larger ensemble size.

Underground Test Area Subproject Phase I Data Analysis Task. Volume VIII - Risk Assessment Documentation Package

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

None

Volume VIII of the documentation for the Phase I Data Analysis Task performed in support of the current Regional Flow Model, Transport Model, and Risk Assessment for the Nevada Test Site Underground Test Area Subproject contains the risk assessment documentation. Because of the size and complexity of the model area, a considerable quantity of data was collected and analyzed in support of the modeling efforts. The data analysis task was consequently broken into eight subtasks, and descriptions of each subtask's activities are contained in one of the eight volumes that comprise the Phase I Data Analysis Documentation.

Parametric uncertainties in global model simulations of black carbon column mass concentration

NASA Astrophysics Data System (ADS)

Pearce, Hana; Lee, Lindsay; Reddington, Carly; Carslaw, Ken; Mann, Graham

2016-04-01

Previous studies have deduced that the annual mean direct radiative forcing from black carbon (BC) aerosol may regionally be up to 5 W m-2 larger than expected due to underestimation of global atmospheric BC absorption in models. We have identified the magnitude and important sources of parametric uncertainty in simulations of BC column mass concentration from a global aerosol microphysics model (GLOMAP-Mode). A variance-based uncertainty analysis of 28 parameters has been performed, based on statistical emulators trained on model output from GLOMAP-Mode. This is the largest number of uncertain model parameters to be considered in a BC uncertainty analysis to date and covers primary aerosol emissions, microphysical processes and structural parameters related to the aerosol size distribution. We will present several recommendations for further research to improve the fidelity of simulated BC. In brief, we find that the standard deviation around the simulated mean annual BC column mass concentration varies globally between 2.5 x 10-9 g cm-2 in remote marine regions and 1.25 x 10-6 g cm-2 near emission sources due to parameter uncertainty Between 60 and 90% of the variance over source regions is due to uncertainty associated with primary BC emission fluxes, including biomass burning, fossil fuel and biofuel emissions. While the contributions to BC column uncertainty from microphysical processes, for example those related to dry and wet deposition, are increased over remote regions, we find that emissions still make an important contribution in these areas. It is likely, however, that the importance of structural model error, i.e. differences between models, is greater than parametric uncertainty. We have extended our analysis to emulate vertical BC profiles at several locations in the mid-Pacific Ocean and identify the parameters contributing to uncertainty in the vertical distribution of black carbon at these locations. We will present preliminary comparisons of emulated BC vertical profiles from the AeroCom multi-model ensemble and Hiaper Pole-to-Pole (HIPPO) observations.

The Latin-American region and the challenges to develop one homogeneous and harmonized hazard model: preliminary results for the Caribbean and Central America regions in the GEM context

NASA Astrophysics Data System (ADS)

Garcia, J.; Arcila, M.; Benito, B.; Eraso, J.; García, R.; Gomez Capera, A.; Pagani, M.; Pinho, R.; Rendon, H.; Torres, Y.

2013-05-01

Latin America is a seismically active region with complex tectonic settings that make the creation of hazard models challenging. Over the past two decades PSHA studies have been completed for this region in the context of global (Shedlock, 1999), regional (Dimaté et al., 1999) and national initiatives. Currently different research groups are developing new models for various nations. The Global Earthquake Model (GEM), an initiative aiming at the creation of a large global community working collaboratively on building hazard and risk models using open standards and tools, is promoting the collaboration between different national projects and groups so as to facilitate the creation of harmonized regional models. The creation of a harmonized hazard model can follow different approaches, varying from a simple patching of available models to a complete homogenisation of basic information and the subsequent creation of a completely new PSHA model. In this contribution we describe the process and results of a first attempt aiming at the creation of a community based model covering the Caribbean and Central America regions. It consists of five main steps: 1- Identification and collection of available PSHA input models; 2- Analysis of the consistency, transparency and reproducibility of each model; 3- Selection (if more then a model exists for the same region); 4- Representation of the models in a standardized format and incorporation of new knowledge from recent studies; 5- Proposal(s) of harmonization We consider some PHSA studies completed over the latest twenty years in the region comprising the Caribbean (CAR), Central America (CAM) and northern South America (SA), we illustrate a tentative harmonization of the seismic source geometries models and we discuss the steps needed toward a complete harmonisation of the models. Our will is to have a model based on best practices and high standards created though a combination of knowledge and competences coming from the scientific community, incorporating national and regional Institutions. This is an ambitious goal that can be pursued only through an intense and open cooperation between all the interested subjects.

Regional SAR Image Segmentation Based on Fuzzy Clustering with Gamma Mixture Model

NASA Astrophysics Data System (ADS)

Li, X. L.; Zhao, Q. H.; Li, Y.

2017-09-01

Most of stochastic based fuzzy clustering algorithms are pixel-based, which can not effectively overcome the inherent speckle noise in SAR images. In order to deal with the problem, a regional SAR image segmentation algorithm based on fuzzy clustering with Gamma mixture model is proposed in this paper. First, initialize some generating points randomly on the image, the image domain is divided into many sub-regions using Voronoi tessellation technique. Each sub-region is regarded as a homogeneous area in which the pixels share the same cluster label. Then, assume the probability of the pixel to be a Gamma mixture model with the parameters respecting to the cluster which the pixel belongs to. The negative logarithm of the probability represents the dissimilarity measure between the pixel and the cluster. The regional dissimilarity measure of one sub-region is defined as the sum of the measures of pixels in the region. Furthermore, the Markov Random Field (MRF) model is extended from pixels level to Voronoi sub-regions, and then the regional objective function is established under the framework of fuzzy clustering. The optimal segmentation results can be obtained by the solution of model parameters and generating points. Finally, the effectiveness of the proposed algorithm can be proved by the qualitative and quantitative analysis from the segmentation results of the simulated and real SAR images.

Quantitative analysis of glycated albumin in serum based on ATR-FTIR spectrum combined with SiPLS and SVM.

PubMed

Li, Yuanpeng; Li, Fucui; Yang, Xinhao; Guo, Liu; Huang, Furong; Chen, Zhenqiang; Chen, Xingdan; Zheng, Shifu

2018-08-05

A rapid quantitative analysis model for determining the glycated albumin (GA) content based on Attenuated total reflectance (ATR)-Fourier transform infrared spectroscopy (FTIR) combining with linear SiPLS and nonlinear SVM has been developed. Firstly, the real GA content in human serum was determined by GA enzymatic method, meanwhile, the ATR-FTIR spectra of serum samples from the population of health examination were obtained. The spectral data of the whole spectra mid-infrared region (4000-600 cm -1 ) and GA's characteristic region (1800-800 cm -1 ) were used as the research object of quantitative analysis. Secondly, several preprocessing steps including first derivative, second derivative, variable standardization and spectral normalization, were performed. Lastly, quantitative analysis regression models were established by using SiPLS and SVM respectively. The SiPLS modeling results are as follows: root mean square error of cross validation (RMSECV T ) = 0.523 g/L, calibration coefficient (R C ) = 0.937, Root Mean Square Error of Prediction (RMSEP T ) = 0.787 g/L, and prediction coefficient (R P ) = 0.938. The SVM modeling results are as follows: RMSECV T  = 0.0048 g/L, R C  = 0.998, RMSEP T  = 0.442 g/L, and R p  = 0.916. The results indicated that the model performance was improved significantly after preprocessing and optimization of characteristic regions. While modeling performance of nonlinear SVM was considerably better than that of linear SiPLS. Hence, the quantitative analysis model for GA in human serum based on ATR-FTIR combined with SiPLS and SVM is effective. And it does not need sample preprocessing while being characterized by simple operations and high time efficiency, providing a rapid and accurate method for GA content determination. Copyright © 2018 Elsevier B.V. All rights reserved.

Modeling ozone episodes in the Baltimore-Washington region

NASA Technical Reports Server (NTRS)

Ryan, William F.

1994-01-01

Surface ozone (O3) concentrations in excess of the National Ambient Air Quality Standard (NAAQS) continue to occur in metropolitan areas in the United States despite efforts to control emissions of O3 precursors. Future O3 control strategies will be based on results from modeling efforts that have just begun in many areas. Two initial questions that arise are model sensitivity to domain-specific conditions and the selection of episodes for model evaluation and control strategy development. For the Baltimore-Washington region (B-W), the presence of the Chesapeake Bay introduces a number of issues relevant to model sensitivity. In this paper, the specific questions of the determination of model volume (mixing height) for the Urban Airshed Model (UAM) is discussed and various alternative methods compared. For the latter question, several analytic approaches, Cluster Analysis and classification and Regression Tree (CART) analysis are undertaken to determine meteorological conditions associated with severe O3 events in the B-W domain.

Improved estimates of net primary productivity from MODIS satellite data at regional and local scales

Treesearch

Yude Pan; Richard Birdsey; John Hom; Kevin McCullough; Kenneth Clark

2006-01-01

We compared estimates of net primary production (NPP) from the MODIS satellite with estimates from a forest ecosystem process model (PnET-CN) and forest inventory and analysis (FIA) data for forest types of the mid-Atlantic region of the United States. The regional means were similar for the three methods and for the dominant oak? hickory forests in the region. However...

Future changes to drought characteristics over the Canadian Prairie Provinces based on NARCCAP multi-RCM ensemble

NASA Astrophysics Data System (ADS)

Masud, M. B.; Khaliq, M. N.; Wheater, H. S.

2017-04-01

This study assesses projected changes to drought characteristics in Alberta, Saskatchewan and Manitoba, the prairie provinces of Canada, using a multi-regional climate model (RCM) ensemble available through the North American Regional Climate Change Assessment Program. Simulations considered include those performed with six RCMs driven by National Center for Environmental Prediction reanalysis II for the 1981-2003 period and those driven by four Atmosphere-Ocean General Circulation Models for the 1970-1999 and 2041-2070 periods (i.e. eleven current and the same number of corresponding future period simulations). Drought characteristics are extracted using two drought indices, namely the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). Regional frequency analysis is used to project changes to selected 20- and 50-year regional return levels of drought characteristics for fifteen homogeneous regions, covering the study area. In addition, multivariate analyses of drought characteristics, derived on the basis of 6-month SPI and SPEI values, are developed using the copula approach for each region. Analysis of multi-RCM ensemble-averaged projected changes to mean and selected return levels of drought characteristics show increases over the southern and south-western parts of the study area. Based on bi- and trivariate joint occurrence probabilities of drought characteristics, the southern regions along with the central regions are found highly drought vulnerable, followed by the southwestern and southeastern regions. Compared to the SPI-based analysis, the results based on SPEI suggest drier conditions over many regions in the future, indicating potential effects of rising temperatures on drought risks. These projections will be useful in the development of appropriate adaptation strategies for the water and agricultural sectors, which play an important role in the economy of the study area.

Examination of Satellite and Model Reanalysis Precipitation with Climate Oscillations

NASA Astrophysics Data System (ADS)

Donato, T. F.; Houser, P. R.

2016-12-01

The purpose of this study is to examine the efficacy of satellite and model reanalysis precipitation with climate oscillations. Specifically, we examine and compare the relationship between the Global Precipitation Climate Project (GPCP) with Modern-Era Retrospective Analysis for Research and Application, Version 2 (MERRA-2) in regards to four climate indices: The North Atlantic Oscillation, Southern Oscillation Index, the Southern Annular Mode and Solar Activity. This analysis covers a 35-year observation period from 1980 through 2015. We ask two questions: How is global and regional precipitation changing over the observation period, and how are global and regional variations in precipitation related to global climate variation? We explore and compare global and regional precipitation trends between the two data sets. To do this, we constructed a total of 56 Regions of Interest (ROI). Nineteen of the ROIs were focused on geographic regions including continents, ocean basins, and marginal seas. Twelve ROIs examine hemispheric processes. The remaining 26 regions are derived from spatial-temporal classification analysis of GPCP data over a ten-year period (2001-2010). These regions include the primary wet and dry monsoon regions, regions influenced by western boundary currents, and orography. We investigate and interpret the monthly, seasonal and yearly global and regional response to the selected climate indices. Initial results indicate that no correlation exist between the GPCP data and Merra-2 data. Preliminary qualitative assessment between GCPC and solar activity suggest a possible relationship in intra-annual variability. This work is performed under the State of the Global Water and Energy Cycle (SWEC) project, a NASA-sponsored program in support of NASA's Energy and Water cycle Study (NEWS).

Regional climates in the GISS global circulation model - Synoptic-scale circulation

NASA Technical Reports Server (NTRS)

Hewitson, B.; Crane, R. G.

1992-01-01

A major weakness of current general circulation models (GCMs) is their perceived inability to predict reliably the regional consequences of a global-scale change, and it is these regional-scale predictions that are necessary for studies of human-environmental response. For large areas of the extratropics, the local climate is controlled by the synoptic-scale atmospheric circulation, and it is the purpose of this paper to evaluate the synoptic-scale circulation of the Goddard Institute for Space Studies (GISS) GCM. A methodology for validating the daily synoptic circulation using Principal Component Analysis is described, and the methodology is then applied to the GCM simulation of sea level pressure over the continental United States (excluding Alaska). The analysis demonstrates that the GISS 4 x 5 deg GCM Model II effectively simulates the synoptic-scale atmospheric circulation over the United States. The modes of variance describing the atmospheric circulation of the model are comparable to those found in the observed data, and these modes explain similar amounts of variance in their respective datasets. The temporal behavior of these circulation modes in the synoptic time frame are also comparable.

Analysis of the impact of immigration on labour market using spatial models

NASA Astrophysics Data System (ADS)

Polonyankina, Tatiana

2017-07-01

This paper investigates the impact of immigration on employment and unemployment of a host country. The question to answer is: How does employment/unemployment in the host country change after an increase in number of immigrants? The analysis is taking into account only legal immigrants in recession period. The model is combining classical regression of cross-sectional data with spatial econometrics models where cross-section dependencies are captured by a spatial matrix. The intention is by using spatial models analyse the sensitivity of employment/unemployment rate on change in a share of immigration in a region. The used panel data are based on the Labour force survey and on available macro data in Eurostat for 3 European countries (Germany, Austria and Czech Republic) grouped into cells by NUTS regions in a recession period.

Italian regional health system structure and expected cancer survival.

PubMed

Vercelli, Marina; Lillini, Roberto; Quaglia, Alberto; Capocaccia, Riccardo

2014-01-01

Few studies deal with the association of socioeconomic and health system resource variables with cancer survival at the Italian regional level, where the greatest number of decisions about social and health policies and resource allocations are taken. The present study aimed to describe the causal relationships between socioeconomic and health system resource factors and regional cancer survival and to compute the expected cancer survival at provincial, regional and area levels. Age-standardized relative survival at 5 years from diagnosis of cases incident in 1995-1998 and followed up to 2004 were derived by gender for 11 sites from the Italian Association of Cancer Registries data bank. The socioeconomic and health system resource variables, describing at a regional level the macro-economy, demography, labor market, and health resources for 1995-2005, came from the Health for All database. A principal components factor analysis was applied to the socioeconomic and health system resource variables. For every site, linear regression models were computed considering the relative survival at 5 years as a dependent variable and the principal components factor analysis factors as independent variables. The factors described the socioeconomic and health-related features of the regional systems and were causally related to the characteristics of the patient taken in charge. The models built by the factors allowed computation of the expected relative survival at 5 years with very good concordance with those observed at regional, macro-regional and national levels. In the regions without any cancer registry, survival was coherent with that of neighboring regions with similar socioeconomic and health system resources characteristics. The models highlighted the causal correlations between socioeconomic and health system resources and cancer survival, suggesting that they could be good evaluation tools for the efficiency of the resources allocation and use.

Sequence-dependent modelling of local DNA bending phenomena: curvature prediction and vibrational analysis.

PubMed

Vlahovicek, K; Munteanu, M G; Pongor, S

1999-01-01

Bending is a local conformational micropolymorphism of DNA in which the original B-DNA structure is only distorted but not extensively modified. Bending can be predicted by simple static geometry models as well as by a recently developed elastic model that incorporate sequence dependent anisotropic bendability (SDAB). The SDAB model qualitatively explains phenomena including affinity of protein binding, kinking, as well as sequence-dependent vibrational properties of DNA. The vibrational properties of DNA segments can be studied by finite element analysis of a model subjected to an initial bending moment. The frequency spectrum is obtained by applying Fourier analysis to the displacement values in the time domain. This analysis shows that the spectrum of the bending vibrations quite sensitively depends on the sequence, for example the spectrum of a curved sequence is characteristically different from the spectrum of straight sequence motifs of identical basepair composition. Curvature distributions are genome-specific, and pronounced differences are found between protein-coding and regulatory regions, respectively, that is, sites of extreme curvature and/or bendability are less frequent in protein-coding regions. A WWW server is set up for the prediction of curvature and generation of 3D models from DNA sequences (http:@www.icgeb.trieste.it/dna).

Non-Contact Heart Rate and Blood Pressure Estimations from Video Analysis and Machine Learning Modelling Applied to Food Sensory Responses: A Case Study for Chocolate.

PubMed

Gonzalez Viejo, Claudia; Fuentes, Sigfredo; Torrico, Damir D; Dunshea, Frank R

2018-06-03

Traditional methods to assess heart rate (HR) and blood pressure (BP) are intrusive and can affect results in sensory analysis of food as participants are aware of the sensors. This paper aims to validate a non-contact method to measure HR using the photoplethysmography (PPG) technique and to develop models to predict the real HR and BP based on raw video analysis (RVA) with an example application in chocolate consumption using machine learning (ML). The RVA used a computer vision algorithm based on luminosity changes on the different RGB color channels using three face-regions (forehead and both cheeks). To validate the proposed method and ML models, a home oscillometric monitor and a finger sensor were used. Results showed high correlations with the G color channel (R² = 0.83). Two ML models were developed using three face-regions: (i) Model 1 to predict HR and BP using the RVA outputs with R = 0.85 and (ii) Model 2 based on time-series prediction with HR, magnitude and luminosity from RVA inputs to HR values every second with R = 0.97. An application for the sensory analysis of chocolate showed significant correlations between changes in HR and BP with chocolate hardness and purchase intention.

Sensitivity of a numerical wave model on wind re-analysis datasets

NASA Astrophysics Data System (ADS)

Lavidas, George; Venugopal, Vengatesan; Friedrich, Daniel

2017-03-01

Wind is the dominant process for wave generation. Detailed evaluation of metocean conditions strengthens our understanding of issues concerning potential offshore applications. However, the scarcity of buoys and high cost of monitoring systems pose a barrier to properly defining offshore conditions. Through use of numerical wave models, metocean conditions can be hindcasted and forecasted providing reliable characterisations. This study reports the sensitivity of wind inputs on a numerical wave model for the Scottish region. Two re-analysis wind datasets with different spatio-temporal characteristics are used, the ERA-Interim Re-Analysis and the CFSR-NCEP Re-Analysis dataset. Different wind products alter results, affecting the accuracy obtained. The scope of this study is to assess different available wind databases and provide information concerning the most appropriate wind dataset for the specific region, based on temporal, spatial and geographic terms for wave modelling and offshore applications. Both wind input datasets delivered results from the numerical wave model with good correlation. Wave results by the 1-h dataset have higher peaks and lower biases, in expense of a high scatter index. On the other hand, the 6-h dataset has lower scatter but higher biases. The study shows how wind dataset affects the numerical wave modelling performance, and that depending on location and study needs, different wind inputs should be considered.

Modeling and Data Analysis at the CCMC to Determine Threat of Spacecraft Surface Charging in Low Earth Orbit

NASA Astrophysics Data System (ADS)

Rastaetter, L.; Kuznetsova, M. M.; Zheng, Y.; Jordanova, V.; Yu, Y.; Minow, J. I.

2016-12-01

Spacecraft surface charging in Low-Earth Orbit occurs primarily in regions of low plasma density when precipitating electrons drive the spacecraft potential. Sudden changes in electric potentials occur when a spacecraft enters and leaves the sunlit region.At the Community Coordinated Modeling Center, we can employ a multitude of models of the ionosphere-thermosphere and inner magnetosphere to identify regions where spacecraft charging can occur based on thresholds of electron precipitation flux and energy and track the proximity of those areas to positions of satellites of interest. The identified regions will be validated and refined based on satellite observations. This work is in conjunction with the Spacecraft Charging Challenge organized by the GEM Workshop in collaboration with CCMC and the SHIELDS project at LANL.

Hook Region Represented in a Cochlear Model

NASA Astrophysics Data System (ADS)

Steele, Charles R.; Kim, Namkeun; Puria, Sunil

2009-02-01

The present interest is in discontinuities. Particularly the geometry of the hook region, with the flexible round window nearly parallel with the basilar membrane, is not represented by a standard box model, in which both stapes and round window are placed at the end. A better model represents the round window by a soft membrane in the wall of scala tympani, with the end closed. This complicates the analysis considerably. Features are that the significant compression wave, i.e., the fast wave, is of negligible magnitude in this region, and that significant evanescent waves occur because of the discontinuities at the beginning and end of the simulated round window. The effect of this on both high frequency, with maximum basilar membrane response in the hook region, and lower frequencies are determined.

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

NASA Astrophysics Data System (ADS)

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

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

Groundwater flow in the Brunswick/Glynn County area, Georgia, 2000-04

USGS Publications Warehouse

Cherry, Gregory S.

2015-01-01

Analysis of simulated water-budget components for 2000 and 2004 indicate that specified-head boundaries in the Floridan aquifer system to the south and southwest of the regional model area control about 70 percent of inflows and nearly 50 percent of outflows to the model region. Other water-budget components indicate an 80-million-gallon-per-day decrease in pumping from the Floridan aquifer system during this period.

Economic Analysis Framework for Freight Transportation Based on Florida Statewide Multi-Modal Freight Model

DOT National Transportation Integrated Search

2018-02-01

Freight transportation plays a vital role in local and regional economy. The markets and businesses from different regions and locations can be connected through freight movements. But it is difficult to quantify the economic contribution of freight ...

Assessment of Technologies for the Space Shuttle External Tank Thermal Protection System and Recommendations for Technology Improvement. Part 2; Structural Analysis Technologies and Modeling Practices

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.; Nemeth, Michael P.; Hilburger, Mark W.

2004-01-01

A technology review and assessment of modeling and analysis efforts underway in support of a safe return to flight of the thermal protection system (TPS) for the Space Shuttle external tank (ET) are summarized. This review and assessment effort focuses on the structural modeling and analysis practices employed for ET TPS foam design and analysis and on identifying analysis capabilities needed in the short-term and long-term. The current understanding of the relationship between complex flight environments and ET TPS foam failure modes are reviewed as they relate to modeling and analysis. A literature review on modeling and analysis of TPS foam material systems is also presented. Finally, a review of modeling and analysis tools employed in the Space Shuttle Program is presented for the ET TPS acreage and close-out foam regions. This review includes existing simplified engineering analysis tools are well as finite element analysis procedures.

Mental health network governance: comparative analysis across Canadian regions.

PubMed

Wiktorowicz, Mary E; Fleury, Marie-Josée; Adair, Carol E; Lesage, Alain; Goldner, Elliot; Peters, Suzanne

2010-10-26

Modes of governance were compared in ten local mental health networks in diverse contexts (rural/urban and regionalized/non-regionalized) to clarify the governance processes that foster inter-organizational collaboration and the conditions that support them. Case studies of ten local mental health networks were developed using qualitative methods of document review, semi-structured interviews and focus groups that incorporated provincial policy, network and organizational levels of analysis. Mental health networks adopted either a corporate structure, mutual adjustment or an alliance governance model. A corporate structure supported by regionalization offered the most direct means for local governance to attain inter-organizational collaboration. The likelihood that networks with an alliance model developed coordination processes depended on the presence of the following conditions: a moderate number of organizations, goal consensus and trust among the organizations, and network-level competencies. In the small and mid-sized urban networks where these conditions were met their alliance realized the inter-organizational collaboration sought. In the large urban and rural networks where these conditions were not met, externally brokered forms of network governance were required to support alliance based models. In metropolitan and rural networks with such shared forms of network governance as an alliance or voluntary mutual adjustment, external mediation by a regional or provincial authority was an important lever to foster inter-organizational collaboration.

Analysis of precipitation teleconnections in CMIP models as a measure of model fidelity in simulating precipitation

NASA Astrophysics Data System (ADS)

Langenbrunner, B.; Neelin, J.; Meyerson, J.

2011-12-01

The accurate representation of precipitation is a recurring issue in global climate models, especially in the tropics. Poor skill in modeling the variability and climate teleconnections associated with El Niño/Southern Oscillation (ENSO) also persisted in the latest Climate Model Intercomparison Project (CMIP) campaigns. Observed ENSO precipitation teleconnections provide a standard by which we can judge a given model's ability to reproduce precipitation and dynamic feedback processes originating in the tropical Pacific. Using CMIP3 Atmospheric Model Intercomparison Project (AMIP) runs as a baseline, we compare precipitation teleconnections between models and observations, and we evaluate these results against available CMIP5 historical and AMIP runs. Using AMIP simulations restricts evaluation to the atmospheric response, as sea surface temperatures (SSTs) in AMIP are prescribed by observations. We use a rank correlation between ENSO SST indices and precipitation to define teleconnections, since this method is robust to outliers and appropriate for non-Gaussian data. Spatial correlations of the modeled and observed teleconnections are then evaluated. We look at these correlations in regions of strong precipitation teleconnections, including equatorial S. America, the "horseshoe" region in the western tropical Pacific, and southern N. America. For each region and season, we create a "normalized projection" of a given model's teleconnection pattern onto that of the observations, a metric that assesses the quality of regional pattern simulations while rewarding signals of correct sign over the region. Comparing this to an area-averaged (i.e., more generous) metric suggests models do better when restrictions on exact spatial dependence are loosened and conservation constraints apply. Model fidelity in regional measures remains far from perfect, suggesting intrinsic issues with the models' regional sensitivities in moist processes.

Permeabilization of brain tissue in situ enables multiregion analysis of mitochondrial function in a single mouse brain.

PubMed

Herbst, Eric A F; Holloway, Graham P

2015-02-15

Mitochondrial function in the brain is traditionally assessed through analysing respiration in isolated mitochondria, a technique that possesses significant tissue and time requirements while also disrupting the cooperative mitochondrial reticulum. We permeabilized brain tissue in situ to permit analysis of mitochondrial respiration with the native mitochondrial morphology intact, removing the need for isolation time and minimizing tissue requirements to ∼2 mg wet weight. The permeabilized brain technique was validated against the traditional method of isolated mitochondria and was then further applied to assess regional variation in the mouse brain with ischaemia-reperfusion injuries. A transgenic mouse model overexpressing catalase within mitochondria was applied to show the contribution of mitochondrial reactive oxygen species to ischaemia-reperfusion injuries in different brain regions. This technique enhances the accessibility of addressing physiological questions in small brain regions and in applying transgenic mouse models to assess mechanisms regulating mitochondrial function in health and disease. Mitochondria function as the core energy providers in the brain and symptoms of neurodegenerative diseases are often attributed to their dysregulation. Assessing mitochondrial function is classically performed in isolated mitochondria; however, this process requires significant isolation time, demand for abundant tissue and disruption of the cooperative mitochondrial reticulum, all of which reduce reliability when attempting to assess in vivo mitochondrial bioenergetics. Here we introduce a method that advances the assessment of mitochondrial respiration in the brain by permeabilizing existing brain tissue to grant direct access to the mitochondrial reticulum in situ. The permeabilized brain preparation allows for instant analysis of mitochondrial function with unaltered mitochondrial morphology using significantly small sample sizes (∼2 mg), which permits the analysis of mitochondrial function in multiple subregions within a single mouse brain. Here this technique was applied to assess regional variation in brain mitochondrial function with acute ischaemia-reperfusion injuries and to determine the role of reactive oxygen species in exacerbating dysfunction through the application of a transgenic mouse model overexpressing catalase within mitochondria. Through creating accessibility to small regions for the investigation of mitochondrial function, the permeabilized brain preparation enhances the capacity for examining regional differences in mitochondrial regulation within the brain, as the majority of genetic models used for unique approaches exist in the mouse model. © 2014 The Authors. The Journal of Physiology © 2014 The Physiological Society.

Multi-element analysis of wines by ICP-MS and ICP-OES and their classification according to geographical origin in Slovenia.

PubMed

Selih, Vid S; Sala, Martin; Drgan, Viktor

2014-06-15

Inductively coupled plasma mass spectrometry and optical emission were used to determine the multi-element composition of 272 bottled Slovenian wines. To achieve geographical classification of the wines by their elemental composition, principal component analysis (PCA) and counter-propagation artificial neural networks (CPANN) have been used. From 49 elements measured, 19 were used to build the final classification models. CPANN was used for the final predictions because of its superior results. The best model gave 82% correct predictions for external set of the white wine samples. Taking into account the small size of whole Slovenian wine growing regions, we consider the classification results were very good. For the red wines, which were mostly represented from one region, even-sub region classification was possible with great precision. From the level maps of the CPANN model, some of the most important elements for classification were identified. Copyright © 2013 Elsevier Ltd. All rights reserved.

A statistical model for predicting the inter-annual variability of birch pollen abundance in Northern and North-Eastern Europe.

PubMed

Ritenberga, Olga; Sofiev, Mikhail; Siljamo, Pilvi; Saarto, Annika; Dahl, Aslog; Ekebom, Agneta; Sauliene, Ingrida; Shalaboda, Valentina; Severova, Elena; Hoebeke, Lucie; Ramfjord, Hallvard

2018-02-15

The paper suggests a methodology for predicting next-year seasonal pollen index (SPI, a sum of daily-mean pollen concentrations) over large regions and demonstrates its performance for birch in Northern and North-Eastern Europe. A statistical model is constructed using meteorological, geophysical and biological characteristics of the previous year). A cluster analysis of multi-annual data of European Aeroallergen Network (EAN) revealed several large regions in Europe, where the observed SPI exhibits similar patterns of the multi-annual variability. We built the model for the northern cluster of stations, which covers Finland, Sweden, Baltic States, part of Belarus, and, probably, Russia and Norway, where the lack of data did not allow for conclusive analysis. The constructed model was capable of predicting the SPI with correlation coefficient reaching up to 0.9 for some stations, odds ratio is infinitely high for 50% of sites inside the region and the fraction of prediction falling within factor of 2 from observations, stays within 40-70%. In particular, model successfully reproduced both the bi-annual cycle of the SPI and years when this cycle breaks down. Copyright © 2017 Elsevier B.V. All rights reserved.

Hierarchical models and Bayesian analysis of bird survey information

USGS Publications Warehouse

Sauer, J.R.; Link, W.A.; Royle, J. Andrew; Ralph, C. John; Rich, Terrell D.

2005-01-01

Summary of bird survey information is a critical component of conservation activities, but often our summaries rely on statistical methods that do not accommodate the limitations of the information. Prioritization of species requires ranking and analysis of species by magnitude of population trend, but often magnitude of trend is a misleading measure of actual decline when trend is poorly estimated. Aggregation of population information among regions is also complicated by varying quality of estimates among regions. Hierarchical models provide a reasonable means of accommodating concerns about aggregation and ranking of quantities of varying precision. In these models the need to consider multiple scales is accommodated by placing distributional assumptions on collections of parameters. For collections of species trends, this allows probability statements to be made about the collections of species-specific parameters, rather than about the estimates. We define and illustrate hierarchical models for two commonly encountered situations in bird conservation: (1) Estimating attributes of collections of species estimates, including ranking of trends, estimating number of species with increasing populations, and assessing population stability with regard to predefined trend magnitudes; and (2) estimation of regional population change, aggregating information from bird surveys over strata. User-friendly computer software makes hierarchical models readily accessible to scientists.

Towards A Synthesis Of Land Dynamics And Hydrological Processes Across Central Asia

NASA Astrophysics Data System (ADS)

Sokolik, I. N.; Tatarskii, V.; Shiklomanov, A. I.; Henebry, G. M.; de Beurs, K.; Laruelle, M.

2016-12-01

We present results from an ongoing project that aims to synthesize land dynamics, hydrological processes, and socio-economic changes across the five countries of Central Asia. We have developed a fully coupled model that takes into account the reconstructed land cover and land use dynamics to simulate dust emissions. A comparable model has been developed to model smoke emissions from wildfires. Both models incorporate land dynamics explicitly. We also present a characterization of land surface change based on a suite of MODIS products including vegetation indices, evapotranspiration, land surface temperature, and albedo. These results are connected with ongoing land privatization reforms that different across the region. We also present a regional analysis of water resources, including the significant impact of using surface water for irrigation in an arid landscape. We applied the University of New Hampshire hydrological model to understand the consequences of changes in climate, water, and land use on regional hydrological processes and water use. Water security and its dynamic have been estimated through an analysis of multiple indices and variables characterizing the water availability and water use. The economic consequences of the water privatization processes will be presented.

Cross ranking of cities and regions: population versus income

NASA Astrophysics Data System (ADS)

Cerqueti, Roy; Ausloos, Marcel

2015-07-01

This paper explores the relationship between the inner economical structure of communities and their population distribution through a rank-rank analysis of official data, along statistical physics ideas within two techniques. The data is taken on Italian cities. The analysis is performed both at a global (national) and at a more local (regional) level in order to distinguish ‘macro’ and ‘micro’ aspects. First, the rank-size rule is found not to be a standard power law, as in many other studies, but a doubly decreasing power law. Next, the Kendall τ and the Spearman ρ rank correlation coefficients which measure pair concordance and the correlation between fluctuations in two rankings, respectively,—as a correlation function does in thermodynamics, are calculated for finding rank correlation (if any) between demography and wealth. Results show non only global disparities for the whole (country) set, but also (regional) disparities, when comparing the number of cities in regions, the number of inhabitants in cities and that in regions, as well as when comparing the aggregated tax income of the cities and that of regions. Different outliers are pointed out and justified. Interestingly, two classes of cities in the country and two classes of regions in the country are found. ‘Common sense’ social, political, and economic considerations sustain the findings. More importantly, the methods show that they allow to distinguish communities, very clearly, when specific criteria are numerically sound. A specific modeling for the findings is presented, i.e. for the doubly decreasing power law and the two phase system, based on statistics theory, e.g. urn filling. The model ideas can be expected to hold when similar rank relationship features are observed in fields. It is emphasized that the analysis makes more sense than one through a Pearson Π value-value correlation analysis

Variation of δ2H, δ18O & δ13C in crude palm oil from different regions in Malaysia: Potential of stable isotope signatures as a key traceability parameter.

PubMed

Muhammad, Syahidah Akmal; Seow, Eng-Keng; Mohd Omar, A K; Rodhi, Ainolsyakira Mohd; Mat Hassan, Hasnuri; Lalung, Japareng; Lee, Sze-Chi; Ibrahim, Baharudin

2018-01-01

A total of 33 crude palm oil samples were randomly collected from different regions in Malaysia. Stable carbon isotopic composition (δ 13 C) was determined using Flash 2000 elemental analyzer while hydrogen and oxygen isotopic compositions (δ 2 H and δ 18 O) were analyzed by Thermo Finnigan TC/EA, wherein both instruments were coupled to an isotope ratio mass spectrometer. The bulk δ 2 H, δ 18 O and δ 13 C of the samples were analyzed by Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA) and Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA). Unsupervised HCA and PCA methods have demonstrated that crude palm oil samples were grouped into clusters according to respective state. A predictive model was constructed by supervised OPLS-DA with good predictive power of 52.60%. Robustness of the predictive model was validated with overall accuracy of 71.43%. Blind test samples were correctly assigned to their respective cluster except for samples from southern region. δ 18 O was proposed as the promising discriminatory marker for discerning crude palm oil samples obtained from different regions. Stable isotopes profile was proven to be useful for origin traceability of crude palm oil samples at a narrower geographical area, i.e. based on regions in Malaysia. Predictive power and accuracy of the predictive model was expected to improve with the increase in sample size. Conclusively, the results in this study has fulfilled the main objective of this work where the simple approach of combining stable isotope analysis with chemometrics can be used to discriminate crude palm oil samples obtained from different regions in Malaysia. Overall, this study shows the feasibility of this approach to be used as a traceability assessment of crude palm oils. Copyright © 2017 The Chartered Society of Forensic Sciences. Published by Elsevier B.V. All rights reserved.

An Analysis of Simulated Wet Deposition of Mercury from the North American Mercury Model Intercomparison Study

EPA Science Inventory

A previous intercomparison of atmospheric mercury models in North America has been extended to compare simulated and observed wet deposition of mercury. Three regional-scale atmospheric mercury models were tested; CMAQ, REMSAD and TEAM. These models were each employed using thr...

Geopotential models in the Australian region

NASA Technical Reports Server (NTRS)

Kearsley, A. H. W.; Holloway, R. D.

1989-01-01

The ability of three high-order geopotential models (OSU81, GPM2 and OSU86E) to recover the gravity anomaly field (delta g) in the Australian region was tested. The region was divided into 2 x 2 deg blocks, and the mean and rms of the residual gravity (delta g measured - delta g modeled) was found to estimate the fit of the model to the point gravity data. The results showed that OSU81 and GPM2 performed similarly, recovering the delta g with a mean value of less than plus or minus 5 mGal in 63 and 70 percent of the blocks, respectively. However, both these models achieved a fit of worse that was plus or minus 13 mGal in 6 to 7 percent of cases. These were in areas either on or near the coast, or in the Central Australian region, inferring that for a precise geoid slope determination in these regions, a detailed analysis of delta g in region is needed. On the other hand, OSU86E produced a very good result, having a mean fit of less than plus or minus 5 mGal in 80 percent of the blocks, and worse than plus or minus 13 mGal in only 1 percent of cases. The rms values for this model were also improved over the other two models, indicating that for applications requiring highest precision, the preferred model is OSU86E.

[Geographical distribution of the Serum creatinine reference values of healthy adults].

PubMed

Wei, De-Zhi; Ge, Miao; Wang, Cong-Xia; Lin, Qian-Yi; Li, Meng-Jiao; Li, Peng

2016-11-20

To explore the relationship between serum creatinine (Scr) reference values in healthy adults and geographic factors and provide evidence for establishing Scr reference values in different regions. We collected 29 697 Scr reference values from healthy adults measured by 347 medical facilities from 23 provinces, 4 municipalities and 5 autonomous regions. We chose 23 geographical factors and analyzed their correlation with Scr reference values to identify the factors correlated significantly with Scr reference values. According to the Principal component analysis and Ridge regression analysis, two predictive models were constructed and the optimal model was chosen after comparison of the two model's fitting degree of predicted results and measured results. The distribution map of Scr reference values was drawn using the Kriging interpolation method. Seven geographic factors, including latitude, annual sunshine duration, annual average temperature, annual average relative humidity, annual precipitation, annual temperature range and topsoil (silt) cation exchange capacity were found to correlate significantly with Scr reference values. The overall distribution of Scr reference values featured a pattern that the values were high in the south and low in the north, varying consistently with the latitude change. The data of the geographic factors in a given region allows the prediction of the Scr values in healthy adults. Analysis of these geographical factors can facilitate the determination of the reference values specific to a region to improve the accuracy for clinical diagnoses.

Contemporary changes of water resources, water and land use in Central Asia based on observations and modeling.

NASA Astrophysics Data System (ADS)

Shiklomanov, A. I.; Prousevitch, A.; Sokolik, I. N.; Lammers, R. B.

2015-12-01

Water is a key agent in Central Asia ultimately determining human well-being, food security, and economic development. There are complex interplays among the natural and anthropogenic drivers effecting the regional hydrological processes and water availability. Analysis of the data combined from regional censuses and remote sensing shows a decline in areas of arable and irrigated lands and a significant decrease in availability of arable and irrigated lands per capita across all Central Asian countries since the middle of 1990thas the result of post-Soviet transformation processes. This change could lead to considerable deterioration in food security and human system sustainability. The change of political situation in the region has also resulted in the escalated problems of water demand between countries in international river basins. We applied the University of New Hampshire - Water Balance Model - Transport from Anthropogenic and Natural Systems (WBM-TrANS) to understand the consequences of changes in climate, water and land use on regional hydrological processes and water availability. The model accounts for sub-pixel land cover types, glacier and snow-pack accumulation/melt across sub-pixel elevation bands, anthropogenic water use (e.g. domestic and industrial consumption, and irrigation for most of existing crop types), hydro-infrastructure for inter-basin water transfer and reservoir/dam regulations. A suite of historical climate re-analysis and temporal extrapolation of MIRCA-2000 crop structure datasets has been used in WBM-TrANS for this project. A preliminary analysis of the model simulations over the last 30 years has shown significant spatial and temporal changes in hydrology and water availability for crops and human across the region due to climatic and anthropogenic causes. We found that regional water availability is mostly impacted by changes in extents and efficiency of crop filed irrigation, especially in highly arid areas of Central Asia, changes in winter snow storage, and shifts in seasonality and intensity of glacier melt waters driven by climatic changes.

Can global hydrological models reproduce large scale river flood regimes?

NASA Astrophysics Data System (ADS)

Eisner, Stephanie; Flörke, Martina

2013-04-01

River flooding remains one of the most severe natural hazards. On the one hand, major flood events pose a serious threat to human well-being, causing deaths and considerable economic damage. On the other hand, the periodic occurrence of flood pulses is crucial to maintain the functioning of riverine floodplains and wetlands, and to preserve the ecosystem services the latter provide. In many regions, river floods reveal a distinct seasonality, i.e. they occur at a particular time during the year. This seasonality is related to regionally dominant flood generating processes which can be expressed in river flood types. While in data-rich regions (esp. Europe and North America) the analysis of flood regimes can be based on observed river discharge time series, this data is sparse or lacking in many other regions of the world. This gap of knowledge can be filled by global modeling approaches. However, to date most global modeling studies have focused on mean annual or monthly water availability and their change over time while simulating discharge extremes, both floods and droughts, still remains a challenge for large scale hydrological models. This study will explore the ability of the global hydrological model WaterGAP3 to simulate the large scale patterns of river flood regimes, represented by seasonal pattern and the dominant flood type. WaterGAP3 simulates the global terrestrial water balance on a 5 arc minute spatial grid (excluding Greenland and Antarctica) at a daily time step. The model accounts for human interference on river flow, i.e. water abstraction for various purposes, e.g. irrigation, and flow regulation by large dams and reservoirs. Our analysis will provide insight in the general ability of global hydrological models to reproduce river flood regimes and thus will promote the creation of a global map of river flood regimes to provide a spatially inclusive and comprehensive picture. Understanding present-day flood regimes can support both flood risk analysis and the assessment of potential regional impacts of climate change on river flooding.

Assessment of possible airborne impact from nuclear risk sites - Part II: probabilistic analysis of atmospheric transport patterns in Euro-Arctic region

NASA Astrophysics Data System (ADS)

Mahura, A. G.; Baklanov, A. A.

2003-10-01

The probabilistic analysis of atmospheric transport patterns from most important nuclear risk sites in the Euro-Arctic region is performed employing the methodology developed within the "Arctic Risk" Project of the NARP Programme (Baklanov and Mahura, 2003). The risk sites are the nuclear power plants in the Northwest Russia, Finland, Sweden, Lithuania, United Kingdom, and Germany as well as the Novaya Zemlya test site of Russia. The geographical regions of interest are the Northern and Central European countries and Northwest Russia. In this study, the employed research tools are the trajectory model to calculate a multiyear dataset of forward trajectories that originated over the risk site locations, and a set of statistical methods (including exploratory, cluster, and probability fields analyses) for analysis of trajectory modelling results. The probabilistic analyses of trajectory modelling results for eleven sites are presented as a set of various indicators of the risk sites possible impact on geographical regions and countries of interest. The nuclear risk site possible impact (on a particular geographical region, territory, country, site, etc.) due to atmospheric transport from the site after hypothetical accidental release of radioactivity can be properly estimated based on a combined interpretation of the indicators (simple characteristics, atmospheric transport pathways, airflow and fast transport probability fields, maximum reaching distance and maximum possible impact zone, typical transport time and precipitation factor fields) for different time periods (annual, seasonal, and monthly) for any selected site (both separately for each site or grouped for several sites) in the Euro-Arctic region. Such estimation could be the useful input information for the decision-making process, risk assessment, and planning of emergency response systems for sites of nuclear, chemical, and biological danger.

The balance sheet technique. Volume I. The balance sheet analysis technique for preconstruction review of airports and highways

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

LaBelle, S.J.; Smith, A.E.; Seymour, D.A.

1977-02-01

The technique applies equally well to new or existing airports. The importance of accurate accounting of emissions, cannot be overstated. The regional oxidant modelling technique used in conjunction with a balance sheet review must be a proportional reduction technique. This type of emission balancing presumes equality of all sources in the analysis region. The technique can be applied successfully in the highway context, either in planning at the system level or looking only at projects individually. The project-by-project reviews could be used to examine each project in the same way as the airport projects are examined for their impact onmore » regional desired emission levels. The primary limitation of this technique is that it should not be used when simulation models have been used for regional oxidant air quality. In the case of highway projects, the balance sheet technique might appear to be limited; the real limitations are in the transportation planning process. That planning process is not well-suited to the needs of air quality forecasting. If the transportation forecasting techniques are insensitive to change in the variables that affect HC emissions, then no internal emission trade-offs can be identified, and the initial highway emission forecasts are themselves suspect. In general, the balance sheet technique is limited by the quality of the data used in the review. Additionally, the technique does not point out effective trade-off strategies, nor does it indicate when it might be worthwhile to ignore small amounts of excess emissions. Used in the context of regional air quality plans based on proportional reduction models, the balance sheet analysis technique shows promise as a useful method by state or regional reviewing agencies.« less

Variation of atmospheric carbon monoxide over the Arctic Ocean during summer 2012

NASA Astrophysics Data System (ADS)

Park, Keyhong; Siek Rhee, Tae; Emmons, Louisa

2014-05-01

Atmospheric carbon monoxide (CO) plays an important role in ozone-related chemistry in the troposphere, especially under low-NOx conditions like the open ocean. During summer 2012, we performed a continuous high-resolution (0.1Hz) shipboard measurement of atmospheric CO over the Arctic Ocean. We also simulated the observation using a 3-D global chemical transport model (the Model for OZone And Related chemical Tracers-4; MOZART-4) for further analysis of the observed results. In the model, tags for each sources and emission regions of CO are applied and this enables us to delineate the source composition of the observations. Along with the observed variation of CO concentration during the research cruise, we will present in detailed analysis of the variation of source components and change of regional contributions. We found large (~80ppbv) variation of CO concentration in the Arctic Ocean which is mostly influenced by the variation of biomass burning activity. The contribution of anthropogenic emission is limited over the Arctic Ocean, although the northeast Asian anthropogenic emission shows a dominant component of transported anthropogenic CO. Also, our analysis shows, near the Bering Strait, Europe is the main emission region for anthropogenic CO.

Projecting Future Land Use Changes in West Africa Driven by Climate and Socioeconomic Factors: Uncertainties and Implications for Adaptation

NASA Astrophysics Data System (ADS)

Wang, G.; Ahmed, K. F.; You, L.

2015-12-01

Land use changes constitute an important regional climate change forcing in West Africa, a region of strong land-atmosphere coupling. At the same time, climate change can be an important driver for land use, although its importance relative to the impact of socio-economic factors may vary significant from region to region. This study compares the contributions of climate change and socioeconomic development to potential future changes of agricultural land use in West Africa and examines various sources of uncertainty using a land use projection model (LandPro) that accounts for the impact of socioeconomic drivers on the demand side and the impact of climate-induced crop yield changes on the supply side. Future crop yield changes were simulated by a process-based crop model driven with future climate projections from a regional climate model, and future changes of food demand is projected using a model for policy analysis of agricultural commodities and trade. The impact of human decision-making on land use was explicitly considered through multiple "what-if" scenarios to examine the range of uncertainties in projecting future land use. Without agricultural intensification, the climate-induced decrease of crop yield together with increase of food demand are found to cause a significant increase in agricultural land use at the expense of forest and grassland by the mid-century, and the resulting land use land cover changes are found to feed back to the regional climate in a way that exacerbates the negative impact of climate on crop yield. Analysis of results from multiple decision-making scenarios suggests that human adaptation characterized by science-informed decision making to minimize land use could be very effective in many parts of the region.

Attributing regional effects of the 2014 Jordanian extreme drought to external climate drivers

NASA Astrophysics Data System (ADS)

Bergaoui, Karim; Mitchell, Dann; Zaaboul, Rashyd; Otto, Friederike; McDonnell, Rachael; Dadson, Simon; Allen, Myles

2015-04-01

Throughout 2014, the regions of Jordan, Israel, Lebanon and Syria have experienced a persistent draught with clear impacts on the local populations. In this study we perform an extreme event attribution analysis of how such a draught has changed under climate change, with a specific focus on the flow rate of the Upper Jordan river and the water level of Lake Tiberious (AKA the Sea of Galilee). Both of which hold major societal, political and religious importance. To perform the analysis we make use of distributed computing power to run thousands of modelled years of 2014 with slightly different initial conditions. We use an atmosphere only model (HadAM3p) with a nested 50 km regional model covering Africa and the Middle East. The 50 km model atmospheric variables will be used directly to force offline our 1 km LIS surface model. Two separate experiments and simulations are performed, 1. for all known climate forcings that are present in 2014, and 2. for a naturalised 2014 scenario where we assume humans never impacted the climate. We perform sensitivity analyses on the observed precipitation over the regions of interest, and determine that the TRMM data is in good agreement with station data obtained from the Jordanian Ministry of Water. Using a combination of the TRMM and model data we are able to make clear statements on the attribution of a 2014-like extreme draught event to human causal factors.

Solution and Crystallographic Structures of the Central Region of the Phosphoprotein from Human Metapneumovirus

PubMed Central

Leyrat, Cedric; Renner, Max; Harlos, Karl; Grimes, Jonathan M.

2013-01-01

Human metapneumovirus (HMPV) of the family Paramyxoviridae is a major cause of respiratory illness worldwide. Phosphoproteins (P) from Paramyxoviridae are essential co-factors of the viral RNA polymerase that form tetramers and possess long intrinsically disordered regions (IDRs). We located the central region of HMPV P (Pced) which is involved in tetramerization using disorder analysis and modeled its 3D structure ab initio using Rosetta fold-and-dock. We characterized the solution-structure of Pced using small angle X-ray scattering (SAXS) and carried out direct fitting to the scattering data to filter out incorrect models. Molecular dynamics simulations (MDS) and ensemble optimization were employed to select correct models and capture the dynamic character of Pced. Our analysis revealed that oligomerization involves a compact central core located between residues 169-194 (Pcore), that is surrounded by flexible regions with α-helical propensity. We crystallized this fragment and solved its structure at 3.1 Å resolution by molecular replacement, using the folded core from our SAXS-validated ab initio model. The RMSD between modeled and experimental tetramers is as low as 0.9 Å, demonstrating the accuracy of the approach. A comparison of the structure of HMPV P to existing mononegavirales Pced structures suggests that Pced evolved under weak selective pressure. Finally, we discuss the advantages of using SAXS in combination with ab initio modeling and MDS to solve the structure of small, homo-oligomeric protein complexes. PMID:24224051

Modeling global Hammond landform regions from 250-m elevation data

USGS Publications Warehouse

Karagulle, Deniz; Frye, Charlie; Sayre, Roger; Breyer, Sean P.; Aniello, Peter; Vaughan, Randy; Wright, Dawn J.

2017-01-01

In 1964, E.H. Hammond proposed criteria for classifying and mapping physiographic regions of the United States. Hammond produced a map entitled “Classes of Land Surface Form in the Forty-Eight States, USA”, which is regarded as a pioneering and rigorous treatment of regional physiography. Several researchers automated Hammond?s model in GIS. However, these were local or regional in application, and resulted in inadequate characterization of tablelands. We used a global 250 m DEM to produce a new characterization of global Hammond landform regions. The improved algorithm we developed for the regional landform modeling: (1) incorporated a profile parameter for the delineation of tablelands; (2) accommodated negative elevation data values; (3) allowed neighborhood analysis window (NAW) size to vary between parameters; (4) more accurately bounded plains regions; and (5) mapped landform regions as opposed to discrete landform features. The new global Hammond landform regions product builds on an existing global Hammond landform features product developed by the U.S. Geological Survey, which, while globally comprehensive, did not include tablelands, used a fixed NAW size, and essentially classified pixels rather than regions. Our algorithm also permits the disaggregation of “mixed” Hammond types (e.g. plains with high mountains) into their component parts.

A Probabilistic Tsunami Hazard Study of the Auckland Region, Part II: Inundation Modelling and Hazard Assessment

NASA Astrophysics Data System (ADS)

Lane, E. M.; Gillibrand, P. A.; Wang, X.; Power, W.

2013-09-01

Regional source tsunamis pose a potentially devastating hazard to communities and infrastructure on the New Zealand coast. But major events are very uncommon. This dichotomy of infrequent but potentially devastating hazards makes realistic assessment of the risk challenging. Here, we describe a method to determine a probabilistic assessment of the tsunami hazard by regional source tsunamis with an "Average Recurrence Interval" of 2,500-years. The method is applied to the east Auckland region of New Zealand. From an assessment of potential regional tsunamigenic events over 100,000 years, the inundation of the Auckland region from the worst 100 events is modelled using a hydrodynamic model and probabilistic inundation depths on a 2,500-year time scale were determined. Tidal effects on the potential inundation were included by coupling the predicted wave heights with the probability density function of tidal heights at the inundation site. Results show that the more exposed northern section of the east coast and outer islands in the Hauraki Gulf face the greatest hazard from regional tsunamis in the Auckland region. Incorporating tidal effects into predictions of inundation reduced the predicted hazard compared to modelling all the tsunamis arriving at high tide giving a more accurate hazard assessment on the specified time scale. This study presents the first probabilistic analysis of dynamic modelling of tsunami inundation for the New Zealand coast and as such provides the most comprehensive assessment of tsunami inundation of the Auckland region from regional source tsunamis available to date.

Artificial equilibrium points in binary asteroid systems with continuous low-thrust

NASA Astrophysics Data System (ADS)

Bu, Shichao; Li, Shuang; Yang, Hongwei

2017-08-01

The positions and dynamical characteristics of artificial equilibrium points (AEPs) in the vicinity of a binary asteroid with continuous low-thrust are studied. The restricted ellipsoid-ellipsoid model of binary system is employed for the binary asteroid system. The positions of AEPs are obtained by this model. It is found that the set of the point L1 or L2 forms a shape of an ellipsoid while the set of the point L3 forms a shape like a "banana". The effect of the continuous low-thrust on the feasible region of motion is analyzed by zero velocity curves. Because of using the low-thrust, the unreachable region can become reachable. The linearized equations of motion are derived for stability's analysis. Based on the characteristic equation of the linearized equations, the stability conditions are derived. The stable regions of AEPs are investigated by a parametric analysis. The effect of the mass ratio and ellipsoid parameters on stable region is also discussed. The results show that the influence of the mass ratio on the stable regions is more significant than the parameters of ellipsoid.

Evaluation of Quality Indicators of Integrated Care in a Regional Psychiatry Budget – A Pre-Post Comparison by Secondary Data Analysis

PubMed Central

Hubmann, Svenja; Birker, Thomas; Hejnal, Torsten; Fischer, Felix

2016-01-01

The Regional Psychiatry Budget (RPB), as a special arrangement within the German Federal Hospital Refund Regulation, is based on the capitation principle. A lump sum is allocated to a major inpatient care provider in a large region on a yearly basis. Under this model, the provider is free to offer all forms of treatment and to construct individual models of integrated care that specifically suit the region and the needs of community members. The present study aimed to evaluate selected aspects that represent a change in the psychiatric health status of patients in the covered region under the conditions of the RPB. We performed a secondary data analysis of administrative data of 19,913 cases generated by the hospital in a pre-post comparison of the periods before and under RPB conditions. The average length of an inpatient stay was reduced by approximately 22 % and could be partially replaced by day care. Selected indicators suggest equal or higher quality of care with stable cost in the population in need of psychiatric care in the district. PMID:28413369

Development of Relative Risk Model for Regional Groundwater Risk Assessment: A Case Study in the Lower Liaohe River Plain, China

PubMed Central

Li, Xianbo; Zuo, Rui; Teng, Yanguo; Wang, Jinsheng; Wang, Bin

2015-01-01

Increasing pressure on water supply worldwide, especially in arid areas, has resulted in groundwater overexploitation and contamination, and subsequent deterioration of the groundwater quality and threats to public health. Environmental risk assessment of regional groundwater is an important tool for groundwater protection. This study presents a new approach for assessing the environmental risk assessment of regional groundwater. It was carried out with a relative risk model (RRM) coupled with a series of indices, such as a groundwater vulnerability index, which includes receptor analysis, risk source analysis, risk exposure and hazard analysis, risk characterization, and management of groundwater. The risk map is a product of the probability of environmental contamination and impact. The reliability of the RRM was verified using Monte Carlo analysis. This approach was applied to the lower Liaohe River Plain (LLRP), northeastern China, which covers 23604 km2. A spatial analysis tool within GIS which was used to interpolate and manipulate the data to develop environmental risk maps of regional groundwater, divided the level of risk from high to low into five ranks (V, IV, III, II, I). The results indicate that areas of relative risk rank (RRR) V cover 2324 km2, covering 9.8% of the area; RRR IV covers 3986 km2, accounting for 16.9% of the area. It is a new and appropriate method for regional groundwater resource management and land use planning, and is a rapid and effective tool for improving strategic decision making to protect groundwater and reduce environmental risk. PMID:26020518

Applying horizontal diffusion on pressure surface to mesoscale models on terrain-following coordinates

Treesearch

Hann-Ming Henry Juang; Ching-Teng Lee; Yongxin Zhang; Yucheng Song; Ming-Chin Wu; Yi-Leng Chen; Kevin Kodama; Shyh-Chin Chen

2005-01-01

The National Centers for Environmental Prediction regional spectral model and mesoscale spectral model (NCEP RSM/MSM) use a spectral computation on perturbation. The perturbation is defined as a deviation between RSM/MSM forecast value and their outer model or analysis value on model sigma-coordinate surfaces. The horizontal diffusion used in the models applies...

Information-computational platform for collaborative multidisciplinary investigations of regional climatic changes and their impacts

NASA Astrophysics Data System (ADS)

Gordov, Evgeny; Lykosov, Vasily; Krupchatnikov, Vladimir; Okladnikov, Igor; Titov, Alexander; Shulgina, Tamara

2013-04-01

Analysis of growing volume of related to climate change data from sensors and model outputs requires collaborative multidisciplinary efforts of researchers. To do it timely and in reliable way one needs in modern information-computational infrastructure supporting integrated studies in the field of environmental sciences. Recently developed experimental software and hardware platform Climate (http://climate.scert.ru/) provides required environment for regional climate change related investigations. The platform combines modern web 2.0 approach, GIS-functionality and capabilities to run climate and meteorological models, process large geophysical datasets and support relevant analysis. It also supports joint software development by distributed research groups, and organization of thematic education for students and post-graduate students. In particular, platform software developed includes dedicated modules for numerical processing of regional and global modeling results for consequent analysis and visualization. Also run of integrated into the platform WRF and «Planet Simulator» models, modeling results data preprocessing and visualization is provided. All functions of the platform are accessible by a user through a web-portal using common graphical web-browser in the form of an interactive graphical user interface which provides, particularly, capabilities of selection of geographical region of interest (pan and zoom), data layers manipulation (order, enable/disable, features extraction) and visualization of results. Platform developed provides users with capabilities of heterogeneous geophysical data analysis, including high-resolution data, and discovering of tendencies in climatic and ecosystem changes in the framework of different multidisciplinary researches. Using it even unskilled user without specific knowledge can perform reliable computational processing and visualization of large meteorological, climatic and satellite monitoring datasets through unified graphical web-interface. Partial support of RF Ministry of Education and Science grant 8345, SB RAS Program VIII.80.2 and Projects 69, 131, 140 and APN CBA2012-16NSY project is acknowledged.

A model and typology of collaboration between professionals in healthcare organizations

PubMed Central

D'Amour, Danielle; Goulet, Lise; Labadie, Jean-François; Martín-Rodriguez, Leticia San; Pineault, Raynald

2008-01-01

Background The new forms of organization of healthcare services entail the development of new clinical practices that are grounded in collaboration. Despite recent advances in research on the subject of collaboration, there is still a need for a better understanding of collaborative processes and for conceptual tools to help healthcare professionals develop collaboration amongst themselves in complex systems. This study draws on D'Amour's structuration model of collaboration to analyze healthcare facilities offering perinatal services in four health regions in the province of Quebec. The objectives are to: 1) validate the indicators of the structuration model of collaboration; 2) evaluate interprofessional and interorganizational collaboration in four health regions; and 3) propose a typology of collaboration Methods A multiple-case research strategy was used. The cases were the healthcare facilities that offer perinatal services in four health regions in the province of Quebec (Canada). The data were collected through 33 semi-structured interviews with healthcare managers and professionals working in the four regions. Written material was also analyzed. The data were subjected to a "mixed" inductive-deductive analysis conducted in two main stages: an internal analysis of each case followed by a cross-sectional analysis of all the cases. Results The collaboration indicators were shown to be valid, although some changes were made to three of them. Analysis of the data showed great variation in the level of collaboration between the cases and on each dimension. The results suggest a three-level typology of collaboration based on the ten indicators: active collaboration, developing collaboration and potential collaboration. Conclusion The model and the typology make it possible to analyze collaboration and identify areas for improvement. Researchers can use the indicators to determine the intensity of collaboration and link it to clinical outcomes. Professionals and administrators can use the model to perform a diagnostic of collaboration and implement interventions to intensify it. PMID:18803881

Patterns and Trends of Primary Production, Inorganic Carbon and Oxygen and Their Ecosystem Impacts in a Regional Biogeochemical Ocean Model for Atlantic Canada

NASA Astrophysics Data System (ADS)

Fennel, K.; Rutherford, K. E.; Kuhn, A. M.; Zhang, W.; Brennan, C. E.; Zhang, R.

2016-12-01

Representing coastal oceans in global biogeochemical models is a challenge, yet the ecosystems in these regions are most vulnerable to the combined stressors of ocean warming, deoxygenation, acidification, eutrophication and fishing. Coastal regions also have large air-sea fluxes of CO2, making them an important but poorly quantified component of the global carbon cycle, and are the most relevant for human activities. Regional model applications that are nested within large-scale or global models are necessary for detailed studies of coastal regions. We present results from such a regional biogeochemical model for the northwestern North Atlantic shelves and adjacent deep ocean of Atlantic Canada. The model is an implementation of the Regional Ocean Modeling System (ROMS) and includes an NPZD-type nitrogen cycle model with explicit representation of dissolved oxygen and inorganic carbon. The region is at the confluence of the Gulf Stream and Labrador Current making it highly dynamic, a challenge for analysis and prediction, and prone to large changes. Historically a rich fishing ground, coastal ecosystems in Atlantic Canada have undergone dramatic changes including the collapse of several economically important fish stocks and the listing of many species as threatened or endangered. Furthermore it is unclear whether the region is a net source or sink of atmospheric CO2 with estimates of the size and direction of the net air-sea CO2 flux remaining controversial. We will discuss simulated patterns of primary production, inorganic carbon fluxes and oxygen trends in the context of circulation features and shelf residence times for the present ocean state and present future projections.

Attribution of spring snow water equivalent (SWE) changes over the northern hemisphere to anthropogenic effects

NASA Astrophysics Data System (ADS)

Jeong, Dae Il; Sushama, Laxmi; Naveed Khaliq, M.

2017-06-01

Snow is an important component of the cryosphere and it has a direct and important influence on water storage and supply in snowmelt-dominated regions. This study evaluates the temporal evolution of snow water equivalent (SWE) for the February-April spring period using the GlobSnow observation dataset for the 1980-2012 period. The analysis is performed for different regions of hemispherical to sub-continental scales for the Northern Hemisphere. The detection-attribution analysis is then performed to demonstrate anthropogenic and natural effects on spring SWE changes for different regions, by comparing observations with six CMIP5 model simulations for three different external forcings: all major anthropogenic and natural (ALL) forcings, greenhouse gas (GHG) forcing only, and natural forcing only. The observed spring SWE generally displays a decreasing trend, due to increasing spring temperatures. However, it exhibits a remarkable increasing trend for the southern parts of East Eurasia. The six CMIP5 models with ALL forcings reproduce well the observed spring SWE decreases at the hemispherical scale and continental scales, whereas important differences are noted for smaller regions such as southern and northern parts of East Eurasia and northern part of North America. The effects of ALL and GHG forcings are clearly detected for the spring SWE decline at the hemispherical scale, based on multi-model ensemble signals. The effects of ALL and GHG forcings, however, are less clear for the smaller regions or with single-model signals, indicating the large uncertainty in regional SWE changes, possibly due to stronger influence of natural climate variability.

First status report on regional ground-water flow modeling for the Paradox Basin, Utah

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

Andrews, R.W.

1984-05-01

Regional ground-water flow within the principal hydrogeologic units of the Paradox Basin is evaluated by developing a conceptual model of the flow regime in the shallow aquifers and the deep-basin brine aquifers and testing these models using a three-dimensional, finite-difference flow code. Semiquantitative sensitivity analysis (a limited parametric study) is conducted to define the system response to changes in hydrologic properties or boundary conditions. A direct method for sensitivity analysis using an adjoint form of the flow equation is applied to the conceptualized flow regime in the Leadville limestone aquifer. All steps leading to the final results and conclusions aremore » incorporated in this report. The available data utilized in this study is summarized. The specific conceptual models, defining the areal and vertical averaging of litho-logic units, aquifer properties, fluid properties, and hydrologic boundary conditions, are described in detail. Two models were evaluated in this study: a regional model encompassing the hydrogeologic units above and below the Paradox Formation/Hermosa Group and a refined scale model which incorporated only the post Paradox strata. The results are delineated by the simulated potentiometric surfaces and tables summarizing areal and vertical boundary fluxes, Darcy velocities at specific points, and ground-water travel paths. Results from the adjoint sensitivity analysis include importance functions and sensitivity coefficients, using heads or the average Darcy velocities to represent system response. The reported work is the first stage of an ongoing evaluation of the Gibson Dome area within the Paradox Basin as a potential repository for high-level radioactive wastes.« less

Climate Projections from the NARCliM Project: Bayesian Model Averaging of Maximum Temperature Projections

NASA Astrophysics Data System (ADS)

Olson, R.; Evans, J. P.; Fan, Y.

2015-12-01

NARCliM (NSW/ACT Regional Climate Modelling Project) is a regional climate project for Australia and the surrounding region. It dynamically downscales 4 General Circulation Models (GCMs) using three Regional Climate Models (RCMs) to provide climate projections for the CORDEX-AustralAsia region at 50 km resolution, and for south-east Australia at 10 km resolution. The project differs from previous work in the level of sophistication of model selection. Specifically, the selection process for GCMs included (i) conducting literature review to evaluate model performance, (ii) analysing model independence, and (iii) selecting models that span future temperature and precipitation change space. RCMs for downscaling the GCMs were chosen based on their performance for several precipitation events over South-East Australia, and on model independence.Bayesian Model Averaging (BMA) provides a statistically consistent framework for weighing the models based on their likelihood given the available observations. These weights are used to provide probability distribution functions (pdfs) for model projections. We develop a BMA framework for constructing probabilistic climate projections for spatially-averaged variables from the NARCliM project. The first step in the procedure is smoothing model output in order to exclude the influence of internal climate variability. Our statistical model for model-observations residuals is a homoskedastic iid process. Comparing RCMs with Australian Water Availability Project (AWAP) observations is used to determine model weights through Monte Carlo integration. Posterior pdfs of statistical parameters of model-data residuals are obtained using Markov Chain Monte Carlo. The uncertainty in the properties of the model-data residuals is fully accounted for when constructing the projections. We present the preliminary results of the BMA analysis for yearly maximum temperature for New South Wales state planning regions for the period 2060-2079.

Winter Precipitation Forecast in the European and Mediterranean Regions Using Cluster Analysis

NASA Astrophysics Data System (ADS)

Totz, Sonja; Tziperman, Eli; Coumou, Dim; Pfeiffer, Karl; Cohen, Judah

2017-12-01

The European climate is changing under global warming, and especially the Mediterranean region has been identified as a hot spot for climate change with climate models projecting a reduction in winter rainfall and a very pronounced increase in summertime heat waves. These trends are already detectable over the historic period. Hence, it is beneficial to forecast seasonal droughts well in advance so that water managers and stakeholders can prepare to mitigate deleterious impacts. We developed a new cluster-based empirical forecast method to predict precipitation anomalies in winter. This algorithm considers not only the strength but also the pattern of the precursors. We compare our algorithm with dynamic forecast models and a canonical correlation analysis-based prediction method demonstrating that our prediction method performs better in terms of time and pattern correlation in the Mediterranean and European regions.

Vector Autoregression, Structural Equation Modeling, and Their Synthesis in Neuroimaging Data Analysis

PubMed Central

Chen, Gang; Glen, Daniel R.; Saad, Ziad S.; Hamilton, J. Paul; Thomason, Moriah E.; Gotlib, Ian H.; Cox, Robert W.

2011-01-01

Vector autoregression (VAR) and structural equation modeling (SEM) are two popular brain-network modeling tools. VAR, which is a data-driven approach, assumes that connected regions exert time-lagged influences on one another. In contrast, the hypothesis-driven SEM is used to validate an existing connectivity model where connected regions have contemporaneous interactions among them. We present the two models in detail and discuss their applicability to FMRI data, and interpretational limits. We also propose a unified approach that models both lagged and contemporaneous effects. The unifying model, structural vector autoregression (SVAR), may improve statistical and explanatory power, and avoids some prevalent pitfalls that can occur when VAR and SEM are utilized separately. PMID:21975109

Hyper-Resolution Groundwater Modeling using MODFLOW 6

NASA Astrophysics Data System (ADS)

Hughes, J. D.; Langevin, C.

2017-12-01

MODFLOW 6 is the latest version of the U.S. Geological Survey's modular hydrologic model. MODFLOW 6 was developed to synthesize many of the recent versions of MODFLOW into a single program, improve the way different process models are coupled, and to provide an object-oriented framework for adding new types of models and packages. The object-oriented framework and underlying numerical solver make it possible to tightly couple any number of hyper-resolution models within coarser regional models. The hyper-resolution models can be used to evaluate local-scale groundwater issues that may be affected by regional-scale forcings. In MODFLOW 6, hyper-resolution meshes can be maintained as separate model datasets, similar to MODFLOW-LGR, which simplifies the development of a coarse regional model with imbedded hyper-resolution models from a coarse regional model. For example, the South Atlantic Coastal Plain regional water availability model was converted from a MODFLOW-2000 model to a MODFLOW 6 model. The horizontal discretization of the original model is approximately 3,218 m x 3,218 m. Hyper-resolution models of the Aiken and Sumter County water budget areas in South Carolina with a horizontal discretization of approximately 322 m x 322 m were developed and were tightly coupled to a modified version of the original coarse regional model that excluded these areas. Hydraulic property and aquifer geometry data from the coarse model were mapped to the hyper-resolution models. The discretization of the hyper-resolution models is fine enough to make detailed analyses of the effect that changes in groundwater withdrawals in the production aquifers have on the water table and surface-water/groundwater interactions. The approach used in this analysis could be applied to other regional water availability models that have been developed by the U.S. Geological Survey to evaluate local scale groundwater issues.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Relevance of Regional Hydro-Climatic Projection Data for Hydrodynamics and Water Quality Modelling of the Baltic Sea

NASA Astrophysics Data System (ADS)

Goldenberg, R.; Vigouroux, G.; Chen, Y.; Bring, A.; Kalantari, Z.; Prieto, C.; Destouni, G.

2017-12-01

The Baltic Sea, located in Northern Europe, is one of the world's largest body of brackish water, enclosed and surrounded by nine different countries. The magnitude of climate change may be particularly large in northern regions, and identifying its impacts on vulnerable inland waters and their runoff and nutrient loading to the Baltic Sea is an important and complex task. Exploration of such hydro-climatic impacts is needed to understand potential future changes in physical, ecological and water quality conditions in the regional coastal and marine waters. In this study, we investigate hydro-climatic changes and impacts on the Baltic Sea by synthesizing multi-model climate projection data from the CORDEX regional downscaling initiative (EURO- and Arctic- CORDEX domains, http://www.cordex.org/). We identify key hydro-climatic variable outputs of these models and assess model performance with regard to their projected temporal and spatial change behavior and impacts on different scales and coastal-marine parts, up to the whole Baltic Sea. Model spreading, robustness and impact implications for the Baltic Sea system are investigated for and through further use in simulations of coastal-marine hydrodynamics and water quality based on these key output variables and their change projections. Climate model robustness in this context is assessed by inter-model spreading analysis and observation data comparisons, while projected change implications are assessed by forcing of linked hydrodynamic and water quality modeling of the Baltic Sea based on relevant hydro-climatic outputs for inland water runoff and waterborne nutrient loading to the Baltic sea, as well as for conditions in the sea itself. This focused synthesis and analysis of hydro-climatically relevant output data of regional climate models facilitates assessment of reliability and uncertainty in projections of driver-impact changes of key importance for Baltic Sea physical, water quality and ecological conditions and their future evolution.

Modeling of Regional Climate Change Effects on Ground-Level Ozone and Childhood Asthma

PubMed Central

Sheffield, Perry E.; Knowlton, Kim; Carr, Jessie L.; Kinney, Patrick L.

2011-01-01

Background The adverse respiratory effects of ground-level ozone are well-established. Ozone is the air pollutant most consistently projected to increase under future climate change. Purpose To project future pediatric asthma emergency department visits associated with ground-level ozone changes, comparing 1990s to 2020s. Methods This study assessed future numbers of asthma emergency department visits for children aged 0–17 years using (1) baseline New York City metropolitan area emergency department rates, (2) a dose–response relationship between ozone levels and pediatric asthma emergency department visits, and (3) projected daily 8-hour maximum ozone concentrations for the 2020s as simulated by a global-to-regional climate change and atmospheric chemistry model. Sensitivity analyses included population projections and ozone precursor changes. This analysis occurred in 2010. Results In this model, climate change could cause an increase in regional summer ozone-related asthma emergency department visits for children aged 0–17 years of 7.3% across the New York City metropolitan region by the 2020s. This effect diminished with inclusion of ozone precursor changes. When population growth is included, the projections of morbidity related to ozone are even larger. Conclusions The results of this analysis demonstrate that the use of regional climate and atmospheric chemistry models make possible the projection of local climate change health effects for specific age groups and specific disease outcomes – such as emergency department visits for asthma. Efforts should be made to improve on this type of modeling to inform local and wider-scale climate change mitigation and adaptation policy. PMID:21855738

Executive summary: Benefit-cost evaluation of an intra-regional air service in the Bay Area and a technology assessment of transportation system investments. [regional planning for the San Francisco Bay area of California

NASA Technical Reports Server (NTRS)

Haefner, L. E.

1978-01-01

The benefits and costs that would result from an intra-regional air service operation in the San Francisco Bay area were determined by utilizing an iterative statistical decision model to evaluate combinations of commuter airport sites and surface transportation facilities in conjunction with service by a given commuter aircraft type in light of area regional growth alternatives and peak and off-peak regional travel patterns. The model evaluates such transportation option with respect to criteria of airline profitability, public acceptance, and public and private non-user costs. In so doing, it incorporates information on modal split, peak and off-peak use of the air commuter fleet, terminal and airport costs, development costs and uses of land in proximity to the airport sites, regional population shifts, and induced zonal shifts in travel demand. The model is multimodal in its analytic capability, and performs exhaustive sensitivity analysis.

Modeling the Impact of Uganda's Safe Male Circumcision Program: Implications for Age and Regional Targeting.

PubMed

Kripke, Katharine; Vazzano, Andrea; Kirungi, William; Musinguzi, Joshua; Opio, Alex; Ssempebwa, Rhobbinah; Nakawunde, Susan; Kyobutungi, Sheila; Akao, Juliet N; Magala, Fred; Mwidu, George; Castor, Delivette; Njeuhmeli, Emmanuel

2016-01-01

Uganda aims to provide safe male circumcision (SMC) to 80% of men ages 15-49 by 2016. To date, only 2 million men have received SMC of the 4.2 million men required. In response to age and regional trends in SMC uptake, the country sought to re-examine its targets with respect to age and subnational region, to assess the program's progress, and to refine the implementation approach. The Decision Makers' Program Planning Tool, Version 2.0 (DMPPT 2.0), was used in conjunction with incidence projections from the Spectrum/AIDS Impact Module (AIM) to conduct this analysis. Population, births, deaths, and HIV incidence and prevalence were used to populate the model. Baseline male circumcision prevalence was derived from the 2011 AIDS Indicator Survey. Uganda can achieve the most immediate impact on HIV incidence by circumcising men ages 20-34. This group will also require the fewest circumcisions for each HIV infection averted. Focusing on men ages 10-19 will offer the greatest impact over a 15-year period, while focusing on men ages 15-34 offers the most cost-effective strategy over the same period. A regional analysis showed little variation in cost-effectiveness of scaling up SMC across eight regions. Scale-up is cost-saving in all regions. There is geographic variability in program progress, highlighting two regions with low baseline rates of circumcision where additional efforts will be needed. Focusing SMC efforts on specific age groups and regions may help to accelerate Uganda's SMC program progress. Policy makers in Uganda have already used model outputs in planning efforts, proposing males ages 10-34 as a priority group for SMC in the 2014 application to the Global Fund's new funding model. As scale-up continues, the country should also consider a greater effort to expand SMC in regions with low MC prevalence.

Modeling the Impact of Uganda’s Safe Male Circumcision Program: Implications for Age and Regional Targeting

PubMed Central

Kripke, Katharine; Vazzano, Andrea; Kirungi, William; Musinguzi, Joshua; Opio, Alex; Ssempebwa, Rhobbinah; Nakawunde, Susan; Kyobutungi, Sheila; Akao, Juliet N.; Magala, Fred; Mwidu, George; Castor, Delivette

2016-01-01

Background Uganda aims to provide safe male circumcision (SMC) to 80% of men ages 15–49 by 2016. To date, only 2 million men have received SMC of the 4.2 million men required. In response to age and regional trends in SMC uptake, the country sought to re-examine its targets with respect to age and subnational region, to assess the program’s progress, and to refine the implementation approach. Methods and Findings The Decision Makers’ Program Planning Tool, Version 2.0 (DMPPT 2.0), was used in conjunction with incidence projections from the Spectrum/AIDS Impact Module (AIM) to conduct this analysis. Population, births, deaths, and HIV incidence and prevalence were used to populate the model. Baseline male circumcision prevalence was derived from the 2011 AIDS Indicator Survey. Uganda can achieve the most immediate impact on HIV incidence by circumcising men ages 20–34. This group will also require the fewest circumcisions for each HIV infection averted. Focusing on men ages 10–19 will offer the greatest impact over a 15-year period, while focusing on men ages 15–34 offers the most cost-effective strategy over the same period. A regional analysis showed little variation in cost-effectiveness of scaling up SMC across eight regions. Scale-up is cost-saving in all regions. There is geographic variability in program progress, highlighting two regions with low baseline rates of circumcision where additional efforts will be needed. Conclusion Focusing SMC efforts on specific age groups and regions may help to accelerate Uganda’s SMC program progress. Policy makers in Uganda have already used model outputs in planning efforts, proposing males ages 10–34 as a priority group for SMC in the 2014 application to the Global Fund’s new funding model. As scale-up continues, the country should also consider a greater effort to expand SMC in regions with low MC prevalence. PMID:27410234

Microfocal angiography of the pulmonary vasculature

NASA Astrophysics Data System (ADS)

Clough, Anne V.; Haworth, Steven T.; Roerig, David T.; Linehan, John H.; Dawson, Christopher A.

1998-07-01

X-ray microfocal angiography provides a means of assessing regional microvascular perfusion parameters using residue detection of vascular indicators. As an application of this methodology, we studied the effects of alveolar hypoxia, a pulmonary vasoconstrictor, on the pulmonary microcirculation to determine changes in regional blood mean transit time, volume and flow between control and hypoxic conditions. Video x-ray images of a dog lung were acquired as a bolus of radiopaque contrast medium passed through the lobar vasculature. X-ray time-absorbance curves were acquired from arterial and microvascular regions-of-interest during both control and hypoxic alveolar gas conditions. A mathematical model based on indicator-dilution theory applied to image residue curves was applied to the data to determine changes in microvascular perfusion parameters. Sensitivity of the model parameters to the model assumptions was analyzed. Generally, the model parameter describing regional microvascular volume, corresponding to area under the microvascular absorbance curve, was the most robust. The results of the model analysis applied to the experimental data suggest a significant decrease in microvascular volume with hypoxia. However, additional model assumptions concerning the flow kinematics within the capillary bed may be required for assessing changes in regional microvascular flow and mean transit time from image residue data.

Assessing Hydrological and Energy Budgets in Amazonia through Regional Downscaling, and Comparisons with Global Reanalysis Products

NASA Astrophysics Data System (ADS)

Nunes, A.; Ivanov, V. Y.

2014-12-01

Although current global reanalyses provide reasonably accurate large-scale features of the atmosphere, systematic errors are still found in the hydrological and energy budgets of such products. In the tropics, precipitation is particularly challenging to model, which is also adversely affected by the scarcity of hydrometeorological datasets in the region. With the goal of producing downscaled analyses that are appropriate for a climate assessment at regional scales, a regional spectral model has used a combination of precipitation assimilation with scale-selective bias correction. The latter is similar to the spectral nudging technique, which prevents the departure of the regional model's internal states from the large-scale forcing. The target area in this study is the Amazon region, where large errors are detected in reanalysis precipitation. To generate the downscaled analysis, the regional climate model used NCEP/DOE R2 global reanalysis as the initial and lateral boundary conditions, and assimilated NOAA's Climate Prediction Center (CPC) MORPHed precipitation (CMORPH), available at 0.25-degree resolution, every 3 hours. The regional model's precipitation was successfully brought closer to the observations, in comparison to the NCEP global reanalysis products, as a result of the impact of a precipitation assimilation scheme on cumulus-convection parameterization, and improved boundary forcing achieved through a new version of scale-selective bias correction. Water and energy budget terms were also evaluated against global reanalyses and other datasets.

Aerosols, Chemistry, and Radiative Forcing: A 3-D Model Analysis of Satellite and ACE-Asia data (ACMAP)

NASA Technical Reports Server (NTRS)

Chin, Mian; Ginoux, Paul; Torres, Omar; Zhao, Xue-Peng

2005-01-01

We propose a research project to incorporate a global 3-D model and satellite data into the multi-national Aerosol Characterization Experiment-Asia (ACE-Asia) mission. Our objectives are (1) to understand the physical, chemical, and optical properties of aerosols and the processes that control those properties over the Asian-Pacific region, (2) to investigate the interaction between aerosols and tropospheric chemistry, and (3) to determine the aerosol radiative forcing over the Asia-Pacific region. We will use the Georgia TecWGoddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model to link satellite observations and the ACE-Asia measurements. First, we will use the GOCART model to simulate aerosols and related species, and evaluate the model with satellite and in-situ observations. Second, the model generated aerosol vertical profiles and compositions will be used to validate the satellite products; and the satellite data will be used for during- and post- mission analysis. Third, we will use the model to analyze and interpret both satellite and ACE- Asia field campaign data and investigate the aerosol-chemistry interactions. Finally, we will calculate aerosol radiative forcing over the Asian-Pacific region, and assess the influence of Asian pollution in the global atmosphere. We propose a research project to incorporate a global 3-D model and satellite data into

Association analysis for feet and legs disorders with whole-genome sequence variants in 3 dairy cattle breeds.

PubMed

Wu, Xiaoping; Guldbrandtsen, Bernt; Lund, Mogens Sandø; Sahana, Goutam

2016-09-01

Identification of genetic variants associated with feet and legs disorders (FLD) will aid in the genetic improvement of these traits by providing knowledge on genes that influence trait variations. In Denmark, FLD in cattle has been recorded since the 1990s. In this report, we used deregressed breeding values as response variables for a genome-wide association study. Bulls (5,334 Danish Holstein, 4,237 Nordic Red Dairy Cattle, and 1,180 Danish Jersey) with deregressed estimated breeding values were genotyped with the Illumina Bovine 54k single nucleotide polymorphism (SNP) genotyping array. Genotypes were imputed to whole-genome sequence variants, and then 22,751,039 SNP on 29 autosomes were used for an association analysis. A modified linear mixed-model approach (efficient mixed-model association eXpedited, EMMAX) and a linear mixed model were used for association analysis. We identified 5 (3,854 SNP), 3 (13,642 SNP), and 0 quantitative trait locus (QTL) regions associated with the FLD index in Danish Holstein, Nordic Red Dairy Cattle, and Danish Jersey populations, respectively. We did not identify any QTL that were common among the 3 breeds. In a meta-analysis of the 3 breeds, 4 QTL regions were significant, but no additional QTL region was identified compared with within-breed analyses. Comparison between top SNP locations within these QTL regions and known genes suggested that RASGRP1, LCORL, MOS, and MITF may be candidate genes for FLD in dairy cattle. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Data Analysis, Modeling, and Ensemble Forecasting to Support NOWCAST and Forecast Activities at the Fallon Naval Station

DTIC Science & Technology

2011-09-30

forecasting and use of satellite data assimilation for model evaluation (Jiang et al, 2011a). He is a task leader on another NSF EPSCoR project...K. Horvath, R. Belu, 2011a: Application of variational data assimilation to dynamical downscaling of regional wind energy resources in the western...1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Data Analysis, Modeling, and Ensemble Forecasting to

Application of a process-based shallow landslide hazard model over a broad area in Central Italy

USGS Publications Warehouse

Gioia, Eleonora; Speranza, Gabriella; Ferretti, Maurizio; Godt, Jonathan W.; Baum, Rex L.; Marincioni, Fausto

2015-01-01

Process-based models are widely used for rainfall-induced shallow landslide forecasting. Previous studies have successfully applied the U.S. Geological Survey’s Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS) model (Baum et al. 2002) to compute infiltration-driven changes in the hillslopes’ factor of safety on small scales (i.e., tens of square kilometers). Soil data input for such models are difficult to obtain across larger regions. This work describes a novel methodology for the application of TRIGRS over broad areas with relatively uniform hydrogeological properties. The study area is a 550-km2 region in Central Italy covered by post-orogenic Quaternary sediments. Due to the lack of field data, we assigned mechanical and hydrological property values through a statistical analysis based on literature review of soils matching the local lithologies. We calibrated the model using rainfall data from 25 historical rainfall events that triggered landslides. We compared the variation of pressure head and factor of safety with the landslide occurrence to identify the best fitting input conditions. Using calibrated inputs and a soil depth model, we ran TRIGRS for the study area. Receiver operating characteristic (ROC) analysis, comparing the model’s output with a shallow landslide inventory, shows that TRIGRS effectively simulated the instability conditions in the post-orogenic complex during historical rainfall scenarios. The implication of this work is that rainfall-induced landslides over large regions may be predicted by a deterministic model, even where data on geotechnical and hydraulic properties as well as temporal changes in topography or subsurface conditions are not available.

Dry spell trend analysis in Kenya and the Murray Darling Basin using daily rainfall

NASA Astrophysics Data System (ADS)

Muita, R. R.; van Ogtrop, F. F.; Vervoort, R. W.

2012-04-01

Important agricultural areas in Kenya and the Murray Darling Basin (MDB) in Australia are largely semi-arid to arid. Persistent dry periods and timing of dry spells directly impact the availability of soil moisture and hence crop production in these regions. Most studies focus on the analysis of dry spell lengths at an annual scale. However, timing and length of dry spells at finer temporal scales is more beneficial for cropping when considering a trade-off between the time scale and the ability to analyse dry spell length. The aim of this study was to analyse the interannual and intra annual variations in dry spell lengths in the regions to inform crop management. This study analysed monthly dry spells based on daily rainfall for 1961-2010 on a limited dataset of 13 locations in Kenya and 17 locations in the MDB. This dataset was the most consistent across both regions and future analysis will incorporate more stations and longer time periods where available. Dry spell lengths were analysed by month and year and trends in monthly and annual dry spell lengths were analysed using Generalised Linear Models (GLM) and the Mann Kendall test (MK). Overall, monthly dryspell lengths are right skewed with higher frequency of shorter dryspells (3-25 days). In Kenya, significant increases in mean dry spell lengths (p≤0.02) are observed in inland arid-to semi humid locations but this temporal trend appears to decrease in highland and the coastal regions. Analysis of the MDB stations suggests changes in seasonality. For example, spatial trends suggest a North-South increase in dry spell length in summer (December - February), but a shortening after February. Generally, the GLM and MK results are similar in the two regions but the MK test tends to give higher values of positive slope coefficients and lower values for negative coefficients compared to GLM. This may limit the ability of finding the best estimates for model coefficients. Previous studies in Australia and Kenya have relied on continuous climatic indices based on global climate models and stochastic processes resulting in limited and mixed results. For agronomical purposes, our results show that direct assessment of dry spells lengths from daily rainfall also indicates changes in dry spells trends in Kenya and the MDB and that such an analysis is easy to use and requires limited assumptions. This initial analysis identifies significant increasing trends in the dry spell lengths in some areas and periods in Kenya and the MDB. This has major implications for crop production in these regions and it is recommended that this information be incorporated in the regions' management decisions. KEY WORDS: monthly dry spell length; Generalized Linear Models; Mann -Kendall test; month; Kenya, Murray Darling Basin (MDB).

An IR Sounding-Based Analysis of the Saharan Air Layer in North Africa

NASA Technical Reports Server (NTRS)

Nicholls, Stephen D.; Mohr, Karen I.

2018-01-01

Intense daytime surface heating over barren-to-sparsely vegetated surfaces results in dry convective mixing. In the absence of external forcing such as mountain waves, the dry convection can produce a deep, well-mixed, nearly isentropic boundary layer that becomes a well-mixed residual layer in the evening. These well-mixed layers (WML) retain their unique mid-tropospheric thermal and humidity structure for several days. To detect the SAL and characterize its properties, AIRS Level 2 Ver. 6 temperature and humidity products (2003-Present) are evaluated against rawinsondes and compared to model analysis at each of the 55 rawinsonde stations in northern Africa. To distinguish WML from Saharan air layers (WMLs of Saharan origin), the detection involved a two-step process: 1) algorithm-based detection of WMLs in dry environments (less than 7 g per kilogram mixing ratio) 2) identification of Sahara air layers (SAL) by applying Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) back trajectories to determine the history of each WML. WML occurrence rates from AIRS closely resemble that from rawinsondes, yet rates from model analysis were up to 30% higher than observations in the Sahara due to model errors. Despite the overly frequent occurrence of WMLs from model analysis, HYSPLIT trajectory analysis showed that SAL occurrence rates (given a WML exists) from rawinsondes, AIRS, and model analysis were nearly identical. Although the number of WMLs varied among the data sources, the proportion of WMLs which were classified as SAL was nearly the same. The analysis of SAL bulk properties showed that AIRS and model analysis exhibited a slight warm and moist bias relative to rawinsondes in non-Saharan locations, but model analysis was notably warmer than rawinsondes and AIRS within the Sahara. The latter result is likely associated with the dearth of available data assimilated by model analysis in the Sahara. The variability of SAL thicknesses was reasonably captured by both AIRS and model analysis, but the former favor layers than are thinner than observations. Finally, further analysis of HYSPLIT trajectories revealed that fewer than 10% and 33% of all SAL back trajectories passed through regions with notable precipitation (>100 mm accumulated along the trajectory path) or Aerosol Optical Depth (AOD greater than 0.4, 75th percentile of AOD) on average, respectively. Trajectory analysis indicated that only 57% of Saharan and 24% of non-Saharan WMLs are definitively of Saharan origin (Saharan requirement: Two consecutive days in Sahara and 24 or more of those hours within 72 hours of detection). Non-SAL WMLs either originate from local-to-regionally generated residual layers or from mid-latitude air streams that do not linger over the Sahara for a sufficient time period. Initial analysis shows these non-SAL WMLs tend to be both notably cooler and slightly moister than their SAL counter parts. Continuing analysis will address what role Saharan and non-Saharan air masses characteristics may play on local and regional environmental conditions.

Adjustment of regional regression models of urban-runoff quality using data for Chattanooga, Knoxville, and Nashville, Tennessee

USGS Publications Warehouse

Hoos, Anne B.; Patel, Anant R.

1996-01-01

Model-adjustment procedures were applied to the combined data bases of storm-runoff quality for Chattanooga, Knoxville, and Nashville, Tennessee, to improve predictive accuracy for storm-runoff quality for urban watersheds in these three cities and throughout Middle and East Tennessee. Data for 45 storms at 15 different sites (five sites in each city) constitute the data base. Comparison of observed values of storm-runoff load and event-mean concentration to the predicted values from the regional regression models for 10 constituents shows prediction errors, as large as 806,000 percent. Model-adjustment procedures, which combine the regional model predictions with local data, are applied to improve predictive accuracy. Standard error of estimate after model adjustment ranges from 67 to 322 percent. Calibration results may be biased due to sampling error in the Tennessee data base. The relatively large values of standard error of estimate for some of the constituent models, although representing significant reduction (at least 50 percent) in prediction error compared to estimation with unadjusted regional models, may be unacceptable for some applications. The user may wish to collect additional local data for these constituents and repeat the analysis, or calibrate an independent local regression model.

Regional intensity-duration-frequency analysis in the Eastern Black Sea Basin, Turkey, by using L-moments and regression analysis

NASA Astrophysics Data System (ADS)

Ghiaei, Farhad; Kankal, Murat; Anilan, Tugce; Yuksek, Omer

2018-01-01

The analysis of rainfall frequency is an important step in hydrology and water resources engineering. However, a lack of measuring stations, short duration of statistical periods, and unreliable outliers are among the most important problems when designing hydrology projects. In this study, regional rainfall analysis based on L-moments was used to overcome these problems in the Eastern Black Sea Basin (EBSB) of Turkey. The L-moments technique was applied at all stages of the regional analysis, including determining homogeneous regions, in addition to fitting and estimating parameters from appropriate distribution functions in each homogeneous region. We studied annual maximum rainfall height values of various durations (5 min to 24 h) from seven rain gauge stations located in the EBSB in Turkey, which have gauging periods of 39 to 70 years. Homogeneity of the region was evaluated by using L-moments. The goodness-of-fit criterion for each distribution was defined as the ZDIST statistics, depending on various distributions, including generalized logistic (GLO), generalized extreme value (GEV), generalized normal (GNO), Pearson type 3 (PE3), and generalized Pareto (GPA). GLO and GEV determined the best distributions for short (5 to 30 min) and long (1 to 24 h) period data, respectively. Based on the distribution functions, the governing equations were extracted for calculation of intensities of 2, 5, 25, 50, 100, 250, and 500 years return periods (T). Subsequently, the T values for different rainfall intensities were estimated using data quantifying maximum amount of rainfall at different times. Using these T values, duration, altitude, latitude, and longitude values were used as independent variables in a regression model of the data. The determination coefficient ( R 2) value indicated that the model yields suitable results for the regional relationship of intensity-duration-frequency (IDF), which is necessary for the design of hydraulic structures in small and medium sized catchments.

Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region: Modeled Productivity in Permafrost Regions

DOE PAGES

Xia, Jianyang; McGuire, A. David; Lawrence, David; ...

2017-01-26

Realistic projection of future climate-carbon (C) cycle feedbacks requires better understanding and an improved representation of the C cycle in permafrost regions in the current generation of Earth system models. Here we evaluated 10 terrestrial ecosystem models for their estimates of net primary productivity (NPP) and responses to historical climate change in permafrost regions in the Northern Hemisphere. In comparison with the satellite estimate from the Moderate Resolution Imaging Spectroradiometer (MODIS; 246 ± 6 g C m -2 yr -1), most models produced higher NPP (309 ± 12 g C m -2 yr -1) over the permafrost region during 2000–2009.more » By comparing the simulated gross primary productivity (GPP) with a flux tower-based database, we found that although mean GPP among the models was only overestimated by 10% over 1982–2009, there was a twofold discrepancy among models (380 to 800 g C m -2 yr -1), which mainly resulted from differences in simulated maximum monthly GPP (GPP max). Most models overestimated C use efficiency (CUE) as compared to observations at both regional and site levels. Further analysis shows that model variability of GPP and CUE are nonlinearly correlated to variability in specific leaf area and the maximum rate of carboxylation by the enzyme Rubisco at 25°C (Vc max_25), respectively. The models also varied in their sensitivities of NPP, GPP, and CUE to historical changes in climate and atmospheric CO 2 concentration. In conclusion, these results indicate that model predictive ability of the C cycle in permafrost regions can be improved by better representation of the processes controlling CUE and GPP max as well as their sensitivity to climate change.« less

Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region: Modeled Productivity in Permafrost Regions

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

Xia, Jianyang; McGuire, A. David; Lawrence, David

Realistic projection of future climate-carbon (C) cycle feedbacks requires better understanding and an improved representation of the C cycle in permafrost regions in the current generation of Earth system models. Here we evaluated 10 terrestrial ecosystem models for their estimates of net primary productivity (NPP) and responses to historical climate change in permafrost regions in the Northern Hemisphere. In comparison with the satellite estimate from the Moderate Resolution Imaging Spectroradiometer (MODIS; 246 ± 6 g C m -2 yr -1), most models produced higher NPP (309 ± 12 g C m -2 yr -1) over the permafrost region during 2000–2009.more » By comparing the simulated gross primary productivity (GPP) with a flux tower-based database, we found that although mean GPP among the models was only overestimated by 10% over 1982–2009, there was a twofold discrepancy among models (380 to 800 g C m -2 yr -1), which mainly resulted from differences in simulated maximum monthly GPP (GPP max). Most models overestimated C use efficiency (CUE) as compared to observations at both regional and site levels. Further analysis shows that model variability of GPP and CUE are nonlinearly correlated to variability in specific leaf area and the maximum rate of carboxylation by the enzyme Rubisco at 25°C (Vc max_25), respectively. The models also varied in their sensitivities of NPP, GPP, and CUE to historical changes in climate and atmospheric CO 2 concentration. In conclusion, these results indicate that model predictive ability of the C cycle in permafrost regions can be improved by better representation of the processes controlling CUE and GPP max as well as their sensitivity to climate change.« less

Study on Web-Based Tool for Regional Agriculture Industry Structure Optimization Using Ajax

NASA Astrophysics Data System (ADS)

Huang, Xiaodong; Zhu, Yeping

According to the research status of regional agriculture industry structure adjustment information system and the current development of information technology, this paper takes web-based regional agriculture industry structure optimization tool as research target. This paper introduces Ajax technology and related application frameworks to build an auxiliary toolkit of decision support system for agricultural policy maker and economy researcher. The toolkit includes a “one page” style component of regional agriculture industry structure optimization which provides agile arguments setting method that enables applying sensitivity analysis and usage of data and comparative advantage analysis result, and a component that can solve the linear programming model and its dual problem by simplex method.

HOT PLASMA FROM SOLAR ACTIVE REGION CORES: A TEST OF AC AND DC CORONAL HEATING MODELS?

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

Schmelz, J. T.; Christian, G. M.; Dhaliwal, R. S.

2015-06-20

Direct current (DC) models of solar coronal heating invoke magnetic reconnection to convert magnetic free energy into heat, whereas alternating current (AC) models invoke wave dissipation. In both cases the energy is supplied by photospheric footpoint motions. For a given footpoint velocity amplitude, DC models predict lower average heating rates but greater temperature variability when compared to AC models. Therefore, evidence of hot plasma (T > 5 MK) in the cores of active regions could be one of the ways for current observations to distinguish between AC and DC models. We have analyzed data from the X-Ray Telescope (XRT) andmore » the Atmospheric Imaging Assembly for 12 quiescent active region cores, all of which were observed in the XRT Be-thick channel. We did Differential Emission Measure (DEM) analysis and achieved good fits for each data set. We then artificially truncated the hot plasma of the DEM model at 5 MK and examined the resulting fits to the data. For some regions in our sample, the XRT intensities continued to be well-matched by the DEM predictions, even without the hot plasma. This truncation, however, resulted in unacceptable fits for the other regions. This result indicates that the hot plasma is present in these regions, even if the precise DEM distribution cannot be determined with the data available. We conclude that reconnection may be heating the hot plasma component of these active regions.« less

Validation of newly designed regional earth system model (RegESM) for Mediterranean Basin

NASA Astrophysics Data System (ADS)

Turuncoglu, Ufuk Utku; Sannino, Gianmaria

2017-05-01

We present a validation analysis of a regional earth system model system (RegESM) for the Mediterranean Basin. The used configuration of the modeling system includes two active components: a regional climate model (RegCM4) and an ocean modeling system (ROMS). To assess the performance of the coupled modeling system in representing the climate of the basin, the results of the coupled simulation (C50E) are compared to the results obtained by a standalone atmospheric simulation (R50E) as well as several observation datasets. Although there is persistent cold bias in fall and winter, which is also seen in previous studies, the model reproduces the inter-annual variability and the seasonal cycles of sea surface temperature (SST) in a general good agreement with the available observations. The analysis of the near-surface wind distribution and the main circulation of the sea indicates that the coupled model can reproduce the main characteristics of the Mediterranean Sea surface and intermediate layer circulation as well as the seasonal variability of wind speed and direction when it is compared with the available observational datasets. The results also reveal that the simulated near-surface wind speed and direction have poor performance in the Gulf of Lion and surrounding regions that also affects the large positive SST bias in the region due to the insufficient horizontal resolution of the atmospheric component of the coupled modeling system. The simulated seasonal climatologies of the surface heat flux components are also consistent with the CORE.2 and NOCS datasets along with the overestimation in net long-wave radiation and latent heat flux (or evaporation, E), although a large observational uncertainty is found in these variables. Also, the coupled model tends to improve the latent heat flux by providing a better representation of the air-sea interaction as well as total heat flux budget over the sea. Both models are also able to reproduce the temporal evolution of the inter-annual anomaly of surface air temperature and precipitation (P) over defined sub-regions. The Mediterranean water budget (E, P and E-P) estimates also show that the coupled model has high skill in the representation of water budget of the Mediterranean Sea. To conclude, the coupled model reproduces climatological land surface fields and the sea surface variables in the range of observation uncertainty and allow studying air-sea interaction and main regional climate characteristics of the basin.

Implementing a national process for estimating growth, removals, and mortality at the Pacific Northwest’s Forest Inventory and Analysis’s Region: modeling diameter growth

Treesearch

Olaf. Kuegler

2015-01-01

The Pacific Northwest Research Station’s Forest Inventory and Analysis Unit began remeasurement of permanently located FIA plots under the annualized design in 2011. With remeasurement has come the need to implement the national FIA system for compiling estimates of forest growth, removals, and mortality. The national system requires regional diameter-growth models to...

Regional Sediment Management (RSM) Modeling Tools: Integration of Advanced Sediment Transport Tools into HEC-RAS

DTIC Science & Technology

2014-06-01

Integration of Advanced Sediment Transport Tools into HEC-RAS by Paul M. Boyd and Stanford A. Gibson PURPOSE: This Coastal and Hydraulics Engineering...Technical Note (CHETN) summarizes the development and initial testing of new sediment transport and modeling tools developed by the U.S. Army Corps...sediment transport within the USACE HEC River Analysis System (HEC-RAS) software package and to determine its applicability to Regional Sediment

Consistency between the global and regional modeling components of CAMS over Europe.

NASA Astrophysics Data System (ADS)

Katragkou, Eleni; Akritidis, Dimitrios; Kontos, Serafim; Zanis, Prodromos; Melas, Dimitrios; Engelen, Richard; Plu, Matthieu; Eskes, Henk

2017-04-01

The Copernicus Atmosphere Monitoring Service (CAMS) is a component of the European Earth Observation programme Copernicus. CAMS consists of two major forecast and analysis systems: i) the CAMS global near-real time service, based on the ECMWF Integrated Forecast System (C-IFS), which provides daily analyses and forecasts of reactive trace gases, greenhouse gases and aerosol concentrations ii) a regional ensemble (ENS) for European air quality, compiled and disseminated by Météo-France, which consists of seven ensemble members. The boundaries from the regional ensemble members are extracted from the global CAMS forecast product. This work reports on the consistency between the global and regional modeling components of CAMS, and the impact of global CAMS boundary conditions on regional forecasts. The current analysis includes ozone (O3) carbon monoxide (CO) and aerosol (PM10/PM2.5) forecasts. The comparison indicates an overall good agreement between the global C-IFS and the regional ENS patterns for O3 and CO, especially above 250m altitude, indicating that the global boundary conditions are efficiently included in the regional ensemble simulations. As expected, differences are found within the PBL, with lower/higher C-IFS O3/CO concentrations over continental Europe with respect to ENS.

Correlation of finite-element structural dynamic analysis with measured free vibration characteristics for a full-scale helicopter fuselage

NASA Technical Reports Server (NTRS)

Kenigsberg, I. J.; Dean, M. W.; Malatino, R.

1974-01-01

The correlation achieved with each program provides the material for a discussion of modeling techniques developed for general application to finite-element dynamic analyses of helicopter airframes. Included are the selection of static and dynamic degrees of freedom, cockpit structural modeling, and the extent of flexible-frame modeling in the transmission support region and in the vicinity of large cut-outs. The sensitivity of predicted results to these modeling assumptions are discussed. Both the Sikorsky Finite-Element Airframe Vibration analysis Program (FRAN/Vibration Analysis) and the NASA Structural Analysis Program (NASTRAN) have been correlated with data taken in full-scale vibration tests of a modified CH-53A helicopter.

The pyramid system for multiscale raster analysis

USGS Publications Warehouse

De Cola, L.; Montagne, N.

1993-01-01

Geographical research requires the management and analysis of spatial data at multiple scales. As part of the U.S. Geological Survey's global change research program a software system has been developed that reads raster data (such as an image or digital elevation model) and produces a pyramid of aggregated lattices as well as various measurements of spatial complexity. For a given raster dataset the system uses the pyramid to report: (1) mean, (2) variance, (3) a spatial autocorrelation parameter based on multiscale analysis of variance, and (4) a monofractal scaling parameter based on the analysis of isoline lengths. The system is applied to 1-km digital elevation model (DEM) data for a 256-km2 region of central California, as well as to 64 partitions of the region. PYRAMID, which offers robust descriptions of data complexity, also is used to describe the behavior of topographic aspect with scale. ?? 1993.

Multilevel Hierarchical Modeling of Benthic Macroinvertebrate Responses to Urbanization in Nine Metropolitan Regions across the Conterminous United States

USGS Publications Warehouse

Kashuba, Roxolana; Cha, YoonKyung; Alameddine, Ibrahim; Lee, Boknam; Cuffney, Thomas F.

2010-01-01

Multilevel hierarchical modeling methodology has been developed for use in ecological data analysis. The effect of urbanization on stream macroinvertebrate communities was measured across a gradient of basins in each of nine metropolitan regions across the conterminous United States. The hierarchical nature of this dataset was harnessed in a multi-tiered model structure, predicting both invertebrate response at the basin scale and differences in invertebrate response at the region scale. Ordination site scores, total taxa richness, Ephemeroptera, Plecoptera, Trichoptera (EPT) taxa richness, and richness-weighted mean tolerance of organisms at a site were used to describe invertebrate responses. Percentage of urban land cover was used as a basin-level predictor variable. Regional mean precipitation, air temperature, and antecedent agriculture were used as region-level predictor variables. Multilevel hierarchical models were fit to both levels of data simultaneously, borrowing statistical strength from the complete dataset to reduce uncertainty in regional coefficient estimates. Additionally, whereas non-hierarchical regressions were only able to show differing relations between invertebrate responses and urban intensity separately for each region, the multilevel hierarchical regressions were able to explain and quantify those differences within a single model. In this way, this modeling approach directly establishes the importance of antecedent agricultural conditions in masking the response of invertebrates to urbanization in metropolitan regions such as Milwaukee-Green Bay, Wisconsin; Denver, Colorado; and Dallas-Fort Worth, Texas. Also, these models show that regions with high precipitation, such as Atlanta, Georgia; Birmingham, Alabama; and Portland, Oregon, start out with better regional background conditions of invertebrates prior to urbanization but experience faster negative rates of change with urbanization. Ultimately, this urbanization-invertebrate response example is used to detail the multilevel hierarchical construction methodology, showing how the result is a set of models that are both statistically more rigorous and ecologically more interpretable than simple linear regression models.

Biogeochemical Trends and Their Ecosystem Impacts in Atlantic Canada

NASA Astrophysics Data System (ADS)

Fennel, Katja; Rutherford, Krysten; Kuhn, Angela; Zhang, Wenxia; Brennan, Katie; Zhang, Rui

2017-04-01

The representation of coastal oceans in global biogeochemical models is a challenge, yet the ecosystems in these regions are most vulnerable to the combined stressors of ocean warming, deoxygenation, acidification, eutrophication and fishing. Coastal regions also have large air-sea fluxes of CO2, making them an important but poorly quantified component of the global carbon cycle, and are the most relevant for human activities. Regional model applications that are nested within large-scale or global models are necessary for detailed studies of coastal regions. We present results from such a regional biogeochemical model for the northwestern North Atlantic shelves and adjacent deep ocean of Atlantic Canada. The model is an implementation of the Regional Ocean Modeling System (ROMS) and includes an NPZD-type nitrogen cycle model with explicit representation of dissolved oxygen and inorganic carbon. The region is at the confluence of the Gulf Stream and Labrador Current making it highly dynamic, a challenge for analysis and prediction, and prone to large changes. Historically a rich fishing ground, coastal ecosystems in Atlantic Canada have undergone dramatic changes including the collapse of several economically important fish stocks and the listing of many species as threatened or endangered. Furthermore it is unclear whether the region is a net source or sink of atmospheric CO2 with estimates of the size and direction of the net air-sea CO2 flux remaining controversial. We will discuss simulated patterns of primary production, inorganic carbon fluxes and oxygen trends in the context of circulation features and shelf residence times for the present ocean state and present future projections.

Evaluation of the Emission, Transport, and Deposition of Mercury, Fine Particulate Matter, and Arsenic from Coal-Based Power Plants in the Ohio River Valley Region

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

Kevin Crist

2005-10-02

Ohio University, in collaboration with CONSOL Energy, Advanced Technology Systems, Inc (ATS) and Atmospheric and Environmental Research, Inc. (AER) as subcontractors, is evaluating the impact of emissions from coal-fired power plants in the Ohio River Valley region as they relate to the transport and deposition of mercury, arsenic, and associated fine particulate matter. This evaluation will involve two interrelated areas of effort: ambient air monitoring and regional-scale modeling analysis. The scope of work for the ambient air monitoring will include the deployment of a surface air monitoring (SAM) station in southeastern Ohio. The SAM station will contain sampling equipment tomore » collect and measure mercury (including speciated forms of mercury and wet and dry deposited mercury), arsenic, particulate matter (PM) mass, PM composition, and gaseous criteria pollutants (CO, NOx, SO{sub 2}, O{sub 3}, etc.). Laboratory analysis of time-integrated samples will be used to obtain chemical speciation of ambient PM composition and mercury in precipitation. Near-real-time measurements will be used to measure the ambient concentrations of PM mass and all gaseous species including Hg{sup 0} and RGM. Approximately of 18 months of field data will be collected at the SAM site to validate the proposed regional model simulations for episodic and seasonal model runs. The ambient air quality data will also provide mercury, arsenic, and fine particulate matter data that can be used by Ohio Valley industries to assess performance on multi-pollutant control systems. The scope of work for the modeling analysis will include (1) development of updated inventories of mercury and arsenic emissions from coal plants and other important sources in the modeled domain; (2) adapting an existing 3-D atmospheric chemical transport model to incorporate recent advancements in the understanding of mercury transformations in the atmosphere; (3) analyses of the flux of Hg0, RGM, arsenic, and fine particulate matter in the different sectors of the study region to identify key transport mechanisms; (4) comparison of cross correlations between species from the model results to observations in order to evaluate characteristics of specific air masses associated with long-range transport from a specified source region; and (5) evaluation of the sensitivity of these correlations to emissions from regions along the transport path. This will be accomplished by multiple model runs with emissions simulations switched on and off from the various source regions. To the greatest extent possible, model results will also be compared to field data collected at other air monitoring sites in the Ohio Valley region, operated independently of this project. These sites may include (1) the DOE National Energy Technologies Laboratory's monitoring site at its suburban Pittsburgh, PA facility; (2) sites in Pittsburgh (Lawrenceville) PA and Holbrook, PA operated by ATS; (3) sites in Steubenville, OH and Pittsburgh, PA operated by U.S. EPA and/or its contractors; and (4) sites operated by State or local air regulatory agencies. Field verification of model results and predictions will provide critical information for the development of cost effective air pollution control strategies by the coal-fired power plants in the Ohio River Valley region.« less

Evaluation of the Emission, Transport, and Deposition of Mercury, Fine Particulate Matter, and Arsenic from Coal-Based Power Plants in the Ohio River Valley Region

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

Kevin Crist

2006-04-02

As stated in the proposal: Ohio University, in collaboration with CONSOL Energy, Advanced Technology Systems, Inc (ATS) and Atmospheric and Environmental Research, Inc. (AER) as subcontractors, is evaluating the impact of emissions from coal-fired power plants in the Ohio River Valley region as they relate to the transport and deposition of mercury, arsenic, and associated fine particulate matter. This evaluation will involve two interrelated areas of effort: ambient air monitoring and regional-scale modeling analysis. The scope of work for the ambient air monitoring will include the deployment of a surface air monitoring (SAM) station in southeastern Ohio. The SAM stationmore » will contain sampling equipment to collect and measure mercury (including speciated forms of mercury and wet and dry deposited mercury), arsenic, particulate matter (PM) mass, PM composition, and gaseous criteria pollutants (CO, NO{sub x}, SO{sub 2}, O{sub 3}, etc.). Laboratory analysis of time-integrated samples will be used to obtain chemical speciation of ambient PM composition and mercury in precipitation. Near-real-time measurements will be used to measure the ambient concentrations of PM mass and all gaseous species including Hg0 and RGM. Approximately 18 months of field data will be collected at the SAM site to validate the proposed regional model simulations for episodic and seasonal model runs. The ambient air quality data will also provide mercury, arsenic, and fine particulate matter data that can be used by Ohio Valley industries to assess performance on multi-pollutant control systems. The scope of work for the modeling analysis will include (1) development of updated inventories of mercury and arsenic emissions from coal plants and other important sources in the modeled domain; (2) adapting an existing 3-D atmospheric chemical transport model to incorporate recent advancements in the understanding of mercury transformations in the atmosphere; (3) analyses of the flux of Hg{sup 0}, RGM, arsenic, and fine particulate matter in the different sectors of the study region to identify key transport mechanisms; (4) comparison of cross correlations between species from the model results to observations in order to evaluate characteristics of specific air masses associated with long-range transport from a specified source region; and (5) evaluation of the sensitivity of these correlations to emissions from regions along the transport path. This will be accomplished by multiple model runs with emissions simulations switched on and off from the various source regions. To the greatest extent possible, model results will also be compared to field data collected at other air monitoring sites in the Ohio Valley region, operated independently of this project. These sites may include (1) the DOE National Energy Technologies Laboratory's monitoring site at its suburban Pittsburgh, PA facility; (2) sites in Pittsburgh (Lawrenceville) PA and Holbrook, PA operated by ATS; (3) sites in Steubenville, OH and Pittsburgh, PA operated by the USEPA and/or its contractors; and (4) sites operated by State or local air regulatory agencies. Field verification of model results and predictions will provide critical information for the development of cost effective air pollution control strategies by the coal-fired power plants in the Ohio River Valley region.« less

EVALUATION OF THE EMISSION, TRANSPORT, AND DEPOSITION OF MERCURY, FINE PARTICULATE MATTER, AND ARSENIC FROM COAL-BASED POWER PLANTS IN THE OHIO RIVER VALLEY REGION

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

Kevin Crist

2005-04-02

Ohio University, in collaboration with CONSOL Energy, Advanced Technology Systems, Inc (ATS) and Atmospheric and Environmental Research, Inc. (AER) as subcontractors, is evaluating the impact of emissions from coal-fired power plants in the Ohio River Valley region as they relate to the transport and deposition of mercury, arsenic, and associated fine particulate matter. This evaluation will involve two interrelated areas of effort: ambient air monitoring and regional-scale modeling analysis. The scope of work for the ambient air monitoring will include the deployment of a surface air monitoring (SAM) station in southeastern Ohio. The SAM station will contain sampling equipment tomore » collect and measure mercury (including speciated forms of mercury and wet and dry deposited mercury), arsenic, particulate matter (PM) mass, PM composition, and gaseous criteria pollutants (CO, NO{sub x}, SO{sub 2}, O{sub 3}, etc.). Laboratory analysis of time-integrated samples will be used to obtain chemical speciation of ambient PM composition and mercury in precipitation. Near-real-time measurements will be used to measure the ambient concentrations of PM mass and all gaseous species including Hg{sup 0} and RGM. Approximately of 18 months of field data will be collected at the SAM site to validate the proposed regional model simulations for episodic and seasonal model runs. The ambient air quality data will also provide mercury, arsenic, and fine particulate matter data that can be used by Ohio Valley industries to assess performance on multi-pollutant control systems. The scope of work for the modeling analysis will include (1) development of updated inventories of mercury and arsenic emissions from coal plants and other important sources in the modeled domain; (2) adapting an existing 3-D atmospheric chemical transport model to incorporate recent advancements in the understanding of mercury transformations in the atmosphere; (3) analyses of the flux of Hg{sup 0}, RGM, arsenic, and fine particulate matter in the different sectors of the study region to identify key transport mechanisms; (4) comparison of cross correlations between species from the model results to observations in order to evaluate characteristics of specific air masses associated with long-range transport from a specified source region; and (5) evaluation of the sensitivity of these correlations to emissions from regions along the transport path. This will be accomplished by multiple model runs with emissions simulations switched on and off from the various source regions. To the greatest extent possible, model results will also be compared to field data collected at other air monitoring sites in the Ohio Valley region, operated independently of this project. These sites may include (1) the DOE National Energy Technologies Laboratory's monitoring site at its suburban Pittsburgh, PA facility; (2) sites in Pittsburgh (Lawrenceville) PA and Holbrook, PA operated by ATS; (3) sites in Steubenville, OH and Pittsburgh, PA operated by U.S. EPA and/or its contractors; and (4) sites operated by State or local air regulatory agencies. Field verification of model results and predictions will provide critical information for the development of cost effective air pollution control strategies by the coal-fired power plants in the Ohio River Valley region.« less

EVALUATION OF THE EMISSION, TRANSPORT, AND DEPOSITION OF MERCURY, FINE PARTICULATE MATTER, AND ARSENIC FROM COAL-BASED POWER PLANTS IN THE OHIO RIVER VALLEY REGION

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

Kevin Crist

2004-10-02

Ohio University, in collaboration with CONSOL Energy, Advanced Technology Systems, Inc (ATS) and Atmospheric and Environmental Research, Inc. (AER) as subcontractors, is evaluating the impact of emissions from coal-fired power plants in the Ohio River Valley region as they relate to the transport and deposition of mercury, arsenic, and associated fine particulate matter. This evaluation will involve two interrelated areas of effort: ambient air monitoring and regional-scale modeling analysis. The scope of work for the ambient air monitoring will include the deployment of a surface air monitoring (SAM) station in southeastern Ohio. The SAM station will contain sampling equipment tomore » collect and measure mercury (including speciated forms of mercury and wet and dry deposited mercury), arsenic, particulate matter (PM) mass, PM composition, and gaseous criteria pollutants (CO, NOx, SO{sub 2}, O{sub 3}, etc.). Laboratory analysis of time-integrated samples will be used to obtain chemical speciation of ambient PM composition and mercury in precipitation. Near-real-time measurements will be used to measure the ambient concentrations of PM mass and all gaseous species including Hg{sup 0} and RGM. Approximately of 18 months of field data will be collected at the SAM site to validate the proposed regional model simulations for episodic and seasonal model runs. The ambient air quality data will also provide mercury, arsenic, and fine particulate matter data that can be used by Ohio Valley industries to assess performance on multi-pollutant control systems. The scope of work for the modeling analysis will include (1) development of updated inventories of mercury and arsenic emissions from coal plants and other important sources in the modeled domain; (2) adapting an existing 3-D atmospheric chemical transport model to incorporate recent advancements in the understanding of mercury transformations in the atmosphere; (3) analyses of the flux of Hg{sup 0}, RGM, arsenic, and fine particulate matter in the different sectors of the study region to identify key transport mechanisms; (4) comparison of cross correlations between species from the model results to observations in order to evaluate characteristics of specific air masses associated with long-range transport from a specified source region; and (5) evaluation of the sensitivity of these correlations to emissions from regions along the transport path. This will be accomplished by multiple model runs with emissions simulations switched on and off from the various source regions. To the greatest extent possible, model results will also be compared to field data collected at other air monitoring sites in the Ohio Valley region, operated independently of this project. These sites may include (1) the DOE National Energy Technologies Laboratory's monitoring site at its suburban Pittsburgh, PA facility; (2) sites in Pittsburgh (Lawrenceville) PA and Holbrook, PA operated by ATS; (3) sites in Steubenville, OH and Pittsburgh, PA operated by U.S. EPA and/or its contractors; and (4) sites operated by State or local air regulatory agencies. Field verification of model results and predictions will provide critical information for the development of cost effective air pollution control strategies by the coal-fired power plants in the Ohio River Valley region.« less

Skeletal maturity determination from hand radiograph by model-based analysis

NASA Astrophysics Data System (ADS)

Vogelsang, Frank; Kohnen, Michael; Schneider, Hansgerd; Weiler, Frank; Kilbinger, Markus W.; Wein, Berthold B.; Guenther, Rolf W.

2000-06-01

Derived from a model based segmentation algorithm for hand radiographs proposed in our former work we now present a method to determine skeletal maturity by an automated analysis of regions of interest (ROI). These ROIs including the epiphyseal and carpal bones, which are most important for skeletal maturity determination, can be extracted out of the radiograph by knowledge based algorithms.

Physiological gas exchange mapping of hyperpolarized 129 Xe using spiral-IDEAL and MOXE in a model of regional radiation-induced lung injury.

PubMed

Zanette, Brandon; Stirrat, Elaine; Jelveh, Salomeh; Hope, Andrew; Santyr, Giles

2018-02-01

To map physiological gas exchange parameters using dissolved hyperpolarized (HP) 129 Xe in a rat model of regional radiation-induced lung injury (RILI) with spiral-IDEAL and the model of xenon exchange (MOXE). Results are compared to quantitative histology of pulmonary tissue and red blood cell (RBC) distribution. Two cohorts (n = 6 each) of age-matched rats were used. One was irradiated in the right-medial lung, producing regional injury. Gas exchange was mapped 4 weeks postirradiation by imaging dissolved-phase HP 129 Xe using spiral-IDEAL at five gas exchange timepoints using a clinical 1.5 T scanner. Physiological lung parameters were extracted regionally on a voxel-wise basis using MOXE. Mean gas exchange parameters, specifically air-capillary barrier thickness (δ) and hematocrit (HCT) in the right-medial lung were compared to the contralateral lung as well as nonirradiated control animals. Whole-lung spectroscopic analysis of gas exchange was also performed. δ was significantly increased (1.43 ± 0.12 μm from 1.07 ± 0.09 μm) and HCT was significantly decreased (17.2 ± 1.2% from 23.6 ± 1.9%) in the right-medial lung (i.e., irradiated region) compared to the contralateral lung of the irradiated rats. These changes were not observed in healthy controls. δ and HCT correlated with histologically measured increases in pulmonary tissue heterogeneity (r = 0.77) and decreases in RBC distribution (r = 0.91), respectively. No changes were observed using whole-lung analysis. This work demonstrates the feasibility of mapping gas exchange using HP 129 Xe in an animal model of RILI 4 weeks postirradiation. Spatially resolved gas exchange mapping is sensitive to regional injury between cohorts that was undetected with whole-lung gas exchange analysis, in agreement with histology. Gas exchange mapping holds promise for assessing regional lung function in RILI and other pulmonary diseases. © 2017 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

The morphology of flare phenomena, magnetic fields, and electric currents in active regions. I - Introduction and methods

NASA Technical Reports Server (NTRS)

Canfield, Richard C.; De La Beaujardiere, J.-F.; Fan, Yuhong; Leka, K. D.; Mcclymont, A. N.; Metcalf, Thomas R.; Mickey, Donald L.; Wuelser, Jean-Pierre; Lites, Bruce W.

1993-01-01

Electric current systems in solar active regions and their spatial relationship to sites of electron precipitation and high-pressure in flares were studied with the purpose of providing observational evidence for or against the flare models commonly discussed in the literature. The paper describes the instrumentation, the data used, and the data analysis methods, as well as improvements made upon earlier studies. Several flare models are overviewed, and the predictions yielded by each model for the relationships of flares to the vertical current systems are discussed.

A modeling analysis program for the JPL Table Mountain Io sodium cloud data

NASA Technical Reports Server (NTRS)

Smyth, W. H.; Goldberg, B. A.

1986-01-01

Progress and achievements in the second year are discussed in three main areas: (1) data quality review of the 1981 Region B/C images; (2) data processing activities; and (3) modeling activities. The data quality review revealed that almost all 1981 Region B/C images are of sufficient quality to be valuable in the analyses of the JPL data set. In the second area, the major milestone reached was the successful development and application of complex image-processing software required to render the original image data suitable for modeling analysis studies. In the third area, the lifetime description of sodium atoms in the planet magnetosphere was improved in the model to include the offset dipole nature of the magnetic field as well as an east-west electric field. These improvements are important in properly representing the basic morphology as well as the east-west asymmetries of the sodium cloud.

Phase unwrapping using region-based markov random field model.

PubMed

Dong, Ying; Ji, Jim

2010-01-01

Phase unwrapping is a classical problem in Magnetic Resonance Imaging (MRI), Interferometric Synthetic Aperture Radar and Sonar (InSAR/InSAS), fringe pattern analysis, and spectroscopy. Although many methods have been proposed to address this problem, robust and effective phase unwrapping remains a challenge. This paper presents a novel phase unwrapping method using a region-based Markov Random Field (MRF) model. Specifically, the phase image is segmented into regions within which the phase is not wrapped. Then, the phase image is unwrapped between different regions using an improved Highest Confidence First (HCF) algorithm to optimize the MRF model. The proposed method has desirable theoretical properties as well as an efficient implementation. Simulations and experimental results on MRI images show that the proposed method provides similar or improved phase unwrapping than Phase Unwrapping MAx-flow/min-cut (PUMA) method and ZpM method.

Physics based model of D-region variability related to VLF propagation effects

NASA Astrophysics Data System (ADS)

Chakravarty, S. C.

2012-07-01

D-region (~60-85 km) electron density profiles measured using large number of sounding rocket experiments carried out from two Indian low latitude stations show large variations with solar zenith angle, season and solar activity. Similarly the ground based multi frequency radio wave absorption technique has provided continuous data on the morphology of the hourly electron density variations. However suitable models of the D-region electron density profile variations both during quiet and disturbed solar conditions over the Indian region are lacking. The renewed interest in the study of the VLF/LF propagation anomalies taking place through perturbations in the D-region electron densities due to various geophysical phenomena requires the availability of a baseline D-region model over low latitudes. The purpose of this paper is to critically review the physical processes of D-region production and loss of free electrons, dynamical coupling due to variety of vertically propagating atmospheric waves, sudden changes brought about by the solar energetic events like CMEs and different categories of X-ray flares. Low latitude region is not likely to be affected by the PMSE or PCA type of events but the changes due to lightning induced mesospheric red sprites and LEPs need to be considered. Based on this analysis, a preliminary low latitude D-region electron density profile model development is proposed. Sample results would illustrate key requirements from such a model in terms of its effectiveness to simulate the low latitude observations of VLF/LF amplitude and phase variations using waveguide propagation models like LWPC.

System and methods for predicting transmembrane domains in membrane proteins and mining the genome for recognizing G-protein coupled receptors

DOEpatents

Trabanino, Rene J; Vaidehi, Nagarajan; Hall, Spencer E; Goddard, William A; Floriano, Wely

2013-02-05

The invention provides computer-implemented methods and apparatus implementing a hierarchical protocol using multiscale molecular dynamics and molecular modeling methods to predict the presence of transmembrane regions in proteins, such as G-Protein Coupled Receptors (GPCR), and protein structural models generated according to the protocol. The protocol features a coarse grain sampling method, such as hydrophobicity analysis, to provide a fast and accurate procedure for predicting transmembrane regions. Methods and apparatus of the invention are useful to screen protein or polynucleotide databases for encoded proteins with transmembrane regions, such as GPCRs.

Stress analysis of the haunch region in a rigid frame bridge.

DOT National Transportation Integrated Search

1977-01-01

The purpose of this study was to obtain an understanding of the behavior and stress distribution in the haunch region of a rigid frame highway bridge. A finite element model of the haunch of the bridge was developed to permit the prediction of stress...

Validation of the ANOCOVA model for regional scale ECa-ECe calibration

USDA-ARS?s Scientific Manuscript database

Over the past decade two approaches have emerged as the preferred means for assessing salinity at regional scale: (1) vegetative indices from satellite imagery (e.g., MODIS enhanced vegetative index, NDVI, etc.) and (2) analysis of covariance (ANOCOVA) calibration of apparent soil electrical conduct...

Downscaling CESM1 climate change projections for the MENA-CORDEX domain using WRF

NASA Astrophysics Data System (ADS)

Zittis, George; Hadjinicolaou, Panos; Lelieveld, Jos

2017-04-01

According to analysis of observations and global climate model projections, the broader Middle East, North Africa and Mediterranean region is found to be a climate change hotspot. Substantial changes in precipitation amounts and patterns and strong summer warming (including an intensification of heat extremes) is a likely future scenario for the region, but a recent uncertainty analysis indicated good model agreement for temperature but much less for precipitation. Although the horizontal resolution of global models has increased over the last years, it is still not adequate for impact and adaptation assessments of regional or national level and further downscaling of the climate information is required. The region is now studied within the CORDEX initiative (Coordinated Regional Climate Downscaling Experiment) with the establishment of a domain covering the Middle East - North Africa (MENA-CORDEX) region (http://mena-cordex.cyi.ac.cy/). In this study, we present the first climate change projections for the MENA produced by dynamically downscaling a bias-corrected output of the CESM1 global earth system model. For the downscaling, we use a climate configuration of the Weather, Research and Forecasting model (WRF). Our simulations use a standard CORDEX Phase I 50-km grid in three simulations, a historical (1950-2005) and two scenario runs (2006-2100) with the greenhouse gas forcing following the RCP 4.5 and 8.5. We evaluate precipitation, temperature and other surface meteorological variables from the historical using gridded and station observational datasets. Maps of projected changes are constructed for different periods in the future as differences of the two scenarios model output against the data from the historical run. The main spatial and temporal patterns of change are discussed, especially in the context of the United Nations Framework Convention on Climate Change agreement in Paris to limit the global average temperature increase to 1.5 degrees above pre-industrial levels.

HABITAT DISTRIBUTION MODELS FOR 37 VERTEBRATE SPECIES ADDRESSED BY THE MULTI-SPECIES HABITAT CONSERVATION PLAN OF CLARK COUNTY, NEVADA

EPA Science Inventory

Thirty-seven species identified in the Clark County Multi-Species Habitat Conservation Plan were

previously modeled through the Southwest Regional Gap Analysis Project. Existing SWReGAP habitat

models and modeling databases were used to facilitate the revision of mo...

Modeling Dynamic Functional Neuroimaging Data Using Structural Equation Modeling

ERIC Educational Resources Information Center

Price, Larry R.; Laird, Angela R.; Fox, Peter T.; Ingham, Roger J.

2009-01-01

The aims of this study were to present a method for developing a path analytic network model using data acquired from positron emission tomography. Regions of interest within the human brain were identified through quantitative activation likelihood estimation meta-analysis. Using this information, a "true" or population path model was then…

Diagnostic Analysis of Ozone Concentrations Simulated by Two Regional-Scale Air Quality Models

EPA Science Inventory

Since the Community Multiscale Air Quality modeling system (CMAQ) and the Weather Research and Forecasting with Chemistry model (WRF/Chem) use different approaches to simulate the interaction of meteorology and chemistry, this study compares the CMAQ and WRF/Chem air quality simu...

A comparative modeling study on non-climatic and climatic risk assessment on Asian Tiger Mosquito (Aedes albopictus)

PubMed Central

Shafapour Tehrany, Mahyat; Solhjouy-fard, Samaneh; Kumar, Lalit

2018-01-01

Aedes albopictus, the Asian Tiger Mosquito, vector of Chikungunya, Dengue Fever and Zika viruses, has proven its hardy adaptability in expansion from its natural Asian, forest edge, tree hole habitat on the back of international trade transportation, re-establishing in temperate urban surrounds, in a range of water receptacles and semi-enclosures of organic matter. Conventional aerial spray mosquito vector controls focus on wetland and stagnant water expanses, proven to miss the protected hollows and crevices favoured by Ae. albopictus. New control or eradication strategies are thus essential, particular in light of potential expansions in the southeastern and eastern USA. Successful regional vector control strategies require risk level analysis. Should strategies prioritize regions with non-climatic or climatic suitability parameters for Ae. albopictus? Our study used current Ae. albopictus distribution data to develop two independent models: (i) regions with suitable non-climatic factors, and (ii) regions with suitable climate for Ae. albopictus in southeastern USA. Non-climatic model processing used Evidential Belief Function (EBF), together with six geographical conditioning factors (raster data layers), to establish the probability index. Validation of the analysis results was estimated with area under the curve (AUC) using Ae. albopictus presence data. Climatic modeling was based on two General Circulation Models (GCMs), Miroc3.2 and CSIRO-MK30 running the RCP 8.5 scenario in MaxEnt software. EBF non-climatic model results achieved a 0.70 prediction rate and 0.73 success rate, confirming suitability of the study site regions for Ae. albopictus establishment. The climatic model results showed the best-fit model comprised Coldest Quarter Mean Temp, Precipitation of Wettest Quarter and Driest Quarter Precipitation factors with mean AUC value of 0.86. Both GCMs showed that the whole study site is highly suitable and will remain suitable climatically, according to the prediction for 2055, for Ae. albopictus expansion. PMID:29576954

Projected changes in precipitation intensity and frequency over complex topography: a multi-model perspective

NASA Astrophysics Data System (ADS)

Fischer, Andreas; Keller, Denise; Liniger, Mark; Rajczak, Jan; Schär, Christoph; Appenzeller, Christof

2014-05-01

Fundamental changes in the hydrological cycle are expected in a future warmer climate. This is of particular relevance for the Alpine region, as a source and reservoir of several major rivers in Europe and being prone to extreme events such as floodings. For this region, climate change assessments based on the ENSEMBLES regional climate models (RCMs) project a significant decrease in summer mean precipitation under the A1B emission scenario by the mid-to-end of this century, while winter mean precipitation is expected to slightly rise. From an impact perspective, projected changes in seasonal means, however, are often insufficient to adequately address the multifaceted challenges of climate change adaptation. In this study, we revisit the full matrix of the ENSEMBLES RCM projections regarding changes in frequency and intensity, precipitation-type (convective versus stratiform) and temporal structure (wet/dry spells and transition probabilities) over Switzerland and surroundings. As proxies for raintype changes, we rely on the model parameterized convective and large-scale precipitation components. Part of the analysis involves a Bayesian multi-model combination algorithm to infer changes from the multi-model ensemble. The analysis suggests a summer drying that evolves altitude-specific: over low-land regions it is associated with wet-day frequency decreases of convective and large-scale precipitation, while over elevated regions it is primarily associated with a decline in large-scale precipitation only. As a consequence, almost all the models project an increase in the convective fraction at elevated Alpine altitudes. The decrease in the number of wet days during summer is accompanied by decreases (increases) in multi-day wet (dry) spells. This shift in multi-day episodes also lowers the likelihood of short dry spell occurrence in all of the models. For spring and autumn the combined multi-model projections indicate higher mean precipitation intensity north of the Alps, while a similar tendency is expected for the winter season over most of Switzerland.

A comparative modeling study on non-climatic and climatic risk assessment on Asian Tiger Mosquito (Aedes albopictus).

PubMed

Shabani, Farzin; Shafapour Tehrany, Mahyat; Solhjouy-Fard, Samaneh; Kumar, Lalit

2018-01-01

Aedes albopictus , the Asian Tiger Mosquito, vector of Chikungunya, Dengue Fever and Zika viruses, has proven its hardy adaptability in expansion from its natural Asian, forest edge, tree hole habitat on the back of international trade transportation, re-establishing in temperate urban surrounds, in a range of water receptacles and semi-enclosures of organic matter. Conventional aerial spray mosquito vector controls focus on wetland and stagnant water expanses, proven to miss the protected hollows and crevices favoured by Ae. albopictus. New control or eradication strategies are thus essential, particular in light of potential expansions in the southeastern and eastern USA. Successful regional vector control strategies require risk level analysis. Should strategies prioritize regions with non-climatic or climatic suitability parameters for Ae. albopictus ? Our study used current Ae. albopictus distribution data to develop two independent models: (i) regions with suitable non-climatic factors, and (ii) regions with suitable climate for Ae. albopictus in southeastern USA. Non-climatic model processing used Evidential Belief Function (EBF), together with six geographical conditioning factors (raster data layers), to establish the probability index. Validation of the analysis results was estimated with area under the curve (AUC) using Ae. albopictus presence data. Climatic modeling was based on two General Circulation Models (GCMs), Miroc3.2 and CSIRO-MK30 running the RCP 8.5 scenario in MaxEnt software. EBF non-climatic model results achieved a 0.70 prediction rate and 0.73 success rate, confirming suitability of the study site regions for Ae. albopictus establishment. The climatic model results showed the best-fit model comprised Coldest Quarter Mean Temp, Precipitation of Wettest Quarter and Driest Quarter Precipitation factors with mean AUC value of 0.86. Both GCMs showed that the whole study site is highly suitable and will remain suitable climatically, according to the prediction for 2055, for Ae. albopictus expansion.

Measuring Efficiency of Health Systems of the Middle East and North Africa (MENA) Region Using Stochastic Frontier Analysis.

PubMed

Hamidi, Samer; Akinci, Fevzi

2016-06-01

The main purpose of this study is to measure the technical efficiency of twenty health systems in the Middle East and North Africa (MENA) region to inform evidence-based health policy decisions. In addition, the effects of alternative stochastic frontier model specification on the empirical results are examined. We conducted a stochastic frontier analysis to estimate the country-level technical efficiencies using secondary panel data for 20 MENA countries for the period of 1995-2012 from the World Bank database. We also tested the effect of alternative frontier model specification using three random-effects approaches: a time-invariant model where efficiency effects are assumed to be static with regard to time, and a time-varying efficiency model where efficiency effects have temporal variation, and one model to account for heterogeneity. The average estimated technical inefficiency of health systems in the MENA region was 6.9 % with a range of 5.7-7.9 % across the three models. Among the top performers, Lebanon, Qatar, and Morocco are ranked consistently high according to the three different inefficiency model specifications. On the opposite side, Sudan, Yemen and Djibouti ranked among the worst performers. On average, the two most technically efficient countries were Qatar and Lebanon. We found that the estimated technical efficiency scores vary substantially across alternative parametric models. Based on the findings reported in this study, most MENA countries appear to be operating, on average, with a reasonably high degree of technical efficiency compared with other countries in the region. However, there is evidence to suggest that there are considerable efficiency gains yet to be made by some MENA countries. Additional empirical research is needed to inform future health policies aimed at improving both the efficiency and sustainability of the health systems in the MENA region.

Visualizing along-strike change in deformation style using analog modeling and digital visualization software

NASA Astrophysics Data System (ADS)

Burberry, C. M.

2012-12-01

It is a well-known phenomenon that deformation style varies in space; both along the strike of a deformed belt and along the strike of individual structures within that belt. This variation in deformation style is traditionally visualized with a series of closely spaced 2D cross-sections. However, the use of 2D section lines implies plane strain along those lines, and the true 3D nature of the deformation is not necessarily captured. By using a combination of remotely sensed data, analog modeling of field datasets and this remote data, and numerical and digital visualization of the finished model, a 3D understanding and restoration of the deformation style within the region can be achieved. The workflow used for this study begins by considering the variation in deformation style which can be observed from satellite images and combining this data with traditional field data, in order to understand the deformation in the region under consideration. The conceptual model developed at this stage is then modeled using a sand and silicone modeling system, where the kinematics and dynamics of the deformation processes can be examined. A series of closely-spaced cross-sections, as well as 3D images of the deformation, are created from the analog model, and input into a digital visualization and modeling system for restoration. In this fashion, a valid 3D model is created where the internal structure of the deformed system can be visualized and mined for information. The region used in the study is the Sawtooth Range, Montana. The region forms part of the Montana Disturbed Belt in the Front Ranges of the Rocky Mountains, along strike from the Alberta Syncline in the Canadian Rocky Mountains. Interpretation of satellite data indicates that the deformation front structures include both folds and thrust structures. The thrust structures vary from hinterland-verging triangle zones to foreland-verging imbricate thrusts along strike, and the folds also vary in geometry along strike. The analog models, constrained by data from exploration wells, indicate that this change in geometry is related to a change in mechanical stratigraphy along the strike of the belt. Results from the kinematic and dynamic analysis of the digital model will also be presented. Additional implications of such a workflow and visualization system include the possibility of creating and viewing multiple cross-sections, including sections created at oblique angles to the original model. This allows the analysis of the non-plane strain component of the models and thus a more complete analysis, understanding and visualization of the deformed region. This workflow and visualization system is applicable to any region where traditional field methods must be coupled with remote data, intensely processed depth data, or analog modeling systems in order to generate valid geologic or geophsyical models.

Oceanic Extreme Model Atmospheres for Aerothermodynamic Calculations,

DTIC Science & Technology

Atmospheric temperature, Atmospheric sounding, Regression analysis, Aerothermodynamics, Marine meteorology, Radiosondes, Weather stations, Newfoundland(Province), Marshall Islands , Arabia, Iran, Coastal regions

Meteorological considerations and satellite retrievals in supporting to the assessment of local hydrologic homogeneity over Italy

NASA Astrophysics Data System (ADS)

Gabriele, Salvatore; Laviola, Sante; Chiaravalloti, Francesco

2014-05-01

Regional frequency analysis is a useful tool for estimating precipitation quantiles more accurately than at-site frequency analysis, especially in the case of regions with a brief history of short-time rainfall records. Since the rainfalls with short duration are mainly due to convective phenomena, usually affecting areas of few square kilometers, the description of these events with traditional tools such as in-situ rain gauges is often incomplete and not exhaustive. Thus, the application of these datasets to the regional analysis typically provides unrealistic description of the event and large miscalculations of the return time, usually higher than observation. Therefore, in order to evaluate the possible regional homogeneity and improve the performance of hydrologic models the inference analysis of the regional climatic regimes is revealed a useful tool. Starting from the intense rainfall of 19 November 2013 over Southern Italy, we demonstrate that the synoptic meteorological situation well-matched with results of Gabriele & Chiaravalloti (2013a, 2013b) where the regional homogeneity has been calculated on the basis of different climate indexes such as Convective Available Potential Energy (CAPE) and the Q-vector Divergence (QD). In support to that analysis two different methodologies based on satellite microwave information have been applied: the Water vapor Strong Lines at 183 GHz (183-WSL) (Laviola and Levizzani, 2011) algorithm provides to define the precipitation patterns while the MicroWave Cloud Classification (MWCC) (Miglietta et al., 2013) characterizes the cloud type in terms of stratiform and convective. Although, this study is still in progress the current results clearly demonstrate that the Mediterranean storms move on a sort of 'preferential trajectories' especially during the months September-November where the most intense convections have been found. Laviola, S., and V. Levizzani, 2011: The 183-WSL fast rainrate retrieval algorithm. Part I: Retrieval design. Atmos. Res., 99, 443-461. Miglietta, M. M., S. Laviola, A, Malvaldi, D. Conte, V. Levizzani, and C. Price, 2013: Analysis of tropical-like cyclone over the Mediterranean Sea through a combined modeling and satellite approach. Geophys. Res. Lett., 40, 2400-2405, doi:10.1002/grl.50432. Gabriele,S., and F. Chiaravalloti, 2013a: Searching regional rainfall homogeneity using atmospheric fields, Advances in Water Resources, 53, 163-174 Gabriele,S., and F. Chiaravalloti, 2013b: Using meteorological information for the regional frequency analysis: an application to Sicily, Water Resour. Manage. 27, 1721-1735

Imaging regional renal function parameters using radionuclide tracers

NASA Astrophysics Data System (ADS)

Qiao, Yi

A compartmental model is given for evaluating kidney function accurately and noninvasively. This model is cast into a parallel multi-compartment structure and each pixel region (picture element) of kidneys is considered as a single kidney compartment. The loss of radionuclide tracers from the blood to the kidney and from the kidney to the bladder are modelled in great detail. Both the uptake function and the excretion function of the kidneys can be evaluated pixel by pixel, and regional diagnostic information on renal function is obtained. Gamma Camera image data are required by this model and a screening test based renal function measurement is provided. The regional blood background is subtracted from the kidney region of interest (ROI) and the kidney regional rate constants are estimated analytically using the Kuhn-Pucker multiplier method in convex programming by considering the input/output behavior of the kidney compartments. The detailed physiological model of the peripheral compartments of the system, which is not available for most radionuclide tracers, is not required in the determination of the kidney regional rate constants and the regional blood background factors within the kidney ROI. Moreover, the statistical significance of measurements is considered to assure the improved statistical properties of the estimated kidney rate constants. The relations between various renal function parameters and the kidney rate constants are established. Multiple renal function measurements can be found from the renal compartmental model. The blood radioactivity curve and the regional (or total) radiorenogram determining the regional (or total) summed behavior of the kidneys are obtained analytically with the consideration of the statistical significance of measurements using convex programming methods for a single peripheral compartment system. In addition, a new technique for the determination of 'initial conditions' in both the blood compartment and the kidney compartment is presented. The blood curve and the radiorenogram are analyzed in great detail and a physiological analysis from the radiorenogram is given. Applications of Kuhn-Tucker multiplier methods are illustrated for the renal compartmental model in the field of nuclear medicine. Conventional kinetic data analysis methods, the maximum likehood method, and the weighted integration method are investigated and used for comparisons. Moreover, the effect of the blood background subtraction is shown by using the gamma camera images in man. Several functional images are calculated and the functional imaging technique is applied for evaluating renal function in man quantitatively and visually and compared with comments from a physician.

Using the OMI Aerosol Index and Absorption Aerosol Optical Depth to evaluate the NASA MERRA Aerosol Reanalysis

NASA Astrophysics Data System (ADS)

Buchard, V.; da Silva, A. M.; Colarco, P. R.; Darmenov, A.; Randles, C. A.; Govindaraju, R.; Torres, O.; Campbell, J.; Spurr, R.

2014-12-01

A radiative transfer interface has been developed to simulate the UV Aerosol Index (AI) from the NASA Goddard Earth Observing System version 5 (GEOS-5) aerosol assimilated fields. The purpose of this work is to use the AI and Aerosol Absorption Optical Depth (AAOD) derived from the Ozone Monitoring Instrument (OMI) measurements as independent validation for the Modern Era Retrospective analysis for Research and Applications Aerosol Reanalysis (MERRAero). MERRAero is based on a version of the GEOS-5 model that is radiatively coupled to the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) aerosol module and includes assimilation of Aerosol Optical Depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Since AI is dependent on aerosol concentration, optical properties and altitude of the aerosol layer, we make use of complementary observations to fully diagnose the model, including AOD from the Multi-angle Imaging SpectroRadiometer (MISR), aerosol retrievals from the Aerosol Robotic Network (AERONET) and attenuated backscatter coefficients from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission to ascertain potential misplacement of plume height by the model. By sampling dust, biomass burning and pollution events in 2007 we have compared model produced AI and AAOD with the corresponding OMI products, identifying regions where the model representation of absorbing aerosols was deficient. As a result of this study over the Saharan dust region, we have obtained a new set of dust aerosol optical properties that retains consistency with the MODIS AOD data that were assimilated, while resulting in better agreement with aerosol absorption measurements from OMI. The analysis conducted over the South African and South American biomass burning regions indicates that revising the spectrally-dependent aerosol absorption properties in the near-UV region improves the modeled-observed AI comparisons. Finally, during a period where the Asian region was mainly dominated by anthropogenic aerosols, we have performed a qualitative analysis in which the specification of anthropogenic emissions in GEOS-5 is adjusted to provide insight into discrepancies observed in AI comparisons.

Using the OMI aerosol index and absorption aerosol optical depth to evaluate the NASA MERRA Aerosol Reanalysis

NASA Astrophysics Data System (ADS)

Buchard, V.; da Silva, A. M.; Colarco, P. R.; Darmenov, A.; Randles, C. A.; Govindaraju, R.; Torres, O.; Campbell, J.; Spurr, R.

2015-05-01

A radiative transfer interface has been developed to simulate the UV aerosol index (AI) from the NASA Goddard Earth Observing System version 5 (GEOS-5) aerosol assimilated fields. The purpose of this work is to use the AI and aerosol absorption optical depth (AAOD) derived from the Ozone Monitoring Instrument (OMI) measurements as independent validation for the Modern Era Retrospective analysis for Research and Applications Aerosol Reanalysis (MERRAero). MERRAero is based on a version of the GEOS-5 model that is radiatively coupled to the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) aerosol module and includes assimilation of aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Since AI is dependent on aerosol concentration, optical properties and altitude of the aerosol layer, we make use of complementary observations to fully diagnose the model, including AOD from the Multi-angle Imaging SpectroRadiometer (MISR), aerosol retrievals from the AErosol RObotic NETwork (AERONET) and attenuated backscatter coefficients from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission to ascertain potential misplacement of plume height by the model. By sampling dust, biomass burning and pollution events in 2007 we have compared model-produced AI and AAOD with the corresponding OMI products, identifying regions where the model representation of absorbing aerosols was deficient. As a result of this study over the Saharan dust region, we have obtained a new set of dust aerosol optical properties that retains consistency with the MODIS AOD data that were assimilated, while resulting in better agreement with aerosol absorption measurements from OMI. The analysis conducted over the southern African and South American biomass burning regions indicates that revising the spectrally dependent aerosol absorption properties in the near-UV region improves the modeled-observed AI comparisons. Finally, during a period where the Asian region was mainly dominated by anthropogenic aerosols, we have performed a qualitative analysis in which the specification of anthropogenic emissions in GEOS-5 is adjusted to provide insight into discrepancies observed in AI comparisons.

Compartmental analysis of [11C]flumazenil kinetics for the estimation of ligand transport rate and receptor distribution using positron emission tomography.

PubMed

Koeppe, R A; Holthoff, V A; Frey, K A; Kilbourn, M R; Kuhl, D E

1991-09-01

The in vivo kinetic behavior of [11C]flumazenil ([11C]FMZ), a non-subtype-specific central benzodiazepine antagonist, is characterized using compartmental analysis with the aim of producing an optimized data acquisition protocol and tracer kinetic model configuration for the assessment of [11C]FMZ binding to benzodiazepine receptors (BZRs) in human brain. The approach presented is simple, requiring only a single radioligand injection. Dynamic positron emission tomography data were acquired on 18 normal volunteers using a 60- to 90-min sequence of scans and were analyzed with model configurations that included a three-compartment, four-parameter model, a three-compartment, three-parameter model, with a fixed value for free plus nonspecific binding; and a two-compartment, two-parameter model. Statistical analysis indicated that a four-parameter model did not yield significantly better fits than a three-parameter model. Goodness of fit was improved for three- versus two-parameter configurations in regions with low receptor density, but not in regions with moderate to high receptor density. Thus, a two-compartment, two-parameter configuration was found to adequately describe the kinetic behavior of [11C]FMZ in human brain, with stable estimates of the model parameters obtainable from as little as 20-30 min of data. Pixel-by-pixel analysis yields functional images of transport rate (K1) and ligand distribution volume (DV"), and thus provides independent estimates of ligand delivery and BZR binding.

Importance of partitioning membranes of the brain and the influence of the neck in head injury modelling.

PubMed

Kumaresan, S; Radhakrishnan, S

1996-01-01

A head injury model consisting of the skull, the CSF, the brain and its partitioning membranes and the neck region is simulated by considering its near actual geometry. Three-dimensional finite-element analysis is carried out to investigate the influence of the partitioning membranes of the brain and the neck in head injury analysis through free-vibration analysis and transient analysis. In free-vibration analysis, the first five modal frequencies are calculated, and in transient analysis intracranial pressure and maximum shear stress in the brain are determined for a given occipital impact load.

Comment on "Detection of emerging sunspot regions in the solar interior".

PubMed

Braun, Douglas C

2012-04-20

Ilonidis et al. (Reports, 19 August 2011, p. 993) report acoustic travel-time decreases associated with emerging sunspot regions before their appearance on the solar surface. An independent analysis using helioseismic holography does not confirm these travel-time anomalies for the four regions illustrated by Ilonidis et al. This negative finding is consistent with expectations based on current emerging flux models.

2010 August 1–2 Sympathetic Eruptions. II. Magnetic Topology of the MHD Background Field

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

Titov, Viacheslav S.; Mikić, Zoran; Török, Tibor

Using a potential field source-surface (PFSS) model, we recently analyzed the global topology of the background coronal magnetic field for a sequence of coronal mass ejections (CMEs) that occurred on 2010 August 1–2. Here we repeat this analysis for the background field reproduced by a magnetohydrodynamic (MHD) model that incorporates plasma thermodynamics. As for the PFSS model, we find that all three CME source regions contain a coronal hole (CH) that is separated from neighboring CHs by topologically very similar pseudo-streamer structures. However, the two models yield very different results for the size, shape, and flux of the CHs. Wemore » find that the helmet-streamer cusp line, which corresponds to a source-surface null line in the PFSS model, is structurally unstable and does not form in the MHD model. Our analysis indicates that, generally, in MHD configurations, this line instead consists of a multiple-null separator passing along the edge of disconnected-flux regions. Some of these regions are transient and may be the origin of the so-called streamer blobs. We show that the core topological structure of such blobs is a three-dimensional “plasmoid” consisting of two conjoined flux ropes of opposite handedness, which connect at a spiral null point of the magnetic field. Our analysis reveals that such plasmoids also appear in pseudo-streamers on much smaller scales. These new insights into the coronal magnetic topology provide some intriguing implications for solar energetic particle events and for the properties of the slow solar wind.« less

2010 August 1-2 Sympathetic Eruptions. II. Magnetic Topology of the MHD Background Field

NASA Astrophysics Data System (ADS)

Titov, Viacheslav S.; Mikić, Zoran; Török, Tibor; Linker, Jon A.; Panasenco, Olga

2017-08-01

Using a potential field source-surface (PFSS) model, we recently analyzed the global topology of the background coronal magnetic field for a sequence of coronal mass ejections (CMEs) that occurred on 2010 August 1-2. Here we repeat this analysis for the background field reproduced by a magnetohydrodynamic (MHD) model that incorporates plasma thermodynamics. As for the PFSS model, we find that all three CME source regions contain a coronal hole (CH) that is separated from neighboring CHs by topologically very similar pseudo-streamer structures. However, the two models yield very different results for the size, shape, and flux of the CHs. We find that the helmet-streamer cusp line, which corresponds to a source-surface null line in the PFSS model, is structurally unstable and does not form in the MHD model. Our analysis indicates that, generally, in MHD configurations, this line instead consists of a multiple-null separator passing along the edge of disconnected-flux regions. Some of these regions are transient and may be the origin of the so-called streamer blobs. We show that the core topological structure of such blobs is a three-dimensional “plasmoid” consisting of two conjoined flux ropes of opposite handedness, which connect at a spiral null point of the magnetic field. Our analysis reveals that such plasmoids also appear in pseudo-streamers on much smaller scales. These new insights into the coronal magnetic topology provide some intriguing implications for solar energetic particle events and for the properties of the slow solar wind.

[Analysis of the technical efficiency of hospitals in the Spanish National Health Service].

PubMed

Pérez-Romero, Carmen; Ortega-Díaz, M Isabel; Ocaña-Riola, Ricardo; Martín-Martín, José Jesús

To analyse the technical efficiency and productivity of general hospitals in the Spanish National Health Service (NHS) (2010-2012) and identify explanatory hospital and regional variables. 230 NHS hospitals were analysed by data envelopment analysis for overall, technical and scale efficiency, and Malmquist index. The robustness of the analysis is contrasted with alternative input-output models. A fixed effects multilevel cross-sectional linear model was used to analyse the explanatory efficiency variables. The average rate of overall technical efficiency (OTE) was 0.736 in 2012; there was considerable variability by region. Malmquist index (2010-2012) is 1.013. A 23% variability in OTE is attributable to the region in question. Statistically significant exogenous variables (residents per 100 physicians, aging index, average annual income per household, essential public service expenditure and public health expenditure per capita) explain 42% of the OTE variability between hospitals and 64% between regions. The number of residents showed a statistically significant relationship. As regards regions, there is a statistically significant direct linear association between OTE and annual income per capita and essential public service expenditure, and an indirect association with the aging index and annual public health expenditure per capita. The significant room for improvement in the efficiency of hospitals is conditioned by region-specific characteristics, specifically aging, wealth and the public expenditure policies of each one. Copyright © 2016 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

An analysis of human-induced land transformations in the San Francisco Bay/Sacramento area

USGS Publications Warehouse

Kirtland, David A.; Gaydos, L.J.; Clarke, Keith; DeCola, Lee; Acevedo, William; Bell, Cindy

1994-01-01

Part of the U.S. Geological Survey's Global Change Research Program involvesstudying the area from the Pacific Ocean to the Sierra foothills to enhance understanding ofthe role that human activities play in global change. The study investigates the ways thathumans transform the land and the effects that changing the landscape may have on regionaland global systems. To accomplish this research, scientists are compiling records ofhistorical transformations in the region's land cover over the last 140 years, developing asimulation model to predict land cover change, and assembling a digital data set to analyzeand describe land transformations. The historical data regarding urban growth focusattention on the significant change the region underwent from 1850 to 1990. Animation isused to visualize a time series of the change in land cover. The historical change is beingused to calibrate a prototype cellular automata model, developed to predict changes in urbanland cover 100 years into the future. Future urban growth scenarios will be developed foranalyzing possible human-induced impacts on land cover at a regional scale. These data aidin documenting and understanding human-induced land transformations from both historical andpredictive perspectives. A descriptive analysis of the region is used to investigate therelationships among data characteristic of the region. These data consist of multilayertopography, climate, vegetation, and population data for a 256-km2 region of centralCalifornia. A variety of multivariate analysis tools are used to integrate the data inraster format from map contours, interpolated climate observations, satellite observations,and population estimates.

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

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

Modeling multi-source flooding disaster and developing simulation framework in Delta

NASA Astrophysics Data System (ADS)

Liu, Y.; Cui, X.; Zhang, W.

2016-12-01

Most Delta regions of the world are densely populated and with advanced economies. However, due to impact of the multi-source flooding (upstream flood, rainstorm waterlogging, storm surge flood), the Delta regions is very vulnerable. The academic circles attach great importance to the multi-source flooding disaster in these areas. The Pearl River Delta urban agglomeration in south China is selected as the research area. Based on analysis of natural and environmental characteristics data of the Delta urban agglomeration(remote sensing data, land use data, topographic map, etc.), hydrological monitoring data, research of the uneven distribution and process of regional rainfall, the relationship between the underlying surface and the parameters of runoff, effect of flood storage pattern, we use an automatic or semi-automatic method for dividing spatial units to reflect the runoff characteristics in urban agglomeration, and develop an Multi-model Ensemble System in changing environment, including urban hydrologic model, parallel computational 1D&2D hydrodynamic model, storm surge forecast model and other professional models, the system will have the abilities like real-time setting a variety of boundary conditions, fast and real-time calculation, dynamic presentation of results, powerful statistical analysis function. The model could be optimized and improved by a variety of verification methods. This work was supported by the National Natural Science Foundation of China (41471427); Special Basic Research Key Fund for Central Public Scientific Research Institutes.

Transient Ejector Analysis (TEA) code user's guide

NASA Technical Reports Server (NTRS)

Drummond, Colin K.

1993-01-01

A FORTRAN computer program for the semi analytic prediction of unsteady thrust augmenting ejector performance has been developed, based on a theoretical analysis for ejectors. That analysis blends classic self-similar turbulent jet descriptions with control-volume mixing region elements. Division of the ejector into an inlet, diffuser, and mixing region allowed flexibility in the modeling of the physics for each region. In particular, the inlet and diffuser analyses are simplified by a quasi-steady-analysis, justified by the assumption that pressure is the forcing function in those regions. Only the mixing region is assumed to be dominated by viscous effects. The present work provides an overview of the code structure, a description of the required input and output data file formats, and the results for a test case. Since there are limitations to the code for applications outside the bounds of the test case, the user should consider TEA as a research code (not as a production code), designed specifically as an implementation of the proposed ejector theory. Program error flags are discussed, and some diagnostic routines are presented.

Process analysis of regional aerosol pollution during spring in the Pearl River Delta region, China

NASA Astrophysics Data System (ADS)

Fan, Qi; Lan, Jing; Liu, Yiming; Wang, Xuemei; Chan, Pakwai; Hong, Yingying; Feng, Yerong; Liu, Yexin; Zeng, Yanjun; Liang, Guixiong

2015-12-01

A numerical simulation analysis was performed for three air pollution episodes in the Pearl River Delta (PRD) region during March 2012 using the third-generation air quality modeling system Models-3/CMAQ. The results demonstrated that particulate matter was the primary pollutant for all three pollution episodes and was accompanied by relatively low visibility in the first two episodes. Weather maps indicate that the first two episodes occurred under the influence of warm, wet southerly air flow systems that led to high humidity throughout the region. The liquid phase reaction of gaseous pollutants resulted in the generation of fine secondary particles, which were identified as the primary source of pollution in the first two episodes. The third pollution episode occurred during a warming period following a cold front. Relative humidity was lower during this episode, and coarse particles were the major pollution contributor. Results of process analysis indicated that emissions sources, horizontal transport and vertical transport were the primary factors affecting pollutant concentrations within the near-surface layer during all three episodes, while aerosol processes, cloud processes, horizontal transport and vertical transport had greater influence at approximately 900 m above ground. Cloud processes had a greater impact during the first two pollution episodes because of the higher relative humidity. In addition, by comparing pollution processes from different cities (Guangzhou and Zhongshan), the study revealed that the first two pollution episodes were the result of local emissions within the PRD region and transport between surrounding cities, while the third episode exhibited prominent regional pollution characteristics and was the result of regional pollutant transport.

AQMEII3: the EU and NA regional scale program of the ...

EPA Pesticide Factsheets

The presentation builds on the work presented last year at the 14th CMAS meeting and it is applied to the work performed in the context of the AQMEII-HTAP collaboration. The analysis is conducted within the framework of the third phase of AQMEII (Air Quality Model Evaluation International Initiative) and encompasses the gauging of model performance through measurement-to-model comparison, error decomposition and time series analysis of the models biases. Through the comparison of several regional-scale chemistry transport modelling systems applied to simulate meteorology and air quality over two continental areas, this study aims at i) apportioning the error to the responsible processes through time-scale analysis, and ii) help detecting causes of models error, and iii) identify the processes and scales most urgently requiring dedicated investigations. The operational metrics (magnitude of the error, sign of the bias, associativity) provide an overall sense of model strengths and deficiencies, while the apportioning of the error into its constituent parts (bias, variance and covariance) can help assess the nature and quality of the error. Each of the error components is analysed independently and apportioned to specific processes based on the corresponding timescale (long scale, synoptic, diurnal, and intra-day) using the error apportionment technique devised in the previous phases of AQMEII. The National Exposure Research Laboratory (NERL) Computational Exposur

Regional analysis of annual maximum rainfall using TL-moments method

NASA Astrophysics Data System (ADS)

Shabri, Ani Bin; Daud, Zalina Mohd; Ariff, Noratiqah Mohd

2011-06-01

Information related to distributions of rainfall amounts are of great importance for designs of water-related structures. One of the concerns of hydrologists and engineers is the probability distribution for modeling of regional data. In this study, a novel approach to regional frequency analysis using L-moments is revisited. Subsequently, an alternative regional frequency analysis using the TL-moments method is employed. The results from both methods were then compared. The analysis was based on daily annual maximum rainfall data from 40 stations in Selangor Malaysia. TL-moments for the generalized extreme value (GEV) and generalized logistic (GLO) distributions were derived and used to develop the regional frequency analysis procedure. TL-moment ratio diagram and Z-test were employed in determining the best-fit distribution. Comparison between the two approaches showed that the L-moments and TL-moments produced equivalent results. GLO and GEV distributions were identified as the most suitable distributions for representing the statistical properties of extreme rainfall in Selangor. Monte Carlo simulation was used for performance evaluation, and it showed that the method of TL-moments was more efficient for lower quantile estimation compared with the L-moments.

Multi-scaling allometric analysis for urban and regional development

NASA Astrophysics Data System (ADS)

Chen, Yanguang

2017-01-01

The concept of allometric growth is based on scaling relations, and it has been applied to urban and regional analysis for a long time. However, most allometric analyses were devoted to the single proportional relation between two elements of a geographical system. Few researches focus on the allometric scaling of multielements. In this paper, a process of multiscaling allometric analysis is developed for the studies on spatio-temporal evolution of complex systems. By means of linear algebra, general system theory, and by analogy with the analytical hierarchy process, the concepts of allometric growth can be integrated with the ideas from fractal dimension. Thus a new methodology of geo-spatial analysis and the related theoretical models emerge. Based on the least squares regression and matrix operations, a simple algorithm is proposed to solve the multiscaling allometric equation. Applying the analytical method of multielement allometry to Chinese cities and regions yields satisfying results. A conclusion is reached that the multiscaling allometric analysis can be employed to make a comprehensive evaluation for the relative levels of urban and regional development, and explain spatial heterogeneity. The notion of multiscaling allometry may enrich the current theory and methodology of spatial analyses of urban and regional evolution.

An integrated regional planning/microsimulation model for the Buffalo/Niagara Falls area

DOT National Transportation Integrated Search

2010-04-01

This presentation examines the major planning issues facing the Buffalo and Niagara Falls area, which include freight, cross border congestion, and domestic issues. A Transportation Analysis and Simulation System (TRANSIMS) model is discussed that co...

NLEAP/GIS approach for identifying and mitigating regional nitrate-nitrogen leaching

USGS Publications Warehouse

Shaffer, M.J.; Hall, M.D.; Wylie, B.K.; Wagner, D.G.; Corwin, D.L.; Loague, K.

1996-01-01

Improved simulation-based methodology is needed to help identify broad geographical areas where potential NO3-N leaching may be occurring from agriculture and suggest management alternatives that minimize the problem. The Nitrate Leaching and Economic Analysis Package (NLEAP) model was applied to estimate regional NO3-N leaching in eastern Colorado. Results show that a combined NLEAP/GIS technology can be used to identify potential NO3-N hot spots in shallow alluvial aquifers under irrigated agriculture. The NLEAP NO3-N Leached (NL) index provided the most promising single index followed by NO3-N Available for Leaching (NAL). The same combined technology also shows promise in identifying Best Management Practice (BMP) methods that help minimize NO3-N leaching in vulnerable areas. Future plans call for linkage of the NLEAP/GIS procedures with groundwater modeling to establish a mechanistic analysis of agriculture-aquifer interactions at a regional scale.

Quantum Transmission Conditions for Diffusive Transport in Graphene with Steep Potentials

NASA Astrophysics Data System (ADS)

Barletti, Luigi; Negulescu, Claudia

2018-05-01

We present a formal derivation of a drift-diffusion model for stationary electron transport in graphene, in presence of sharp potential profiles, such as barriers and steps. Assuming the electric potential to have steep variations within a strip of vanishing width on a macroscopic scale, such strip is viewed as a quantum interface that couples the classical regions at its left and right sides. In the two classical regions, where the potential is assumed to be smooth, electron and hole transport is described in terms of semiclassical kinetic equations. The diffusive limit of the kinetic model is derived by means of a Hilbert expansion and a boundary layer analysis, and consists of drift-diffusion equations in the classical regions, coupled by quantum diffusive transmission conditions through the interface. The boundary layer analysis leads to the discussion of a four-fold Milne (half-space, half-range) transport problem.

Spatial Durbin model analysis macroeconomic loss due to natural disasters

NASA Astrophysics Data System (ADS)

Kusrini, D. E.; Mukhtasor

2015-03-01

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

Improving the representation of clouds, radiation, and precipitation using spectral nudging in the Weather Research and Forecasting model

NASA Astrophysics Data System (ADS)

Spero, Tanya L.; Otte, Martin J.; Bowden, Jared H.; Nolte, Christopher G.

2014-10-01

Spectral nudging—a scale-selective interior constraint technique—is commonly used in regional climate models to maintain consistency with large-scale forcing while permitting mesoscale features to develop in the downscaled simulations. Several studies have demonstrated that spectral nudging improves the representation of regional climate in reanalysis-forced simulations compared with not using nudging in the interior of the domain. However, in the Weather Research and Forecasting (WRF) model, spectral nudging tends to produce degraded precipitation simulations when compared to analysis nudging—an interior constraint technique that is scale indiscriminate but also operates on moisture fields which until now could not be altered directly by spectral nudging. Since analysis nudging is less desirable for regional climate modeling because it dampens fine-scale variability, changes are proposed to the spectral nudging methodology to capitalize on differences between the nudging techniques and aim to improve the representation of clouds, radiation, and precipitation without compromising other fields. These changes include adding spectral nudging toward moisture, limiting nudging to below the tropopause, and increasing the nudging time scale for potential temperature, all of which collectively improve the representation of mean and extreme precipitation, 2 m temperature, clouds, and radiation, as demonstrated using a model-simulated 20 year historical period. Such improvements to WRF may increase the fidelity of regional climate data used to assess the potential impacts of climate change on human health and the environment and aid in climate change mitigation and adaptation studies.

Regional climate change predictions from the Goddard Institute for Space Studies high resolution GCM

NASA Technical Reports Server (NTRS)

Crane, Robert G.; Hewitson, Bruce

1990-01-01

Model simulations of global climate change are seen as an essential component of any program aimed at understanding human impact on the global environment. A major weakness of current general circulation models (GCMs), however, is their inability to predict reliably the regional consequences of a global scale change, and it is these regional scale predictions that are necessary for studies of human/environmental response. This research is directed toward the development of a methodology for the validation of the synoptic scale climatology of GCMs. This is developed with regard to the Goddard Institute for Space Studies (GISS) GCM Model 2, with the specific objective of using the synoptic circulation form a doubles CO2 simulation to estimate regional climate change over North America, south of Hudson Bay. This progress report is specifically concerned with validating the synoptic climatology of the GISS GCM, and developing the transfer function to derive grid-point temperatures from the synoptic circulation. Principal Components Analysis is used to characterize the primary modes of the spatial and temporal variability in the observed and simulated climate, and the model validation is based on correlations between component loadings, and power spectral analysis of the component scores. The results show that the high resolution GISS model does an excellent job of simulating the synoptic circulation over the U.S., and that grid-point temperatures can be predicted with reasonable accuracy from the circulation patterns.

Using WRF for Regional Climate Modeling: An Emphasis on the Southeast U.S. for Future Air Quality

EPA Science Inventory

This presentation describes preliminary analysis of a five-member regional climate ensemble (developed by AMAD and its contractors, including UNC) to determine if there is any consensus on projected changes to the placement of the North Atlantic Subtropical High (NASH, or Bermuda...

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

ERIC Educational Resources Information Center

Clark, Roger; Filinson, Rachel

1991-01-01

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

Essays in Societal System Dynamics and Transportation : Report of the Third Annual Workshop in Urban and Regional Systems Analysis

DOT National Transportation Integrated Search

1981-03-01

This document contains the White Papers on urban-regional modeling presented at the Workshop as well as additional research papers aimed at increasing our understanding of the relationships between transportation and society. The ultimate aim is to p...

Risk Assessment in Relation to the Effect of Climate Change on Water Shortage in the Taichung Area

NASA Astrophysics Data System (ADS)

Hsiao, J.; Chang, L.; Ho, C.; Niu, M.

2010-12-01

Rapid economic development has stimulated a worldwide greenhouse effect and induced global climate change. Global climate change has increased the range of variation in the quantity of regional river flows between wet and dry seasons, which effects the management of regional water resources. Consequently, the influence of climate change has become an important issue in the management of regional water resources. In this study, the Monte Carlo simulation method was applied to risk analysis of shortage of water supply in the Taichung area. This study proposed a simulation model that integrated three models: weather generator model, surface runoff model, and water distribution model. The proposed model was used to evaluate the efficiency of the current water supply system and the potential effectiveness of two additional plans for water supply: the “artificial lakes” plan and the “cross-basin water transport” plan. A first-order Markov Chain method and two probability distribution models, exponential distribution and normal distribution, were used in the weather generator model. In the surface runoff model, researchers selected the Generalized Watershed Loading Function model (GWLF) to simulate the relationship between quantity of rainfall and basin outflow. A system dynamics model (SD) was applied to the water distribution model. Results of the simulation indicated that climate change could increase the annual quantity of river flow in the Dachia River and Daan River basins. However, climate change could also increase the difference in the quantity of river flow between wet and dry seasons. Simulation results showed that in current system case or in the additional plan cases, shortage status of water for both public and agricultural uses with conditions of climate change will be mostly worse than that without conditions of climate change except for the shortage status for the public use in the current system case. With or without considering the effect of climate change, the additional plans, especially the “cross-basin water transport” plan, for water supply could significantly increase the supply of water for public use. The proposed simulation model and results of analysis in this study could provide valuable reference for decision-makers in regards to risk analysis of regional water supply.

Modeling and Analysis of Large Amplitude Flight Maneuvers

NASA Technical Reports Server (NTRS)

Anderson, Mark R.

2004-01-01

Analytical methods for stability analysis of large amplitude aircraft motion have been slow to develop because many nonlinear system stability assessment methods are restricted to a state-space dimension of less than three. The proffered approach is to create regional cell-to-cell maps for strategically located two-dimensional subspaces within the higher-dimensional model statespace. These regional solutions capture nonlinear behavior better than linearized point solutions. They also avoid the computational difficulties that emerge when attempting to create a cell map for the entire state-space. Example stability results are presented for a general aviation aircraft and a micro-aerial vehicle configuration. The analytical results are consistent with characteristics that were discovered during previous flight-testing.

Landsat analysis of tropical forest succession employing a terrain model

NASA Technical Reports Server (NTRS)

Barringer, T. H.; Robinson, V. B.; Coiner, J. C.; Bruce, R. C.

1980-01-01

Landsat multispectral scanner (MSS) data have yielded a dual classification of rain forest and shadow in an analysis of a semi-deciduous forest on Mindonoro Island, Philippines. Both a spatial terrain model, using a fifth side polynomial trend surface analysis for quantitatively estimating the general spatial variation in the data set, and a spectral terrain model, based on the MSS data, have been set up. A discriminant analysis, using both sets of data, has suggested that shadowing effects may be due primarily to local variations in the spectral regions and can therefore be compensated for through the decomposition of the spatial variation in both elevation and MSS data.

Network analysis of mesoscale optical recordings to assess regional, functional connectivity.

PubMed

Lim, Diana H; LeDue, Jeffrey M; Murphy, Timothy H

2015-10-01

With modern optical imaging methods, it is possible to map structural and functional connectivity. Optical imaging studies that aim to describe large-scale neural connectivity often need to handle large and complex datasets. In order to interpret these datasets, new methods for analyzing structural and functional connectivity are being developed. Recently, network analysis, based on graph theory, has been used to describe and quantify brain connectivity in both experimental and clinical studies. We outline how to apply regional, functional network analysis to mesoscale optical imaging using voltage-sensitive-dye imaging and channelrhodopsin-2 stimulation in a mouse model. We include links to sample datasets and an analysis script. The analyses we employ can be applied to other types of fluorescence wide-field imaging, including genetically encoded calcium indicators, to assess network properties. We discuss the benefits and limitations of using network analysis for interpreting optical imaging data and define network properties that may be used to compare across preparations or other manipulations such as animal models of disease.

Impact of lateral boundary conditions on regional analyses

NASA Astrophysics Data System (ADS)

Chikhar, Kamel; Gauthier, Pierre

2017-04-01

Regional and global climate models are usually validated by comparison to derived observations or reanalyses. Using a model in data assimilation results in a direct comparison to observations to produce its own analyses that may reveal systematic errors. In this study, regional analyses over North America are produced based on the fifth-generation Canadian Regional Climate Model (CRCM5) combined with the variational data assimilation system of the Meteorological Service of Canada (MSC). CRCM5 is driven at its boundaries by global analyses from ERA-interim or produced with the global configuration of the CRCM5. Assimilation cycles for the months of January and July 2011 revealed systematic errors in winter through large values in the mean analysis increments. This bias is attributed to the coupling of the lateral boundary conditions of the regional model with the driving data particularly over the northern boundary where a rapidly changing large scale circulation created significant cross-boundary flows. Increasing the time frequency of the lateral driving and applying a large-scale spectral nudging improved significantly the circulation through the lateral boundaries which translated in a much better agreement with observations.

Comparative analysis of meteorological performance of coupled chemistry-meteorology models in the context of AQMEII phase 2

EPA Science Inventory

Air pollution simulations critically depend on the quality of the underlying meteorology. In phase 2 of the Air Quality Model Evaluation International Initiative (AQMEII-2), thirteen modeling groups from Europe and four groups from North America operating eight different regional...

Presentation--HABITAT DISTRIBUTION MODELS FOR 37 VERTEBRATE SPECIES IN THE MOJAVE DESERT ECOREGION OF NEVADA, ARIZONA, AND UTAH

EPA Science Inventory

Thirty-seven terrestrial vertebrate species in the Clark County Multi-Species Habitat Conservation Plan (MSHCP) were previously modeled through the Southwest Regional Gap Analysis Project (SWReGAP), using a deductive approach. To increase the applicability of such habitat models ...

Stability analysis and wave dynamics of an extended hybrid traffic flow model

NASA Astrophysics Data System (ADS)

Wang, Yu-Qing; Zhou, Chao-Fan; Li, Wei-Kang; Yan, Bo-Wen; Jia, Bin; Wang, Ji-Xin

2018-02-01

The stability analysis and wave dynamic properties of an extended hybrid traffic flow model, WZY model, are intensively studied in this paper. The linear stable condition obtained by the linear stability analysis is presented. Besides, by means of analyzing Korteweg-de Vries equation, we present soliton waves in the metastable region. Moreover, the multiscale perturbation technique is applied to derive the traveling wave solution of the model. Furthermore, by means of performing Darboux transformation, the first-order and second-order doubly-periodic solutions and rational solutions are presented. It can be found that analytical solutions match well with numerical simulations.

Fevers and Chills: Separating thermal and synchrotron components in SNR spectra

NASA Astrophysics Data System (ADS)

Fedor, Emily Elizabeth; Martina-Hood, Hyourin; Stage, Michael D.

2018-06-01

Spatially-resolved spectroscopy is an extremely powerful tool in X-ray analysis of extended sources, but can be computationally difficult if a source exhibits complex morphology. For example, high-resolution Chandra data of bright Galactic supernova remnants (Cas A, Tycho, etc.) allow extractions of high-quality spectra from tens to hundreds of thousands of regions, providing a rich laboratory for localizing emission from processes such as thermal line emission, bremsstrahlung, and synchrotron. This soft-band analysis informs our understanding of the typically nonthermal hard X-ray emission observed with other lower-resolution instruments. The analysis is complicated by both projection effects and the presence of multiple emission mechanisms in some regions. In particular, identifying regions with significant nonthermal emission is critical to understanding acceleration processes in remnants. Fitting tens of thousands of regions with complex, multi-component models can be time-consuming and involve so many free parameters that little constraint can be placed on the values. Previous work by Stage & Allen ('06, '07, '11) on Cas A used a technique to identify regions dominated by the highest-cutoff synchrotron emission by fitting with a simple thermal emission model and identifying regions with anomalously high apparent temperatures (caused by presence of the high-energy tail of the synchrotron emission component). Here, we present a similar technique. We verify the previous approach and, more importantly, expand it to include a method to identify regions containing strong lower-cutoff synchrotron radiation. Such regions might be associated with the reverse-shock of a supernova. Identification of a nonthermal electron population in the interior of an SNR would have significant implications for the energy balance and emission mechanisms producing the high-energy (> 10 keV) spectrum.

Development and Utilization of Regional Oceanic Modeling System (ROMS). Delicacy, Imprecision, and Uncertainty of Oceanic Simulations: An Investigation with the Regional Oceanic Modeling System (ROMS). Submesoscale Flows and Mixing in the Ocean Surface Layer Using the Regional Oceanic Modeling System (ROMS). Eddy Effects in General Circulation, Spanning Mean Currents, Mesoscale Eddies, and Topographic Generation, including Submesoscale Nests

DTIC Science & Technology

2012-09-30

unbalanced motions is likely to occur. Due to an rapidly expanding set of investigation on oceanic flows at submesoscales, it is increasingly clear...Uchiyama, E. M. Lane, J. M. Restrepo, & J. C. McWilliams, 2011: A vortex force analysis of the interaction of rip currents and gravity waves. J. Geophys...particular topographic features, the torque is pervasively positive (cyclonic) along the Stream, in opposition to the anticyclonic wind curl in the

Population analysis of the cingulum bundle using the tubular surface model for schizophrenia detection

NASA Astrophysics Data System (ADS)

Mohan, Vandana; Sundaramoorthi, Ganesh; Kubicki, Marek; Terry, Douglas; Tannenbaum, Allen

2010-03-01

We propose a novel framework for population analysis of DW-MRI data using the Tubular Surface Model. We focus on the Cingulum Bundle (CB) - a major tract for the Limbic System and the main connection of the Cingulate Gyrus, which has been associated with several aspects of Schizophrenia symptomatology. The Tubular Surface Model represents a tubular surface as a center-line with an associated radius function. It provides a natural way to sample statistics along the length of the fiber bundle and reduces the registration of fiber bundle surfaces to that of 4D curves. We apply our framework to a population of 20 subjects (10 normal, 10 schizophrenic) and obtain excellent results with neural network based classification (90% sensitivity, 95% specificity) as well as unsupervised clustering (k-means). Further, we apply statistical analysis to the feature data and characterize the discrimination ability of local regions of the CB, as a step towards localizing CB regions most relevant to Schizophrenia.

Spatial modeling of cutaneous leishmaniasis in the Andean region of Colombia

PubMed Central

Pérez-Flórez, Mauricio; Ocampo, Clara Beatriz; Valderrama-Ardila, Carlos; Alexander, Neal

2016-01-01

The objective of this research was to identify environmental risk factors for cutaneous leishmaniasis (CL) in Colombia and map high-risk municipalities. The study area was the Colombian Andean region, comprising 715 rural and urban municipalities. We used 10 years of CL surveillance: 2000-2009. We used spatial-temporal analysis - conditional autoregressive Poisson random effects modelling - in a Bayesian framework to model the dependence of municipality-level incidence on land use, climate, elevation and population density. Bivariable spatial analysis identified rainforests, forests and secondary vegetation, temperature, and annual precipitation as positively associated with CL incidence. By contrast, livestock agroecosystems and temperature seasonality were negatively associated. Multivariable analysis identified land use - rainforests and agro-livestock - and climate - temperature, rainfall and temperature seasonality - as best predictors of CL. We conclude that climate and land use can be used to identify areas at high risk of CL and that this approach is potentially applicable elsewhere in Latin America. PMID:27355214

A model for the study of ligand binding to the ribosomal RNA helix h44

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

Dibrov, Sergey M.; Parsons, Jerod; Hermann, Thomas

2010-09-02

Oligonucleotide models of ribosomal RNA domains are powerful tools to study the binding and molecular recognition of antibiotics that interfere with bacterial translation. Techniques such as selective chemical modification, fluorescence labeling and mutations are cumbersome for the whole ribosome but readily applicable to model RNAs, which are readily crystallized and often give rise to higher resolution crystal structures suitable for detailed analysis of ligand-RNA interactions. Here, we have investigated the HX RNA construct which contains two adjacent ligand binding regions of helix h44 in 16S ribosomal RNA. High-resolution crystal structure analysis confirmed that the HX RNA is a faithful structuralmore » model of the ribosomal target. Solution studies showed that HX RNA carrying a fluorescent 2-aminopurine modification provides a model system that can be used to monitor ligand binding to both the ribosomal decoding site and, through an indirect effect, the hygromycin B interaction region.« less

Comparative analysis of remotely-sensed data products via ecological niche modeling of avian influenza case occurrences in Middle Eastern poultry.

PubMed

Bodbyl-Roels, Sarah; Peterson, A Townsend; Xiao, Xiangming

2011-03-28

Ecological niche modeling integrates known sites of occurrence of species or phenomena with data on environmental variation across landscapes to infer environmental spaces potentially inhabited (i.e., the ecological niche) to generate predictive maps of potential distributions in geographic space. Key inputs to this process include raster data layers characterizing spatial variation in environmental parameters, such as vegetation indices from remotely sensed satellite imagery. The extent to which ecological niche models reflect real-world distributions depends on a number of factors, but an obvious concern is the quality and content of the environmental data layers. We assessed ecological niche model predictions of H5N1 avian flu presence quantitatively within and among four geographic regions, based on models incorporating two means of summarizing three vegetation indices derived from the MODIS satellite. We evaluated our models for predictive ability using partial ROC analysis and GLM ANOVA to compare performance among indices and regions. We found correlations between vegetation indices to be high, such that they contain information that overlaps broadly. Neither the type of vegetation index used nor method of summary affected model performance significantly. However, the degree to which model predictions had to be transferred (i.e., projected onto landscapes and conditions not represented on the landscape of training) impacted predictive strength greatly (within-region model predictions far out-performed models projected among regions). Our results provide the first quantitative tests of most appropriate uses of different remotely sensed data sets in ecological niche modeling applications. While our testing did not result in a decisive "best" index product or means of summarizing indices, it emphasizes the need for careful evaluation of products used in modeling (e.g. matching temporal dimensions and spatial resolution) for optimum performance, instead of simple reliance on large numbers of data layers.

Projected changes in rainfall and temperature over homogeneous regions of India

NASA Astrophysics Data System (ADS)

Patwardhan, Savita; Kulkarni, Ashwini; Rao, K. Koteswara

2018-01-01

The impact of climate change on the characteristics of seasonal maximum and minimum temperature and seasonal summer monsoon rainfall is assessed over five homogeneous regions of India using a high-resolution regional climate model. Providing REgional Climate for Climate Studies (PRECIS) is developed at Hadley Centre for Climate Prediction and Research, UK. The model simulations are carried out over South Asian domain for the continuous period of 1961-2098 at 50-km horizontal resolution. Here, three simulations from a 17-member perturbed physics ensemble (PPE) produced using HadCM3 under the Quantifying Model Uncertainties in Model Predictions (QUMP) project of Hadley Centre, Met. Office, UK, have been used as lateral boundary conditions (LBCs) for the 138-year simulations of the regional climate model under Intergovernmental Panel on Climate Change (IPCC) A1B scenario. The projections indicate the increase in the summer monsoon (June through September) rainfall over all the homogeneous regions (15 to 19%) except peninsular India (around 5%). There may be marginal change in the frequency of medium and heavy rainfall events (>20 mm) towards the end of the present century. The analysis over five homogeneous regions indicates that the mean maximum surface air temperatures for the pre-monsoon season (March-April-May) as well as the mean minimum surface air temperature for winter season (January-February) may be warmer by around 4 °C towards the end of the twenty-first century.

The use of transition region characteristics to improve the numerical simulation of heat transfer in bypass transitional flows

NASA Technical Reports Server (NTRS)

Simon, Frederick F.

1993-01-01

A method is presented for improving the numerical prediction of bypass transition heat transfer on a flat plate in a high-disturbance environment with zero or favorable pressure gradient. The method utilizes low Reynolds number k-epsilon turbulence models in combination with the characteristic parameters of the transition region. The parameters representing the characteristics of the transition region used are the intermittency, transition length and turbulent spot properties. An analysis is made of the transition length in terms of turbulent spot variables. The nondimensional spot formation rate, required for the prediction of the transition length, is shown by the analysis to be a function of the spot spreading angle, the dimensionless spot velocity ratio and the dimensionless spot area ratio. The intermittency form of the k-epsilon equations were derived from conditionally averaged equations which have been shown to be an improvement over global-time-averaged equations for the numerical calculation of the transition region. The numerical predictions are in general good agreement with the experimental data and indicate the potential use of the method in accelerating flows. Turbulence models of the k-epsilon type are known to underpredict the transition length. The present work demonstrates how incorporating transition region characteristics improves the ability of two-equation turbulence models to simulate bypass transition for flat plates with potential application to turbine vanes and blades.

Theoretical Analysis of Thermodynamic Measurements near a Liquid-Gas Critical Point

NASA Technical Reports Server (NTRS)

Barmatz, M.; Zhong, Fang; Hahn, Inseob

2003-01-01

Over the years, many ground-based studies have been performed near liquid-gas critical points to elucidate the expected divergences in thermodynamic quantities. The unambiguous interpretation of these studies very near the critical point is hindered by a gravity-induced density stratification. However, these ground-based measurements can give insight into the crossover behavior between the asymptotic critical region near the transition and the mean field region farther away. We have completed a detailed analysis of heat capacity, susceptibility and coexistence curve measurements near the He-3 liquid-gas critical point using the minimal-subtraction renormalization (MSR) scheme within the phi(exp 4) model. This MSR scheme, using only two adjustable parameters, provides a reasonable global fit to all of these experimental measurements in the gravity-free region out to a reduced temperature of |t| approx. 2x10(exp -2). Recently this approach has also been applied to the earlier microgravity measurements of Haupt and Straub in SF(sub 6) with surprising results. The conclusions drawn from the MSR analyses will be presented. Measurements in the gravity-affected region closer to the He-3 critical point have also been analyzed using the recent crossover parametric model (CPM) of the equation-of-state. The results of fitting heat capacity measurements to the CPM model along the He-3 critical isochore in the gravity-affected region will also be presented.

Mental health network governance: comparative analysis across Canadian regions

PubMed Central

Wiktorowicz, Mary E; Fleury, Marie-Josée; Adair, Carol E; Lesage, Alain; Goldner, Elliot; Peters, Suzanne

2010-01-01

Objective Modes of governance were compared in ten local mental health networks in diverse contexts (rural/urban and regionalized/non-regionalized) to clarify the governance processes that foster inter-organizational collaboration and the conditions that support them. Methods Case studies of ten local mental health networks were developed using qualitative methods of document review, semi-structured interviews and focus groups that incorporated provincial policy, network and organizational levels of analysis. Results Mental health networks adopted either a corporate structure, mutual adjustment or an alliance governance model. A corporate structure supported by regionalization offered the most direct means for local governance to attain inter-organizational collaboration. The likelihood that networks with an alliance model developed coordination processes depended on the presence of the following conditions: a moderate number of organizations, goal consensus and trust among the organizations, and network-level competencies. In the small and mid-sized urban networks where these conditions were met their alliance realized the inter-organizational collaboration sought. In the large urban and rural networks where these conditions were not met, externally brokered forms of network governance were required to support alliance based models. Discussion In metropolitan and rural networks with such shared forms of network governance as an alliance or voluntary mutual adjustment, external mediation by a regional or provincial authority was an important lever to foster inter-organizational collaboration. PMID:21289999

Satellite-enhanced dynamical downscaling for the analysis of extreme events

NASA Astrophysics Data System (ADS)

Nunes, Ana M. B.

2016-09-01

The use of regional models in the downscaling of general circulation models provides a strategy to generate more detailed climate information. In that case, boundary-forcing techniques can be useful to maintain the large-scale features from the coarse-resolution global models in agreement with the inner modes of the higher-resolution regional models. Although those procedures might improve dynamics, downscaling via regional modeling still aims for better representation of physical processes. With the purpose of improving dynamics and physical processes in regional downscaling of global reanalysis, the Regional Spectral Model—originally developed at the National Centers for Environmental Prediction—employs a newly reformulated scale-selective bias correction, together with the 3-hourly assimilation of the satellite-based precipitation estimates constructed from the Climate Prediction Center morphing technique. The two-scheme technique for the dynamical downscaling of global reanalysis can be applied in analyses of environmental disasters and risk assessment, with hourly outputs, and resolution of about 25 km. Here the satellite-enhanced dynamical downscaling added value is demonstrated in simulations of the first reported hurricane in the western South Atlantic Ocean basin through comparisons with global reanalyses and satellite products available in ocean areas.

Modeling Hydrological Services in Shade Grown Coffee Systems: Case Study of the Pico Duarte Region of the Dominican Republic

NASA Astrophysics Data System (ADS)

Erickson, J. D.; Gross, L.; Agosto Filion, N.; Bagstad, K.; Voigt, B. G.; Johnson, G.

2010-12-01

The modification of hydrologic systems in coffee-dominated landscapes varies widely according to the degree of shade trees incorporated in coffee farms. Compared to mono-cropping systems, shade coffee can produce both on- and off-farm benefits in the form of soil retention, moderation of sediment transport, and lower hydropower generating costs. The Pico Duarte Coffee Region and surrounding Madres de Las Aguas (Mother of Waters) Conservation Area in the Dominican Republic is emblematic of the challenges and opportunities of ecosystem service management in coffee landscapes. Shade coffee poly-cultures in the region play an essential role in ensuring ecosystem function to conserve water resources, as well as provide habitat for birds, sequester carbon, and provide consumptive resources to households. To model the provision, use, and flow of ecosystem services from coffee farms in the region, an application of the Artificial Intelligence for Ecosystem Services (ARIES) model was developed with particular focus on sediment regulation. ARIES incorporates an array of techniques from data mining, image analysis, neural networks, Bayesian statistics, information theory, and expert systems to model the production, delivery, and demand for ecosystem services. Geospatial data on slope, soils, and vegetation cover is combined with on-farm data collection of coffee production, tree diversity, and intercropping of household food. Given hydropower production and river recreation in the region, the management of sedimentation through on-farm practices has substantial, currently uncompensated value that has received recent attention as the foundation for a payment for ecosystem services system. Scenario analysis of the implications of agro-forestry management choices on farmer livelihoods and the multiple beneficiaries of farm-provided hydrological services provide a foundation for ongoing discussions in the region between local, national, and international interests.

Overlap in the functional neural systems involved in semantic and episodic memory retrieval.

PubMed

Rajah, M N; McIntosh, A R

2005-03-01

Neuroimaging and neuropsychological data suggest that episodic and semantic memory may be mediated by distinct neural systems. However, an alternative perspective is that episodic and semantic memory represent different modes of processing within a single declarative memory system. To examine whether the multiple or the unitary system view better represents the data we conducted a network analysis using multivariate partial least squares (PLS ) activation analysis followed by covariance structural equation modeling (SEM) of positron emission tomography data obtained while healthy adults performed episodic and semantic verbal retrieval tasks. It is argued that if performance of episodic and semantic retrieval tasks are mediated by different memory systems, then there should differences in both regional activations and interregional correlations related to each type of retrieval task, respectively. The PLS results identified brain regions that were differentially active during episodic retrieval versus semantic retrieval. Regions that showed maximal differences in regional activity between episodic retrieval tasks were used to construct separate functional models for episodic and semantic retrieval. Omnibus tests of these functional models failed to find a significant difference across tasks for both functional models. The pattern of path coefficients for the episodic retrieval model were not different across tasks, nor were the path coefficients for the semantic retrieval model. The SEM results suggest that the same memory network/system was engaged across tasks, given the similarities in path coefficients. Therefore, activation differences between episodic and semantic retrieval may ref lect variation along a continuum of processing during task performance within the context of a single memory system.

Downscaling, 2-way Nesting, and Data Assimilative Modeling in Coastal and Shelf Waters of the U.S. Mid-Atlantic Bight and Gulf of Maine

NASA Astrophysics Data System (ADS)

Wilkin, J.; Levin, J.; Lopez, A.; Arango, H.

2016-02-01

Coastal ocean models that downscale output from basin and global scale models are widely used to study regional circulation at enhanced resolution and locally important ecosystem, biogeochemical, and geomorphologic processes. When operated as now-cast or forecast systems, these models offer predictions that assist decision-making for numerous maritime applications. We describe such a system for shelf waters of the Mid-Atlantic Bight (MAB) and Gulf of Maine (GoM) where the MARACOOS and NERACOOS associations of U.S. IOOS operate coastal ocean observing systems that deliver a dense observation set using CODAR HF-radar, autonomous underwater glider vehicles (AUGV), telemetering moorings, and drifting buoys. Other U.S. national and global observing systems deliver further sustained observations from moorings, ships, profiling floats, and a constellation of satellites. Our MAB and GoM re-analysis and forecast system uses the Regional Ocean Modeling System (ROMS; myroms.org) with 4-dimensional Variational (4D-Var) data assimilation to adjust initial conditions, boundary conditions, and surface forcing in each analysis cycle. Data routinely assimilated include CODAR velocities, altimeter satellite sea surface height (with coastal corrections), satellite temperature, in situ CTD data from AUGV and ships (NMFS Ecosystem Monitoring voyages), and all in situ data reported via the WMO GTS network. A climatological data assimilative analysis of hydrographic and long-term mean velocity observations specifies the regional Mean Dynamic Topography that augments altimeter sea level anomaly data and is also used to adjust boundary condition biases that would otherwise be introduced in the process of downscaling from global models. System performance is described with respect to the impact of satellite, CODAR and in situ observations on analysis skill. Results from a 2-way nested modeling system that adds enhanced resolution over the NSF OOI Pioneer Array in the central MAB are also shown.

Infrastructure and social tie: Spatial model approach on understanding poverty in Malang regency, Indonesia

NASA Astrophysics Data System (ADS)

Ari, I. R. D.; Hasyim, A. W.; Pratama, B. A.; Helmy, M.; Sheilla, M. N.

2017-06-01

Poverty is a problem that requires attention from the government especially in developing countries such as Indonesia. This Research takes Place at Kasembon District because it has 53,19% family below poverty line in the region. The purpose of this research is to measure poverty based on 3 poverty indicators published by World Bank and 1 multidimensional poverty index. Furthermore, this research invesitigas the relationship between poverty with social and infrastructure in Kasembon District. This study using social network analysis, hot spots analysis, and regression analysis with ordinary least squares. From the poverty indicators known that Pondokagung Village has the highest poverty rate compared to another region. Results from regression model indicate that social and infrastructure affecting poverty in Kasembon District. Social parameter that affecting poverty is density. Infrastructure parameter that affecting poverty is length of paved road. Coefficient value of density is the largest in the model. Therefore it can be concluded that social factors can give more opportunity to reduce poverty rates in Kasembon District. In the local model of paved road coefficient, it is known that the coefficient for each village has not much different value from the global model.

Comparison of Grid Nudging and Spectral Nudging Techniques for Dynamical Climate Downscaling within the WRF Model

NASA Astrophysics Data System (ADS)

Fan, X.; Chen, L.; Ma, Z.

2010-12-01

Climate downscaling has been an active research and application area in the past several decades focusing on regional climate studies. Dynamical downscaling, in addition to statistical methods, has been widely used in downscaling as the advanced modern numerical weather and regional climate models emerge. The utilization of numerical models enables that a full set of climate variables are generated in the process of downscaling, which are dynamically consistent due to the constraints of physical laws. While we are generating high resolution regional climate, the large scale climate patterns should be retained. To serve this purpose, nudging techniques, including grid analysis nudging and spectral nudging, have been used in different models. There are studies demonstrating the benefit and advantages of each nudging technique; however, the results are sensitive to many factors such as nudging coefficients and the amount of information to nudge to, and thus the conclusions are controversy. While in a companion work of developing approaches for quantitative assessment of the downscaled climate, in this study, the two nudging techniques are under extensive experiments in the Weather Research and Forecasting (WRF) model. Using the same model provides fair comparability. Applying the quantitative assessments provides objectiveness of comparison. Three types of downscaling experiments were performed for one month of choice. The first type is serving as a base whereas the large scale information is communicated through lateral boundary conditions only; the second is using the grid analysis nudging; and the third is using spectral nudging. Emphases are given to the experiments of different nudging coefficients and nudging to different variables in the grid analysis nudging; while in spectral nudging, we focus on testing the nudging coefficients, different wave numbers on different model levels to nudge.

Southern Arizona hydroclimate over the last 3000 years: a comparison of speleothem elemental data and climate model simulations

NASA Astrophysics Data System (ADS)

King, J.; Harrington, M. D.; Cole, J. E.; Drysdale, R.; Woodhead, J. D.; Fasullo, J.; Stevenson, S.; Otto-Bliesner, B. L.; Overpeck, J. T.; Edwards, R. L.; Henderson, G. M.

2017-12-01

Understanding long-term hydroclimate is particularly important in semiarid regions where prolonged droughts may be exacerbated by a warming climate. In many regions, speleothem trace elements correlate with regional wet and dry climate signals. In the drought-prone Southwestern US (SW), wet and dry episodes are strongly influenced by seasonal changes in atmospheric circulation and teleconnections to remote forcing. Here, we address the need for seasonal moisture reconstructions using paleoclimate and climate model approaches. First, we present a high-resolution (sub-annual) record of speleothem trace elements spanning the last 3000 years from Fort Huachuca Cave, AZ, to investigate the variability of regional seasonal precipitation and sustained regional droughts. In a principal component (PC) analysis of the speleothem, trace elements associated with wet (Sr, Ba) and dry (P, Y, Zn) episodes load strongly and inversely, and the associated PC signals correlate with local gridded precipitation data over the last 50 years (R > 0.6, p < 0.1). These results suggest that the elemental signals provide a seasonal moisture record for Southern Arizona. We use the record to examine the frequency and timing of extreme droughts in the region and compare the speleothem record's frequency domain characteristics with other regional moisture records and with climate model output. The speleothem record demonstrates strong low-frequency variability with pronounced multi-decadal dry periods, a feature notably lacking in drought metrics from simulations of the last millennium. We also examine the seasonal SW precipitation response to modes of climate variability and external forcings, including volcanic eruptions, in both the speleothem record and the Community Earth System Model's Last Millennium Ensemble (CESM-LME). Notably, ENSO and volcanic forcing have a discernable effect on SW seasonal precipitation in model simulations, particularly when the two processes combine to shift the position of the ITCZ. This integrated analysis of paleodata with climate model results will help us identify and explain discrepancies between these information sources and improve stakeholders' ability to anticipate and prepare for future drought.

Multi-RCM ensemble downscaling of global seasonal forecasts (MRED)

NASA Astrophysics Data System (ADS)

Arritt, R. W.

2008-12-01

The Multi-RCM Ensemble Downscaling (MRED) project was recently initiated to address the question, Can regional climate models provide additional useful information from global seasonal forecasts? MRED will use a suite of regional climate models to downscale seasonal forecasts produced by the new National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS) seasonal forecast system and the NASA GEOS5 system. The initial focus will be on wintertime forecasts in order to evaluate topographic forcing, snowmelt, and the potential usefulness of higher resolution, especially for near-surface fields influenced by high resolution orography. Each regional model will cover the conterminous US (CONUS) at approximately 32 km resolution, and will perform an ensemble of 15 runs for each year 1982-2003 for the forecast period 1 December - 30 April. MRED will compare individual regional and global forecasts as well as ensemble mean precipitation and temperature forecasts, which are currently being used to drive macroscale land surface models (LSMs), as well as wind, humidity, radiation, turbulent heat fluxes, which are important for more advanced coupled macro-scale hydrologic models. Metrics of ensemble spread will also be evaluated. Extensive analysis will be performed to link improvements in downscaled forecast skill to regional forcings and physical mechanisms. Our overarching goal is to determine what additional skill can be provided by a community ensemble of high resolution regional models, which we believe will eventually define a strategy for more skillful and useful regional seasonal climate forecasts.

Impacts of Climate Policy on Regional Air Quality, Health, and Air Quality Regulatory Procedures

NASA Astrophysics Data System (ADS)

Thompson, T. M.; Selin, N. E.

2011-12-01

Both the changing climate, and the policy implemented to address climate change can impact regional air quality. We evaluate the impacts of potential selected climate policies on modeled regional air quality with respect to national pollution standards, human health and the sensitivity of health uncertainty ranges. To assess changes in air quality due to climate policy, we couple output from a regional computable general equilibrium economic model (the US Regional Energy Policy [USREP] model), with a regional air quality model (the Comprehensive Air Quality Model with Extensions [CAMx]). USREP uses economic variables to determine how potential future U.S. climate policy would change emissions of regional pollutants (CO, VOC, NOx, SO2, NH3, black carbon, and organic carbon) from ten emissions-heavy sectors of the economy (electricity, coal, gas, crude oil, refined oil, energy intensive industry, other industry, service, agriculture, and transportation [light duty and heavy duty]). Changes in emissions are then modeled using CAMx to determine the impact on air quality in several cities in the Northeast US. We first calculate the impact of climate policy by using regulatory procedures used to show attainment with National Ambient Air Quality Standards (NAAQS) for ozone and particulate matter. Building on previous work, we compare those results with the calculated results and uncertainties associated with human health impacts due to climate policy. This work addresses a potential disconnect between NAAQS regulatory procedures and the cost/benefit analysis required for and by the Clean Air Act.

On the dust load and rainfall relationship in South Asia: an analysis from CMIP5

NASA Astrophysics Data System (ADS)

Singh, Charu; Ganguly, Dilip; Dash, S. K.

2018-01-01

This study is aimed at examining the consistency of the relationship between load of dust and rainfall simulated by different climate models and its implication for the Indian summer monsoon system. Monthly mean outputs of 12 climate models, obtained from the archive of the Coupled Model Intercomparison Project phase 5 (CMIP5) for the period 1951-2004, are analyzed to investigate the relationship between dust and rainfall. Comparative analysis of the model simulated precipitation with the India Meteorological Department (IMD) gridded rainfall, CRU TS3.21 and GPCP version 2.2 data sets show significant differences between the spatial patterns of JJAS rainfall as well as annual cycle of rainfall simulated by various models and observations. Similarly, significant inter-model differences are also noted in the simulation of load of dust, nevertheless it is further noted that most of the CMIP5 models are able to capture the major dust sources across the study region. Although the scatter plot analysis and the lead-lag pattern correlation between the dust load and the rainfall show strong relationship between the dust load over distant sources and the rainfall in the South Asian region in individual models, the temporal scale of this association indicates large differences amongst the models. Our results caution that it would be pre-mature to draw any robust conclusions on the time scale of the relationship between dust and the rainfall in the South Asian region based on either CMIP5 results or limited number of previous studies. Hence, we would like to emphasize upon the fact that any conclusions drawn on the relationship between the dust load and the South Asian rainfall using model simulation is highly dependent on the degree of complexity incorporated in those models such as the representation of aerosol life cycle, their interaction with clouds, precipitation and other components of the climate system.

Passive-solar homes for Texas

NASA Astrophysics Data System (ADS)

Garrison, M. L.

1982-06-01

Acceptance of passive solar technologies has been slow within the conventional building trades in Texas because it is a common misconception that solar is expensive, and data on local applications is severely limited or nonexistent. It is the purpose of this solar development to move passive solar design into the mainstream of public acceptance by helping to overcome and eliminate these barriers. Specifically, the goal is to develop a set of regional climatic building standards to help guide the conventional building trade toward the utilization of soft energy systems which will reduce overall consumption at a price and convenience most Texans can afford. To meet this objective, eight sample passive design structures are presented. These designs represent state of the art regional applications of passive solar space conditioning. The methodology used in the passive solar design process included: analysis of regional climatic data; analysis of historical regional building prototypes; determination of regional climatic design priorities and assets; prototypical design models for the discretionary housing market; quantitative thermal analysis of prototypical designs; and construction drawings of building prototypes.

Depth resolved compositional analysis of aluminium oxide thin film using non-destructive soft x-ray reflectivity technique

NASA Astrophysics Data System (ADS)

Sinha, Mangalika; Modi, Mohammed H.

2017-10-01

In-depth compositional analysis of 240 Å thick aluminium oxide thin film has been carried out using soft x-ray reflectivity (SXR) and x-ray photoelectron spectroscopy technique (XPS). The compositional details of the film is estimated by modelling the optical index profile obtained from the SXR measurements over 60-200 Å wavelength region. The SXR measurements are carried out at Indus-1 reflectivity beamline. The method suggests that the principal film region is comprised of Al2O3 and AlOx (x = 1.6) phases whereas the interface region comprised of SiO2 and AlOx (x = 1.6) mixture. The soft x-ray reflectivity technique combined with XPS measurements explains the compositional details of principal layer. Since the interface region cannot be analyzed with the XPS technique in a non-destructive manner in such a case the SXR technique is a powerful tool for nondestructive compositional analysis of interface region.

Test-retest reliability of effective connectivity in the face perception network.

PubMed

Frässle, Stefan; Paulus, Frieder Michel; Krach, Sören; Jansen, Andreas

2016-02-01

Computational approaches have great potential for moving neuroscience toward mechanistic models of the functional integration among brain regions. Dynamic causal modeling (DCM) offers a promising framework for inferring the effective connectivity among brain regions and thus unraveling the neural mechanisms of both normal cognitive function and psychiatric disorders. While the benefit of such approaches depends heavily on their reliability, systematic analyses of the within-subject stability are rare. Here, we present a thorough investigation of the test-retest reliability of an fMRI paradigm for DCM analysis dedicated to unraveling intra- and interhemispheric integration among the core regions of the face perception network. First, we examined the reliability of face-specific BOLD activity in 25 healthy volunteers, who performed a face perception paradigm in two separate sessions. We found good to excellent reliability of BOLD activity within the DCM-relevant regions. Second, we assessed the stability of effective connectivity among these regions by analyzing the reliability of Bayesian model selection and model parameter estimation in DCM. Reliability was excellent for the negative free energy and good for model parameter estimation, when restricting the analysis to parameters with substantial effect sizes. Third, even when the experiment was shortened, reliability of BOLD activity and DCM results dropped only slightly as a function of the length of the experiment. This suggests that the face perception paradigm presented here provides reliable estimates for both conventional activation and effective connectivity measures. We conclude this paper with an outlook on potential clinical applications of the paradigm for studying psychiatric disorders. Hum Brain Mapp 37:730-744, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

A Stimulus-Locked Vector Autoregressive Model for Slow Event-Related fMRI Designs

PubMed Central

Siegle, Greg

2009-01-01

Summary Neuroscientists have become increasingly interested in exploring dynamic relationships among brain regions. Such a relationship, when directed from one region toward another, is denoted by “effective connectivity.” An fMRI experimental paradigm which is well-suited for examination of effective connectivity is the slow event-related design. This design presents stimuli at sufficient temporal spacing for determining within-trial trajectories of BOLD activation, allowing for the analysis of stimulus-locked temporal covariation of brain responses in multiple regions. This may be especially important for emotional stimuli processing, which can evolve over the course of several seconds, if not longer. However, while several methods have been devised for determining fMRI effective connectivity, few are adapted to event-related designs, which include non-stationary BOLD responses and multiple levels of nesting. We propose a model tailored for exploring effective connectivity of multiple brain regions in event-related fMRI designs - a semi-parametric adaptation of vector autoregressive (VAR) models, termed “stimulus-locked VAR” (SloVAR). Connectivity coefficients vary as a function of time relative to stimulus onset, are regularized via basis expansions, and vary randomly across subjects. SloVAR obtains flexible, data-driven estimates of effective connectivity and hence is useful for building connectivity models when prior information on dynamic regional relationships is sparse. Indices derived from the coefficient estimates can also be used to relate effective connectivity estimates to behavioral or clinical measures. We demonstrate the SloVAR model on a sample of clinically depressed and normal controls, showing that early but not late cortico-amygdala connectivity appears crucial to emotional control and early but not late cortico-cortico connectivity predicts depression severity in the depressed group, relationships that would have been missed in a more traditional VAR analysis. PMID:19236927

Analysis of events with b-jets and a pair of leptons of the same charge in pp collisions at √s = 8 TeV with the ATLAS detector

DOE PAGES

Aad, G.; Abbott, B.; Abdallah, J.; ...

2015-10-22

An analysis is presented of events containing jets including at least one b -tagged jet, sizeable missing transverse momentum, and at least two leptons including a pair of the same electric charge, with the scalar sum of the jet and lepton transverse momenta being large. A data sample with an integrated luminosity of 20.3 fb –1 of pp collisions at √s = 8 TeV recorded by the ATLAS detector at the Large Hadron Collider is used. Standard Model processes rarely produce these final states, but there are several models of physics beyond the Standard Model that predict an enhanced ratemore » of production of such events; the ones considered here are production of vector-like quarks, enhanced four-top-quark production, pair production of chiral b'-quarks, and production of two positively charged top quarks. Eleven signal regions are defined; subsets of these regions are combined when searching for each class of models. In the three signal regions primarily sensitive to positively charged top quark pair production, the data yield is consistent with the background expectation. There are more data events than expected from background in the set of eight signal regions defined for searching for vector-like quarks and chiral b'-quarks, but the significance of the discrepancy is less than two standard deviations. Furthermore, the discrepancy reaches 2.5 standard deviations in the set of five signal regions defined for searching for four-top-quark production. The results are used to set 95% CL limits on various models.« less

Influence of different abutment diameter of implants on the peri-implant stress in the crestal bone: A three-dimensional finite element analysis--In vitro study.

PubMed

Aradya, Anupama; Kumar, U Krishna; Chowdhary, Ramesh

2016-01-01

The study was designed to evaluate and compare stress distribution in transcortical section of bone with normal abutment and platform switched abutment under vertical and oblique forces in posterior mandible region. A three-dimensional finite element model was designed using ANSYS 13.0 software. The type of bone selection for the model was made of type II mandibular bone, having cortical bone thickness ranging from 0.595 mm to 1.515 mm with the crestal region measuring 1.5 mm surrounding dense trabecular bone. The implant will be modulated at 5 mm restorative platform and tapering down to 4.5 mm wide at the threads, 13 mm long with an abutment 3 mm in height. The models will be designed for two situations: (1) An implant with a 5 mm diameter abutment representing a standard platform in the posterior mandible region. (2) An implant with a 4.5 mm diameter abutment representing platform switching in the posterior mandible region. Force application was performed in both oblique and vertical conditions using 100 N as a representative masticatory force. For oblique loading, a force of 100 N was applied at 15° from the vertical axis. von Mises stress analysis was evaluated. The results of the study showed cortical stress in the conventional and platform switching model under oblique forces were 59.329 MPa and 39.952 MPa, respectively. Cortical stress in the conventional and platform switching model under vertical forces was 13.914 MPa and 12.793 MPa, respectively. Results from this study showed the platform switched abutment led to relative decrease in von Mises stress in transcortical section of bone compared to normal abutment under vertical and oblique forces in posterior mandible region.

Multi-Factor Impact Analysis of Agricultural Production in Bangladesh with Climate Change

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; Major, David C.; Yu, Winston H.; Alam, Mozaharul; Hussain, Sk. Ghulam; Khan, Abu Saleh; Hassan, Ahmadul; Al Hossain, Bhuiya Md. Tamim; Goldberg, Richard; Horton, Radley M.;

Multivariate functional response regression, with application to fluorescence spectroscopy in a cervical pre-cancer study.

PubMed

Zhu, Hongxiao; Morris, Jeffrey S; Wei, Fengrong; Cox, Dennis D

2017-07-01

Many scientific studies measure different types of high-dimensional signals or images from the same subject, producing multivariate functional data. These functional measurements carry different types of information about the scientific process, and a joint analysis that integrates information across them may provide new insights into the underlying mechanism for the phenomenon under study. Motivated by fluorescence spectroscopy data in a cervical pre-cancer study, a multivariate functional response regression model is proposed, which treats multivariate functional observations as responses and a common set of covariates as predictors. This novel modeling framework simultaneously accounts for correlations between functional variables and potential multi-level structures in data that are induced by experimental design. The model is fitted by performing a two-stage linear transformation-a basis expansion to each functional variable followed by principal component analysis for the concatenated basis coefficients. This transformation effectively reduces the intra-and inter-function correlations and facilitates fast and convenient calculation. A fully Bayesian approach is adopted to sample the model parameters in the transformed space, and posterior inference is performed after inverse-transforming the regression coefficients back to the original data domain. The proposed approach produces functional tests that flag local regions on the functional effects, while controlling the overall experiment-wise error rate or false discovery rate. It also enables functional discriminant analysis through posterior predictive calculation. Analysis of the fluorescence spectroscopy data reveals local regions with differential expressions across the pre-cancer and normal samples. These regions may serve as biomarkers for prognosis and disease assessment.

Multi-Parametric MRI and Texture Analysis to Visualize Spatial Histologic Heterogeneity and Tumor Extent in Glioblastoma.

PubMed

Hu, Leland S; Ning, Shuluo; Eschbacher, Jennifer M; Gaw, Nathan; Dueck, Amylou C; Smith, Kris A; Nakaji, Peter; Plasencia, Jonathan; Ranjbar, Sara; Price, Stephen J; Tran, Nhan; Loftus, Joseph; Jenkins, Robert; O'Neill, Brian P; Elmquist, William; Baxter, Leslie C; Gao, Fei; Frakes, David; Karis, John P; Zwart, Christine; Swanson, Kristin R; Sarkaria, Jann; Wu, Teresa; Mitchell, J Ross; Li, Jing

2015-01-01

Genetic profiling represents the future of neuro-oncology but suffers from inadequate biopsies in heterogeneous tumors like Glioblastoma (GBM). Contrast-enhanced MRI (CE-MRI) targets enhancing core (ENH) but yields adequate tumor in only ~60% of cases. Further, CE-MRI poorly localizes infiltrative tumor within surrounding non-enhancing parenchyma, or brain-around-tumor (BAT), despite the importance of characterizing this tumor segment, which universally recurs. In this study, we use multiple texture analysis and machine learning (ML) algorithms to analyze multi-parametric MRI, and produce new images indicating tumor-rich targets in GBM. We recruited primary GBM patients undergoing image-guided biopsies and acquired pre-operative MRI: CE-MRI, Dynamic-Susceptibility-weighted-Contrast-enhanced-MRI, and Diffusion Tensor Imaging. Following image coregistration and region of interest placement at biopsy locations, we compared MRI metrics and regional texture with histologic diagnoses of high- vs low-tumor content (≥80% vs <80% tumor nuclei) for corresponding samples. In a training set, we used three texture analysis algorithms and three ML methods to identify MRI-texture features that optimized model accuracy to distinguish tumor content. We confirmed model accuracy in a separate validation set. We collected 82 biopsies from 18 GBMs throughout ENH and BAT. The MRI-based model achieved 85% cross-validated accuracy to diagnose high- vs low-tumor in the training set (60 biopsies, 11 patients). The model achieved 81.8% accuracy in the validation set (22 biopsies, 7 patients). Multi-parametric MRI and texture analysis can help characterize and visualize GBM's spatial histologic heterogeneity to identify regional tumor-rich biopsy targets.

A recent deep earthquake doublet in light of long-term evolution of Nazca subduction

NASA Astrophysics Data System (ADS)

Zahradník, J.; Čížková, H.; Bina, C. R.; Sokos, E.; Janský, J.; Tavera, H.; Carvalho, J.

2017-03-01

Earthquake faulting at ~600 km depth remains puzzling. Here we present a new kinematic interpretation of two Mw7.6 earthquakes of November 24, 2015. In contrast to teleseismic analysis of this doublet, we use regional seismic data providing robust two-point source models, further validated by regional back-projection and rupture-stop analysis. The doublet represents segmented rupture of a ˜30-year gap in a narrow, deep fault zone, fully consistent with the stress field derived from neighbouring 1976-2015 earthquakes. Seismic observations are interpreted using a geodynamic model of regional subduction, incorporating realistic rheology and major phase transitions, yielding a model slab that is nearly vertical in the deep-earthquake zone but stagnant below 660 km, consistent with tomographic imaging. Geodynamically modelled stresses match the seismically inferred stress field, where the steeply down-dip orientation of compressive stress axes at ˜600 km arises from combined viscous and buoyant forces resisting slab penetration into the lower mantle and deformation associated with slab buckling and stagnation. Observed fault-rupture geometry, demonstrated likelihood of seismic triggering, and high model temperatures in young subducted lithosphere, together favour nanometric crystallisation (and associated grain-boundary sliding) attending high-pressure dehydration as a likely seismogenic mechanism, unless a segment of much older lithosphere is present at depth.

Shock-capturing parabolized Navier-Stokes model /SCIPVIS/ for the analysis of turbulent underexpanded jets

NASA Technical Reports Server (NTRS)

Dash, S. M.; Wolf, D. E.

1983-01-01

A new computational model, SCIPVIS, has been developed to predict the multiple-cell wave/shock structure in under or over-expanded turbulent jets. SCIPVIS solves the parabolized Navier-Stokes jet mixing equations utilizing a shock-capturing approach in supersonic regions of the jet and a pressure-split approach in subsonic regions. Turbulence processes are represented by the solution of compressibility corrected two-equation turbulence models. The formation of Mach discs in the jet and the interactive turbulent mixing process occurring behind the disc are handled in a detailed fashion. SCIPVIS presently analyzes jets exhausting into a quiescent or supersonic external stream for which a single-pass spatial marching solution can be obtained. The iterative coupling of SCIPVIS with a potential flow solver for the analysis of subsonic/transonic external streams is under development.

Analysis and Operational Feasibility of Potable Water Production

DTIC Science & Technology

2015-09-01

III. MODELING, SIMULATION, AND TEST RESULTS ANALYSIS ..............27 A. INTRODUCTION...Regions of Study ......................57 Table 10. Drinking Water Tests ...chemicals, and coliform bacteria. Testing of the condensed water is important to ensure potability, as common tests have been conducted to ensure

Winter precipitation forecast in the European and Mediterranean regions using cluster analysis

NASA Astrophysics Data System (ADS)

Molnos, S.

2017-12-01

The European and Mediterranean climates are sensitive to large-scale circulation of the atmosphere andocean making it difficult to forecast precipitation or temperature on seasonal time-scales. In addition, theMediterranean region has been identified as a hotspot for climate change and already today a drying in theMediterranean region is observed.Thus, it is critically important to predict seasonal droughts as early as possible such that water managersand stakeholders can mitigate impacts.We developed a novel cluster-based forecast method to empirically predict winter's precipitationanomalies in European and Mediterranean regions using precursors in autumn. This approach does notonly utilizes the amplitude but also the pattern of the precursors in generating the forecast.Using a toy model we show that it achieves a better forecast skill than more traditional regression models. Furthermore, we compare our algorithm with dynamic forecast models demonstrating that our prediction method performs better in terms of time and pattern correlation in the Mediterranean and European regions.

Modeling spatial invasion of Ebola in West Africa.

PubMed

D'Silva, Jeremy P; Eisenberg, Marisa C

2017-09-07

The 2014-2016 Ebola Virus Disease (EVD) epidemic in West Africa was the largest ever recorded, representing a fundamental shift in Ebola epidemiology with unprecedented spatiotemporal complexity. To understand the spatiotemporal dynamics of EVD in West Africa, we developed spatial transmission models using a gravity-model framework at both the national and district-level scales, which we used to compare effectiveness of local interventions (e.g. local quarantine) and long-range interventions (e.g. border-closures). The country-level gravity model captures the epidemic data, including multiple waves of initial epidemic growth observed in Guinea. We found that local-transmission reductions were most effective in Liberia, while long-range transmission was dominant in Sierra Leone. Both models illustrated that interventions in one region result in an amplified protective effect on other regions by preventing spatial transmission. In the district-level model, interventions in the strongest of these amplifying regions reduced total cases in all three countries by over 20%, in spite of the region itself generating only ∼0.1% of total cases. This model structure and associated intervention analysis provide information that can be used by public health policymakers to assist planning and response efforts for future epidemics. Copyright © 2017 Elsevier Ltd. All rights reserved.

Model Data Interoperability for the United States Integrated Ocean Observing System (IOOS)

NASA Astrophysics Data System (ADS)

Signell, Richard P.

2010-05-01

Model data interoperability for the United States Integrated Ocean Observing System (IOOS) was initiated with a focused one year project. The problem was that there were many regional and national providers of oceanographic model data; each had unique file conventions, distribution techniques and analysis tools that made it difficult to compare model results and observational data. To solve this problem, a distributed system was built utilizing a customized middleware layer and a common data model. This allowed each model data provider to keep their existing model and data files unchanged, yet deliver model data via web services in a common form. With standards-based applications that used these web services, end users then had a common way to access data from any of the models. These applications included: (1) a 2D mapping and animation using a web browser application, (2) an advanced 3D visualization and animation using a desktop application, and (3) a toolkit for a common scientific analysis environment. Due to the flexibility and low impact of the approach on providers, rapid progress was made. The system was implemented in all eleven US IOOS regions and at the NOAA National Coastal Data Development Center, allowing common delivery of regional and national oceanographic model forecast and archived results that cover all US waters. The system, based heavily on software technology from the NSF-sponsored Unidata Program Center, is applicable to any structured gridded data, not just oceanographic model data. There is a clear pathway to expand the system to include unstructured grid (e.g. triangular grid) data.

Empirical Storm-Time Correction to the International Reference Ionosphere Model E-Region Electron and Ion Density Parameterizations Using Observations from TIMED/SABER

NASA Technical Reports Server (NTRS)

Mertens, Christoper J.; Winick, Jeremy R.; Russell, James M., III; Mlynczak, Martin G.; Evans, David S.; Bilitza, Dieter; Xu, Xiaojing

2007-01-01

The response of the ionospheric E-region to solar-geomagnetic storms can be characterized using observations of infrared 4.3 micrometers emission. In particular, we utilize nighttime TIMED/SABER measurements of broadband 4.3 micrometers limb emission and derive a new data product, the NO+(v) volume emission rate, which is our primary observation-based quantity for developing an empirical storm-time correction the IRI E-region electron density. In this paper we describe our E-region proxy and outline our strategy for developing the empirical storm model. In our initial studies, we analyzed a six day storm period during the Halloween 2003 event. The results of this analysis are promising and suggest that the ap-index is a viable candidate to use as a magnetic driver for our model.

Analysis of regional total factor energy efficiency in China under environmental constraints: based on undesirable-minds and DEA window model

NASA Astrophysics Data System (ADS)

Zhang, Shuying; Li, Deshan; Li, Shuangqiang; Jiang, Hanyu; Shen, Yuqing

2017-06-01

With China’s entrance into the new economy, the improvement of energy efficiency has become an important indicator to measure the quality of ecological civilization construction and economic development. According to the panel data of Chinese regions in 1996-2014, the nearest distance to the efficient frontier of Undesirable-MinDS Xeon model and DEA window model have been used to calculate the total factor energy efficiency of China’s regions. Study found that: Under environmental constraints, China’s total factor energy efficiency has increased after the first drop in the overall 1996-2014, and then increases again. And the difference between the regions is very large, showing a characteristic of “the east is the highest, the west is lower, and lowest is in the central” finally, this paper puts forward relevant policy suggestions.

Contextual Compression of Large-Scale Wind Turbine Array Simulations: Preprint

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

Gruchalla, Kenny M; Brunhart-Lupo, Nicholas J; Potter, Kristin C

Data sizes are becoming a critical issue particularly for HPC applications. We have developed a user-driven lossy wavelet-based storage model to facilitate the analysis and visualization of large-scale wind turbine array simulations. The model stores data as heterogeneous blocks of wavelet coefficients, providing high-fidelity access to user-defined data regions believed the most salient, while providing lower-fidelity access to less salient regions on a block-by-block basis. In practice, by retaining the wavelet coefficients as a function of feature saliency, we have seen data reductions in excess of 94 percent, while retaining lossless information in the turbine-wake regions most critical to analysismore » and providing enough (low-fidelity) contextual information in the upper atmosphere to track incoming coherent turbulent structures. Our contextual wavelet compression approach has allowed us to deliver interactive visual analysis while providing the user control over where data loss, and thus reduction in accuracy, in the analysis occurs. We argue this reduced but contexualized representation is a valid approach and encourages contextual data management.« less

Contextual Compression of Large-Scale Wind Turbine Array Simulations

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

Gruchalla, Kenny M; Brunhart-Lupo, Nicholas J; Potter, Kristin C

Data sizes are becoming a critical issue particularly for HPC applications. We have developed a user-driven lossy wavelet-based storage model to facilitate the analysis and visualization of large-scale wind turbine array simulations. The model stores data as heterogeneous blocks of wavelet coefficients, providing high-fidelity access to user-defined data regions believed the most salient, while providing lower-fidelity access to less salient regions on a block-by-block basis. In practice, by retaining the wavelet coefficients as a function of feature saliency, we have seen data reductions in excess of 94 percent, while retaining lossless information in the turbine-wake regions most critical to analysismore » and providing enough (low-fidelity) contextual information in the upper atmosphere to track incoming coherent turbulent structures. Our contextual wavelet compression approach has allowed us to deliver interative visual analysis while providing the user control over where data loss, and thus reduction in accuracy, in the analysis occurs. We argue this reduced but contextualized representation is a valid approach and encourages contextual data management.« less

Fused cerebral organoids model interactions between brain regions.

PubMed

Bagley, Joshua A; Reumann, Daniel; Bian, Shan; Lévi-Strauss, Julie; Knoblich, Juergen A

2017-07-01

Human brain development involves complex interactions between different regions, including long-distance neuronal migration or formation of major axonal tracts. Different brain regions can be cultured in vitro within 3D cerebral organoids, but the random arrangement of regional identities limits the reliable analysis of complex phenotypes. Here, we describe a coculture method combining brain regions of choice within one organoid tissue. By fusing organoids of dorsal and ventral forebrain identities, we generate a dorsal-ventral axis. Using fluorescent reporters, we demonstrate CXCR4-dependent GABAergic interneuron migration from ventral to dorsal forebrain and describe methodology for time-lapse imaging of human interneuron migration. Our results demonstrate that cerebral organoid fusion cultures can model complex interactions between different brain regions. Combined with reprogramming technology, fusions should offer researchers the possibility to analyze complex neurodevelopmental defects using cells from neurological disease patients and to test potential therapeutic compounds.

Development of a Novel Rabies Simulation Model for Application in a Non-endemic Environment

PubMed Central

Dürr, Salome; Ward, Michael P.

2015-01-01

Domestic dog rabies is an endemic disease in large parts of the developing world and also epidemic in previously free regions. For example, it continues to spread in eastern Indonesia and currently threatens adjacent rabies-free regions with high densities of free-roaming dogs, including remote northern Australia. Mathematical and simulation disease models are useful tools to provide insights on the most effective control strategies and to inform policy decisions. Existing rabies models typically focus on long-term control programs in endemic countries. However, simulation models describing the dog rabies incursion scenario in regions where rabies is still exotic are lacking. We here describe such a stochastic, spatially explicit rabies simulation model that is based on individual dog information collected in two remote regions in northern Australia. Illustrative simulations produced plausible results with epidemic characteristics expected for rabies outbreaks in disease free regions (mean R0 1.7, epidemic peak 97 days post-incursion, vaccination as the most effective response strategy). Systematic sensitivity analysis identified that model outcomes were most sensitive to seven of the 30 model parameters tested. This model is suitable for exploring rabies spread and control before an incursion in populations of largely free-roaming dogs that live close together with their owners. It can be used for ad-hoc contingency or response planning prior to and shortly after incursion of dog rabies in previously free regions. One challenge that remains is model parameterisation, particularly how dogs’ roaming and contacts and biting behaviours change following a rabies incursion in a previously rabies free population. PMID:26114762

Exploration of OMI Products for Air Quality Applications Through Comparisons with Models and Observations

NASA Technical Reports Server (NTRS)

Pickering, K. E.; Ziemke, J.; Bucsela, E.; Gleason, J.; Marufu, L.; Dickerson, R.; Mathur, R.; Davidson, P.; Duncan, B.; Bhartia, P. K.

2006-01-01

The Ozone Monitoring Instrument (OMI) on board NASA s Aura satellite was launched in July 2004, and is now providing daily global observations of total column ozone, NO2, and SO2, as well as aerosol information. Algorithms have also been developed to produce daily tropospheric ozone and NO2 products. The tropospheric ozone product reported here is a tropospheric residual computed through use of Aura Microwave Limb Sounder (MLS) ozone profile data to quantify stratospheric ozone. We are investigating the applicability of OMI products for use in air quality modeling, forecasting, and analysis. These investigations include comparison of the OMI tropospheric O3 and NO2 products with global and regional models and with lower tropospheric aircraft observations. Large-scale transport of pollution seen in the OM1 tropospheric O3 data is compared with output from NASA's Global Modeling Initiative global chemistry and transport model. On the regional scale we compare the OMI tropospheric O3 and NO2 with fields from the National Oceanic and Atmospheric Administration and Environmental Protection Agency (NOAA/EPA) operational Eta/CMAQ air quality forecasting model over the eastern United States. This 12-km horizontal resolution model output is roughly of equivalent resolution to the OMI pixel data. Correlation analysis between lower tropospheric aircraft O3 profile data taken by the University of Maryland over the Mid-Atlantic States and OMI tropospheric column mean volume mixing ratio for O3 will be presented. These aircraft data are representative of the lowest 3 kilometers of the atmosphere, the region in which much of the locally-generated and regionally-transported ozone exists.

Quantification of uncertainties related to the regional application of a conceptual hydrological model in Benin (West Africa)

NASA Astrophysics Data System (ADS)

Bormann, H.; Diekkrüger, B.

2003-04-01

A conceptual model is presented to simulate the water fluxes of regional catchments in Benin (West Africa). The model is applied in the framework of the IMPETUS project (an integrated approach to the efficient management of scarce water resources in West Africa) which aims to assess the effects of environmental and anthropogenic changes on the regional hydrological processes and on the water availability in Benin. In order to assess the effects of decreasing precipitation and increasing human activities on the hydrological processes in the upper Ouémé valley, a scenario analysis is performed to predict possible changes. Therefore a regional hydrological model is proposed which reproduces the recent hydrological processes, and which is able to consider the changes of landscape properties.The study presented aims to check the validity of the conceptual and lumped model under the conditions of the subhumid tree savannah and therefore analyses the importance of possible sources of uncertainty. Main focus is set on the uncertainties caused by input data, model parameters and model structure. As the model simulates the water fluxes at the catchment outlet of the Térou river (3133 km2) in a sufficient quality, first results of a scenario analysis are presented. Changes of interest are the expected future decrease in amount and temporal structure of the precipitation (e.g. minus X percent precipitation during the whole season versus minus X percent precipitation in the end of the rainy season, alternatively), the decrease in soil water storage capacity which is caused by erosion, and the increasing consumption of ground water for drinking water and agricultural purposes. Resuming from the results obtained, the perspectives of lumped and conceptual models are discussed with special regard to available management options of this kind of models. Advantages and disadvantages compared to alternative model approaches (process based, physics based) are discussed.

A Dynamic Coupled Magnetosphere-Ionosphere-Ring Current Model

NASA Astrophysics Data System (ADS)

Pembroke, Asher

In this thesis we describe a coupled model of Earth's magnetosphere that consists of the Lyon-Fedder-Mobarry (LFM) global magnetohydrodynamics (MHD) simulation, the MIX ionosphere solver and the Rice Convection Model (RCM). We report some results of the coupled model using idealized inputs and model parameters. The algorithmic and physical components of the model are described, including the transfer of magnetic field information and plasma boundary conditions to the RCM and the return of ring current plasma properties to the LFM. Crucial aspects of the coupling include the restriction of RCM to regions where field-line averaged plasma-beta ¡=1, the use of a plasmasphere model, and the MIX ionosphere model. Compared to stand-alone MHD, the coupled model produces a substantial increase in ring current pressure and reduction of the magnetic field near the Earth. In the ionosphere, stronger region-1 and region-2 Birkeland currents are seen in the coupled model but with no significant change in the cross polar cap potential drop, while the region-2 currents shielded the low-latitude convection potential. In addition, oscillations in the magnetic field are produced at geosynchronous orbit with the coupled code. The diagnostics of entropy and mass content indicate that these oscillations are associated with low-entropy flow channels moving in from the tail and may be related to bursty bulk flows and bubbles seen in observations. As with most complex numerical models, there is the ongoing challenge of untangling numerical artifacts and physics, and we find that while there is still much room for improvement, the results presented here are encouraging. Finally, we introduce several new methods for magnetospheric visualization and analysis, including a fluid-spatial volume for RCM and a field-aligned analysis mesh for the LFM. The latter allows us to construct novel visualizations of flux tubes, drift surfaces, topological boundaries, and bursty-bulk flows.

Extension of RCC Topological Relations for 3d Complex Objects Components Extracted from 3d LIDAR Point Clouds

NASA Astrophysics Data System (ADS)

Xing, Xu-Feng; Abolfazl Mostafavia, Mir; Wang, Chen

2016-06-01

Topological relations are fundamental for qualitative description, querying and analysis of a 3D scene. Although topological relations for 2D objects have been extensively studied and implemented in GIS applications, their direct extension to 3D is very challenging and they cannot be directly applied to represent relations between components of complex 3D objects represented by 3D B-Rep models in R3. Herein we present an extended Region Connection Calculus (RCC) model to express and formalize topological relations between planar regions for creating 3D model represented by Boundary Representation model in R3. We proposed a new dimension extended 9-Intersection model to represent the basic relations among components of a complex object, including disjoint, meet and intersect. The last element in 3*3 matrix records the details of connection through the common parts of two regions and the intersecting line of two planes. Additionally, this model can deal with the case of planar regions with holes. Finally, the geometric information is transformed into a list of strings consisting of topological relations between two planar regions and detailed connection information. The experiments show that the proposed approach helps to identify topological relations of planar segments of point cloud automatically.

Regiones Extendidas de gas ionizado en radiogalaxias FR II. Estudio espectroscópico y cinemático.

NASA Astrophysics Data System (ADS)

Reynaldi, V.; Feinstein, C.

The EELR are regions of highly-excited ionized gas that extend throughout the outskirts of their host galaxies. Concerning FR II radio galaxies, alignment between optical and radio structures were found for several sources. We investigate the ionizing mechanisms of these regions through long-slit spectroscopic analysis. Photoionization models, where both the AGN and a mixed intergalactic medium may explain the ionization state of the regions are studied. But also the shock-ionization model is tested since it can provide a local budget of ionizing photons created by expanding radiative shock waves driven by the radio jet. Throughout this work we discuss spectroscopic and kinematical results obtained with GMOS/Gemini. FULL TEXT IN SPANISH

Development of the NHM-LETKF regional reanalysis system assimilating conventional observations only

NASA Astrophysics Data System (ADS)

Fukui, S.; Iwasaki, T.; Saito, K. K.; Seko, H.; Kunii, M.

2016-12-01

The information about long-term high-resolution atmospheric fields is very useful for studying meso-scale responses to climate change or analyzing extreme events. We are developing a NHM-LETKF (the local ensemble transform Kalman filter with the nonhydrostatic model of the Japan Meteorological Agency (JMA)) regional reanalysis system assimilating only conventional observations that are available over about 60 years such as surface observations at observatories and upper air observations with radiosondes. The domain covers Japan and its surroundings. Before the long-term reanalysis is performed, an experiment using the system was conducted over August in 2014 in order to identify effectiveness and problems of the regional reanalysis system. In this study, we investigated the six-hour accumulated precipitations obtained by integration from the analysis fields. The reproduced precipitation was compared with the JMA's Radar/Rain-gauge Analyzed Precipitation data over Japan islands and the precipitation of JRA-55, which is used as lateral boundary conditions. The comparisons reveal the underestimation of the precipitation in the regional reanalysis. The underestimation is improved by extending the forecast time. In the regional reanalysis system, the analysis fields are derived using the ensemble mean fields, where the conflicting components among ensemble members are filtered out. Therefore, it is important to tune the inflation factor and lateral boundary perturbations not to smooth the analysis fields excessively and to consider more time to spin-up the fields. In the extended run, the underestimation still remains. This implies that the underestimation is attributed to the forecast model itself as well as the analysis scheme.

Radiogenomics to characterize regional genetic heterogeneity in glioblastoma

PubMed Central

Hu, Leland S.; Ning, Shuluo; Eschbacher, Jennifer M.; Baxter, Leslie C.; Gaw, Nathan; Ranjbar, Sara; Plasencia, Jonathan; Dueck, Amylou C.; Peng, Sen; Smith, Kris A.; Nakaji, Peter; Karis, John P.; Quarles, C. Chad; Wu, Teresa; Loftus, Joseph C.; Jenkins, Robert B.; Sicotte, Hugues; Kollmeyer, Thomas M.; O'Neill, Brian P.; Elmquist, William; Hoxworth, Joseph M.; Frakes, David; Sarkaria, Jann; Swanson, Kristin R.; Tran, Nhan L.; Li, Jing; Mitchell, J. Ross

2017-01-01

Background Glioblastoma (GBM) exhibits profound intratumoral genetic heterogeneity. Each tumor comprises multiple genetically distinct clonal populations with different therapeutic sensitivities. This has implications for targeted therapy and genetically informed paradigms. Contrast-enhanced (CE)-MRI and conventional sampling techniques have failed to resolve this heterogeneity, particularly for nonenhancing tumor populations. This study explores the feasibility of using multiparametric MRI and texture analysis to characterize regional genetic heterogeneity throughout MRI-enhancing and nonenhancing tumor segments. Methods We collected multiple image-guided biopsies from primary GBM patients throughout regions of enhancement (ENH) and nonenhancing parenchyma (so called brain-around-tumor, [BAT]). For each biopsy, we analyzed DNA copy number variants for core GBM driver genes reported by The Cancer Genome Atlas. We co-registered biopsy locations with MRI and texture maps to correlate regional genetic status with spatially matched imaging measurements. We also built multivariate predictive decision-tree models for each GBM driver gene and validated accuracies using leave-one-out-cross-validation (LOOCV). Results We collected 48 biopsies (13 tumors) and identified significant imaging correlations (univariate analysis) for 6 driver genes: EGFR, PDGFRA, PTEN, CDKN2A, RB1, and TP53. Predictive model accuracies (on LOOCV) varied by driver gene of interest. Highest accuracies were observed for PDGFRA (77.1%), EGFR (75%), CDKN2A (87.5%), and RB1 (87.5%), while lowest accuracy was observed in TP53 (37.5%). Models for 4 driver genes (EGFR, RB1, CDKN2A, and PTEN) showed higher accuracy in BAT samples (n = 16) compared with those from ENH segments (n = 32). Conclusion MRI and texture analysis can help characterize regional genetic heterogeneity, which offers potential diagnostic value under the paradigm of individualized oncology. PMID:27502248

Gradient Analysis and Classification of Carolina Bay Vegetation: A Framework for Bay Wetlands Conservation and Restoration

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

Diane De Steven,Ph.D.; Maureen Tone,PhD.

1997-10-01

This report address four project objectives: (1) Gradient model of Carolina bay vegetation on the SRS--The authors use ordination analyses to identify environmental and landscape factors that are correlated with vegetation composition. Significant factors can provide a framework for site-based conservation of existing diversity, and they may also be useful site predictors for potential vegetation in bay restorations. (2) Regional analysis of Carolina bay vegetation diversity--They expand the ordination analyses to assess the degree to which SRS bays encompass the range of vegetation diversity found in the regional landscape of South Carolina's western Upper Coastal Plain. Such comparisons can indicatemore » floristic status relative to regional potentials and identify missing species or community elements that might be re-introduced or restored. (3) Classification of vegetation communities in Upper Coastal Plain bays--They use cluster analysis to identify plant community-types at the regional scale, and explore how this classification may be functional with respect to significant environmental and landscape factors. An environmentally-based classification at the whole-bay level can provide a system of templates for managing bays as individual units and for restoring bays to desired plant communities. (4) Qualitative model for bay vegetation dynamics--They analyze present-day vegetation in relation to historic land uses and disturbances. The distinctive history of SRS bays provides the possibility of assessing pathways of post-disturbance succession. They attempt to develop a coarse-scale model of vegetation shifts in response to changing site factors; such qualitative models can provide a basis for suggesting management interventions that may be needed to maintain desired vegetation in protected or restored bays.« less

Evaluation of the diagnostic potential of ex vivo Raman spectroscopy in gastric cancers: fingerprint versus high wavenumber

NASA Astrophysics Data System (ADS)

Zhou, Xueqian; Dai, Jianhua; Chen, Yao; Duan, Guangjie; Liu, Yulong; Zhang, Hua; Wu, Hongbo; Peng, Guiyong

2016-10-01

The aim of this study was to apply Raman spectroscopy in the high wavenumber (HW) region (2800 to 3000 cm-1) for ex vivo detection of gastric cancer and compare its diagnostic potential with that of the fingerprint (FP) region (800 to 1800 cm-1). Raman spectra were collected in the FP and HW regions to differentiate between normal mucosa (n=38) and gastric cancer (n=37). The distinctive Raman spectral differences between normal and cancer tissues are observed at 853, 879, 1157, 1319, 1338, 1448, and 2932 cm-1 and are primarily related to proteins, lipids, nucleic acids, collagen, and carotenoids in the tissue. In FP and HW Raman spectroscopy for diagnosis of gastric cancer, multivariate diagnostic algorithms based on partial-least-squares discriminant analysis, together with leave-one-sample-out cross validation, yielded diagnostic sensitivities of 94.59% and 81.08%, and specificities of 86.84% and 71.05%, respectively. Receiver operating characteristic analysis further confirmed that the FP region model performance is superior to that of the HW region model. Better differentiation between normal and gastric cancer tissues can be achieved using FP Raman spectroscopy and PLS-DA techniques, but the complementary natures of the FP and HW regions make both of them useful in diagnosis of gastric cancer.

Implications of the Fermi-LAT Pass 8 Galactic Center excess on supersymmetric dark matter

NASA Astrophysics Data System (ADS)

Achterberg, Abraham; van Beekveld, Melissa; Caron, Sascha; Gómez-Vargas, Germán A.; Hendriks, Luc; Ruiz de Austri, Roberto

2017-12-01

The Fermi Collaboration has recently updated their analysis of gamma rays from the center of the Galaxy. They reconfirm the presence of an unexplained emission feature which is most prominent in the region of 1–10 GeV, known as the Galactic Center GeV excess (GCE). Although the GCE is now firmly detected, an interpretation of this emission as a signal of self-annihilating dark matter (DM) particles is not unambiguously possible due to systematic effects in the gamma-ray modeling estimated in the Galactic Plane. In this paper we build a covariance matrix, collecting different systematic uncertainties investigated in the Fermi Collaboration's paper that affect the GCE spectrum. We show that models where part of the GCE is due to annihilating DM is still consistent with the new data. We also re-evaluate the parameter space regions of the minimal supersymmetric Standard Model (MSSM) that can contribute dominantly to the GCE via neutralino DM annihilation. All recent constraints from DM direct detection experiments such as PICO, LUX, PandaX and Xenon1T, limits on the annihilation cross section from dwarf spheroidal galaxies and the Large Hadron Collider limits are considered in this analysis. Due to a slight shift in the energy spectrum of the GC excess with respect to the previous Fermi analysis, and the recent limits from direct detection experiments, we find a slightly shifted parameter region of the MSSM, compared to our previous analysis, that is consistent with the GCE. Neutralinos with a mass between 85–220 GeV can describe the excess via annihilation into a pair of W-bosons or top quarks. Remarkably, there are models with low fine-tuning among the regions that we have found. The complete set of solutions will be probed by upcoming direct detection experiments and with dedicated searches in the upcoming data of the Large Hadron Collider.

Estimating raw material equivalents on a macro-level: comparison of multi-regional input-output analysis and hybrid LCI-IO.

PubMed

Schoer, Karl; Wood, Richard; Arto, Iñaki; Weinzettel, Jan

2013-12-17

The mass of material consumed by a population has become a useful proxy for measuring environmental pressure. The "raw material equivalents" (RME) metric of material consumption addresses the issue of including the full supply chain (including imports) when calculating national or product level material impacts. The RME calculation suffers from data availability, however, as quantitative data on production practices along the full supply chain (in different regions) is required. Hence, the RME is currently being estimated by three main approaches: (1) assuming domestic technology in foreign economies, (2) utilizing region-specific life-cycle inventories (in a hybrid framework), and (3) utilizing multi-regional input-output (MRIO) analysis to explicitly cover all regions of the supply chain. While the first approach has been shown to give inaccurate results, this paper focuses on the benefits and costs of the latter two approaches. We analyze results from two key (MRIO and hybrid) projects modeling raw material equivalents, adjusting the models in a stepwise manner in order to quantify the effects of individual conceptual elements. We attempt to isolate the MRIO gap, which denotes the quantitative impact of calculating the RME of imports by an MRIO approach instead of the hybrid model, focusing on the RME of EU external trade imports. While, the models give quantitatively similar results, differences become more pronounced when tracking more detailed material flows. We assess the advantages and disadvantages of the two approaches and look forward to ways to further harmonize data and approaches.

Global water cycle

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.; Christy, John R.; Goodman, Steven J.; Miller, Tim L.; Fitzjarrald, Dan; Lapenta, Bill; Wang, Shouping

1991-01-01

The primary objective is to determine the scope and interactions of the global water cycle with all components of the Earth system and to understand how it stimulates and regulates changes on both global and regional scales. The following subject areas are covered: (1) water vapor variability; (2) multi-phase water analysis; (3) diabatic heating; (4) MSU (Microwave Sounding Unit) temperature analysis; (5) Optimal precipitation and streamflow analysis; (6) CCM (Community Climate Model) hydrological cycle; (7) CCM1 climate sensitivity to lower boundary forcing; and (8) mesoscale modeling of atmosphere/surface interaction.

Multi-Model Ensemble Approaches to Data Assimilation Using the 4D-Local Ensemble Transform Kalman Filter

DTIC Science & Technology

2013-09-30

accuracy of the analysis . Root mean square difference ( RMSD ) is much smaller for RIP than for either Simple Ocean Data Assimilation or Incremental... Analysis Update globally for temperature as well as salinity. Regionally the same results were found, with only one exception in which the salinity RMSD ...short-term forecast using a numerical model with the observations taken within the forecast time window. The resulting state is the so-called “ analysis

Impacts of Megacities on Regional Air Quality from MOPITT Observations and MOZART Model Results

NASA Astrophysics Data System (ADS)

Emmons, L. K.; Edwards, D. P.; Hess, P. G.; Lamarque, J.; Pfister, G.; Wiedinmyer, C.; Clerbaux, C.

2007-05-01

The emissions from large cities, such as Mexico City, Los Angeles and Tokyo, as well as densely populated regions in India, China, etc., can clearly be seen in the CO retrievals from the Measurements of Pollution in the Troposphere (MOPITT) instrument on the Terra satellite and will be illustrated in this presentation. To assist in the flight planning and analysis of the MILAGRO field campaigns in Mexico during March 2006, MOPITT CO retrievals were assimilated in the global chemical transport model MOZART, using fire emissions based on satellite observations. To understand the impacts of Mexico City and other megacities on regional air quality, additional simulations of MOZART have been performed. The CO emissions from different types of sources (biomass burning, industry, etc.) are "tagged" in the model to show their relative contribution to the regional atmospheric composition. In addition, NO emissions from a single megacity or region are tagged to identify the contribution of ozone from a given source. The contribution from Mexico City pollution to the regional and global atmosphere will be compared to other megacities.

Plant traits, productivity, biomass and soil properties from forest sites in the Pacific Northwest, 1999-2014.

PubMed

Berner, Logan T; Law, Beverly E

2016-01-19

Plant trait measurements are needed for evaluating ecological responses to environmental conditions and for ecosystem process model development, parameterization, and testing. We present a standardized dataset integrating measurements from projects conducted by the Terrestrial Ecosystem Research and Regional Analysis- Pacific Northwest (TERRA-PNW) research group between 1999 and 2014 across Oregon and Northern California, where measurements were collected for scaling and modeling regional terrestrial carbon processes with models such as Biome-BGC and the Community Land Model. The dataset contains measurements of specific leaf area, leaf longevity, leaf carbon and nitrogen for 35 tree and shrub species derived from more than 1,200 branch samples collected from over 200 forest plots, including several AmeriFlux sites. The dataset also contains plot-level measurements of forest composition, structure (e.g., tree biomass), and productivity, as well as measurements of soil structure (e.g., bulk density) and chemistry (e.g., carbon). Publically-archiving regional datasets of standardized, co-located, and geo-referenced plant trait measurements will advance the ability of earth system models to capture species-level climate sensitivity at regional to global scales.

Plant traits, productivity, biomass and soil properties from forest sites in the Pacific Northwest, 1999-2014

NASA Astrophysics Data System (ADS)

Berner, Logan T.; Law, Beverly E.

2016-01-01

Plant trait measurements are needed for evaluating ecological responses to environmental conditions and for ecosystem process model development, parameterization, and testing. We present a standardized dataset integrating measurements from projects conducted by the Terrestrial Ecosystem Research and Regional Analysis- Pacific Northwest (TERRA-PNW) research group between 1999 and 2014 across Oregon and Northern California, where measurements were collected for scaling and modeling regional terrestrial carbon processes with models such as Biome-BGC and the Community Land Model. The dataset contains measurements of specific leaf area, leaf longevity, leaf carbon and nitrogen for 35 tree and shrub species derived from more than 1,200 branch samples collected from over 200 forest plots, including several AmeriFlux sites. The dataset also contains plot-level measurements of forest composition, structure (e.g., tree biomass), and productivity, as well as measurements of soil structure (e.g., bulk density) and chemistry (e.g., carbon). Publically-archiving regional datasets of standardized, co-located, and geo-referenced plant trait measurements will advance the ability of earth system models to capture species-level climate sensitivity at regional to global scales.

Turing instability in reaction-diffusion models on complex networks

NASA Astrophysics Data System (ADS)

Ide, Yusuke; Izuhara, Hirofumi; Machida, Takuya

2016-09-01

In this paper, the Turing instability in reaction-diffusion models defined on complex networks is studied. Here, we focus on three types of models which generate complex networks, i.e. the Erdős-Rényi, the Watts-Strogatz, and the threshold network models. From analysis of the Laplacian matrices of graphs generated by these models, we numerically reveal that stable and unstable regions of a homogeneous steady state on the parameter space of two diffusion coefficients completely differ, depending on the network architecture. In addition, we theoretically discuss the stable and unstable regions in the cases of regular enhanced ring lattices which include regular circles, and networks generated by the threshold network model when the number of vertices is large enough.

Dynamic analysis of gas-core reactor system

NASA Technical Reports Server (NTRS)

Turner, K. H., Jr.

1973-01-01

A heat transfer analysis was incorporated into a previously developed model CODYN to obtain a model of open-cycle gaseous core reactor dynamics which can predict the heat flux at the cavity wall. The resulting model was used to study the sensitivity of the model to the value of the reactivity coefficients and to determine the system response for twenty specified perturbations. In addition, the model was used to study the effectiveness of several control systems in controlling the reactor. It was concluded that control drums located in the moderator region capable of inserting reactivity quickly provided the best control.

Analysis of a thin-walled pressurized torus in contact with a plane. [aircraft tires study

NASA Technical Reports Server (NTRS)

Mack, M. J., Jr.; Gassman, P. M.; Baumgarten, J. R.

1983-01-01

Finite element analysis is applied to study the large deflection of a standing torus loaded by a plane. The internally pressurized thin-walled structure is found to have an elliptical footprint area. Considerable bulge occurs in the sidewall in the region of the load plane. Stress distributions throughout the torus are shown for various load levels and for various modeling strategies at a given load level. In large load ranges finite element calculations show compressive circumferential stress and negative curvature in the footprint region. Results are compared with inelastic wall analysis.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Health care networks implementation and regional governance challenges in the Legal Amazon Region: an analysis of the QualiSUS-Rede Project.

PubMed

Casanova, Angela Oliveira; Cruz, Marly Marques; Giovanella, Ligia; Alves, Glaydes Dos Reis; Cardoso, Gisela Cordeiro Pereira

2017-04-01

This paper aims to analyze the potential, limits and challenges of regional governance in the implementation process of health care networks in three Brazilian regions: Alto Solimões (Amazonas), Belém (Pará) and an interstate region comprising Tocantins, Pará and Maranhão states (Topama). The study is based on the evaluation study on the implementation of the Quality Health Care Network Development and Improvement Project (QualiSUS-Rede). This is a qualitative multiple case study with the analysis of official documents and use of semi-structured interviews with key stakeholders conducted from July to December 2014. Governance review encompassed three components: stakeholders involved, especially local steering groups and their regional coordination capacity; strategies used for strengthening regional governance, anchored on the intervention's modeling; and implementation of local health care networks. Results point that the regional managing commissions were the main governance strategy and that the QualiSUS-Rede Project strengthened regional governance and integration differently in every case, depending on stakeholders' administration and consensus capacity on regional and political priorities.

Cluster analysis of multiple planetary flow regimes

NASA Technical Reports Server (NTRS)

Mo, Kingtse; Ghil, Michael

1987-01-01

A modified cluster analysis method was developed to identify spatial patterns of planetary flow regimes, and to study transitions between them. This method was applied first to a simple deterministic model and second to Northern Hemisphere (NH) 500 mb data. The dynamical model is governed by the fully-nonlinear, equivalent-barotropic vorticity equation on the sphere. Clusters of point in the model's phase space are associated with either a few persistent or with many transient events. Two stationary clusters have patterns similar to unstable stationary model solutions, zonal, or blocked. Transient clusters of wave trains serve as way stations between the stationary ones. For the NH data, cluster analysis was performed in the subspace of the first seven empirical orthogonal functions (EOFs). Stationary clusters are found in the low-frequency band of more than 10 days, and transient clusters in the bandpass frequency window between 2.5 and 6 days. In the low-frequency band three pairs of clusters determine, respectively, EOFs 1, 2, and 3. They exhibit well-known regional features, such as blocking, the Pacific/North American (PNA) pattern and wave trains. Both model and low-pass data show strong bimodality. Clusters in the bandpass window show wave-train patterns in the two jet exit regions. They are related, as in the model, to transitions between stationary clusters.

Development of a composite repair and the associated inspection intervals for the F-111C stiffener runout region

NASA Technical Reports Server (NTRS)

Jones, R.; Molent, L.; Paul, J.; Saunders, T.; Chiu, W. K.

1994-01-01

This paper presents an overview of the structural aspects of the design and development of a local reinforcement designed to lower the stresses in a region of the F-111C wing fitting which is prone to cracking. The stress analysis, with particular emphasis on the use of a unified constitutive model for the cyclic inelastic response of the structure, representative specimen testing, thermal analysis and full scale static testing of this design are summarized.

Water Vapor Winds and Their Application to Climate Change Studies

NASA Technical Reports Server (NTRS)

Jedlovec, Gary J.; Lerner, Jeffrey A.

2000-01-01

The retrieval of satellite-derived winds and moisture from geostationary water vapor imagery has matured to the point where it may be applied to better understanding longer term climate changes that were previously not possible using conventional measurements or model analysis in data-sparse regions. In this paper, upper-tropospheric circulation features and moisture transport covering ENSO periods are presented and discussed. Precursors and other detectable interannual climate change signals are analyzed and compared to model diagnosed features. Estimates of winds and humidity over data-rich regions are used to show the robustness of the data and its value over regions that have previously eluded measurement.

Transitional flow in thin tubes for space station freedom radiator

NASA Technical Reports Server (NTRS)

Loney, Patrick; Ibrahim, Mounir

1995-01-01

A two dimensional finite volume method is used to predict the film coefficients in the transitional flow region (laminar or turbulent) for the radiator panel tubes. The code used to perform this analysis is CAST (Computer Aided Simulation of Turbulent Flows). The information gathered from this code is then used to augment a Sinda85 model that predicts overall performance of the radiator. A final comparison is drawn between the results generated with a Sinda85 model using the Sinda85 provided transition region heat transfer correlations and the Sinda85 model using the CAST generated data.

Fretting Stresses in Single Crystal Superalloy Turbine Blade Attachments

NASA Technical Reports Server (NTRS)

Arakere, Nagaraj K.; Swanson, Gregory

2000-01-01

Single crystal nickel base superalloy turbine blades are being utilized in rocket engine turbopumps and turbine engines because of their superior creep, stress rupture, melt resistance and thermomechanical fatigue capabilities over polycrystalline alloys. Currently the most widely used single crystal nickel base turbine blade superalloys are PWA 1480/1493 and PWA 1484. These alloys play an important role in commercial, military and space propulsion systems. High Cycle Fatigue (HCF) induced failures in aircraft gas turbine and rocket engine turbopump blades is a pervasive problem. Blade attachment regions are prone to fretting fatigue failures. Single crystal nickel base superalloy turbine blades are especially prone to fretting damage because the subsurface shear stresses induced by fretting action at the attachment regions can result in crystallographic initiation and crack growth along octahedral planes. Furthermore, crystallographic crack growth on octahedral planes under fretting induced mixed mode loading can be an order of magnitude faster than under pure mode I loading. This paper presents contact stress evaluation in the attachment region for single crystal turbine blades used in the NASA alternate Advanced High Pressure Fuel Turbo Pump (HPFTP/AT) for the Space Shuttle Main Engine (SSME). Single crystal materials have highly orthotropic properties making the position of the crystal lattice relative to the part geometry a significant factor in the overall analysis. Blades and the attachment region are modeled using a large-scale 3D finite element (FE) model capable of accounting for contact friction, material orthotrophy, and variation in primary and secondary crystal orientation. Contact stress analysis in the blade attachment regions is presented as a function of coefficient of friction and primary and secondary crystal orientation, Stress results are used to discuss fretting fatigue failure analysis of SSME blades. Attachment stresses are seen to reach peak values at locations where fretting cracks have been observed. Fretting stresses at the attachment region are seen to vary significantly as a function of crystal orientation. Attempts to adapt techniques used for estimating fatigue life in the airfoil region, for life calculations in the attachment region, are presented. An effective model for predicting crystallographic crack initiation under mixed mode loading is required for life prediction under fretting action.