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The Defense Modeling and Simulation Office (DMS0) sponsored surveys to be taken to establish the DoD requirements and capabilities for the natural environment and environmental effects in military models and simulations. The survey was conducted as a task within the DMS0 Project, Environmental Effects for Distributed Interactive Simulation, E2DIS (Heckathorn, 1994). A tri-service survey team was established and the Science Technology Corporation (STC) was selected to conduct a survey of DoD requirements for environmental effects in military M&S and a second survey to catalog the current and eminent models and data bases relevant to satisfying those requirements. STC also conducted an analysis of the shortfalls between stated requirements and current capabilities. This paper describes the results of the surveys and the analyses of needed new capabilities.

The Defense Modeling and Simulation Office (DMS0) sponsored surveys to be taken to establish the DoD requirements and capabilities for the natural environment and environmental effects in military models and simulations. The survey was conducted as a task within the DMS0 Project, Environmental Effects for Distributed Interactive Simulation, E2DIS (Heckathorn, 1994). A tri-service survey team was established and the Science Technology Corporation (STC) was selected to conduct a survey of DoD requirements for environmental effects in military M&S and a second survey to catalog the current and eminent models and data bases relevant to satisfying those requirements. STC also conducted an analysis of the shortfalls between stated requirements and current capabilities. This paper describes the results of the surveys and the analyses of needed new capabilities.

The quenching of star formation in satellite galaxies is observed over a wide range of dark matter halo masses and galaxy environments. In the recent Guo et al (2011) and Fu et al (2013) semi-analytic + N-body models, the gaseous environment of the satellite galaxy is governed by the properties of the dark matter subhalo in which it resides. This quantity depends of the resolution of the N-body simulation, leading to a divergent fraction of quenched satellites in high- and low-resolution simulations. Here, we incorporate an analytic model to trace the subhaloes below the resolution limit. We demonstrate that we then obtain better converged results between the Millennium I and II simulations, especially for the satellites in the massive haloes ($\rm log M_{halo}=[14,15]$). We also include a new physical model for the ram-pressure stripping of cold gas in satellite galaxies. However, we find very clear discrepancies with observed trends in quenched satellite galaxy fractions as a function of stellar mass at fixed halo mass. At fixed halo mass, the quenched fraction of satellites does not depend on stellar mass in the models, but increases strongly with mass in the data. In addition to the over-prediction of low-mass passive satellites, the models also predict too few quenched central galaxies with low stellar masses, so the problems in reproducing quenched fractions are not purely of environmental origin. Further improvements to the treatment of the gas-physical processes regulating the star formation histories of galaxies are clearly necessary to resolve these problems.

The quenching of star formation in satellite galaxies is observed over a wide range of dark matter halo masses and galaxy environments. In the recent Guo et al (2011) and Fu et al (2013) semi-analytic + N-body models, the gaseous environment of the satellite galaxy is governed by the properties of the dark matter subhalo in which it resides. This quantity depends of the resolution of the N-body simulation, leading to a divergent fraction of quenched satellites in high- and low-resolution simulations. Here, we incorporate an analytic model to trace the subhaloes below the resolution limit. We demonstrate that we then obtain better converged results between the Millennium I and II simulations, especially for the satellites in the massive haloes ($\rm log M_{halo}=[14,15]$). We also include a new physical model for the ram-pressure stripping of cold gas in satellite galaxies. However, we find very clear discrepancies with observed trends in quenched satellite galaxy fractions as a function of stellar mass at fixed halo mass. At fixed halo mass, the quenched fraction of satellites does not depend on stellar mass in the models, but increases strongly with mass in the data. In addition to the over-prediction of low-mass passive satellites, the models also predict too few quenched central galaxies with low stellar masses, so the problems in reproducing quenched fractions are not purely of environmental origin. Further improvements to the treatment of the gas-physical processes regulating the star formation histories of galaxies are clearly necessary to resolve these problems.

The quenching of star formation in satellite galaxies is observed over a wide range of dark matter halo masses and galaxy environments. In the recent Guo et al (2011) and Fu et al (2013) semi-analytic + N-body models, the gaseous environment of the satellite galaxy is governed by the properties of the dark matter subhalo in which it resides. This quantity depends of the resolution of the N-body simulation, leading to a divergent fraction of quenched satellites in high- and low-resolution simulations. Here, we incorporate an analytic model to trace the subhaloes below the resolution limit. We demonstrate that we then obtain better converged results between the Millennium I and II simulations, especially for the satellites in the massive haloes ($\rm log M_{halo}=[14,15]$). We also include a new physical model for the ram-pressure stripping of cold gas in satellite galaxies. However, we find very clear discrepancies with observed trends in quenched satellite galaxy fractions as a function of stellar mass at fixed halo mass. At fixed halo mass, the quenched fraction of satellites does not depend on stellar mass in the models, but increases strongly with mass in the data. In addition to the over-prediction of low-mass passive satellites, the models also predict too few quenched central galaxies with low stellar masses, so the problems in reproducing quenched fractions are not purely of environmental origin. Further improvements to the treatment of the gas-physical processes regulating the star formation histories of galaxies are clearly necessary to resolve these problems.

An attack on, or chemical spill near, Iraq's Oil Terminals could have disastrous effects on Iraq's economy. The impacts from a drifting mine or chemical spill are highly dependent upon environmental conditions that can either adversely effect continued operations or hinder the safety of personnel. Operational Planners ability to create legitimate scenarios to train and combat these situations is key to continued safe operation of the terminals. To accomplish this, planners must understand the impacts of using climatology versus near real-time data in the evaluation of the scenarios. The near real-time environmental data were provided by the Navy's ocean atmospheric operational models. This study examines the benefits of knowing the environment to understand their impacts to operations in the northern Persian Gulf. Three different scenarios were examined to understand the impact to Oil Terminal operations in the event of drifting mines or a chemical spill. The chemical spill was examined from the outlook of a major collision with a barge that spilled either Liquefied Ammonia or Mustard Gas. The Ammonia scenario was further analyzed in the atmosphere. This study demonstrates the impact that near real-time environmental conditions can have over climatological data for Operational Planners.

The need for elucidating the effects of environmental factors in the determination of the novel corona virus (COVID-19) is very vital. This study is a methodological study to compare three different test models (1. Artificial neural networks (ANN), 2. Adaptive neuro fuzzy inference system (ANFIS), 3. A linear classical model (MLR)) used to determine the relationship between COVID-19 spread and environmental factors (temperature, humidity and wind). These data were obtained from the studies (Pirouz, Haghshenas, Haghshenas, & Piro, 2020) with confirmed COVID-19 patients in Wuhan, China, using temperature, humidity and wind as the independent variables. The measured and the predicted results were checked based on three different performance indices; Root mean square error (RMSE), determination coefficient (R2 ) and correlation coefficient (R). The results showed that ANFIS and ANN are more promising over the classical MLR models having an average R-values of 0.90 in both calibration and verification stages. The findings indicated that ANFIS outperformed MLR and ANN. In addition, their performance skills boosted up to 25% and 9% respectively based on the determination coefficient for the prediction of confirmed COVID-19 cases in Wuhan city of China. Overall, the results depict the reliability and ability of AI-based models (ANFIS and ANN) for the simulation of COVID-19 using the effects of various environmental variables.

In this study, we have carried out a detailed, statistical analysis of isolated model galaxies, taking advantage of publicly available hierarchical galaxy formation models. To select isolated galaxies, we employ 2D methods widely used in the observational literature, as well as a more stringent 3D isolation criterion that uses the full 3D-real space information. In qualitative agreement with observational results, isolated model galaxies have larger fractions of late-type, star forming galaxies with respect to randomly selected samples of galaxies with the same mass distribution. We also find that the samples of isolated model galaxies typically contain a fraction of less than 15 per cent of satellite galaxies, that reside at the outskirts of their parent haloes where the galaxy number density is low. Projection effects cause a contamination of 2D samples of about 18 per cent, while we estimate a typical completeness of 65 per cent. Our model isolated samples also include a very small (few per cent) fraction of bulge dominated galaxies (B/T > 0.8) whose bulges have been built mainly by minor mergers. Our study demonstrates that about 65-70 per cent of 2D isolated galaxies that are classified as isolated at z = 0 have indeed been completely isolated since z = 1 and only 7 per cent have had more than 3 neighbours within a comoving radius of 1 Mpc. Irrespectively of the isolation criteria, roughly 45 per cent of isolated galaxies have experienced at least one merger event in the past (most of the mergers are minor, with mass ratios between 1:4 and 1:10). The latter point validates the approximation that isolated galaxies have been mainly influenced by internal processes.

General Background Pro-environmental behaviour refers to any behaviour or set of behaviours that minimise harm to the environment or benefit the environment (Steg & Vlek, 2009). Given the impact of human behaviour on environmental challenges (Abbass et al., 2022), understanding pro-environmental behaviour is a priority for environmental psychologists. While many studies focused on specific pro-environmental behaviours in isolation (e.g., recycling, energy conservation), it is still unclear whether there is a common underlying factor that drives engagement in multiple pro-environmental behaviours. Research suggests that pro-environmental behaviours are influenced by multiple factors that may vary across behavioural domains and contexts (Gifford & Nilsson, 2014). These factors include personal motivations, such as environmental concern, financial considerations, and health concerns, as well as external factors like policy frameworks, social norms, and infrastructural availability. There might be common motivators that drive engagement in multiple pro-environmental behaviours, such as the concept of a “moral circle”. Bratanova et al. (2012) found that individuals who perceive animals, future generations, and the environment as part of their ‘moral circle’ are more likely to engage in a variety of more sustainable practices. This suggests that while pro-environmental behaviours may vary across different contexts, a broader ethical orientation might be an important underlying factor. Some argue for a multidimensional approach to pro-environmental behaviour that considers these behaviours as distinct yet interconnected, while others suggest that a general pro-environmental tendency could account for the observed consistencies (Steg & Vlek, 2009). Understanding whether a unified pro-environmental factor exists, or if behaviours are driven by specific, context-dependent factors, is important for designing effective interventions that target the most salient motivators for various behavioural domains. Measurement of PEB To be able to investigate the structure of pro-environmental behaviour, a measure incorporating all relevant domains of pro-environmental behaviour is needed. A number of measures of pro-environmental behaviour (PEBs) have been developed and used in primary research (e.g., Kaiser & Wilson, 2004; Markle, 2013). However, Gatersleben (2023) highlights that environmental impact (i.e., changes in the environment caused by human activities) is not often considered by environmental psychologists when they choose the behaviours they want to measure. As such, the most environmentally impactful behaviours may not always form the focus of empirical investigations. A new impact-focused scale will be developed as part of the current study, that will support exploration of the factor structure of pro-environmental behaviours. This will encompass seven dimensions. Six of the selected domains are impact-focused: water conservation, energy conservation, resource management, transportation, food consumption, and family planning. Although not considered impact-focused, the domain of civic actions was also included as a separate domain. Lange and Dewitte (2019) identified that public sphere behaviours (e.g., environmental activism) have not been as often included in measures of pro-environmental behaviour as private sphere behaviours (e.g., sustainable waste disposal). Markle (2013) also justified adding “environmental citizenship behaviours”, such as membership in an environmental organisation and donating money, to his impact-focused scale based on Stern’s observation (2000, p.409) “[a]lthough these behaviors affect the environment only indirectly, by influencing public policies, the effects may be large, because public policies can change the behaviors of many people and organizations at once”. Current study The current study aims to investigate the structure of pro-environmental behaviour. To achieve this, we will develop a measure of pro-environmental behaviour that encompasses most environmentally significant behaviours. Specifically, we are interested in whether there is a single underlying pro-environmental factor (“e-factor”) that influences engagement in different behavioural domains (e.g., energy conservation, resource management, and sustainable transportation). We hypothesise that there might be an underlying pro-environmental factor that captures a general propensity towards pro-environmental behaviours. As pro-environmental behaviours can be driven by different goals, and not all pro-environmental behaviours are conducted with the goal of being more sustainable. We will conduct exploratory analyses including additional variables (i.e., environmental concern, pro-social behaviour, pro-environmental identity, financial concern, and health concern) modelled as predictors of the items or correlates of the model. For instance, it is possible that health concerns may predict more sustainable food consumption, as more sustainable foods (e.g., pulses) are often considered healthier than the less sustainable alternatives (e.g., meat products); however, it is unlikely that health concerns will predict engagement in civic actions as taking part in environmental demonstrations.

General Background Pro-environmental behaviour refers to any behaviour or set of behaviours that minimise harm to the environment or benefit the environment (Steg & Vlek, 2009). Given the impact of human behaviour on environmental challenges (Abbass et al., 2022), understanding pro-environmental behaviour is a priority for environmental psychologists. While many studies focused on specific pro-environmental behaviours in isolation (e.g., recycling, energy conservation), it is still unclear whether there is a common underlying factor that drives engagement in multiple pro-environmental behaviours. Research suggests that pro-environmental behaviours are influenced by multiple factors that may vary across behavioural domains and contexts (Gifford & Nilsson, 2014). These factors include personal motivations, such as environmental concern, financial considerations, and health concerns, as well as external factors like policy frameworks, social norms, and infrastructural availability. There might be common motivators that drive engagement in multiple pro-environmental behaviours, such as the concept of a “moral circle”. Bratanova et al. (2012) found that individuals who perceive animals, future generations, and the environment as part of their ‘moral circle’ are more likely to engage in a variety of more sustainable practices. This suggests that while pro-environmental behaviours may vary across different contexts, a broader ethical orientation might be an important underlying factor. Some argue for a multidimensional approach to pro-environmental behaviour that considers these behaviours as distinct yet interconnected, while others suggest that a general pro-environmental tendency could account for the observed consistencies (Steg & Vlek, 2009). Understanding whether a unified pro-environmental factor exists, or if behaviours are driven by specific, context-dependent factors, is important for designing effective interventions that target the most salient motivators for various behavioural domains. Measurement of PEB To be able to investigate the structure of pro-environmental behaviour, a measure incorporating all relevant domains of pro-environmental behaviour is needed. A number of measures of pro-environmental behaviour (PEBs) have been developed and used in primary research (e.g., Kaiser & Wilson, 2004; Markle, 2013). However, Gatersleben (2023) highlights that environmental impact (i.e., changes in the environment caused by human activities) is not often considered by environmental psychologists when they choose the behaviours they want to measure. As such, the most environmentally impactful behaviours may not always form the focus of empirical investigations. A new impact-focused scale will be developed as part of the current study, that will support exploration of the factor structure of pro-environmental behaviours. This will encompass seven dimensions. Six of the selected domains are impact-focused: water conservation, energy conservation, resource management, transportation, food consumption, and family planning. Although not considered impact-focused, the domain of civic actions was also included as a separate domain. Lange and Dewitte (2019) identified that public sphere behaviours (e.g., environmental activism) have not been as often included in measures of pro-environmental behaviour as private sphere behaviours (e.g., sustainable waste disposal). Markle (2013) also justified adding “environmental citizenship behaviours”, such as membership in an environmental organisation and donating money, to his impact-focused scale based on Stern’s observation (2000, p.409) “[a]lthough these behaviors affect the environment only indirectly, by influencing public policies, the effects may be large, because public policies can change the behaviors of many people and organizations at once”. Current study The current study aims to investigate the structure of pro-environmental behaviour. To achieve this, we will develop a measure of pro-environmental behaviour that encompasses most environmentally significant behaviours. Specifically, we are interested in whether there is a single underlying pro-environmental factor (“e-factor”) that influences engagement in different behavioural domains (e.g., energy conservation, resource management, and sustainable transportation). We hypothesise that there might be an underlying pro-environmental factor that captures a general propensity towards pro-environmental behaviours. As pro-environmental behaviours can be driven by different goals, and not all pro-environmental behaviours are conducted with the goal of being more sustainable. We will conduct exploratory analyses including additional variables (i.e., environmental concern, pro-social behaviour, pro-environmental identity, financial concern, and health concern) modelled as predictors of the items or correlates of the model. For instance, it is possible that health concerns may predict more sustainable food consumption, as more sustainable foods (e.g., pulses) are often considered healthier than the less sustainable alternatives (e.g., meat products); however, it is unlikely that health concerns will predict engagement in civic actions as taking part in environmental demonstrations.

Effective planning and management of water resources require models to predict and evaluate the multiple biological, economic, physical, and social impacts that may result from any proposed hydraulic infrastructure design plan or operating policy. Different stakeholders care about different sets of these impacts. Models allow planners to identify the tradeoffs among the values of various conflicting objectives that are of interest to the stakeholders. Models can also aid in the synthesis of alternative designs, plans, or policies that may help reduce conflicts among the interested stakeholders. Those who develop and use models to assist in the solution of planning and management issues and problems must work with specialists from multiple disciplines. These multiple impact prediction models must be developed and calibrated based on knowledge that comes from these different disciplines.

The Defense Modeling and Simulation Office (DMSO) has sponsored the Environmental Effects for Distributed Interactive Simulation (E2DIS) Project, which is composed of eight tasks including the Survey Task. The Survey Task had three objectives: to develop a baseline of the Military Services current requirements for incorporation of the atmosphere and near-space environment and their effects in military models and simulations (the Requirements Survey), to identify atmospheric and near-space environmental models and databases and effects models and databases that are currently available from the services (the Capabilities Survey), and to compare the results from both survey efforts and make appropriate recommendations. In a series of three reports, Part I describes the results and findings from the Requirements Survey; this report, Part II, describes the results and findings from the Capabilities Survey; and Part III compares and assesses the results of both surveys. The Survey Team received questionnaires for 152 models and databases that were quality controlled and entered into an automated database management system for analysis. The results of the analysis are presented in this report. Both the Capabilities Survey database and the Requirements Survey database are available from PL/GPAA.

This technical report describes the general methodology behind the validation and verification of the RF environmental models as applied to HWIL simulation. The different phases of verification including implementation of RF models and propagated RF signals are presented. Validation of environmental models is discussed with emphasis on quantitative methods.

This article is from Ground Water , volume 51 . Abstract Detecting and quantifying small drawdown at observation wells distant from the pumping well greatly expands the characterized aquifer volume. However, this detection is often obscured by water level fluctuations such as barometric and tidal effects. A reliable analytical approach for distinguishing drawdown from nonpumping water-level fluctuations is presented and tested here. Drawdown is distinguished by analytically simulating all pumping and nonpumping water-level stresses simultaneously during the period of record. Pumping signals are generated with Theis models, where the pumping schedule is translated into water-level change with the Theis solution. This approach closely matched drawdowns simulated with a complex three-dimensional, hypothetical model and reasonably estimated drawdowns from an aquifer test conducted in a complex hydrogeologic system. Pumping-induced changes generated with a numerical model and analytical Theis model agreed (RMS as low as 0.007 m) in cases where pumping signals traveled more than 1 km across confining units and fault structures. Maximum drawdowns of about 0.05 m were analytically estimated from field investigations where environmental fluctuations approached 0.2 m during the analysis period.

This publication consists of papers given at a workshop on Modulators of Fish Immune Responses held in Breckenridge, Colorado, USA, in September 1993. This is the first of a series of workshops to be held every two years to keep up with advances in the field. The subject matter ranged from the use of fish as sensitive indicators of environmental contaminants to research, more basic in nature Non-immunoglobulin-mediated ('innate') immunity was one of the key topics. Immediate results of xenobiotic influences and immunostimulators can be detected by assays such as phagocytosis, superoxide anion production, chemotaxis and serum lysozyme concentrations. Invertebrate (shellfish) phagocytes were also found to generate superoxide and process xenobiotics. Advances in cytokine studies in fish also bring intervention in fish immune systems within the realm of possibility. Conference, RA III.

The Defense Modeling and Simulation Office has sponsored the Environmental Effects for Distributed Interactive Simulation (E2DlS) Project, which is composed of eight tasks including the Survey Task. The Survey Task had three objectives: to develop a baseline of the Military Services' current requirements for incorporation of the atmosphere and near-space environment and their effects in military models and simulations (the Requirements Survey), to identify atmospheric and near-space-environment models and databases and environmental effects models that are currently available from the services (the Capabilities Survey), and to compare the results from both survey efforts (the Analysis). This report, Part I of a three-part series, describes the results of the analysis of the Requirements Survey; Part II describes the results of the analysis of the Capabilities Survey; and Part Ill describes the results of the comparative analysis of the two surveys . The Requirements Survey identified 208 military models and simulations, whose sponsors provided 78 questionnaires, 74 of which were entered into the database management system. A qualitative and quantitative analysis of the responses to questionnaires is presented in this report, including a case study of wind, the most-required atmospheric data type. Requirements for these specific data are analyzed in terms of their horizontal, vertical, and temporal fidelity. The analysis yielded some unexpected results, especially the lack of requirements for atmospheric effects on forces, platforms, and weapon systems in the 74 surveyed military models and simulations. The Survey Team concluded from its analysis that a strong need exists for collaboration between the environmental science and support community and the military's modeling and simulation community.

An overview of studies conducted to establish the requirements for advanced subsystem analytical tools is presented. Modifications are defined for updating current computer programs used to analyze environmental control, life support, and electric power supply systems so that consumables for future advanced spacecraft may be managed.

The PI, Andrew Majda, and Co-PI s, Sam Stechmann (University of Wisconsin), John Harlim (North Carolina State University), Duane Waliser (UCLA/Cal Tech) just received the MURI funding in early August 2012 with a one-day MURI kickoff meeting July 13,2012 so this report is necessarily brief. Nevertheless, there are some exciting initial MURI developments to report on two MURI topics. A) Limits of Predictability in the North Pacific Sector of a Comprehensive Climate Model Majda and new Courant Institute Assistant Professor and MURI collaborator, Dimitri Giannakis, have just submitted a paper to GRL (1). We study limits of interannual to decadal predictability of sea surface temperature (SST) in the North Pacific sector of the Community Climate System Model version 3 (CCSM3). Using a set of low-frequency and intermittent spatiotemporal SST modes acquired through nonlinear Laplacian spectral analysis (a nonlinear data manifold generalization of singular spectrum analysis), we build a hierarchy of regression models with external factors to determine which modes govern the dynamic evolution and predictability of prominent large-scale patterns, namely the Pacific Decadal Oscillation (PDO) and North Pacific Gyre Oscillation (NPGO). Retaining key triple correlations between prognostic variables and external factors, as well as the seasonality of the data, we find that the PDO and NPGO modes of CCSM3 can be described with remarkably high fidelity as an outcome of forcing by the intermittent modes (with phase demodulation by the seasonal cycle) and cubic interactions between the low-frequency modes. Our results differ from the classical picture of ENSO-driven autoregressive models for North Pacific SST variability, providing evidence that intermittent processes, such as variability of the Kuroshio current, limit longrange predictability in this climate model.

The HZETRN code has been identified by NASA for engineering design in the next phase of space exploration highlighting a return to the Moon in preparation for a Mars mission. In response, a new series of algorithms beginning with 2005 HZETRN, will be issued by correcting some prior limitations and improving control of propagated errors along with established code verification processes. Code validation processes will use new/improved low Earth orbit (LEO) environmental models with a recently improved International Space Station (ISS) shield model to validate computational models and procedures using measured data aboard ISS. These validated models will provide a basis for flight-testing the designs of future space vehicles and systems of the Constellation program in the LEO environment.

Predicting the environmental fate of novel munitions compounds requires data for the key properties that control contaminant fate, and the most common way to predict these properties is with empirical quantitative structure-activity relationships (QSARs). However, the traditional approach to QSAR development (calibration with experimental data) is challenging for new explosives compounds because of limitations to the availability of these materials. Some of the necessary environmental fate properties can be calculated directly from molecular structure theory, but reliable calculations of this type require considerable theoretical expertise and computational effort. To overcome this combination of challenges, we used a hybrid, partially in silico approach to QSAR development, where some of the calibration data (both the target variable and the descriptor variables) were calculated from molecular structure theory.

In this viewgraph presentation, the following space radiations are covered: solar particle events, galactic cosmic rays, and trapped particles. Characteristics and models for each are presented.

Enhancements to the infrasound software tool kit, InfraMAp, have been integrated in three main areas: propagation modeling, environmental variability modeling, and stochastic localization techniques. All new model functionality is included in a next-generation release of the tool kit. The modeling advances improve propagation predictions and understanding of environmental effects, and they have been used to evaluate the localization performance and confidence bounds of operational infrasonic networks. New propagation modeling features include a high altitude, low frequency absorption model, a synthetic waveform generator from ray tracing, and an improved Parabolic Equation (PE) propagation algorithm. In environmental variability, a range-dependent spectral gravity wave model has been developed that generates wind perturbation fields for use in evaluating propagation variability. Finally, regional infrasound networks can be defined and used to compute source localizations and associated areas of uncertainty, based upon both measurement data and modeling results.

My long-term goal is the development of a data assimilative model system in which optical observations are linked directly and mechanistically to predictions of biological, chemical and physical dynamics of the ocean. The primary objectives are: 1. Continue to develop optical proxies for biological properties and processes in the upper ocean. 2. Establish a framework for modeling the dynamics of optical properties in the ocean, directly and mechanistically. 3. Integrate optical dynamics into state-of-the-art ocean models.

Most published habitat suitability index (HSI) models for warmwater fishes have too many variables, many of which time-consuming and difficult to measure. In addition, suitability index scores are calculated using nonuniform methods that often yield different values for closely related species. Based upon the literature and the results of field studies in the Little Cypress Basin, Texas, and the Yazoo River, Mississippi, closely related species of warmwater fishes were placed into groups. For each group, a community model was developed based on five variables: percent pools, average current velocity, percent cover, pH, and dissolved oxygen. Results are compared with the unmodified models, and methods used to develop and test these models are discussed. Keywords: Habitat evaluation, Environment.

The existing approaches to the mathematical modeling and optimization of a water pollution problem are briefly surveyed. A proposed geometric programming model of a water pollution and treatment system, which easily lends itself to the theory and application of nonlinear programming sensitivity analysis techniques, is studied in detail. As in previous work by the author of the model, the optimal waste treatment facilities along the Upper Hudson River are presented for three different environmental policies, leaving the sensitivity analysis study for a following report. Previous results were obtained using a geometric programming code, while the present study makes use of the SUMT code. It is shown that the policy of fixed dissolved oxygen requirement yields the mininum annual waste treatment cost, relative to two other policies. Moreover, it is shown that a variable dissolved oxygen policy yields relatively uniform treatment levels in the treatment plants at appreciabley reduced cost compared to the costs involved in strict uniform treatment policy. the results of the present study are consistent with, but not identical to, the finding reported in previous work. The discrepancy in the coefficients involved in the dissolved oxygen constraints used by these two studies is the main reason for the differences observed. A listing of a computer program developed to calculate these coefficients is included. (Author)

The Defense Modeling and Simulation Office has sponsored the Environmental Effects for Distributed Interactive Simulation (E2DlS) Project, which is composed of eight tasks including the Survey Task. The Survey Task had three objectives: to develop a baseline of the Military Services' current requirements for incorporation of the atmosphere and near space environment and their effects in military models and simulations (the Requirements Survey), to identify atmospheric and near-space-environment models and databases and environmental effects models and databases that are currently available from the services (the Capabilities Survey), and to compare the results from both survey efforts and make appropriate recommendations. This report, Part III of a three-part series, describes the results of a comparative analysis of the two surveys, whose results are reported in Part I (the Requirements Survey) and Part II (the Capabilities Survey). The analysis focuses on the eight most-needed types of environmental data, as determined from the Requirements Survey, and shows that the capabilities for providing these data, especially at high fidelity, are deficient. Requirements and capabilities are compared in terms of their horizontal, vertical, and temporal fidelity. Capabilities are deficient if they satisfy less than 75 percent of the requirements. The most significant deficiencies are found in models and databases of aerosols, fog, humidity, and visibility.

The purpose of this technical note is to provide guidelines on the use of conceptual models to improve system-wide planning and operation of water resource projects of the Corps of Engineers. Conceptual models provide a tool to represent, communicate, and analyze the structure, functions, and hierarchical relationships of the systems affected by Corps activities. The movement toward ecosystem restoration projects and toward sustainability of economic and ecologically viable systems has brought into focus the need to approach some Corps activities on a system-wide basis including: 1) Understanding the response of natural resources to environmental change or stress. 2) Supplying reliable services, e.g., flood damage reduction, maintenance of biodiversity. 3) Designing and managing projects in a sustainable manner.

Matter near a gravitational lens galaxy or projected along the line of sight (LOS) can affect strong lensing observables by more than contemporary measurement errors. We simulate lens fields with realistic three-dimensional mass configurations (self-consistently including voids), and then fit mock lensing observables with increasingly complex lens models to quantify biases and uncertainties associated with different ways of treating the lens environment (ENV) and LOS. We identify the combination of mass, projected offset, and redshift that determines the importance of a perturbing galaxy for lensing. Foreground structures have a stronger effect on the lens potential than background structures, due to nonlinear effects in the foreground and downweighting in the background. There is dramatic variation in the net strength of ENV/LOS effects across different lens fields; modeling fields individually yields stronger priors for $H_0$ than ray tracing through $N$-body simulations. Models that ignore mass outside the lens yield poor fits and biased results. Adding external shear can account for tidal stretching from galaxies at redshifts $z \ge z_{\rm lens}$, but it requires corrections for external convergence and cannot reproduce nonlinear effects from foreground galaxies. Using the tidal approximation is reasonable for most perturbers as long as nonlinear redshift effects are included. Even then, the scatter in $H_0$ is limited by the lens profile degeneracy. Asymmetric image configurations produced by highly elliptical lens galaxies are less sensitive to the lens profile degeneracy, so they offer appealing targets for precision lensing analyses in future surveys like LSST and Euclid.

Matter near a gravitational lens galaxy or projected along the line of sight (LOS) can affect strong lensing observables by more than contemporary measurement errors. We simulate lens fields with realistic three-dimensional mass configurations (self-consistently including voids), and then fit mock lensing observables with increasingly complex lens models to quantify biases and uncertainties associated with different ways of treating the lens environment (ENV) and LOS. We identify the combination of mass, projected offset, and redshift that determines the importance of a perturbing galaxy for lensing. Foreground structures have a stronger effect on the lens potential than background structures, due to nonlinear effects in the foreground and downweighting in the background. There is dramatic variation in the net strength of ENV/LOS effects across different lens fields; modeling fields individually yields stronger priors for $H_0$ than ray tracing through $N$-body simulations. Models that ignore mass outside the lens yield poor fits and biased results. Adding external shear can account for tidal stretching from galaxies at redshifts $z \ge z_{\rm lens}$, but it requires corrections for external convergence and cannot reproduce nonlinear effects from foreground galaxies. Using the tidal approximation is reasonable for most perturbers as long as nonlinear redshift effects are included. Even then, the scatter in $H_0$ is limited by the lens profile degeneracy. Asymmetric image configurations produced by highly elliptical lens galaxies are less sensitive to the lens profile degeneracy, so they offer appealing targets for precision lensing analyses in future surveys like LSST and Euclid.

Matter near a gravitational lens galaxy or projected along the line of sight (LOS) can affect strong lensing observables by more than contemporary measurement errors. We simulate lens fields with realistic three-dimensional mass configurations (self-consistently including voids), and then fit mock lensing observables with increasingly complex lens models to quantify biases and uncertainties associated with different ways of treating the lens environment (ENV) and LOS. We identify the combination of mass, projected offset, and redshift that determines the importance of a perturbing galaxy for lensing. Foreground structures have a stronger effect on the lens potential than background structures, due to nonlinear effects in the foreground and downweighting in the background. There is dramatic variation in the net strength of ENV/LOS effects across different lens fields; modeling fields individually yields stronger priors for $H_0$ than ray tracing through $N$-body simulations. Models that ignore mass outside the lens yield poor fits and biased results. Adding external shear can account for tidal stretching from galaxies at redshifts $z \ge z_{\rm lens}$, but it requires corrections for external convergence and cannot reproduce nonlinear effects from foreground galaxies. Using the tidal approximation is reasonable for most perturbers as long as nonlinear redshift effects are included. Even then, the scatter in $H_0$ is limited by the lens profile degeneracy. Asymmetric image configurations produced by highly elliptical lens galaxies are less sensitive to the lens profile degeneracy, so they offer appealing targets for precision lensing analyses in future surveys like LSST and Euclid.

A sample environmental control and life support model performance analysis using the environmental analysis routines library is presented. An example of a complete model set up and execution is provided. The particular model was synthesized to utilize all of the component performance routines and most of the program options.

This report describes a capability called MEDOC which includes a suite of codes used for the assessment/ prediction of Multiscale Environmental Dispersion Over Complex Terrain. The codes which were originally developed by and for the nuclear power industry have been adapted under a program described in this report, to a broader range of problems involving chemical and biological, as well as nuclear, sources which are of concern to the U.S. Defense Nuclear Agency (DNA) and the national defense community. MEDOC can operate in either a prognostic or diagnostic mode, providing both the meteorological and the concentration transport/dispersion fields over a range of atmospheric scales from local (approx 10's of KM), to regional (approx 1OO's of KM). Alternate methodologies, from first principles based to more approximate, are provided to allow various degrees of fidelity and computational efficiency. Thus MEDOC provides appropriate models for a variety of applications such as guidance for local scale emergency response, forecasts for regional scale impacts, and future planning studies. The codes are operational on either a super computer (CRAY), or a workstation level platform (IBM RlSC16000), and have been installed on workstations where they are exercised by DNA personnel.

This report describes a capability called MEDOC which includes a suite of codes used for the assessment/ prediction of Multiscale Environmental Dispersion Over Complex Terrain. The codes which were originally developed by and for the nuclear power industry have been adapted under a program described in this report, to a broader range of problems involving chemical and biological, as well as nuclear, sources which are of concern to the U.S. Defense Nuclear Agency (DNA) and the national defense community. MEDOC can operate in either a prognostic or diagnostic mode, providing both the meteorological and the concentration transport/dispersion fields over a range of atmospheric scales from local (approx 10's of KM), to regional (approx 1OO's of KM). Alternate methodologies, from first principles based to more approximate, are provided to allow various degrees of fidelity and computational efficiency. Thus MEDOC provides appropriate models for a variety of applications such as guidance for local scale emergency response, forecasts for regional scale impacts, and future planning studies. The codes are operational on either a super computer (CRAY), or a workstation level platform (IBM RlSC16000), and have been installed on workstations where they are exercised by DNA personnel.

A consistent environmental-acoustic model for a deep moving ocean is formulated. The acoustic model for regularly-perturbed SOFAR rays is approximately solved using a type of WKB(J) expansion. Interfacing conditions between the hydrodynamics and acoustics are developed which lead to constraints on acoustic frequency and transmission range. As an application, transmissions are considered through stochastic internal-wave fields, which have been modeled in a previously-published paper by the authors. Formulas for ray phase variances derived. These formulas are asymptotically evaluated for rays with relatively significant depth variation, using the stationary phase method. New results are obtained for the dependence of the variances on internal-wave primitives, such as energy spectra. Expected multipath intensity is calculated for transmission through an ocean with static state modeled by a bilinear sound-speed profile. The effects of the internal-wave field and of varying internal-wave parameters on the expected intensity are shown to be significant. (Author)

In order to understand underlying processes governing environmental and physical processes, and predict future outcomes, a complex computer model is frequently required to simulate these dynamics. However there is inevitably uncertainty related to the exact parametric form or the values of such parameters to be used when developing these simulators, with \emph{ranges} of plausible values prevalent in the literature. Systematic errors introduced by failing to account for these uncertainties have the potential to have a large effect on resulting estimates in unknown quantities of interest. Due to the complexity of these types of models, it is often unfeasible to run large numbers of training runs that are usually required for full statistical emulators of the environmental processes. We therefore present a method for accounting for uncertainties in complex environmental simulators without the need for very large numbers of training runs and illustrate the method through an application to the Met Office's atmospheric transport model NAME. We conclude that there are two principle parameters that are linked with variability in NAME outputs, namely the free tropospheric turbulence parameter and particle release height. Our results suggest the former should be significantly larger than is currently implemented as a default in NAME, whilst changes in the latter most likely stem from inconsistencies between the model specified ground height at the observation locations and the true height at this location. Estimated discrepancies from independent data are consistent with the discrepancy between modelled and true ground height.

In order to understand underlying processes governing environmental and physical processes, and predict future outcomes, a complex computer model is frequently required to simulate these dynamics. However there is inevitably uncertainty related to the exact parametric form or the values of such parameters to be used when developing these simulators, with \emph{ranges} of plausible values prevalent in the literature. Systematic errors introduced by failing to account for these uncertainties have the potential to have a large effect on resulting estimates in unknown quantities of interest. Due to the complexity of these types of models, it is often unfeasible to run large numbers of training runs that are usually required for full statistical emulators of the environmental processes. We therefore present a method for accounting for uncertainties in complex environmental simulators without the need for very large numbers of training runs and illustrate the method through an application to the Met Office's atmospheric transport model NAME. We conclude that there are two principle parameters that are linked with variability in NAME outputs, namely the free tropospheric turbulence parameter and particle release height. Our results suggest the former should be significantly larger than is currently implemented as a default in NAME, whilst changes in the latter most likely stem from inconsistencies between the model specified ground height at the observation locations and the true height at this location. Estimated discrepancies from independent data are consistent with the discrepancy between modelled and true ground height.

The Infant Health and Development Program (IHDP) is an intervention designed to facilitate social development in low birthweight (LBW) children. This report does not deal with the full complexity of operations involving program components as they interact to shape social competence. Rather, the report represents a first or "setting" stage, a look at the ecology of social development in LBW children independent of intervention. The study's purpose was threefold: (1) to look at simple relationships between various aspects of home environment and components of social competence; (2) to study primacy and recency effects with respect to social competence at the age of 3 years; and (3) to identify interactions among home environment components that relate to social competence. Participants in the study were 549 children who had participated in the IHDP. The measures used were the HOME Inventory, Achenbach Child Behavior Checklist, Richman-Graham Behavior Checklist, Adaptive Social Behavior Inventory, and measures of mother-child interactions. As expected, the home environments of children with low birth weight were related to the social competence of the children. Significant relations were obtained from parental ratings of children's social problems and adaptive behavior and from direct observations of children's social behavior in problem-solving situations. Results suggest that intervention may have an effect when a child has a reasonably responsive environment in the first year of life. Five tables show the statistical correlations. Contains 7 references. (LB)

Memristors are used to compare three gathering techniques in an already-mapped environment where resource locations are known. The All Site model, which apportions gatherers based on the modeled memristance of that path, proves to be good at increasing overall efficiency and decreasing time to fully deplete an environment, however it only works well when the resources are of similar quality. The Leaf Cutter method, based on Leaf Cutter Ant behaviour, assigns all gatherers first to the best resource, and once depleted, uses the All Site model to spread them out amongst the rest. The Leaf Cutter model is better at increasing resource influx in the short-term and vastly out-performs the All Site model in a more varied environments. It is demonstrated that memristor based abstractions of gatherer models provide potential methods for both the comparison and implementation of agent controls.

Memristors are used to compare three gathering techniques in an already-mapped environment where resource locations are known. The All Site model, which apportions gatherers based on the modeled memristance of that path, proves to be good at increasing overall efficiency and decreasing time to fully deplete an environment, however it only works well when the resources are of similar quality. The Leaf Cutter method, based on Leaf Cutter Ant behaviour, assigns all gatherers first to the best resource, and once depleted, uses the All Site model to spread them out amongst the rest. The Leaf Cutter model is better at increasing resource influx in the short-term and vastly out-performs the All Site model in a more varied environments. It is demonstrated that memristor based abstractions of gatherer models provide potential methods for both the comparison and implementation of agent controls.

Memristors are used to compare three gathering techniques in an already-mapped environment where resource locations are known. The All Site model, which apportions gatherers based on the modeled memristance of that path, proves to be good at increasing overall efficiency and decreasing time to fully deplete an environment, however it only works well when the resources are of similar quality. The Leaf Cutter method, based on Leaf Cutter Ant behaviour, assigns all gatherers first to the best resource, and once depleted, uses the All Site model to spread them out amongst the rest. The Leaf Cutter model is better at increasing resource influx in the short-term and vastly out-performs the All Site model in a more varied environments. It is demonstrated that memristor based abstractions of gatherer models provide potential methods for both the comparison and implementation of agent controls.

Memristors are used to compare three gathering techniques in an already-mapped environment where resource locations are known. The All Site model, which apportions gatherers based on the modeled memristance of that path, proves to be good at increasing overall efficiency and decreasing time to fully deplete an environment, however it only works well when the resources are of similar quality. The Leaf Cutter method, based on Leaf Cutter Ant behaviour, assigns all gatherers first to the best resource, and once depleted, uses the All Site model to spread them out amongst the rest. The Leaf Cutter model is better at increasing resource influx in the short-term and vastly out-performs the All Site model in a more varied environments. It is demonstrated that memristor based abstractions of gatherer models provide potential methods for both the comparison and implementation of agent controls.

The talk will present some of the algorithms developed as part of my graduate work at Carnegie Mellon. Speech is the natural medium of communication for humans, and in the last decade various speech technologies like automatic speech recognition (ASR), voice response systems etc. have considerably matured. The above systems rely on the clarity of the captured speech but many of the real-world environments include noise and reverberation that mitigate the system performance. The key focus of the talk will on the ASR robustness to reverberation. We first provide a new framework to adequately and efficiently represent the problem of reverberation in the speech spectral and cepstral feature domains and later develop different dereverberation algorithms on the proposed framework. The algorithms reduce the uncertainly involved in dereverberation tasks by using speech knowledge in terms of cepstral auto-correlation, cepstral distribution, and, non-negativity and sparsity of spectral values. We demonstrate the success of our algorithms on clean-training as well as matched-training.Apart from dereverberation, we also provide two approaches for noise robustness. One of them is in terms of audio-visual feature combination with new visual features being derived from the profile-view images of a person. The second noise robustness approach is via temporal-difference operation in speech spectral domain, where via a theoretical analysis, we also predict an expected improvement in the SNR threshold shift for white-noise conditions. Finally, we combine our individual dereverberation and noise compensation approaches for a joint noise and reverberation compensation task.Website: http://www.ece.cmu.edu/~kshitizk ©2010 Microsoft Corporation. All rights reserved.

The talk will present some of the algorithms developed as part of my graduate work at Carnegie Mellon. Speech is the natural medium of communication for humans, and in the last decade various speech technologies like automatic speech recognition (ASR), voice response systems etc. have considerably matured. The above systems rely on the clarity of the captured speech but many of the real-world environments include noise and reverberation that mitigate the system performance. The key focus of the talk will on the ASR robustness to reverberation. We first provide a new framework to adequately and efficiently represent the problem of reverberation in the speech spectral and cepstral feature domains and later develop different dereverberation algorithms on the proposed framework. The algorithms reduce the uncertainly involved in dereverberation tasks by using speech knowledge in terms of cepstral auto-correlation, cepstral distribution, and, non-negativity and sparsity of spectral values. We demonstrate the success of our algorithms on clean-training as well as matched-training.Apart from dereverberation, we also provide two approaches for noise robustness. One of them is in terms of audio-visual feature combination with new visual features being derived from the profile-view images of a person. The second noise robustness approach is via temporal-difference operation in speech spectral domain, where via a theoretical analysis, we also predict an expected improvement in the SNR threshold shift for white-noise conditions. Finally, we combine our individual dereverberation and noise compensation approaches for a joint noise and reverberation compensation task.Website: http://www.ece.cmu.edu/~kshitizk ©2010 Microsoft Corporation. All rights reserved.

We investigate the smallest set of requirements for inducing non-Markovian dynamics in a collisional model of open quantum systems. This is done by introducing correlations in the state of the environment and analyzing the divisibility of the quantum maps from consecutive time steps. Our model and results serve as a platform for the microscopic study of non-Markovian behavior as well as an example of a simple scenario of non-Markovianity with purely contractive maps, i.e. with no back-flow of information between system and environment.

We investigate the smallest set of requirements for inducing non-Markovian dynamics in a collisional model of open quantum systems. This is done by introducing correlations in the state of the environment and analyzing the divisibility of the quantum maps from consecutive time steps. Our model and results serve as a platform for the microscopic study of non-Markovian behavior as well as an example of a simple scenario of non-Markovianity with purely contractive maps, i.e. with no back-flow of information between system and environment.

We investigate the smallest set of requirements for inducing non-Markovian dynamics in a collisional model of open quantum systems. This is done by introducing correlations in the state of the environment and analyzing the divisibility of the quantum maps from consecutive time steps. Our model and results serve as a platform for the microscopic study of non-Markovian behavior as well as an example of a simple scenario of non-Markovianity with purely contractive maps, i.e. with no back-flow of information between system and environment.

This article is from Genetics, Selection, Evolution : GSE , volume 46 . Abstract Background: Identifying the relevant environmental variables that cause GxE interaction is often difficult when they cannot be experimentally manipulated. Two statistical approaches can be applied to address this question. When data on candidate environmental variables are available, GxE interaction can be quantified as a function of specific environmental variables using a reaction norm model. Alternatively, a factor analytic model can be used to identify the latent common factor that explains GxE interaction. This factor can be correlated with known environmental variables to identify those that are relevant. Previously, we reported a significant GxE interaction for body weight at harvest in rainbow trout reared on three continents. Here we explore their possible causes. Methods: Reaction norm and factor analytic models were used to identify which environmental variables (age at harvest, water temperature, oxygen, and photoperiod) may have caused the observed GxE interaction. Data on body weight at harvest was recorded on 8976 offspring reared in various locations: (1) a breeding environment in the USA (nucleus), (2) a recirculating aquaculture system in the Freshwater Institute in West Virginia, USA, (3) a high-altitude farm in Peru, and (4) a low-water temperature farm in Germany. Akaike and Bayesian information criteria were used to compare models. Results: The combination of days to harvest multiplied with daily temperature (Day*Degree) and photoperiod were identified by the reaction norm model as the environmental variables responsible for the GxE interaction. The latent common factor that was identified by the factor analytic model showed the highest correlation with Day*Degree. Day*Degree and photoperiod were the environmental variables that differed most between Peru and other environments. Akaike and Bayesian information criteria indicated that the factor analytical model was more parsimonious than the reaction norm model. Conclusions: Day*Degree and photoperiod were identified as environmental variables responsible for the strong GxE interaction for body weight at harvest in rainbow trout across four environments. Both the reaction norm and the factor analytic models can help identify the environmental variables responsible for GxE interaction. A factor analytic model is preferred over a reaction norm model when limited information on differences in environmental variables between farms is available.

Philip Morris Records; bibliography; report; extr, extra

In hierarchical models, density fluctuations on different scales are correlated. This induces correlations between dark halo masses, their formation histories, and their larger-scale environments. In turn, this produces a correlation between galaxy properties and environment. This correlation is entirely statistical in nature. We show how the observed clustering of galaxies can be used to quantify the importance of this statistical correlation relative to other physical effects which may also give rise to correlations between the properties of galaxies and their surroundings. We also develop a halo model description of this environmental dependence of clustering.

This document represents the registration of the scoping review protocol for the study "Environmental enrichment influence on the predictive validity of anxiety models in mice: a scoping review"