Directional selection causes decanalization in a group I ribozyme.

PubMed

Hayden, Eric J; Weikert, Christian; Wagner, Andreas

2012-01-01

A canalized genotype is robust to environmental or genetic perturbations. Canalization is expected to result from stabilizing selection on a well-adapted phenotype. Decanalization, the loss of robustness, might follow periods of directional selection toward a new optimum. The evolutionary forces causing decanalization are still unknown, in part because it is difficult to determine the fitness effects of mutations in populations of organisms with complex genotypes and phenotypes. Here, we report direct experimental measurements of robustness in a system with a simple genotype and phenotype, the catalytic activity of an RNA enzyme. We find that the robustness of a population of RNA enzymes decreases during a period of directional selection in the laboratory. The decrease in robustness is primarily caused by the selective sweep of a genotype that is decanalized relative to the wild-type, both in terms of mutational robustness and environmental robustness (thermodynamic stability). Our results experimentally demonstrate that directional selection can cause decanalization on short time scales, and demonstrate co-evolution of mutational and environmental robustness.

Molecular mechanisms governing differential robustness of development and environmental responses in plants

PubMed Central

Lachowiec, Jennifer; Queitsch, Christine; Kliebenstein, Daniel J.

2016-01-01

Background Robustness to genetic and environmental perturbation is a salient feature of multicellular organisms. Loss of developmental robustness can lead to severe phenotypic defects and fitness loss. However, perfect robustness, i.e. no variation at all, is evolutionarily unfit as organisms must be able to change phenotype to properly respond to changing environments and biotic challenges. Plasticity is the ability to adjust phenotypes predictably in response to specific environmental stimuli, which can be considered a transient shift allowing an organism to move from one robust phenotypic state to another. Plants, as sessile organisms that undergo continuous development, are particularly dependent on an exquisite fine-tuning of the processes that balance robustness and plasticity to maximize fitness. Scope and Conclusions This paper reviews recently identified mechanisms, both systems-level and molecular, that modulate robustness, and discusses their implications for the optimization of plant fitness. Robustness in living systems arises from the structure of genetic networks, the specific molecular functions of the underlying genes, and their interactions. This very same network responsible for the robustness of specific developmental states also has to be built such that it enables plastic yet robust shifts in response to environmental changes. In plants, the interactions and functions of signal transduction pathways activated by phytohormones and the tendency for plants to tolerate whole-genome duplications, tandem gene duplication and hybridization are emerging as major regulators of robustness in development. Despite their obvious implications for plant evolution and plant breeding, the mechanistic underpinnings by which plants modulate precise levels of robustness, plasticity and evolvability in networks controlling different phenotypes are under-studied. PMID:26473020

Fuzzy robust credibility-constrained programming for environmental management and planning.

PubMed

Zhang, Yimei; Hang, Guohe

2010-06-01

In this study, a fuzzy robust credibility-constrained programming (FRCCP) is developed and applied to the planning for waste management systems. It incorporates the concepts of credibility-based chance-constrained programming and robust programming within an optimization framework. The developed method can reflect uncertainties presented as possibility-density by fuzzy-membership functions. Fuzzy credibility constraints are transformed to the crisp equivalents with different credibility levels, and ordinary fuzzy inclusion constraints are determined by their robust deterministic constraints by setting a-cut levels. The FRCCP method can provide different system costs under different credibility levels (lambda). From the results of sensitivity analyses, the operation cost of the landfill is a critical parameter. For the management, any factors that would induce cost fluctuation during landfilling operation would deserve serious observation and analysis. By FRCCP, useful solutions can be obtained to provide decision-making support for long-term planning of solid waste management systems. It could be further enhanced through incorporating methods of inexact analysis into its framework. It can also be applied to other environmental management problems.

Scaling environmental change through the community level: a trait-based response-and-effect framework for plants

Treesearch

Katharine N. Suding; Sandra Lavorel; F. Stuart Chapin; Johannes H.C. Cornelissen; Sandra Diaz; Eric Garnier; Deborah Goldberg; David U. Hooper; Stephen T. Jackson; Marie-Laure Navas

2008-01-01

Predicting ecosystem responses to global change is a major challenge in ecology. A critical step in that challenge is to understand how changing environmental conditions influence processes across levels of ecological organization. While direct scaling from individual to ecosystem dynamics can lead to robust and mechanistic predictions, new approaches are needed to...

Ultraviolet Light Surface Treatment as an Environmentally Benign Process for Production, Maintenance and Repair of Military Composite Structures

NASA Astrophysics Data System (ADS)

Drzal, Lawrence T.

2002-02-01

The principal objective of this work is to develop a low-cost, high-speed, environmentally benign, dry surface treatment method for production, and repair of military composite structures using ultraviolet (UV) light in ambient air. The potential advantage of this method is that it would eliminate volatile organic wastes (VOCs), reduce or eliminate the use of solutions and detergents, and provide a robust surface that would enhance or eliminate the use of solutions and detergents, and provide a robust surface that would enhance the wetting and spreading of paints, coatings and adhesives on polymeric and inorganic surfaces treated by this method. A manufacturing base for UV production equipment is in place although not for this application. There is a need for development of an environmentally friendly, cost effective as well as a robust surface treatment method that can clean a surface as well as create a beneficial chemistry for painting and produce optimum adhesive bonding of polymers, polymer composites and metal surfaces. With this in mind, three main technical objectives were sought in the work. The first objective was to determine the usefulness of UV and UV/O(3) to surface treatments to clean and chemically modify the surface of typical PMCs used in DOD systems. The second objective was to determine the effectiveness of this surface preparation for production and/or repair of adhesively bonded, painted and/or coated polymer matrix composite structures. Finally, a determination of the environmental and performance benefits of this method as a new environmentally benign processing method for the production and/or re air of adhesively SERDP, SERDP collection, robust surface, polymeric surface, inorganic surface, volatile organic compounds (VOC) emissions.

Improving Ecological Response Monitoring of Environmental Flows

NASA Astrophysics Data System (ADS)

King, Alison J.; Gawne, Ben; Beesley, Leah; Koehn, John D.; Nielsen, Daryl L.; Price, Amina

2015-05-01

Environmental flows are now an important restoration technique in flow-degraded rivers, and with the increasing public scrutiny of their effectiveness and value, the importance of undertaking scientifically robust monitoring is now even more critical. Many existing environmental flow monitoring programs have poorly defined objectives, nonjustified indicator choices, weak experimental designs, poor statistical strength, and often focus on outcomes from a single event. These negative attributes make them difficult to learn from. We provide practical recommendations that aim to improve the performance, scientific robustness, and defensibility of environmental flow monitoring programs. We draw on the literature and knowledge gained from working with stakeholders and managers to design, implement, and monitor a range of environmental flow types. We recommend that (1) environmental flow monitoring programs should be implemented within an adaptive management framework; (2) objectives of environmental flow programs should be well defined, attainable, and based on an agreed conceptual understanding of the system; (3) program and intervention targets should be attainable, measurable, and inform program objectives; (4) intervention monitoring programs should improve our understanding of flow-ecological responses and related conceptual models; (5) indicator selection should be based on conceptual models, objectives, and prioritization approaches; (6) appropriate monitoring designs and statistical tools should be used to measure and determine ecological response; (7) responses should be measured within timeframes that are relevant to the indicator(s); (8) watering events should be treated as replicates of a larger experiment; (9) environmental flow outcomes should be reported using a standard suite of metadata. Incorporating these attributes into future monitoring programs should ensure their outcomes are transferable and measured with high scientific credibility.

Environmental Noise, Genetic Diversity and the Evolution of Evolvability and Robustness in Model Gene Networks

PubMed Central

Steiner, Christopher F.

2012-01-01

The ability of organisms to adapt and persist in the face of environmental change is accepted as a fundamental feature of natural systems. More contentious is whether the capacity of organisms to adapt (or “evolvability”) can itself evolve and the mechanisms underlying such responses. Using model gene networks, I provide evidence that evolvability emerges more readily when populations experience positively autocorrelated environmental noise (red noise) compared to populations in stable or randomly varying (white noise) environments. Evolvability was correlated with increasing genetic robustness to effects on network viability and decreasing robustness to effects on phenotypic expression; populations whose networks displayed greater viability robustness and lower phenotypic robustness produced more additive genetic variation and adapted more rapidly in novel environments. Patterns of selection for robustness varied antagonistically with epistatic effects of mutations on viability and phenotypic expression, suggesting that trade-offs between these properties may constrain their evolutionary responses. Evolution of evolvability and robustness was stronger in sexual populations compared to asexual populations indicating that enhanced genetic variation under fluctuating selection combined with recombination load is a primary driver of the emergence of evolvability. These results provide insight into the mechanisms potentially underlying rapid adaptation as well as the environmental conditions that drive the evolution of genetic interactions. PMID:23284934

Robust Design of Biological Circuits: Evolutionary Systems Biology Approach

PubMed Central

Chen, Bor-Sen; Hsu, Chih-Yuan; Liou, Jing-Jia

2011-01-01

Artificial gene circuits have been proposed to be embedded into microbial cells that function as switches, timers, oscillators, and the Boolean logic gates. Building more complex systems from these basic gene circuit components is one key advance for biologic circuit design and synthetic biology. However, the behavior of bioengineered gene circuits remains unstable and uncertain. In this study, a nonlinear stochastic system is proposed to model the biological systems with intrinsic parameter fluctuations and environmental molecular noise from the cellular context in the host cell. Based on evolutionary systems biology algorithm, the design parameters of target gene circuits can evolve to specific values in order to robustly track a desired biologic function in spite of intrinsic and environmental noise. The fitness function is selected to be inversely proportional to the tracking error so that the evolutionary biological circuit can achieve the optimal tracking mimicking the evolutionary process of a gene circuit. Finally, several design examples are given in silico with the Monte Carlo simulation to illustrate the design procedure and to confirm the robust performance of the proposed design method. The result shows that the designed gene circuits can robustly track desired behaviors with minimal errors even with nontrivial intrinsic and external noise. PMID:22187523

Robust design of biological circuits: evolutionary systems biology approach.

PubMed

Chen, Bor-Sen; Hsu, Chih-Yuan; Liou, Jing-Jia

2011-01-01

Artificial gene circuits have been proposed to be embedded into microbial cells that function as switches, timers, oscillators, and the Boolean logic gates. Building more complex systems from these basic gene circuit components is one key advance for biologic circuit design and synthetic biology. However, the behavior of bioengineered gene circuits remains unstable and uncertain. In this study, a nonlinear stochastic system is proposed to model the biological systems with intrinsic parameter fluctuations and environmental molecular noise from the cellular context in the host cell. Based on evolutionary systems biology algorithm, the design parameters of target gene circuits can evolve to specific values in order to robustly track a desired biologic function in spite of intrinsic and environmental noise. The fitness function is selected to be inversely proportional to the tracking error so that the evolutionary biological circuit can achieve the optimal tracking mimicking the evolutionary process of a gene circuit. Finally, several design examples are given in silico with the Monte Carlo simulation to illustrate the design procedure and to confirm the robust performance of the proposed design method. The result shows that the designed gene circuits can robustly track desired behaviors with minimal errors even with nontrivial intrinsic and external noise.

Cooperative vehicles for robust traffic congestion reduction: An analysis based on algorithmic, environmental and agent behavioral factors

PubMed Central

Desai, Prajakta; Desai, Aniruddha

2017-01-01

Traffic congestion continues to be a persistent problem throughout the world. As vehicle-to-vehicle communication develops, there is an opportunity of using cooperation among close proximity vehicles to tackle the congestion problem. The intuition is that if vehicles could cooperate opportunistically when they come close enough to each other, they could, in effect, spread themselves out among alternative routes so that vehicles do not all jam up on the same roads. Our previous work proposed a decentralized multiagent based vehicular congestion management algorithm entitled Congestion Avoidance and Route Allocation using Virtual Agent Negotiation (CARAVAN), wherein the vehicles acting as intelligent agents perform cooperative route allocation using inter-vehicular communication. This paper focuses on evaluating the practical applicability of this approach by testing its robustness and performance (in terms of travel time reduction), across variations in: (a) environmental parameters such as road network topology and configuration; (b) algorithmic parameters such as vehicle agent preferences and route cost/preference multipliers; and (c) agent-related parameters such as equipped/non-equipped vehicles and compliant/non-compliant agents. Overall, the results demonstrate the adaptability and robustness of the decentralized cooperative vehicles approach to providing global travel time reduction using simple local coordination strategies. PMID:28792513

Cooperative vehicles for robust traffic congestion reduction: An analysis based on algorithmic, environmental and agent behavioral factors.

PubMed

Desai, Prajakta; Loke, Seng W; Desai, Aniruddha

2017-01-01

Traffic congestion continues to be a persistent problem throughout the world. As vehicle-to-vehicle communication develops, there is an opportunity of using cooperation among close proximity vehicles to tackle the congestion problem. The intuition is that if vehicles could cooperate opportunistically when they come close enough to each other, they could, in effect, spread themselves out among alternative routes so that vehicles do not all jam up on the same roads. Our previous work proposed a decentralized multiagent based vehicular congestion management algorithm entitled Congestion Avoidance and Route Allocation using Virtual Agent Negotiation (CARAVAN), wherein the vehicles acting as intelligent agents perform cooperative route allocation using inter-vehicular communication. This paper focuses on evaluating the practical applicability of this approach by testing its robustness and performance (in terms of travel time reduction), across variations in: (a) environmental parameters such as road network topology and configuration; (b) algorithmic parameters such as vehicle agent preferences and route cost/preference multipliers; and (c) agent-related parameters such as equipped/non-equipped vehicles and compliant/non-compliant agents. Overall, the results demonstrate the adaptability and robustness of the decentralized cooperative vehicles approach to providing global travel time reduction using simple local coordination strategies.

Supervisor Expertise, Teacher Autonomy and Environmental Robustness.

ERIC Educational Resources Information Center

Street, Sue; Licata, Joseph W.

This study examines the collective perspective that teachers in schools have about the relationship between the supervisory expertise of the principal, teacher work autonomy, and school environmental robustness. Supervisory expertise, and teachers' satisfaction with the supervisory process, is measured with the "Fidelity of Supervision…

A queuing-theory-based interval-fuzzy robust two-stage programming model for environmental management under uncertainty

NASA Astrophysics Data System (ADS)

Sun, Y.; Li, Y. P.; Huang, G. H.

2012-06-01

In this study, a queuing-theory-based interval-fuzzy robust two-stage programming (QB-IRTP) model is developed through introducing queuing theory into an interval-fuzzy robust two-stage (IRTP) optimization framework. The developed QB-IRTP model can not only address highly uncertain information for the lower and upper bounds of interval parameters but also be used for analysing a variety of policy scenarios that are associated with different levels of economic penalties when the promised targets are violated. Moreover, it can reflect uncertainties in queuing theory problems. The developed method has been applied to a case of long-term municipal solid waste (MSW) management planning. Interval solutions associated with different waste-generation rates, different waiting costs and different arriving rates have been obtained. They can be used for generating decision alternatives and thus help managers to identify desired MSW management policies under various economic objectives and system reliability constraints.

Multi-Contextual Segregation and Environmental Justice Research: Toward Fine-Scale Spatiotemporal Approaches.

PubMed

Park, Yoo Min; Kwan, Mei-Po

2017-10-10

Many environmental justice studies have sought to examine the effect of residential segregation on unequal exposure to environmental factors among different social groups, but little is known about how segregation in non-residential contexts affects such disparity. Based on a review of the relevant literature, this paper discusses the limitations of traditional residence-based approaches in examining the association between socioeconomic or racial/ethnic segregation and unequal environmental exposure in environmental justice research. It emphasizes that future research needs to go beyond residential segregation by considering the full spectrum of segregation experienced by people in various geographic and temporal contexts of everyday life. Along with this comprehensive understanding of segregation, the paper also highlights the importance of assessing environmental exposure at a high spatiotemporal resolution in environmental justice research. The successful integration of a comprehensive concept of segregation, high-resolution data and fine-grained spatiotemporal approaches to assessing segregation and environmental exposure would provide more nuanced and robust findings on the associations between segregation and disparities in environmental exposure and their health impacts. Moreover, it would also contribute to significantly expanding the scope of environmental justice research.

Environmental Assessment for BRAC Actions for the 137th Airlift Wing Relocation, KC-135R Aircraft Robust, and Associated Construction at the 507th Air Refueling Wing Tinker Air Force Base, Oklahoma

DTIC Science & Technology

2007-10-01

increase in both civilian and military personnel. In the 1970s, the base took over management of new weapons including the A-7D Corsair , the E-3A...one- bay hangar that would be utilized for scheduled maintenance. The existing ramp would be expanded to provide hangar access. Buildings 1041 and... Bay Hangar KC-1󈧧R Aircraft and 137th Airlift Wing Relocation The United States Air Force has prepared three Environmental Assessments (EAs

Meeting in Florida: Using Asymmetric Flow Field-Flow Fractionation (AF4) to Determine C60 Colloidal Size Distributions

EPA Science Inventory

The study of nanomaterials in environmental systems requires robust and specific analytical methods. Analytical methods which discriminate based on particle size and molecular composition are not widely available. Asymmetric Flow Field-Flow Fractionation (AF4) is a separation...

Optimisation in the Design of Environmental Sensor Networks with Robustness Consideration

PubMed Central

Budi, Setia; de Souza, Paulo; Timms, Greg; Malhotra, Vishv; Turner, Paul

2015-01-01

This work proposes the design of Environmental Sensor Networks (ESN) through balancing robustness and redundancy. An Evolutionary Algorithm (EA) is employed to find the optimal placement of sensor nodes in the Region of Interest (RoI). Data quality issues are introduced to simulate their impact on the performance of the ESN. Spatial Regression Test (SRT) is also utilised to promote robustness in data quality of the designed ESN. The proposed method provides high network representativeness (fit for purpose) with minimum sensor redundancy (cost), and ensures robustness by enabling the network to continue to achieve its objectives when some sensors fail. PMID:26633392

A Robust Approach to Risk Assessment Based on Species Sensitivity Distributions.

PubMed

Monti, Gianna S; Filzmoser, Peter; Deutsch, Roland C

2018-05-03

The guidelines for setting environmental quality standards are increasingly based on probabilistic risk assessment due to a growing general awareness of the need for probabilistic procedures. One of the commonly used tools in probabilistic risk assessment is the species sensitivity distribution (SSD), which represents the proportion of species affected belonging to a biological assemblage as a function of exposure to a specific toxicant. Our focus is on the inverse use of the SSD curve with the aim of estimating the concentration, HCp, of a toxic compound that is hazardous to p% of the biological community under study. Toward this end, we propose the use of robust statistical methods in order to take into account the presence of outliers or apparent skew in the data, which may occur without any ecological basis. A robust approach exploits the full neighborhood of a parametric model, enabling the analyst to account for the typical real-world deviations from ideal models. We examine two classic HCp estimation approaches and consider robust versions of these estimators. In addition, we also use data transformations in conjunction with robust estimation methods in case of heteroscedasticity. Different scenarios using real data sets as well as simulated data are presented in order to illustrate and compare the proposed approaches. These scenarios illustrate that the use of robust estimation methods enhances HCp estimation. © 2018 Society for Risk Analysis.

The Nitrogen Balancing Act: Tracking the Environmental Performance of Food Production

PubMed Central

McLellan, Eileen L; Cassman, Kenneth G; Eagle, Alison J; Woodbury, Peter B; Sela, Shai; Tonitto, Christina; Marjerison, Rebecca D; van Es, Harold M

2018-01-01

Abstract Farmers, food supply-chain entities, and policymakers need a simple but robust indicator to demonstrate progress toward reducing nitrogen pollution associated with food production. We show that nitrogen balance—the difference between nitrogen inputs and nitrogen outputs in an agricultural production system—is a robust measure of nitrogen losses that is simple to calculate, easily understood, and based on readily available farm data. Nitrogen balance provides farmers with a means of demonstrating to an increasingly concerned public that they are succeeding in reducing nitrogen losses while also improving the overall sustainability of their farming operation. Likewise, supply-chain companies and policymakers can use nitrogen balance to track progress toward sustainability goals. We describe the value of nitrogen balance in translating environmental targets into actionable goals for farmers and illustrate the potential roles of science, policy, and agricultural support networks in helping farmers achieve them. PMID:29662247

Environmental Impact: Reinforce a Culture of Continuous Learning with These Key Elements

ERIC Educational Resources Information Center

Edwards, Brian; Gammell, Jessica

2017-01-01

Fostering a robust professional learning culture in schools is vital for attracting and retaining high-caliber talent. Education leaders are looking for guidance on how to establish and sustain an environment that fosters continuous learning. Based on their experience in helping educators design and implement professional learning systems, the…

ISFET Based Microsensors for Environmental Monitoring

PubMed Central

Jimenez-Jorquera, Cecilia; Orozco, Jahir; Baldi, Antoni

2010-01-01

The use of microsensors for in-field monitoring of environmental parameters is gaining interest due to their advantages over conventional sensors. Among them microsensors based on semiconductor technology offer additional advantages such as small size, robustness, low output impedance and rapid response. Besides, the technology used allows integration of circuitry and multiple sensors in the same substrate and accordingly they can be implemented in compact probes for particular applications e.g., in situ monitoring and/or on-line measurements. In the field of microsensors for environmental applications, Ion Selective Field Effect Transistors (ISFETs) have a special interest. They are particularly helpful for measuring pH and other ions in small volumes and they can be integrated in compact flow cells for continuous measurements. In this paper the technologies used to fabricate ISFETs and a review of the role of ISFETs in the environmental field are presented. PMID:22315527

Multi-Contextual Segregation and Environmental Justice Research: Toward Fine-Scale Spatiotemporal Approaches

PubMed Central

Park, Yoo Min; Kwan, Mei-Po

2017-01-01

Many environmental justice studies have sought to examine the effect of residential segregation on unequal exposure to environmental factors among different social groups, but little is known about how segregation in non-residential contexts affects such disparity. Based on a review of the relevant literature, this paper discusses the limitations of traditional residence-based approaches in examining the association between socioeconomic or racial/ethnic segregation and unequal environmental exposure in environmental justice research. It emphasizes that future research needs to go beyond residential segregation by considering the full spectrum of segregation experienced by people in various geographic and temporal contexts of everyday life. Along with this comprehensive understanding of segregation, the paper also highlights the importance of assessing environmental exposure at a high spatiotemporal resolution in environmental justice research. The successful integration of a comprehensive concept of segregation, high-resolution data and fine-grained spatiotemporal approaches to assessing segregation and environmental exposure would provide more nuanced and robust findings on the associations between segregation and disparities in environmental exposure and their health impacts. Moreover, it would also contribute to significantly expanding the scope of environmental justice research. PMID:28994744

Posture recognition based on fuzzy logic for home monitoring of the elderly.

PubMed

Brulin, Damien; Benezeth, Yannick; Courtial, Estelle

2012-09-01

We propose in this paper a computer vision-based posture recognition method for home monitoring of the elderly. The proposed system performs human detection prior to the posture analysis; posture recognition is performed only on a human silhouette. The human detection approach has been designed to be robust to different environmental stimuli. Thus, posture is analyzed with simple and efficient features that are not designed to manage constraints related to the environment but only designed to describe human silhouettes. The posture recognition method, based on fuzzy logic, identifies four static postures and is robust to variation in the distance between the camera and the person, and to the person's morphology. With an accuracy of 74.29% of satisfactory posture recognition, this approach can detect emergency situations such as a fall within a health smart home.

Local Environmental Grassroots Activism: Contributions from Environmental Psychology, Sociology and Politics

PubMed Central

Mihaylov, Nikolay L.; Perkins, Douglas D.

2015-01-01

Local environmental grassroots activism is robust and globally ubiquitous despite the ebbs and flows of the general environmental movement. In this review we synthesize social movement, environmental politics, and environmental psychology literatures to answer the following questions: How does the environment emerge as a topic for community action and how a particular environmental discourse (preservation, conservation, public health, Deep Ecology, justice, localism and other responses to modernization and development) becomes dominant? How does a community coalesce around the environmental issue and its particular framing? What is the relationship between local and supralocal (regional, national, global) activism? We contrast “Not in My Back Yard” (NIMBY) activism and environmental liberation and discuss the significance of local knowledge and scale, nature as an issue for activism, place attachment and its disruption, and place-based power inequalities. Environmental psychology contributions to established scholarship on environmental activism are proposed: the components of place attachment are conceptualized in novel ways and a continuous dweller and activist place attachment is elaborated. PMID:25806672

Local environmental grassroots activism: contributions from environmental psychology, sociology and politics.

PubMed

Mihaylov, Nikolay L; Perkins, Douglas D

2015-03-23

Local environmental grassroots activism is robust and globally ubiquitous despite the ebbs and flows of the general environmental movement. In this review we synthesize social movement, environmental politics, and environmental psychology literatures to answer the following questions: How does the environment emerge as a topic for community action and how a particular environmental discourse (preservation, conservation, public health, Deep Ecology, justice, localism and other responses to modernization and development) becomes dominant? How does a community coalesce around the environmental issue and its particular framing? What is the relationship between local and supralocal (regional, national, global) activism? We contrast "Not in My Back Yard" (NIMBY) activism and environmental liberation and discuss the significance of local knowledge and scale, nature as an issue for activism, place attachment and its disruption, and place-based power inequalities. Environmental psychology contributions to established scholarship on environmental activism are proposed: the components of place attachment are conceptualized in novel ways and a continuous dweller and activist place attachment is elaborated.

On the Interplay between the Evolvability and Network Robustness in an Evolutionary Biological Network: A Systems Biology Approach

PubMed Central

Chen, Bor-Sen; Lin, Ying-Po

2011-01-01

In the evolutionary process, the random transmission and mutation of genes provide biological diversities for natural selection. In order to preserve functional phenotypes between generations, gene networks need to evolve robustly under the influence of random perturbations. Therefore, the robustness of the phenotype, in the evolutionary process, exerts a selection force on gene networks to keep network functions. However, gene networks need to adjust, by variations in genetic content, to generate phenotypes for new challenges in the network’s evolution, ie, the evolvability. Hence, there should be some interplay between the evolvability and network robustness in evolutionary gene networks. In this study, the interplay between the evolvability and network robustness of a gene network and a biochemical network is discussed from a nonlinear stochastic system point of view. It was found that if the genetic robustness plus environmental robustness is less than the network robustness, the phenotype of the biological network is robust in evolution. The tradeoff between the genetic robustness and environmental robustness in evolution is discussed from the stochastic stability robustness and sensitivity of the nonlinear stochastic biological network, which may be relevant to the statistical tradeoff between bias and variance, the so-called bias/variance dilemma. Further, the tradeoff could be considered as an antagonistic pleiotropic action of a gene network and discussed from the systems biology perspective. PMID:22084563

Uncertainty analysis and robust trajectory linearization control of a flexible air-breathing hypersonic vehicle

NASA Astrophysics Data System (ADS)

Pu, Zhiqiang; Tan, Xiangmin; Fan, Guoliang; Yi, Jianqiang

2014-08-01

Flexible air-breathing hypersonic vehicles feature significant uncertainties which pose huge challenges to robust controller designs. In this paper, four major categories of uncertainties are analyzed, that is, uncertainties associated with flexible effects, aerodynamic parameter variations, external environmental disturbances, and control-oriented modeling errors. A uniform nonlinear uncertainty model is explored for the first three uncertainties which lumps all uncertainties together and consequently is beneficial for controller synthesis. The fourth uncertainty is additionally considered in stability analysis. Based on these analyses, the starting point of the control design is to decompose the vehicle dynamics into five functional subsystems. Then a robust trajectory linearization control (TLC) scheme consisting of five robust subsystem controllers is proposed. In each subsystem controller, TLC is combined with the extended state observer (ESO) technique for uncertainty compensation. The stability of the overall closed-loop system with the four aforementioned uncertainties and additional singular perturbations is analyzed. Particularly, the stability of nonlinear ESO is also discussed from a Liénard system perspective. At last, simulations demonstrate the great control performance and the uncertainty rejection ability of the robust scheme.

A facile fluorescent "turn-off" method for sensing paraquat based on pyranine-paraquat interaction

NASA Astrophysics Data System (ADS)

Zhao, Zuzhi; Zhang, Fengwei; Zhang, Zipin

2018-06-01

Development of a technically simple yet effective method for paraquat (PQ) detection is of great importance due to its high clinical and environmental relevance. In this study, we developed a pyranine-based fluorescent "turn-off" method for PQ sensing based on pyranine-PQ interaction. We investigated the dependence of analytical performance of this method on the experimental conditions, such as the ion strength, medium pH, and so on. Under the optimized conditions, the method is sensitive and selective, and could be used for PQ detection in real-world sample. This study essentially provides a readily accessible fluorescent system for PQ sensing which is cheap, robust, and technically simple, and it is envisaged to find more interesting clinical and environmental applications.

Review: Deciphering animal robustness. A synthesis to facilitate its use in livestock breeding and management.

PubMed

Friggens, N C; Blanc, F; Berry, D P; Puillet, L

2017-12-01

As the environments in which livestock are reared become more variable, animal robustness becomes an increasingly valuable attribute. Consequently, there is increasing focus on managing and breeding for it. However, robustness is a difficult phenotype to properly characterise because it is a complex trait composed of multiple components, including dynamic elements such as the rates of response to, and recovery from, environmental perturbations. In this review, the following definition of robustness is used: the ability, in the face of environmental constraints, to carry on doing the various things that the animal needs to do to favour its future ability to reproduce. The different elements of this definition are discussed to provide a clearer understanding of the components of robustness. The implications for quantifying robustness are that there is no single measure of robustness but rather that it is the combination of multiple and interacting component mechanisms whose relative value is context dependent. This context encompasses both the prevailing environment and the prevailing selection pressure. One key issue for measuring robustness is to be clear on the use to which the robustness measurements will employed. If the purpose is to identify biomarkers that may be useful for molecular phenotyping or genotyping, the measurements should focus on the physiological mechanisms underlying robustness. However, if the purpose of measuring robustness is to quantify the extent to which animals can adapt to limiting conditions then the measurements should focus on the life functions, the trade-offs between them and the animal's capacity to increase resource acquisition. The time-related aspect of robustness also has important implications. Single time-point measurements are of limited value because they do not permit measurement of responses to (and recovery from) environmental perturbations. The exception being single measurements of the accumulated consequence of a good (or bad) adaptive capacity, such as productive longevity and lifetime efficiency. In contrast, repeated measurements over time have a high potential for quantification of the animal's ability to cope with environmental challenges. Thus, we should be able to quantify differences in adaptive capacity from the data that are increasingly becoming available with the deployment of automated monitoring technology on farm. The challenge for future management and breeding will be how to combine various proxy measures to obtain reliable estimates of robustness components in large populations. A key aspect for achieving this is to define phenotypes from consideration of their biological properties and not just from available measures.

Ceramic Integration Technologies for Energy and Aerospace Applications

NASA Technical Reports Server (NTRS)

Singh, Mrityunjay; Asthana, Ralph N.

2007-01-01

Robust and affordable integration technologies for advanced ceramics are required to improve the performance, reliability, efficiency, and durability of components, devices, and systems based on them in a wide variety of energy, aerospace, and environmental applications. Many thermochemical and thermomechanical factors including joint design, analysis, and optimization must be considered in integration of similar and dissimilar material systems.

Modulated Acquisition of Spatial Distortion Maps

PubMed Central

Volkov, Alexey; Gros, Jerneja Žganec; Žganec, Mario; Javornik, Tomaž; Švigelj, Aleš

2013-01-01

This work discusses a novel approach to image acquisition which improves the robustness of captured data required for 3D range measurements. By applying a pseudo-random code modulation to sequential acquisition of projected patterns the impact of environmental factors such as ambient light and mutual interference is significantly reduced. The proposed concept has been proven with an experimental range sensor based on the laser triangulation principle. The proposed design can potentially enhance the use of this principle to a variety of outdoor applications, such as autonomous vehicles, pedestrians' safety, collision avoidance, and many other tasks, where robust real-time distance detection in real world environment is crucial. PMID:23966196

Modulated acquisition of spatial distortion maps.

PubMed

Volkov, Alexey; Gros, Jerneja Zganec; Zganec, Mario; Javornik, Tomaž; Svigelj, Aleš

2013-08-21

This work discusses a novel approach to image acquisition which improves the robustness of captured data required for 3D range measurements. By applying a pseudo-random code modulation to sequential acquisition of projected patterns the impact of environmental factors such as ambient light and mutual interference is significantly reduced. The proposed concept has been proven with an experimental range sensor based on the laser triangulation principle. The proposed design can potentially enhance the use of this principle to a variety of outdoor applications, such as autonomous vehicles, pedestrians' safety, collision avoidance, and many other tasks, where robust real-time distance detection in real world environment is crucial.

Water-based acrylate copolymer/silica hybrids for facile preparation of robust and durable superhydrophobic coatings

NASA Astrophysics Data System (ADS)

Li, Meng; Li, Yu; Xue, Fang; Jing, Xinli

2018-07-01

Resin based superhydrophobic coatings are effective to construct robust superhydrophobic surfaces on large scale without limitation of substrates. However, for most of the common resin based superhydrophobic coatings, it is inevitable to deteriorate environmental or health problems due to release of a large amount volatile solvents. In this work, a kind of water-based organic/inorganic hybrid consisted of acrylate copolymers and superhydrophobic silica nanoparticles were synthesized. The highly water-repellent silica nanoparticles were successfully involved into the aqueous dispersion of acrylate copolymers without additional surfactants. The as-synthesized hybrids simultaneously retain the excellent film-forming property of acrylate resins and amplify the contributions of low surface energy nanoparticles to the superhydrophobicity. Robust superhydrophobic coatings (CA > 160°, CA < 7°) with high adhesion strength, good scratch-resistance and excellent abrasion-resistance were constructed using the synthesized hybrids with significantly reduced content of low surface energy particles and organic solvent. The hybrid coating can stand abrasion up to 300 cycles with a fine sand paper and up to 1200 cycles under rough sand paper abrasion. Benefited from its good water-repellence property, the hybrid coating with a water-based formula not only showed improved water-resistance in comparison with commercial products; but also displayed attractive performances in self-cleaning and oil/water separation processes.

A Robust Crowdsourcing-Based Indoor Localization System.

PubMed

Zhou, Baoding; Li, Qingquan; Mao, Qingzhou; Tu, Wei

2017-04-14

WiFi fingerprinting-based indoor localization has been widely used due to its simplicity and can be implemented on the smartphones. The major drawback of WiFi fingerprinting is that the radio map construction is very labor-intensive and time-consuming. Another drawback of WiFi fingerprinting is the Received Signal Strength (RSS) variance problem, caused by environmental changes and device diversity. RSS variance severely degrades the localization accuracy. In this paper, we propose a robust crowdsourcing-based indoor localization system (RCILS). RCILS can automatically construct the radio map using crowdsourcing data collected by smartphones. RCILS abstracts the indoor map as the semantics graph in which the edges are the possible user paths and the vertexes are the location where users may take special activities. RCILS extracts the activity sequence contained in the trajectories by activity detection and pedestrian dead-reckoning. Based on the semantics graph and activity sequence, crowdsourcing trajectories can be located and a radio map is constructed based on the localization results. For the RSS variance problem, RCILS uses the trajectory fingerprint model for indoor localization. During online localization, RCILS obtains an RSS sequence and realizes localization by matching the RSS sequence with the radio map. To evaluate RCILS, we apply RCILS in an office building. Experiment results demonstrate the efficiency and robustness of RCILS.

A Robust Crowdsourcing-Based Indoor Localization System

PubMed Central

Zhou, Baoding; Li, Qingquan; Mao, Qingzhou; Tu, Wei

2017-01-01

WiFi fingerprinting-based indoor localization has been widely used due to its simplicity and can be implemented on the smartphones. The major drawback of WiFi fingerprinting is that the radio map construction is very labor-intensive and time-consuming. Another drawback of WiFi fingerprinting is the Received Signal Strength (RSS) variance problem, caused by environmental changes and device diversity. RSS variance severely degrades the localization accuracy. In this paper, we propose a robust crowdsourcing-based indoor localization system (RCILS). RCILS can automatically construct the radio map using crowdsourcing data collected by smartphones. RCILS abstracts the indoor map as the semantics graph in which the edges are the possible user paths and the vertexes are the location where users may take special activities. RCILS extracts the activity sequence contained in the trajectories by activity detection and pedestrian dead-reckoning. Based on the semantics graph and activity sequence, crowdsourcing trajectories can be located and a radio map is constructed based on the localization results. For the RSS variance problem, RCILS uses the trajectory fingerprint model for indoor localization. During online localization, RCILS obtains an RSS sequence and realizes localization by matching the RSS sequence with the radio map. To evaluate RCILS, we apply RCILS in an office building. Experiment results demonstrate the efficiency and robustness of RCILS. PMID:28420108

Building a Robust 21st Century Chemical Testing Program at the U.S. Environmental Protection Agency: Recommendations for Strengthening Scientific Engagement

PubMed Central

Dantzker, Heather C.; Portier, Christopher J.

2014-01-01

Background: Biological pathway-based chemical testing approaches are central to the National Research Council’s vision for 21st century toxicity testing. Approaches such as high-throughput in vitro screening offer the potential to evaluate thousands of chemicals faster and cheaper than ever before and to reduce testing on laboratory animals. Collaborative scientific engagement is important in addressing scientific issues arising in new federal chemical testing programs and for achieving stakeholder support of their use. Objectives: We present two recommendations specifically focused on increasing scientific engagement in the U.S. Environmental Protection Agency (EPA) ToxCast™ initiative. Through these recommendations we seek to bolster the scientific foundation of federal chemical testing efforts such as ToxCast™ and the public health decisions that rely upon them. Discussion: Environmental Defense Fund works across disciplines and with diverse groups to improve the science underlying environmental health decisions. We propose that the U.S. EPA can strengthen the scientific foundation of its new chemical testing efforts and increase support for them in the scientific research community by a) expanding and diversifying scientific input into the development and application of new chemical testing methods through collaborative workshops, and b) seeking out mutually beneficial research partnerships. Conclusions: Our recommendations provide concrete actions for the U.S. EPA to increase and diversify engagement with the scientific research community in its ToxCast™ initiative. We believe that such engagement will help ensure that new chemical testing data are scientifically robust and that the U.S. EPA gains the support and acceptance needed to sustain new testing efforts to protect public health. Citation: McPartland J, Dantzker HC, Portier CJ. 2015. Building a robust 21st century chemical testing program at the U.S. Environmental Protection Agency: recommendations for strengthening scientific engagement. Environ Health Perspect 123:1–5; http://dx.doi.org/10.1289/ehp.1408601 PMID:25343778

A novel scattering switch-on detection technique for target-induced plasmon-coupling based sensing by single-particle optical anisotropy imaging.

PubMed

Peng, Lan; Cao, Xuan; Xiong, Bin; He, Yan; Yeung, Edward S

2016-06-18

We reported a novel scattering switch-on detection technique using flash-lamp polarization darkfield microscopy (FLPDM) for target-induced plasmon-coupling based sensing in homogeneous solution. With this method, we demonstrated sub-nM sensitivity for hydrogen sulfide (H2S) detection over a dynamic range of five orders of magnitude. This robust technique holds great promise for applications in toxic environmental pollutants and biological molecules.

How robust is a robust policy? A comparative analysis of alternative robustness metrics for supporting robust decision analysis.

NASA Astrophysics Data System (ADS)

Kwakkel, Jan; Haasnoot, Marjolijn

2015-04-01

In response to climate and socio-economic change, in various policy domains there is increasingly a call for robust plans or policies. That is, plans or policies that performs well in a very large range of plausible futures. In the literature, a wide range of alternative robustness metrics can be found. The relative merit of these alternative conceptualizations of robustness has, however, received less attention. Evidently, different robustness metrics can result in different plans or policies being adopted. This paper investigates the consequences of several robustness metrics on decision making, illustrated here by the design of a flood risk management plan. A fictitious case, inspired by a river reach in the Netherlands is used. The performance of this system in terms of casualties, damages, and costs for flood and damage mitigation actions is explored using a time horizon of 100 years, and accounting for uncertainties pertaining to climate change and land use change. A set of candidate policy options is specified up front. This set of options includes dike raising, dike strengthening, creating more space for the river, and flood proof building and evacuation options. The overarching aim is to design an effective flood risk mitigation strategy that is designed from the outset to be adapted over time in response to how the future actually unfolds. To this end, the plan will be based on the dynamic adaptive policy pathway approach (Haasnoot, Kwakkel et al. 2013) being used in the Dutch Delta Program. The policy problem is formulated as a multi-objective robust optimization problem (Kwakkel, Haasnoot et al. 2014). We solve the multi-objective robust optimization problem using several alternative robustness metrics, including both satisficing robustness metrics and regret based robustness metrics. Satisficing robustness metrics focus on the performance of candidate plans across a large ensemble of plausible futures. Regret based robustness metrics compare the performance of a candidate plan with the performance of other candidate plans across a large ensemble of plausible futures. Initial results suggest that the simplest satisficing metric, inspired by the signal to noise ratio, results in very risk averse solutions. Other satisficing metrics, which handle the average performance and the dispersion around the average separately, provide substantial additional insights into the trade off between the average performance, and the dispersion around this average. In contrast, the regret-based metrics enhance insight into the relative merits of candidate plans, while being less clear on the average performance or the dispersion around this performance. These results suggest that it is beneficial to use multiple robustness metrics when doing a robust decision analysis study. Haasnoot, M., J. H. Kwakkel, W. E. Walker and J. Ter Maat (2013). "Dynamic Adaptive Policy Pathways: A New Method for Crafting Robust Decisions for a Deeply Uncertain World." Global Environmental Change 23(2): 485-498. Kwakkel, J. H., M. Haasnoot and W. E. Walker (2014). "Developing Dynamic Adaptive Policy Pathways: A computer-assisted approach for developing adaptive strategies for a deeply uncertain world." Climatic Change.

Conversion Coatings for Aluminum Alloys by Chemical Vapor Deposition Mechanisms

NASA Technical Reports Server (NTRS)

Reye, John T.; McFadden, Lisa S.; Gatica, Jorge E.; Morales, Wilfredo

2004-01-01

With the rise of environmental awareness and the renewed importance of environmentally friendly processes, the United States Environmental Protection Agency has targeted surface pre-treatment processes based on chromates. Indeed, this process has been subject to regulations under the Clean Water Act as well as other environmental initiatives, and there is today a marked movement to phase the process out in the near future. Therefore, there is a clear need for new advances in coating technology that could provide practical options for replacing present industrial practices. Depending on the final application, such coatings might be required to be resistant to corrosion, act as chemically resistant coatings, or both. This research examined a chemical vapor deposition (CVD) mechanism to deposit uniform conversion coatings onto aluminum alloy substrates. Robust protocols based on solutions of aryl phosphate ester and multi-oxide conversion coating (submicron) films were successfully grown onto the aluminum alloy samples. These films were characterized by X-ray Photoelectron Spectroscopy (XPS). Preliminary results indicate the potential of this technology to replace aqueous-based chromate processes.

Application of an indicator based on taxonomic relatedness of ciliated protozoan assemblages for marine environmental assessment.

PubMed

Xu, Henglong; Jiang, Yong; Al-Rasheid, Khaled A S; Al-Farraj, Saleh A; Song, Weibo

2011-08-01

Ciliated protozoa play important roles in aquatic ecosystems especially regarding their functions in micro-food web and have many advantages in environmental assessment compared with most other eukaryotic organisms. The aims of this study were focused on analyzing the application of an indicator based on taxonomic relatedness of ciliated protozoan assemblages for marine environmental assessment. The spatial taxonomic patterns and diversity measures in response to physical-chemical variables were studied based on data from samples collected during 1-year cycle in the semi-enclosed Jiaozhou Bay, northern China. The spatial patterns of ciliate communities were significantly correlated with the changes of environmental status. The taxonomic distinctness (Δ*) and the average taxonomic distinctness (Δ+) were significantly negatively correlated with the changes of nutrients (e.g., nitrate nitrogen and soluble active phosphate; P<0.05). Pairwise indices of Δ+ and the variation in taxonomic distinctness (Λ+) showed a decreasing trend of departure from the expected taxonomic breadth in response to the eutrophication stress and anthropogenic impact. The taxonomic relatedness (especially the pairwise Δ+ and Λ+) indices of ciliate communities are robust as an indicator with scientifically operational value in marine environmental assessment.

Combining U.S.-based prioritization tools to improve screening level accountability for environmental impact: the case of the chemical manufacturing industry.

PubMed

Zhou, Xiaoying; Schoenung, Julie M

2009-12-15

There are two quantitative indicators that are most widely used to assess the extent of compliance of industrial facilities with environmental regulations: the quantity of hazardous waste generated and the amount of toxics released. These indicators, albeit useful in terms of some environmental monitoring, fail to account for direct or indirect effects on human and environmental health, especially when aggregating total quantity of releases for a facility or industry sector. Thus, there is a need for a more comprehensive approach that can prioritize a particular chemical (or industry sector) on the basis of its relevant environmental performance and impact on human health. Accordingly, the objective of the present study is to formulate an aggregation of tools that can simultaneously capture multiple effects and several environmental impact categories. This approach allows us to compare and combine results generated with the aid of select U.S.-based quantitative impact assessment tools, thereby supplementing compliance-based metrics such as data from the U.S. Toxic Release Inventory. A case study, which presents findings for the U.S. chemical manufacturing industry, is presented to illustrate the aggregation of these tools. Environmental impacts due to both upstream and manufacturing activities are also evaluated for each industry sector. The proposed combinatorial analysis allows for a more robust evaluation for rating and prioritizing the environmental impacts of industrial waste.

Environmentally Benign Production of Stretchable and Robust Superhydrophobic Silicone Monoliths.

PubMed

Davis, Alexander; Surdo, Salvatore; Caputo, Gianvito; Bayer, Ilker S; Athanassiou, Athanassia

2018-01-24

Superhydrophobic materials hold an enormous potential in sectors as important as aerospace, food industries, or biomedicine. Despite this great promise, the lack of environmentally friendly production methods and limited robustness remain the two most pertinent barriers to the scalability, large-area production, and widespread use of superhydrophobic materials. In this work, highly robust superhydrophobic silicone monoliths are produced through a scalable and environmentally friendly emulsion technique. It is first found that stable and surfactantless water-in-polydimethylsiloxane (PDMS) emulsions can be formed through mechanical mixing. Increasing the internal phase fraction of the precursor emulsion is found to increase porosity and microtexture of the final monoliths, rendering them superhydrophobic. Silica nanoparticles can also be dispersed in the aqueous internal phase to create micro/nanotextured monoliths, giving further improvements in superhydrophobicity. Due to the elastomeric nature of PDMS, superhydrophobicity can be maintained even while the material is mechanically strained or compressed. In addition, because of their self-similarity, the monoliths show outstanding robustness to knife-scratch, tape-peel, and finger-wipe tests, as well as rigorous sandpaper abrasion. Superhydrophobicity was also unchanged when exposed to adverse environmental conditions including corrosive solutions, UV light, extreme temperatures, and high-energy droplet impact. Finally, important properties for eventual adoption in real-world applications including self-cleaning, stain-repellence, and blood-repellence are demonstrated.

Review: ecotoxicity of organic and organo-metallic antifouling co-biocides and implications for environmental hazard and risk assessments in aquatic ecosystems.

PubMed

Martins, Samantha Eslava; Fillmann, Gilberto; Lillicrap, Adam; Thomas, Kevin V

2018-01-01

Hazard assessments of Irgarol 1051, diuron, 2-(thiocyanomethylthio)benzothiazole (TCMTB), dichloro-octylisothiazolin (DCOIT), chlorothalonil, dichlofluanid, thiram, zinc pyrithione, copper pyrithione, triphenylborane pyridine (TPBP), capsaicin, nonivamide, tralopyril and medetomidine were performed to establish robust environmental quality standards (EQS), based on predicted no effect concentrations (PNECs). Microalgae, zooplankton, fish and amphibians were the most sensitive ecological groups to all the antifoulants evaluated, especially in the early life stages. No differences were identified between freshwater and seawater species. The use of toxicity tests with non-standard species is encouraged because they increase the datasets, allowing EQS to be derived from probabilistic-based PNECs whilst reducing uncertainties. The global ban of tributyltin (TBT) has been heralded as a major environmental success; however, substitute antifoulants may also pose risks to aquatic ecosystems. Environmental risk assessments (ERAs) have driven decision-makings for regulating antifouling products, but in many countries there is still a lack of regulation of antifouling biocides which should be addressed.

A μ analysis-based, controller-synthesis framework for robust bioinspired visual navigation in less-structured environments.

PubMed

Keshavan, J; Gremillion, G; Escobar-Alvarez, H; Humbert, J S

2014-06-01

Safe, autonomous navigation by aerial microsystems in less-structured environments is a difficult challenge to overcome with current technology. This paper presents a novel visual-navigation approach that combines bioinspired wide-field processing of optic flow information with control-theoretic tools for synthesis of closed loop systems, resulting in robustness and performance guarantees. Structured singular value analysis is used to synthesize a dynamic controller that provides good tracking performance in uncertain environments without resorting to explicit pose estimation or extraction of a detailed environmental depth map. Experimental results with a quadrotor demonstrate the vehicle's robust obstacle-avoidance behaviour in a straight line corridor, an S-shaped corridor and a corridor with obstacles distributed in the vehicle's path. The computational efficiency and simplicity of the current approach offers a promising alternative to satisfying the payload, power and bandwidth constraints imposed by aerial microsystems.

Prepreg and Melt Infiltration Technology Developed for Affordable, Robust Manufacturing of Ceramic Matrix Composites

NASA Technical Reports Server (NTRS)

Singh, Mrityunjay; Petko, Jeannie F.

2004-01-01

Affordable fiber-reinforced ceramic matrix composites with multifunctional properties are critically needed for high-temperature aerospace and space transportation applications. These materials have various applications in advanced high-efficiency and high-performance engines, airframe and propulsion components for next-generation launch vehicles, and components for land-based systems. A number of these applications require materials with specific functional characteristics: for example, thick component, hybrid layups for environmental durability and stress management, and self-healing and smart composite matrices. At present, with limited success and very high cost, traditional composite fabrication technologies have been utilized to manufacture some large, complex-shape components of these materials. However, many challenges still remain in developing affordable, robust, and flexible manufacturing technologies for large, complex-shape components with multifunctional properties. The prepreg and melt infiltration (PREMI) technology provides an affordable and robust manufacturing route for low-cost, large-scale production of multifunctional ceramic composite components.

Management of clandestine drug laboratories: need for evidence-based environmental health policies.

PubMed

Al-Obaidi, Tamara A; Fletcher, Stephanie M

2014-01-01

Clandestine drug laboratories (CDLs) have been emerging and increasing as a public health problem in Australia, with methamphetamine being the dominant illegally manufactured drug. However, management and remediation of contaminated properties are still limited in terms of regulation and direction, especially in relation to public and environmental health practice. Therefore, this review provides an update on the hazards and health effects associated with CDLs, with a specific look at the management of these labs from an Australian perspective. Particularly, the paper attempts to describe the policy landscape for management of CDLs, and identifies current gaps and how further research may be utilised to advance understanding and management of CDLs and inform public health policies. The paper highlights a significant lack of evidence-based policies and guidelines to guide regulatory authority including environmental health officers in Australia. Only recently, the national Clandestine Drug Laboratory Guidelines were developed to assist relevant authority and specialists manage and carry out investigations and remediation of contaminated sites. However, only three states have developed state-based guidelines, some of which are inadequate to meet environmental health requirements. The review recommends well-needed inter-sectoral collaborations and further research to provide an evidence base for the development of robust policies and standard operating procedures for safe and effective environmental health management and remediation of CDLs.

Optimal diabatic dynamics of Majorana-based quantum gates

NASA Astrophysics Data System (ADS)

Rahmani, Armin; Seradjeh, Babak; Franz, Marcel

2017-08-01

In topological quantum computing, unitary operations on qubits are performed by adiabatic braiding of non-Abelian quasiparticles, such as Majorana zero modes, and are protected from local environmental perturbations. In the adiabatic regime, with timescales set by the inverse gap of the system, the errors can be made arbitrarily small by performing the process more slowly. To enhance the performance of quantum information processing with Majorana zero modes, we apply the theory of optimal control to the diabatic dynamics of Majorana-based qubits. While we sacrifice complete topological protection, we impose constraints on the optimal protocol to take advantage of the nonlocal nature of topological information and increase the robustness of our gates. By using the Pontryagin's maximum principle, we show that robust equivalent gates to perfect adiabatic braiding can be implemented in finite times through optimal pulses. In our implementation, modifications to the device Hamiltonian are avoided. Focusing on thermally isolated systems, we study the effects of calibration errors and external white and 1 /f (pink) noise on Majorana-based gates. While a noise-induced antiadiabatic behavior, where a slower process creates more diabatic excitations, prohibits indefinite enhancement of the robustness of the adiabatic scheme, our fast optimal protocols exhibit remarkable stability to noise and have the potential to significantly enhance the practical performance of Majorana-based information processing.

Environmental dredging residual generation and management.

PubMed

Patmont, Clay; LaRosa, Paul; Narayanan, Raghav; Forrest, Casey

2018-05-01

The presence and magnitude of sediment contamination remaining in a completed dredge area can often dictate the success of an environmental dredging project. The need to better understand and manage this remaining contamination, referred to as "postdredging residuals," has increasingly been recognized by practitioners and investigators. Based on recent dredging projects with robust characterization programs, it is now understood that the residual contamination layer in the postdredging sediment comprises a mixture of contaminated sediments that originate from throughout the dredge cut. This mixture of contaminated sediments initially exhibits fluid mud properties that can contribute to sediment transport and contamination risk outside of the dredge area. This article reviews robust dredging residual evaluations recently performed in the United States and Canada, including the Hudson River, Lower Fox River, Ashtabula River, and Esquimalt Harbour, along with other projects. These data better inform the understanding of residuals generation, leading to improved models of dredging residual formation to inform remedy evaluation, selection, design, and implementation. Data from these projects confirm that the magnitude of dredging residuals is largely determined by site conditions, primarily in situ sediment fluidity or liquidity as measured by dry bulk density. While the generation of dredging residuals cannot be avoided, residuals can be successfully and efficiently managed through careful development and implementation of site-specific management plans. Integr Environ Assess Manag 2018;14:335-343. © 2018 The Authors. Integrated Environmental Assessment and Management Published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC). © 2018 The Authors. Integrated Environmental Assessment and Management Published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Structural damage detection based on stochastic subspace identification and statistical pattern recognition: I. Theory

NASA Astrophysics Data System (ADS)

Ren, W. X.; Lin, Y. Q.; Fang, S. E.

2011-11-01

One of the key issues in vibration-based structural health monitoring is to extract the damage-sensitive but environment-insensitive features from sampled dynamic response measurements and to carry out the statistical analysis of these features for structural damage detection. A new damage feature is proposed in this paper by using the system matrices of the forward innovation model based on the covariance-driven stochastic subspace identification of a vibrating system. To overcome the variations of the system matrices, a non-singularity transposition matrix is introduced so that the system matrices are normalized to their standard forms. For reducing the effects of modeling errors, noise and environmental variations on measured structural responses, a statistical pattern recognition paradigm is incorporated into the proposed method. The Mahalanobis and Euclidean distance decision functions of the damage feature vector are adopted by defining a statistics-based damage index. The proposed structural damage detection method is verified against one numerical signal and two numerical beams. It is demonstrated that the proposed statistics-based damage index is sensitive to damage and shows some robustness to the noise and false estimation of the system ranks. The method is capable of locating damage of the beam structures under different types of excitations. The robustness of the proposed damage detection method to the variations in environmental temperature is further validated in a companion paper by a reinforced concrete beam tested in the laboratory and a full-scale arch bridge tested in the field.

Directing Environmental Science towards Disease Surveillance Objectives: Waterborne Pathogens in the Developed World

NASA Astrophysics Data System (ADS)

Bridge, J. W.; Oliver, D.; Heathwaite, A.; Banwart, S.; Going Underground: Human Pathogens in The Soil-Water Environment Working Group

2010-12-01

We present the findings and recommendations of a recent UK working group convened to identify research priorities in environmental science and epidemiology of waterborne pathogens. Robust waterborne disease surveillance in the developed world remains a critical need, despite broad success of regulation and water treatment. Recent estimates suggest waterborne pathogens result in between 12 million and 19.5 million cases of illness per year in the US alone. Across the developed world, the value of preventing acute waterborne disease in 150 million people using small community or single-user supplies is estimated at above US$ 4,671 million. The lack of a high quality, reliable environmental knowledge base for waterborne pathogens is a key obstacle. Substantial improvements in understanding of pathogen survival and transport in soils, sediments and water are required both to aid identification of environmental aetiologies for organisms isolated in disease cases and to support novel mitigation responses directed towards specific exposure risks. However, the focus in monitoring and regulation on non-pathogenic faecal indicator organisms (easier and cheaper to detect in water samples) creates a lack of motivation to conduct detailed environmental studies of the actual pathogens likely to be encountered in disease surveillance. Robust disease surveillance may be regarded as an essential objective in epidemiology; but it constitutes a significant shift in perspective for the water industry. The health sector can play a vital role in changing attitudes by explicitly placing value on environmental water research which looks beyond compliance with water quality standards towards informing disease surveillance and influencing health outcomes. The summary of critical research priorities we outline provides a focus for developing and strengthening dialogue between health and water sectors to achieve a common goal - sophisticated management of waterborne diseases through sophisticated understanding of their environmental sources and dynamics.

Who Really Wants an Ambitious Large-Scale Restoration of the Seine Estuary? A Strategic Analysis of a Science-Policy Interface Locked in a Stalemate.

PubMed

Coreau, Audrey; Narcy, Jean-Baptiste; Lumbroso, Sarah

2018-05-01

The development of ecosystem knowledge is an essential condition for effective environmental management but using available knowledge to solve environmental controversies is still difficult in "real" situations. This paper explores the conditions under which ecological knowledge could contribute to the environmental strategies and actions of stakeholders at science-policy interface. Ecological restoration of the Seine estuary is an example of an environmental issue whose overall management has run into difficulties despite the production of a large amount of knowledge by a dedicated organization, GIP Seine Aval. Thanks to an action-research project, based on a futures study, we analyze the reasons of these difficulties and help the GIP Seine Aval adopt a robust strategy to overcome them. According to our results, most local stakeholders involved in the large-scale restoration project emphasize the need for a clear divide between knowledge production and environmental action. This kind of divide may be strategic in a context where the robustness of environmental decisions is strongly depending on the mobilization of "neutral" scientific knowledge. But in our case study, this rather blocks action because some powerful stakeholders continuously ask for more knowledge before taking action. The construction and analysis of possible future scenarios has led to three alternative strategies being identified to counter this stalemate situation: (1) to circumvent difficulties by creating indirect links between knowledge and actions; (2) to use knowledge to sustain advocacy for the interests of each and every stakeholder; (3) to involve citizens in decisions about knowledge production and use, so that environmental issues weight more on the local political agenda.

Integrating environmental gap analysis with spatial conservation prioritization: a case study from Victoria, Australia.

PubMed

Sharafi, Seyedeh Mahdieh; Moilanen, Atte; White, Matt; Burgman, Mark

2012-12-15

Gap analysis is used to analyse reserve networks and their coverage of biodiversity, thus identifying gaps in biodiversity representation that may be filled by additional conservation measures. Gap analysis has been used to identify priorities for species and habitat types. When it is applied to identify gaps in the coverage of environmental variables, it embodies the assumption that combinations of environmental variables are effective surrogates for biodiversity attributes. The question remains of how to fill gaps in conservation systems efficiently. Conservation prioritization software can identify those areas outside existing conservation areas that contribute to the efficient covering of gaps in biodiversity features. We show how environmental gap analysis can be implemented using high-resolution information about environmental variables and ecosystem condition with the publicly available conservation prioritization software, Zonation. Our method is based on the conversion of combinations of environmental variables into biodiversity features. We also replicated the analysis by using Species Distribution Models (SDMs) as biodiversity features to evaluate the robustness and utility of our environment-based analysis. We apply the technique to a planning case study of the state of Victoria, Australia. Copyright © 2012 Elsevier Ltd. All rights reserved.

Environmental Accounting Using Emergy: Evaluation of Minnesota

EPA Science Inventory

Often questions related to environmental policy are difficult to resolve successfully, because robust solutions depend on accurately balancing the needs of both human and natural systems. To accomplish this end the socioeconomic and environmental effects of policies must be expre...

Topological properties of robust biological and computational networks

PubMed Central

Navlakha, Saket; He, Xin; Faloutsos, Christos; Bar-Joseph, Ziv

2014-01-01

Network robustness is an important principle in biology and engineering. Previous studies of global networks have identified both redundancy and sparseness as topological properties used by robust networks. By focusing on molecular subnetworks, or modules, we show that module topology is tightly linked to the level of environmental variability (noise) the module expects to encounter. Modules internal to the cell that are less exposed to environmental noise are more connected and less robust than external modules. A similar design principle is used by several other biological networks. We propose a simple change to the evolutionary gene duplication model which gives rise to the rich range of module topologies observed within real networks. We apply these observations to evaluate and design communication networks that are specifically optimized for noisy or malicious environments. Combined, joint analysis of biological and computational networks leads to novel algorithms and insights benefiting both fields. PMID:24789562

Common solutions for power, communication and robustness in operations of large measurement networks within Research Infrastructures

NASA Astrophysics Data System (ADS)

Huber, Robert; Beranzoli, Laura; Fiebig, Markus; Gilbert, Olivier; Laj, Paolo; Mazzola, Mauro; Paris, Jean-Daniel; Pedersen, Helle; Stocker, Markus; Vitale, Vito; Waldmann, Christoph

2017-04-01

European Environmental Research Infrastructures (RI) frequently comprise in situ observatories from large-scale networks of platforms or sites to local networks of various sensors. Network operation is usually a cumbersome aspect of these RIs facing specific technological problems related to operations in remote areas, maintenance of the network, transmission of observation values, etc.. Robust inter-connection within and across these networks is still at infancy level and the burden increases with remoteness of the station, harshness of environmental conditions, and unavailability of classic communication systems, which is a common feature here. Despite existing RIs having developed ad-hoc solutions to overcome specific problems and innovative technologies becoming available, no common approach yet exists. Within the European project ENVRIplus, a dedicated work package aims to stimulate common network operation technologies and approaches in terms of power supply and storage, robustness, and data transmission. Major objectives of this task are to review existing technologies and RI requirements, propose innovative solutions and evaluate the standardization potential prior to wider deployment across networks. Focus areas within these efforts are: improving energy production and storage units, testing robustness of RI equipment towards extreme conditions as well as methodologies for robust data transmission. We will introduce current project activities which are coordinated at various levels including the engineering as well as the data management perspective, and explain how environmental RIs can benefit from the developments.

Complying with Executive Order 13148 using the Enterprise Environmental Safety And Occupational Health Management Information System.

PubMed

McFarland, Michael J; Nelson, Tim M; Rasmussen, Steve L; Palmer, Glenn R; Olivas, Arthur C

2005-03-01

All U.S. Department of Defense (DoD) facilities are required under Executive Order (EO) 13148, "Greening the Government through Leadership in Environmental Management," to establish quality-based environmental management systems (EMSs) that support environmental decision-making and verification of continuous environmental improvement by December 31, 2005. Compliance with EO 13148 as well as other federal, state, and local environmental regulations places a significant information management burden on DoD facilities. Cost-effective management of environmental data compels DoD facilities to establish robust database systems that not only address the complex and multifaceted environmental monitoring, record-keeping, and reporting requirements demanded by these rules but enable environmental management decision-makers to gauge improvements in environmental performance. The Enterprise Environmental Safety and Occupational Health Management Information System (EESOH-MIS) is a new electronic database developed by the U.S. Air Force to manage both the data needs associated with regulatory compliance programs across its facilities as well as the non-regulatory environmental information that supports installation business practices. The U.S. Air Force, which has adopted the Plan-Do-Check-Act methodology as the EMS standard that it will employ to address EO 13148 requirements.

Flexible daylight memory displays EASL DMD: a new approach toward displays for cockpit and soldier systems

NASA Astrophysics Data System (ADS)

Holter, Borre; Kamfjord, Thor G.; Fossum, Richard; Fagerberg, Ragnar

2000-08-01

The Norwegian based company PolyDisplayR ASA, in collaboration with the Norwegian Army Material Command and SINTEF, has refined, developed and shown with color and black/white technology demonstrators an electrically addressed Smectic A reflective LCD technology featuring: (1) Good contrast, all-round viewing angle and readability under all light conditions (no wash-out in direct sunlight). (2) Infinite memory -- image remains without power -- very low power consumption, no or very low radiation ('silent display') and narrow band updating. (3) Clear, sharp and flicker-free images. (4) Large number of gray tones and colors possible. (5) Simple construction and production -- reduced cost, higher yield, more robust and environmentally friendly. (6) Possibility for lighter, more robust and flexible displays based on plastic substrates. The results and future implementation possibilities for cockpit and soldier-system displays are discussed.

Tractable Quantification of Metastability for Robust Bipedal Locomotion

DTIC Science & Technology

2015-06-01

environmental conditions, including rough terrain. The intuitive and meaningful robustness quanti cation adopted in this thesis begins by stochastic...the system as a Markov chain. Then, failure rates can be easily quanti ed by calculating the expected number of steps before failure. Once robustness is...sensor noise . . . . . . . . . . . . . . . . . . . 54 5.8 Performance evaluation on the dense mesh . . . . . . . . . . . . . . . . . 56 5.9 Stability of

Robust vehicle detection under various environmental conditions using an infrared thermal camera and its application to road traffic flow monitoring.

PubMed

Iwasaki, Yoichiro; Misumi, Masato; Nakamiya, Toshiyuki

2013-06-17

We have already proposed a method for detecting vehicle positions and their movements (henceforth referred to as "our previous method") using thermal images taken with an infrared thermal camera. Our experiments have shown that our previous method detects vehicles robustly under four different environmental conditions which involve poor visibility conditions in snow and thick fog. Our previous method uses the windshield and its surroundings as the target of the Viola-Jones detector. Some experiments in winter show that the vehicle detection accuracy decreases because the temperatures of many windshields approximate those of the exterior of the windshields. In this paper, we propose a new vehicle detection method (henceforth referred to as "our new method"). Our new method detects vehicles based on tires' thermal energy reflection. We have done experiments using three series of thermal images for which the vehicle detection accuracies of our previous method are low. Our new method detects 1,417 vehicles (92.8%) out of 1,527 vehicles, and the number of false detection is 52 in total. Therefore, by combining our two methods, high vehicle detection accuracies are maintained under various environmental conditions. Finally, we apply the traffic information obtained by our two methods to traffic flow automatic monitoring, and show the effectiveness of our proposal.

Robust phase-shifting interferometry resistant to multiple disturbances

NASA Astrophysics Data System (ADS)

Liu, Qian; Yue, Xiaobin; Li, Lulu; Zhang, Hui; He, Jianguo

2018-04-01

Phase-shifting interferometry (PSI) is sensitive to many disturbances, including the environmental vibration, laser instability, phase-shifting error and camera nonlinearity. A robust PSI (RPSI) based on the temporal spectrum analysis is proposed to suppress the effects of these common disturbances. RPSI retrieves wavefront phase from the temporal Fourier spectrum peak, which is identified by detecting the modulus of spectrum, and a referencing method is presented to improve the phase extracting accuracy. Simulations demonstrate the feasibility and effectiveness of RPSI. Experimental results indicate that RPSI is resistant to common disturbances in implementing PSI and achieves accuracy better than 0.03 rad in the disturbed environment. RPSI relaxes requirements on the hardware, environment and operator, and provides an easy-to-use design of an interferometer.

Advanced Space Flight and Environmental Concerns

NASA Technical Reports Server (NTRS)

Whitaker, A.

2001-01-01

The aerospace industry has conquered numerous environmental challenges during the last decade. The aerospace industry of today has evolved due in part to the environmental challenges, becoming stronger, more robust, learning to push the limits of technology, materials and manufacturing, and performing cutting edge engineering.

Green Fabrication of Ultrathin Co3O4 Nanosheets from Metal-Organic Framework for Robust High-Rate Supercapacitors.

PubMed

Xiao, Zhenyu; Fan, Lili; Xu, Ben; Zhang, Shanqing; Kang, Wenpei; Kang, Zixi; Lin, Huan; Liu, Xiuping; Zhang, Shiyu; Sun, Daofeng

2017-12-06

Two-dimensional cobalt oxide (Co 3 O 4 ) is a promising candidate for robust electrochemical capacitors with high performance. Herein, we use 2,3,5,6-tetramethyl-1,4-diisophthalate as a recyclable ligand to construct a Co-based metal-organic framework of UPC-9, and subsequently, we obtain ultrathin hierarchical Co 3 O 4 hexagonal nanosheets with a thickness of 3.5 nm through a hydrolysis and calcination process. A remarkable and excellent specific capacitance of 1121 F·g -1 at a current density of 1 A·g -1 and 873 F·g -1 at a current density of 25 A·g -1 were achieved for the as-prepared asymmetric supercapacitor, which can be attributed to the ultrathin 2D morphology and the rich macroporous and mesoporous structures of the ultrathin Co 3 O 4 nanosheets. This synthesis strategy is environmentally benign and economically viable due to the fact that the costly organic ligand molecules are recycled, reducing the materials cost as well as the environmental cost for the synthesis process.

A resource oriented webs service for environmental modeling

NASA Astrophysics Data System (ADS)

Ferencik, Ioan

2013-04-01

Environmental modeling is a largely adopted practice in the study of natural phenomena. Environmental models can be difficult to build and use and thus sharing them within the community is an important aspect. The most common approach to share a model is to expose it as a web service. In practice the interaction with this web service is cumbersome due to lack of standardized contract and the complexity of the model being exposed. In this work we investigate the use of a resource oriented approach in exposing environmental models as web services. We view a model as a layered resource build atop the object concept from Object Oriented Programming, augmented with persistence capabilities provided by an embedded object database to keep track of its state and implementing the four basic principles of resource oriented architectures: addressability, statelessness, representation and uniform interface. For implementation we use exclusively open source software: Django framework, dyBase object oriented database and Python programming language. We developed a generic framework of resources structured into a hierarchy of types and consequently extended this typology with recurses specific to the domain of environmental modeling. To test our web service we used cURL, a robust command-line based web client.

Using a Novel Wireless-Networked Decentralized Control Scheme under Unpredictable Environmental Conditions

PubMed Central

Chang, Chung-Liang; Huang, Yi-Ming; Hong, Guo-Fong

2015-01-01

The direction of sunshine or the installation sites of environmental control facilities in the greenhouse result in different temperature and humidity levels in the various zones of the greenhouse, and thus, the production quality of crop is inconsistent. This study proposed a wireless-networked decentralized fuzzy control scheme to regulate the environmental parameters of various culture zones within a greenhouse. The proposed scheme can create different environmental conditions for cultivating different crops in various zones and achieve diversification or standardization of crop production. A star-type wireless sensor network is utilized to communicate with each sensing node, actuator node, and control node in various zones within the greenhouse. The fuzzy rule-based inference system is used to regulate the environmental parameters for temperature and humidity based on real-time data of plant growth response provided by a growth stage selector. The growth stage selector defines the control ranges of temperature and humidity of the various culture zones according to the leaf area of the plant, the number of leaves, and the cumulative amount of light. The experimental results show that the proposed scheme is stable and robust and provides basis for future greenhouse applications. PMID:26569264

Buffered Qualitative Stability explains the robustness and evolvability of transcriptional networks

PubMed Central

Albergante, Luca; Blow, J Julian; Newman, Timothy J

2014-01-01

The gene regulatory network (GRN) is the central decision‐making module of the cell. We have developed a theory called Buffered Qualitative Stability (BQS) based on the hypothesis that GRNs are organised so that they remain robust in the face of unpredictable environmental and evolutionary changes. BQS makes strong and diverse predictions about the network features that allow stable responses under arbitrary perturbations, including the random addition of new connections. We show that the GRNs of E. coli, M. tuberculosis, P. aeruginosa, yeast, mouse, and human all verify the predictions of BQS. BQS explains many of the small- and large‐scale properties of GRNs, provides conditions for evolvable robustness, and highlights general features of transcriptional response. BQS is severely compromised in a human cancer cell line, suggesting that loss of BQS might underlie the phenotypic plasticity of cancer cells, and highlighting a possible sequence of GRN alterations concomitant with cancer initiation. DOI: http://dx.doi.org/10.7554/eLife.02863.001 PMID:25182846

Buffered Qualitative Stability explains the robustness and evolvability of transcriptional networks.

PubMed

Albergante, Luca; Blow, J Julian; Newman, Timothy J

2014-09-02

The gene regulatory network (GRN) is the central decision-making module of the cell. We have developed a theory called Buffered Qualitative Stability (BQS) based on the hypothesis that GRNs are organised so that they remain robust in the face of unpredictable environmental and evolutionary changes. BQS makes strong and diverse predictions about the network features that allow stable responses under arbitrary perturbations, including the random addition of new connections. We show that the GRNs of E. coli, M. tuberculosis, P. aeruginosa, yeast, mouse, and human all verify the predictions of BQS. BQS explains many of the small- and large-scale properties of GRNs, provides conditions for evolvable robustness, and highlights general features of transcriptional response. BQS is severely compromised in a human cancer cell line, suggesting that loss of BQS might underlie the phenotypic plasticity of cancer cells, and highlighting a possible sequence of GRN alterations concomitant with cancer initiation. Copyright © 2014, Albergante et al.

Leader-follower formation control of underactuated surface vehicles based on sliding mode control and parameter estimation.

PubMed

Sun, Zhijian; Zhang, Guoqing; Lu, Yu; Zhang, Weidong

2018-01-01

This paper studies the leader-follower formation control of underactuated surface vehicles with model uncertainties and environmental disturbances. A parameter estimation and upper bound estimation based sliding mode control scheme is proposed to solve the problem of the unknown plant parameters and environmental disturbances. For each of these leader-follower formation systems, the dynamic equations of position and attitude are analyzed using coordinate transformation with the aid of the backstepping technique. All the variables are guaranteed to be uniformly ultimately bounded stable in the closed-loop system, which is proven by the distribution design Lyapunov function synthesis. The main advantages of this approach are that: first, parameter estimation based sliding mode control can enhance the robustness of the closed-loop system in presence of model uncertainties and environmental disturbances; second, a continuous function is developed to replace the signum function in the design of sliding mode scheme, which devotes to reduce the chattering of the control system. Finally, numerical simulations are given to demonstrate the effectiveness of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Dephosphorylation and quantification of organic phosphorus in poultry litter by purified phytic-acid high affinity Aspergillus phosphohydrolases.

PubMed

Dao, Thanh H; Hoang, Khanh Q

2008-08-01

Extracellular phosphohydrolases mediate the dephosphorylation of phosphoesters and influence bioavailability and loss of agricultural P to the environment to pose risks of impairment of sensitive aquatic ecosystems. Induction and culture of five strains of Aspergillus were conducted to develop a source of high-affinity and robust phosphohydrolases for detecting environmental P and quantifying bioactive P pools in heterogeneous environmental specimens. Enzyme stability and activity against organic P in poultry litter were evaluated in 71 samples collected across poultry producing regions of Arkansas, Maryland, and Oklahoma of the US Differences existed in strains' adaptability to fermentation medium as they showed a wide range of phytate-degrading activity. Phosphohydrolases from Aspergillus ficuum had highest activity when the strain was cultured on a primarily chemical medium, compared to Aspergillus oryzae which preferred a wheat bran-based organic medium. Kinetics parameters of A. ficuum enzymes (K(m)=210 microM; V(max) of 407 nmol s(-1)) indicated phytic acid-degrading potential equivalent to that of commercial preparations. Purified A. ficuum phosphohydrolases effectively quantified litter bioactive P pools, showing that organic P occurred at an average of 54 (+/-14)% of total P, compared to inorganic phosphates, which averaged 41 (+/-12)%. Litter management and land application options must consider the high water-extractable and organic P concentrations and the biological availability of the organic enzyme-labile P pool. Robustness of A. ficuum enzymes and simplicity of the in situ ligand-based enzyme assay may thus increase routine assessment of litter bioactive P composition to sense for on-farm accumulation of such environmentally-sensitive P forms.

Adaptive Environmental Source Localization and Tracking with Unknown Permittivity and Path Loss Coefficients †

PubMed Central

Fidan, Barış; Umay, Ilknur

2015-01-01

Accurate signal-source and signal-reflector target localization tasks via mobile sensory units and wireless sensor networks (WSNs), including those for environmental monitoring via sensory UAVs, require precise knowledge of specific signal propagation properties of the environment, which are permittivity and path loss coefficients for the electromagnetic signal case. Thus, accurate estimation of these coefficients has significant importance for the accuracy of location estimates. In this paper, we propose a geometric cooperative technique to instantaneously estimate such coefficients, with details provided for received signal strength (RSS) and time-of-flight (TOF)-based range sensors. The proposed technique is integrated to a recursive least squares (RLS)-based adaptive localization scheme and an adaptive motion control law, to construct adaptive target localization and adaptive target tracking algorithms, respectively, that are robust to uncertainties in aforementioned environmental signal propagation coefficients. The efficiency of the proposed adaptive localization and tracking techniques are both mathematically analysed and verified via simulation experiments. PMID:26690441

I: Biomarker quantification in fish exposed to crude oil as input to species sensitivity distributions and threshold values for environmental monitoring.

PubMed

Sanni, Steinar; Björkblom, Carina; Jonsson, Henrik; Godal, Brit F; Liewenborg, Birgitta; Lyng, Emily; Pampanin, Daniela M

2017-04-01

The aim of this study was to determine a suitable set of biomarker based methods for environmental monitoring in sub-arctic and temperate offshore areas using scientific knowledge on the sensitivity of fish species to dispersed crude oil. Threshold values for environmental monitoring and risk assessment were obtained based on a quantitative comparison of biomarker responses. Turbot, halibut, salmon and sprat were exposed for up to 8 weeks to five different sub-lethal concentrations of dispersed crude oil. Biomarkers assessing PAH metabolites, oxidative stress, detoxification system I activity, genotoxicity, immunotoxicity, endocrine disruption, general cellular stress and histological changes were measured. Results showed that PAH metabolites, CYP1A/EROD, DNA adducts and histopathology rendered the most robust results across the different fish species, both in terms of sensitivity and dose-responsiveness. The reported results contributed to forming links between biomonitoring and risk assessment procedures by using biomarker species sensitivity distributions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Effect of replacement of tin doped indium oxide (ITO) by ZnO: analysis of environmental impact categories

NASA Astrophysics Data System (ADS)

Ziemińska-Stolarska, Aleksandra; Barecka, Magda; Zbiciński, Ireneusz

2017-10-01

Abundant use of natural resources is doubtlessly one of the greatest challenges of sustainable development. Process alternatives, which enable sustainable manufacturing of valuable products from more accessible resources, are consequently required. One of examples of limited resources is Indium, currently broadly used for tin doped indium oxide (ITO) for production of transparent conductive films (TCO) in electronics industry. Therefore, candidates for Indium replacement, which would offer as good performance as the industrial state-of-the-art technology based on ITO are widely studied. However, the environmental impact of new layers remains unknown. Hence, this paper studies the environmental effect of ITO replacement by zinc oxide (ZnO) by means life cycle assessment (LCA) methodology. The analysis enables to quantify the environmental impact over the entire period of life cycle of products—during manufacturing, use phase and waste generation. The analysis was based on experimental data for deposition process. Further, analysis of different impact categories was performed in order to determine specific environmental effects related to technology change. What results from the analysis, is that ZnO is a robust alternative material for ITO replacement regarding environmental load and energy efficiency of deposition process which is also crucial for sustainable TCO layer production.

The Contribution of Environmental Assessment to Sustainable Development: Toward a Richer Empirical Understanding

NASA Astrophysics Data System (ADS)

Cashmore, Matthew; Bond, Alan; Cobb, Dick

2007-09-01

It has long been suggested that environmental assessment has the potential to contribute to sustainable development through mechanisms above and beyond informing design and consent decisions, and while theories have been proposed to explain how this might occur, few have been subjected to rigorous empirical validation. This research advances the theoretical debate by building a rich empirical understanding of environmental assessment’s practical outcomes, from which its potential to contribute to sustainable development can be gauged. Three case study environmental assessment processes in England were investigated using a combination of data generated from content analysis, in-depth interviews, and a questionnaire survey. Four categories of outcomes are delineated based on the research data: learning outcomes; governance outcomes; attitudinal and value changes; and developmental outcomes. The data provide a robust critique of mainstream theory, with its focus on design and consent decisions. The article concludes with an examination of the consequences of the context-specific nature of environmental assessment practices in terms of developing theory and focusing future research.

The Navigation Guide systematic review methodology: a rigorous and transparent method for translating environmental health science into better health outcomes.

PubMed

Woodruff, Tracey J; Sutton, Patrice

2014-10-01

Synthesizing what is known about the environmental drivers of health is instrumental to taking prevention-oriented action. Methods of research synthesis commonly used in environmental health lag behind systematic review methods developed in the clinical sciences over the past 20 years. We sought to develop a proof of concept of the "Navigation Guide," a systematic and transparent method of research synthesis in environmental health. The Navigation Guide methodology builds on best practices in research synthesis in evidence-based medicine and environmental health. Key points of departure from current methods of expert-based narrative review prevalent in environmental health include a prespecified protocol, standardized and transparent documentation including expert judgment, a comprehensive search strategy, assessment of "risk of bias," and separation of the science from values and preferences. Key points of departure from evidence-based medicine include assigning a "moderate" quality rating to human observational studies and combining diverse evidence streams. The Navigation Guide methodology is a systematic and rigorous approach to research synthesis that has been developed to reduce bias and maximize transparency in the evaluation of environmental health information. Although novel aspects of the method will require further development and validation, our findings demonstrated that improved methods of research synthesis under development at the National Toxicology Program and under consideration by the U.S. Environmental Protection Agency are fully achievable. The institutionalization of robust methods of systematic and transparent review would provide a concrete mechanism for linking science to timely action to prevent harm.

Testing the robustness of management decisions to uncertainty: Everglades restoration scenarios.

PubMed

Fuller, Michael M; Gross, Louis J; Duke-Sylvester, Scott M; Palmer, Mark

2008-04-01

To effectively manage large natural reserves, resource managers must prepare for future contingencies while balancing the often conflicting priorities of different stakeholders. To deal with these issues, managers routinely employ models to project the response of ecosystems to different scenarios that represent alternative management plans or environmental forecasts. Scenario analysis is often used to rank such alternatives to aid the decision making process. However, model projections are subject to uncertainty in assumptions about model structure, parameter values, environmental inputs, and subcomponent interactions. We introduce an approach for testing the robustness of model-based management decisions to the uncertainty inherent in complex ecological models and their inputs. We use relative assessment to quantify the relative impacts of uncertainty on scenario ranking. To illustrate our approach we consider uncertainty in parameter values and uncertainty in input data, with specific examples drawn from the Florida Everglades restoration project. Our examples focus on two alternative 30-year hydrologic management plans that were ranked according to their overall impacts on wildlife habitat potential. We tested the assumption that varying the parameter settings and inputs of habitat index models does not change the rank order of the hydrologic plans. We compared the average projected index of habitat potential for four endemic species and two wading-bird guilds to rank the plans, accounting for variations in parameter settings and water level inputs associated with hypothetical future climates. Indices of habitat potential were based on projections from spatially explicit models that are closely tied to hydrology. For the American alligator, the rank order of the hydrologic plans was unaffected by substantial variation in model parameters. By contrast, simulated major shifts in water levels led to reversals in the ranks of the hydrologic plans in 24.1-30.6% of the projections for the wading bird guilds and several individual species. By exposing the differential effects of uncertainty, relative assessment can help resource managers assess the robustness of scenario choice in model-based policy decisions.

Expanding Health Technology Assessments to Include Effects on the Environment.

PubMed

Marsh, Kevin; Ganz, Michael L; Hsu, John; Strandberg-Larsen, Martin; Gonzalez, Raquel Palomino; Lund, Niels

2016-01-01

There is growing awareness of the impact of human activity on the climate and the need to stem this impact. Public health care decision makers from Sweden and the United Kingdom have started examining environmental impacts when assessing new technologies. This article considers the case for incorporating environmental impacts into the health technology assessment (HTA) process and discusses the associated challenges. Two arguments favor incorporating environmental impacts into HTA: 1) environmental changes could directly affect people's health and 2) policy decision makers have broad mandates and objectives extending beyond health care. Two types of challenges hinder this process. First, the nascent evidence base is insufficient to support the accurate comparison of technologies' environmental impacts. Second, cost-utility analysis, which is favored by many HTA agencies, could capture some of the value of environmental impacts, especially those generating health impacts, but might not be suitable for addressing broader concerns. Both cost-benefit and multicriteria decision analyses are potential methods for evaluating health and environmental outcomes, but are less familiar to health care decision makers. Health care is an important and sizable sector of the economy that could warrant closer policy attention to its impact on the environment. Considerable work is needed to track decision makers' demands, augment the environmental evidence base, and develop robust methods for capturing and incorporating environmental data as part of HTA. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

A robust and flexible Geospatial Modeling Interface (GMI) for environmental model deployment and evaluation

USDA-ARS?s Scientific Manuscript database

This paper provides an overview of the GMI (Geospatial Modeling Interface) simulation framework for environmental model deployment and assessment. GMI currently provides access to multiple environmental models including AgroEcoSystem-Watershed (AgES-W), Nitrate Leaching and Economic Analysis 2 (NLEA...

Shortcuts to adiabaticity by counterdiabatic driving for trapped-ion displacement in phase space

PubMed Central

An, Shuoming; Lv, Dingshun; del Campo, Adolfo; Kim, Kihwan

2016-01-01

The application of adiabatic protocols in quantum technologies is severely limited by environmental sources of noise and decoherence. Shortcuts to adiabaticity by counterdiabatic driving constitute a powerful alternative that speed up time-evolution while mimicking adiabatic dynamics. Here we report the experimental implementation of counterdiabatic driving in a continuous variable system, a shortcut to the adiabatic transport of a trapped ion in phase space. The resulting dynamics is equivalent to a ‘fast-motion video' of the adiabatic trajectory. The robustness of this protocol is shown to surpass that of competing schemes based on classical local controls and Fourier optimization methods. Our results demonstrate that shortcuts to adiabaticity provide a robust speedup of quantum protocols of wide applicability in quantum technologies. PMID:27669897

Environmentally Resistant Mo-Si-B-Based Coatings

NASA Astrophysics Data System (ADS)

Perepezko, J. H.; Sossaman, T. A.; Taylor, M.

2017-06-01

High-temperature applications have demonstrated aluminide-coated nickel-base superalloys to be remarkably effective, but are reaching their service limit. Alternate materials such as refractory (e.g., W, Mo) silicide alloys and SiC composites are being considered to extend high temperature capability, but the silica surfaces on these materials require coatings for enhanced environmental resistance. This can be accomplished with a Mo-Si-B-based coating that is deposited by a spray deposition of Mo followed by a chemical vapor deposition of Si and B by pack cementation to develop an aluminoborosilica surface. Oxidation of the as-deposited (Si + B)-pack coatings proceeds with partial consumption of the initial MoSi2 forming amorphous silica. This Si depletion leads to formation of a B-saturated Mo5Si3 (T1) phase. Reactions between the Mo and the B rich phases develop an underlying Mo5SiB2 (T2) layer. The T1 phase saturated with B has robust oxidation resistance, and the Si depletion is prevented by the underlying diffusion barrier (T2). Further, due to the natural phase transformation characteristics of the Mo-Si-B system, cracks or scratches to the outer silica and T1 layers can be repaired from the Si and B reservoirs of T2 + MoB layer to yield a self-healing characteristic. Mo-Si-B-based coatings demonstrate robust performance up to at least 1700 °C not only to the rigors of elevated temperature oxidation, but also to CMAS attack, hot corrosion attack, water vapor and thermal cycling.

Cultivating Sustainable and Authentic Service-Learning Partnerships in the Environmental Sciences

NASA Astrophysics Data System (ADS)

Ivanochko, Tara; Grain, Kari

2017-04-01

The two-term, community service-learning capstone course for Environmental Sciences at the University of British Columbia, Canada, aims to support both community and students using authentic science practice in service of the community. During the course development, we implemented a routine process for student and community feedback, instructor reflection and course revision. Drawing on data from 23 interviews and 9 focus groups collected over three years, findings from this study highlight ways that community partnerships can be sustained while students have an authentic science experience. Based on data collected from community partners, we highlight the key processes, challenges, successes, and practical considerations in the creation and sustainability of a scientifically robust service-learning course.

Hormonal Signal Amplification Mediates Environmental Conditions during Development and Controls an Irreversible Commitment to Adulthood

PubMed Central

Schaedel, Oren N.; Gerisch, Birgit; Antebi, Adam; Sternberg, Paul W.

2012-01-01

Many animals can choose between different developmental fates to maximize fitness. Despite the complexity of environmental cues and life history, different developmental fates are executed in a robust fashion. The nematode Caenorhabditis elegans serves as a powerful model to examine this phenomenon because it can adopt one of two developmental fates (adulthood or diapause) depending on environmental conditions. The steroid hormone dafachronic acid (DA) directs development to adulthood by regulating the transcriptional activity of the nuclear hormone receptor DAF-12. The known role of DA suggests that it may be the molecular mediator of environmental condition effects on the developmental fate decision, although the mechanism is yet unknown. We used a combination of physiological and molecular biology techniques to demonstrate that commitment to reproductive adult development occurs when DA levels, produced in the neuroendocrine XXX cells, exceed a threshold. Furthermore, imaging and cell ablation experiments demonstrate that the XXX cells act as a source of DA, which, upon commitment to adult development, is amplified and propagated in the epidermis in a DAF-12 dependent manner. This positive feedback loop increases DA levels and drives adult programs in the gonad and epidermis, thus conferring the irreversibility of the decision. We show that the positive feedback loop canalizes development by ensuring that sufficient amounts of DA are dispersed throughout the body and serves as a robust fate-locking mechanism to enforce an organism-wide binary decision, despite noisy and complex environmental cues. These mechanisms are not only relevant to C. elegans but may be extended to other hormonal-based decision-making mechanisms in insects and mammals. PMID:22505848

Wisconsin’s Environmental Public Health Tracking Network: Information Systems Design for Childhood Cancer Surveillance

PubMed Central

Hanrahan, Lawrence P.; Anderson, Henry A.; Busby, Brian; Bekkedal, Marni; Sieger, Thomas; Stephenson, Laura; Knobeloch, Lynda; Werner, Mark; Imm, Pamela; Olson, Joseph

2004-01-01

In this article we describe the development of an information system for environmental childhood cancer surveillance. The Wisconsin Cancer Registry annually receives more than 25,000 incident case reports. Approximately 269 cases per year involve children. Over time, there has been considerable community interest in understanding the role the environment plays as a cause of these cancer cases. Wisconsin’s Public Health Information Network (WI-PHIN) is a robust web portal integrating both Health Alert Network and National Electronic Disease Surveillance System components. WI-PHIN is the information technology platform for all public health surveillance programs. Functions include the secure, automated exchange of cancer case data between public health–based and hospital-based cancer registrars; web-based supplemental data entry for environmental exposure confirmation and hypothesis testing; automated data analysis, visualization, and exposure–outcome record linkage; directories of public health and clinical personnel for role-based access control of sensitive surveillance information; public health information dissemination and alerting; and information technology security and critical infrastructure protection. For hypothesis generation, cancer case data are sent electronically to WI-PHIN and populate the integrated data repository. Environmental data are linked and the exposure–disease relationships are explored using statistical tools for ecologic exposure risk assessment. For hypothesis testing, case–control interviews collect exposure histories, including parental employment and residential histories. This information technology approach can thus serve as the basis for building a comprehensive system to assess environmental cancer etiology. PMID:15471739

Psychopathic Personality Traits and Environmental Contexts: Differential Correlates, Gender Differences, and Genetic Mediation

PubMed Central

Hicks, Brian M.; Carlson, Marie D.; Blonigen, Daniel M.; Patrick, Christopher J.; Iacono, William G.; MGue, Matt

2011-01-01

Theorists have speculated that primary psychopathy (or Factor 1 affective-interpersonal features) is prominently heritable whereas secondary psychopathy (or Factor 2 social deviance) is more environmentally determined. We tested this differential heritability hypothesis using a large adolescent twin sample. Trait-based proxies of primary and secondary psychopathic tendencies were assessed using Multidimensional Personality Questionnaire (MPQ; Tellegen & Waller, 2008) estimates of Fearless Dominance and Impulsive Antisociality, respectively (Benning et al., 2005). The environmental contexts of family, school, peers, and stressful life events were assessed using multiple raters and methods. Consistent with prior research, MPQ Impulsive Antisociality was robustly associated with each environmental risk factor, and these associations were significantly greater than those for MPQ Fearless Dominance. However, MPQ Fearless Dominance and Impulsive Antisociality exhibited similar heritability, and genetic effects mediated the associations between MPQ Impulsive Antisociality and the environmental measures. Results were largely consistent across male and female twins. We conclude that gene-environment correlations rather than main effects of genes and environments account for the differential environmental correlates of primary and secondary psychopathy. PMID:22452762

Correcting systematic inflation in genetic association tests that consider interaction effects: application to a genome-wide association study of posttraumatic stress disorder.

PubMed

Almli, Lynn M; Duncan, Richard; Feng, Hao; Ghosh, Debashis; Binder, Elisabeth B; Bradley, Bekh; Ressler, Kerry J; Conneely, Karen N; Epstein, Michael P

2014-12-01

Genetic association studies of psychiatric outcomes often consider interactions with environmental exposures and, in particular, apply tests that jointly consider gene and gene-environment interaction effects for analysis. Using a genome-wide association study (GWAS) of posttraumatic stress disorder (PTSD), we report that heteroscedasticity (defined as variability in outcome that differs by the value of the environmental exposure) can invalidate traditional joint tests of gene and gene-environment interaction. To identify the cause of bias in traditional joint tests of gene and gene-environment interaction in a PTSD GWAS and determine whether proposed robust joint tests are insensitive to this problem. The PTSD GWAS data set consisted of 3359 individuals (978 men and 2381 women) from the Grady Trauma Project (GTP), a cohort study from Atlanta, Georgia. The GTP performed genome-wide genotyping of participants and collected environmental exposures using the Childhood Trauma Questionnaire and Trauma Experiences Inventory. We performed joint interaction testing of the Beck Depression Inventory and modified PTSD Symptom Scale in the GTP GWAS. We assessed systematic bias in our interaction analyses using quantile-quantile plots and genome-wide inflation factors. Application of the traditional joint interaction test to the GTP GWAS yielded systematic inflation across different outcomes and environmental exposures (inflation-factor estimates ranging from 1.07 to 1.21), whereas application of the robust joint test to the same data set yielded no such inflation (inflation-factor estimates ranging from 1.01 to 1.02). Simulated data further revealed that the robust joint test is valid in different heteroscedasticity models, whereas the traditional joint test is invalid. The robust joint test also has power similar to the traditional joint test when heteroscedasticity is not an issue. We believe the robust joint test should be used in candidate-gene studies and GWASs of psychiatric outcomes that consider environmental interactions. To make the procedure useful for applied investigators, we created a software tool that can be called from the popular PLINK package for analysis.

Correcting Systematic Inflation in Genetic Association Tests That Consider Interaction Effects

PubMed Central

Almli, Lynn M.; Duncan, Richard; Feng, Hao; Ghosh, Debashis; Binder, Elisabeth B.; Bradley, Bekh; Ressler, Kerry J.; Conneely, Karen N.; Epstein, Michael P.

2015-01-01

IMPORTANCE Genetic association studies of psychiatric outcomes often consider interactions with environmental exposures and, in particular, apply tests that jointly consider gene and gene-environment interaction effects for analysis. Using a genome-wide association study (GWAS) of posttraumatic stress disorder (PTSD), we report that heteroscedasticity (defined as variability in outcome that differs by the value of the environmental exposure) can invalidate traditional joint tests of gene and gene-environment interaction. OBJECTIVES To identify the cause of bias in traditional joint tests of gene and gene-environment interaction in a PTSD GWAS and determine whether proposed robust joint tests are insensitive to this problem. DESIGN, SETTING, AND PARTICIPANTS The PTSD GWAS data set consisted of 3359 individuals (978 men and 2381 women) from the Grady Trauma Project (GTP), a cohort study from Atlanta, Georgia. The GTP performed genome-wide genotyping of participants and collected environmental exposures using the Childhood Trauma Questionnaire and Trauma Experiences Inventory. MAIN OUTCOMES AND MEASURES We performed joint interaction testing of the Beck Depression Inventory and modified PTSD Symptom Scale in the GTP GWAS. We assessed systematic bias in our interaction analyses using quantile-quantile plots and genome-wide inflation factors. RESULTS Application of the traditional joint interaction test to the GTP GWAS yielded systematic inflation across different outcomes and environmental exposures (inflation-factor estimates ranging from 1.07 to 1.21), whereas application of the robust joint test to the same data set yielded no such inflation (inflation-factor estimates ranging from 1.01 to 1.02). Simulated data further revealed that the robust joint test is valid in different heteroscedasticity models, whereas the traditional joint test is invalid. The robust joint test also has power similar to the traditional joint test when heteroscedasticity is not an issue. CONCLUSIONS AND RELEVANCE We believe the robust joint test should be used in candidate-gene studies and GWASs of psychiatric outcomes that consider environmental interactions. To make the procedure useful for applied investigators, we created a software tool that can be called from the popular PLINK package for analysis. PMID:25354142

Robust Vehicle Detection under Various Environmental Conditions Using an Infrared Thermal Camera and Its Application to Road Traffic Flow Monitoring

PubMed Central

Iwasaki, Yoichiro; Misumi, Masato; Nakamiya, Toshiyuki

2013-01-01

We have already proposed a method for detecting vehicle positions and their movements (henceforth referred to as “our previous method”) using thermal images taken with an infrared thermal camera. Our experiments have shown that our previous method detects vehicles robustly under four different environmental conditions which involve poor visibility conditions in snow and thick fog. Our previous method uses the windshield and its surroundings as the target of the Viola-Jones detector. Some experiments in winter show that the vehicle detection accuracy decreases because the temperatures of many windshields approximate those of the exterior of the windshields. In this paper, we propose a new vehicle detection method (henceforth referred to as “our new method”). Our new method detects vehicles based on tires' thermal energy reflection. We have done experiments using three series of thermal images for which the vehicle detection accuracies of our previous method are low. Our new method detects 1,417 vehicles (92.8%) out of 1,527 vehicles, and the number of false detection is 52 in total. Therefore, by combining our two methods, high vehicle detection accuracies are maintained under various environmental conditions. Finally, we apply the traffic information obtained by our two methods to traffic flow automatic monitoring, and show the effectiveness of our proposal. PMID:23774988

Planning for the closure of uncontrolled landfills in Turkey to reduce environmental impacts.

PubMed

Ergene Şentürk, Didar; Alp, Emre

2016-11-01

Landfilling is the most preferred solid waste disposal method in Turkey owing to both economic and technical reasons. However, beside the sanitary landfills there are also hundreds of uncontrolled waste sites located throughout Turkey, which are often left either abandoned or burning. Because there is a lack of legislative guidelines governing the closure and rehabilitation of these dumpsites, the municipalities that are responsible for waste management do not initiate the proactive strategies required for the closure of these sites. In this study, a method based on a multi-criteria analysis is conducted for different dumpsites in Turkey to evaluate the level of negative impacts on the environment. This method is based on the use of environmental indices for a quantitative assessment of the landfills, such as environmental interaction between the source and the receptors, environmental values of the receptors, and operational conditions. It was possible to assess the robustness of the proposed methodology since the pre- and post-groundwater quality monitoring data was available from the study sites that were closed and rehabilitated in 2014. The results of this study show that the method based on a multi-criteria analysis is an effective tool while in the preliminary planning stages of closure and rehabilitation activities of uncontrolled waste landfills. © The Author(s) 2016.

Environmental Barcoding: A Next-Generation Sequencing Approach for Biomonitoring Applications Using River Benthos

PubMed Central

Hajibabaei, Mehrdad; Shokralla, Shadi; Zhou, Xin; Singer, Gregory A. C.; Baird, Donald J.

2011-01-01

Timely and accurate biodiversity analysis poses an ongoing challenge for the success of biomonitoring programs. Morphology-based identification of bioindicator taxa is time consuming, and rarely supports species-level resolution especially for immature life stages. Much work has been done in the past decade to develop alternative approaches for biodiversity analysis using DNA sequence-based approaches such as molecular phylogenetics and DNA barcoding. On-going assembly of DNA barcode reference libraries will provide the basis for a DNA-based identification system. The use of recently introduced next-generation sequencing (NGS) approaches in biodiversity science has the potential to further extend the application of DNA information for routine biomonitoring applications to an unprecedented scale. Here we demonstrate the feasibility of using 454 massively parallel pyrosequencing for species-level analysis of freshwater benthic macroinvertebrate taxa commonly used for biomonitoring. We designed our experiments in order to directly compare morphology-based, Sanger sequencing DNA barcoding, and next-generation environmental barcoding approaches. Our results show the ability of 454 pyrosequencing of mini-barcodes to accurately identify all species with more than 1% abundance in the pooled mixture. Although the approach failed to identify 6 rare species in the mixture, the presence of sequences from 9 species that were not represented by individuals in the mixture provides evidence that DNA based analysis may yet provide a valuable approach in finding rare species in bulk environmental samples. We further demonstrate the application of the environmental barcoding approach by comparing benthic macroinvertebrates from an urban region to those obtained from a conservation area. Although considerable effort will be required to robustly optimize NGS tools to identify species from bulk environmental samples, our results indicate the potential of an environmental barcoding approach for biomonitoring programs. PMID:21533287

IMPLICATIONS OF USING ROBUST BAYESIAN ANALYSIS TO REPRESENT DIVERSE SOURCES OF UNCERTAINTY IN INTEGRATED ASSESSMENT

EPA Science Inventory

In our previous research, we showed that robust Bayesian methods can be used in environmental modeling to define a set of probability distributions for key parameters that captures the effects of expert disagreement, ambiguity, or ignorance. This entire set can then be update...

Robustness of Greenbergerendash Horneendash Zeilinger and W states against Dzyaloshinskii-Moriya interaction

NASA Astrophysics Data System (ADS)

Sharma, Kapil K.; Pandey, S. N.

2016-12-01

In this article, the robustness of tripartite Greenberger-Horne-Zeilinger (GHZ) and W states is investigated against Dzyaloshinskii-Moriya (i.e. DM) interaction. We consider a closed system of three qubits and an environmental qubit. The environmental qubit interacts with any one of the three qubits through DM interaction. The tripartite system is initially prepared in GHZ and W states, respectively. The composite four qubits system evolve with unitary dynamics. We detach the environmental qubit by tracing out from four qubits, and profound impact of DM interaction is studied on the initial entanglement of the system. As a result, we find that the bipartite partitions of W states suffer from entanglement sudden death (i.e. ESD), while tripartite entanglement does not. On the other hand, bipartite partitions and tripartite entanglement in GHZ states do not feel any influence of DM interaction. So, we find that GHZ states have robust character than W states. In this work, we consider generalised GHZ and W states, and three π is used as an entanglement measure. This study can be useful in quantum information processing where unwanted DM interaction takes place.

Doing Good Again? A Multilevel Institutional Perspective on Corporate Environmental Responsibility and Philanthropic Strategy.

PubMed

Liu, Wei; Wei, Qiao; Huang, Song-Qin; Tsai, Sang-Bing

2017-10-24

This study investigates the relationship between corporate environmental responsibility and corporate philanthropy. Using a sample of Chinese listed firms from 2008 to 2013, this paper examines the role of corporate environmental responsibility in corporate philanthropy and the moderating influence of the institutional environment using multilevel analysis. The results show that corporate eco-friendly events are positively associated with corporate philanthropic strategy to a significant degree. Provincial-level government intervention positively moderate the positive relationship between eco-friendly events and corporate philanthropy and government corruption is negatively moderate the relationship. All these results are robust according to robustness checks. These findings provide a new perspective on corporate philanthropic strategy as a means to obtain critical resources from the government in order to compensate for the loss made on environmental responsibility. Moreover, the institutional environment is proved here to play an important role in corporate philanthropic strategy.

Doing Good Again? A Multilevel Institutional Perspective on Corporate Environmental Responsibility and Philanthropic Strategy

PubMed Central

Liu, Wei; Wei, Qiao; Huang, Song-Qin

2017-01-01

This study investigates the relationship between corporate environmental responsibility and corporate philanthropy. Using a sample of Chinese listed firms from 2008 to 2013, this paper examines the role of corporate environmental responsibility in corporate philanthropy and the moderating influence of the institutional environment using multilevel analysis. The results show that corporate eco-friendly events are positively associated with corporate philanthropic strategy to a significant degree. Provincial-level government intervention positively moderate the positive relationship between eco-friendly events and corporate philanthropy and government corruption is negatively moderate the relationship. All these results are robust according to robustness checks. These findings provide a new perspective on corporate philanthropic strategy as a means to obtain critical resources from the government in order to compensate for the loss made on environmental responsibility. Moreover, the institutional environment is proved here to play an important role in corporate philanthropic strategy. PMID:29064451

Vision Sensor-Based Road Detection for Field Robot Navigation

PubMed Central

Lu, Keyu; Li, Jian; An, Xiangjing; He, Hangen

2015-01-01

Road detection is an essential component of field robot navigation systems. Vision sensors play an important role in road detection for their great potential in environmental perception. In this paper, we propose a hierarchical vision sensor-based method for robust road detection in challenging road scenes. More specifically, for a given road image captured by an on-board vision sensor, we introduce a multiple population genetic algorithm (MPGA)-based approach for efficient road vanishing point detection. Superpixel-level seeds are then selected in an unsupervised way using a clustering strategy. Then, according to the GrowCut framework, the seeds proliferate and iteratively try to occupy their neighbors. After convergence, the initial road segment is obtained. Finally, in order to achieve a globally-consistent road segment, the initial road segment is refined using the conditional random field (CRF) framework, which integrates high-level information into road detection. We perform several experiments to evaluate the common performance, scale sensitivity and noise sensitivity of the proposed method. The experimental results demonstrate that the proposed method exhibits high robustness compared to the state of the art. PMID:26610514

Robust optimization on sustainable biodiesel supply chain produced from waste cooking oil under price uncertainty.

PubMed

Zhang, Yong; Jiang, Yunjian

2017-02-01

Waste cooking oil (WCO)-for-biodiesel conversion is regarded as the "waste-to-wealthy" industry. This paper addresses the design of a WCO-for-biodiesel supply chain at both strategic and tactical levels. The supply chain of this problem is studied, which is based on a typical mode of the waste collection (from restaurants' kitchen) and conversion in the cities. The supply chain comprises three stakeholders: WCO supplier, integrated bio-refinery and demand zone. Three key problems should be addressed for the optimal design of the supply chain: (1) the number, sizes and locations of bio-refinery; (2) the sites and amount of WCO collected; (3) the transportation plans of WCO and biodiesel. A robust mixed integer linear model with muti-objective (economic, environmental and social objectives) is proposed for these problems. Finally, a large-scale practical case study is adopted based on Suzhou, a city in the east of China, to verify the proposed models. Copyright © 2016 Elsevier Ltd. All rights reserved.

Design and fabrication of a 1-DOF drive mode and 2-DOF sense mode micro-gyroscope using SU-8 based UV-LIGA process

NASA Astrophysics Data System (ADS)

Verma, Payal; Juneja, Sucheta; Savelyev, Dmitry A.; Khonina, Svetlana N.; Gopal, Ram

2016-04-01

This paper presents design and fabrication of a 1-DOF (degree-of-freedom) drive mode and 2-DOF sense mode micro-gyroscope. It is an inherently robust structure and offers a high sense frequency bandwidth. The proposed design utilizes resonance of the1-DOF drive mode oscillator and employs dynamic amplification concept in sense modes to increase the sensitivity while maintaining robustness. The 2-DOF in the sense direction renders the device immune to process imperfections and environmental effects. The design is simulated using FEA software (CoventorWare®). The device is designed considering process compatibility with SU-8 based UV-LIGA process, which is an economical fabrication technique. The complete fabrication process is presented along with SEM images of the fabricated device. The device has 9 µm thick Nickel as the key structural layer with an overall reduced key structure size of 2.2 mm by 2.1 mm.

The contribution of science to risk-based decision-making: lessons from the development of full-scale treatment measures for acidic mine waters at Wheal Jane, UK.

PubMed

Younger, Paul L; Coulton, Richard H; Froggatt, Eric C

2005-02-01

The use of risk-based decision-making in environmental management is often assumed to rely primarily on the availability of robust scientific data and insights, while in practice socio-economic criteria are often of considerable importance. However, the relative contributions to decision-making made by scientific and socio-economic inputs are rarely assessed, and even less commonly reported. Such an assessment has been made for a major remediation project in southwest England, in which some 300 l/s of highly acidic, metalliferous mine waters are now being treated using oxidation and chemical neutralisation. In the process of reaching the decision to commission the treatment plant, a wide range of scientific studies were undertaken, including: biological impact assessments, hydrogeological investigations of the effect of pumping on the flooded mine system, and hydrological and geochemical characterisation, together with integrated catchment modelling, of pollutant sources and pathways. These investigations revealed that, despite the spectacular nature of the original mine water outburst in 1992, the ecology of the Fal estuary remains remarkably robust. No scientific evidence emerged of any grounds for concern over the estuarine ecology, even if mine water were left to flow untreated. However, a rare ecological resource known as "maerl" (a form of calcified seaweed) is harvested annually in the estuary, providing significant revenue to the local economy and underpinning the 'clean' image of local sea water. Social and environmental benefit surveys revealed strong public perceptions that any visible discoloration in the estuary must indicate a diminution in quality of the maerl, to the detriment of both the public image and economy of the area. This factor proved sufficient to justify the continued pump-and-treat operations at the mine site. Although the decisive factor in the end was socio-economic in nature, robust assessment of this factor could not have been made without robust scientific evidence. It is concluded that investment in investigating and contributing to the formation of public perceptions is just as important as investing in scientific investigations per se.

Low-Temperature Fabrication of Robust, Transparent, and Flexible Thin-Film Transistors with a Nanolaminated Insulator.

PubMed

Kwon, Jeong Hyun; Park, Junhong; Lee, Myung Keun; Park, Jeong Woo; Jeon, Yongmin; Shin, Jeong Bin; Nam, Minwoo; Kim, Choong-Ki; Choi, Yang-Kyu; Choi, Kyung Cheol

2018-05-09

The lack of reliable, transparent, and flexible electrodes and insulators for applications in thin-film transistors (TFTs) makes it difficult to commercialize transparent, flexible TFTs (TF-TFTs). More specifically, conventional high process temperatures and the brittleness of these elements have been hurdles in developing flexible substrates vulnerable to heat. Here, we propose electrode and insulator fabrication techniques considering process temperature, transmittance, flexibility, and environmental stability. A transparent and flexible indium tin oxide (ITO)/Ag/ITO (IAI) electrode and an Al 2 O 3 /MgO (AM)-laminated insulator were optimized at the low temperature of 70 °C for the fabrication of TF-TFTs on a polyethylene terephthalate (PET) substrate. The optimized IAI electrode with a sheet resistance of 7 Ω/sq exhibited the luminous transmittance of 85.17% and maintained its electrical conductivity after exposure to damp heat conditions because of an environmentally stable ITO capping layer. In addition, the electrical conductivity of IAI was maintained after 10 000 bending cycles with a tensile strain of 3% because of the ductile Ag film. In the metal/insulator/metal structure, the insulating and mechanical properties of the optimized AM-laminated film deposited at 70 °C were significantly improved because of the highly dense nanolaminate system, compared to those of the Al 2 O 3 film deposited at 70 °C. In addition, the amorphous indium-gallium-zinc oxide (a-IGZO) was used as the active channel for TF-TFTs because of its excellent chemical stability. In the environmental stability test, the ITO, a-IGZO, and AM-laminated films showed the excellent environmental stability. Therefore, our IGZO-based TFT with IAI electrodes and the 70 °C AM-laminated insulator was fabricated to evaluate robustness, transparency, flexibility, and process temperature, resulting in transfer characteristics comparable to those of an IGZO-based TFT with a 150 °C Al 2 O 3 insulator.

Absolute Quantification of Norovirus Capsid Protein in Food, Water, and Soil Using Synthetic Peptides with Electrospray and MALDI Mass Spectrometry

PubMed Central

Hartmann, Erica M.; Colquhoun, David R.; Schwab, Kellogg J.; Halden, Rolf U.

2015-01-01

Norovirus infections are one of the most prominent public health problems of microbial origin in the U.S. and other industrialized countries. Surveillance is necessary to prevent secondary infection, confirm successful cleanup after outbreaks, and track the causative agent. Quantitative mass spectrometry, based on absolute quantitation with stable-isotope labeled peptides, is a promising tool for norovirus monitoring because of its speed, sensitivity, and robustness in the face of environmental inhibitors. In the current study, we present two new methods for the detection of the norovirus genogroup I capsid protein using electrospray and matrixassisted laser desorption/ionization (MALDI) mass spectrometry. The peptide TLDPIEVPLEDVR was used to quantify norovirus-like particles down to 500 attomoles with electrospray and 100 attomoles with MALDI. With MALDI, we also demonstrate a detection limit of 1 femtomole and a quantitative dynamic range of 5 orders of magnitude in the presence of an environmental matrix effect. Due to the rapid processing time and applicability to a wide range of environmental sample types (bacterial lysate, produce, milk, soil, and groundwater), mass spectrometry-based absolute quantitation has a strong potential for use in public health and environmental sciences. PMID:25603302

FISH ASSEMBLAGES AS INDICATORS OF LAKE SUPERIOR COASTAL WETLAND CONDITION

EPA Science Inventory

Fish assemblages associated with coastal wetlands in Lake Superior are poorly described. Understanding the environmental factors structuring the biota in these habitats is essential to developing robust indicators of their condition. To identify key environmental influences struc...

MPLEx: a Robust and Universal Protocol for Single-Sample Integrative Proteomic, Metabolomic, and Lipidomic Analyses

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

Nakayasu, Ernesto S.; Nicora, Carrie D.; Sims, Amy C.

2016-05-03

ABSTRACT Integrative multi-omics analyses can empower more effective investigation and complete understanding of complex biological systems. Despite recent advances in a range of omics analyses, multi-omic measurements of the same sample are still challenging and current methods have not been well evaluated in terms of reproducibility and broad applicability. Here we adapted a solvent-based method, widely applied for extracting lipids and metabolites, to add proteomics to mass spectrometry-based multi-omics measurements. Themetabolite,protein, andlipidextraction (MPLEx) protocol proved to be robust and applicable to a diverse set of sample types, including cell cultures, microbial communities, and tissues. To illustrate the utility of thismore » protocol, an integrative multi-omics analysis was performed using a lung epithelial cell line infected with Middle East respiratory syndrome coronavirus, which showed the impact of this virus on the host glycolytic pathway and also suggested a role for lipids during infection. The MPLEx method is a simple, fast, and robust protocol that can be applied for integrative multi-omic measurements from diverse sample types (e.g., environmental,in vitro, and clinical). IMPORTANCEIn systems biology studies, the integration of multiple omics measurements (i.e., genomics, transcriptomics, proteomics, metabolomics, and lipidomics) has been shown to provide a more complete and informative view of biological pathways. Thus, the prospect of extracting different types of molecules (e.g., DNAs, RNAs, proteins, and metabolites) and performing multiple omics measurements on single samples is very attractive, but such studies are challenging due to the fact that the extraction conditions differ according to the molecule type. Here, we adapted an organic solvent-based extraction method that demonstrated broad applicability and robustness, which enabled comprehensive proteomics, metabolomics, and lipidomics analyses from the same sample.« less

Functional Design of Highly Robust and Flexible Thin-Film Encapsulation Composed of Quasi-Perfect Sublayers for Transparent, Flexible Displays.

PubMed

Kwon, Jeong Hyun; Jeon, Yongmin; Choi, Seungyeop; Park, Jeong Woo; Kim, Hyuncheol; Choi, Kyung Cheol

2017-12-20

In this study, a structurally and materially designed thin-film encapsulation is proposed to guarantee the reliability of transparent, flexible displays by significantly improving their barrier properties, mechanical stability, and environmental reliability, all of which are essential for organic light-emitting diode (OLED) encapsulation. We fabricated a bioinspired, nacre-like ZnO/Al 2 O 3 /MgO laminate structure (ZAM) using atomic layer deposition for the microcrack toughening effect. The ZAM film was formed with intentional voids and defects through the formation of a quasi-perfect sublayer, rather than the simple fabrication of nanolaminate structures. The 240 nm thick ZAM-based multibarrier (ZAM-TFE) with a compressively strained organic layer demonstrated an optical transmittance of 91.35% in the visible range, an extremely low water vapor transmission rate of 2.06 × 10 -6 g/m 2 /day, a mechanical stability enduring a strain close to 1%, and a residual stress close to 0, showing significant improvement of key TFE properties in comparison to an Al 2 O 3 -based multibarrier. In addition, ZAM-TFE demonstrated superior environmental resistance without degradation of barrier properties in a severe environment of 85 °C and 90% relative humidity (RH). Thus, our structurally and materially designed ZAM film has been well optimized in terms of its applicability as a gas diffusion barrier as well as in terms of its mechanical and environmental reliability. Finally, we confirmed the feasibility of the ZAM-TFE through application in OLEDs. The low-temperature ZAM-TFE technology showed great potential to provide a highly robust and flexible TFE of TFOLEDs.

Estimating the mean and standard deviation of environmental data with below detection limit observations: Considering highly skewed data and model misspecification.

PubMed

Shoari, Niloofar; Dubé, Jean-Sébastien; Chenouri, Shoja'eddin

2015-11-01

In environmental studies, concentration measurements frequently fall below detection limits of measuring instruments, resulting in left-censored data. Some studies employ parametric methods such as the maximum likelihood estimator (MLE), robust regression on order statistic (rROS), and gamma regression on order statistic (GROS), while others suggest a non-parametric approach, the Kaplan-Meier method (KM). Using examples of real data from a soil characterization study in Montreal, we highlight the need for additional investigations that aim at unifying the existing literature. A number of studies have examined this issue; however, those considering data skewness and model misspecification are rare. These aspects are investigated in this paper through simulations. Among other findings, results show that for low skewed data, the performance of different statistical methods is comparable, regardless of the censoring percentage and sample size. For highly skewed data, the performance of the MLE method under lognormal and Weibull distributions is questionable; particularly, when the sample size is small or censoring percentage is high. In such conditions, MLE under gamma distribution, rROS, GROS, and KM are less sensitive to skewness. Related to model misspecification, MLE based on lognormal and Weibull distributions provides poor estimates when the true distribution of data is misspecified. However, the methods of rROS, GROS, and MLE under gamma distribution are generally robust to model misspecifications regardless of skewness, sample size, and censoring percentage. Since the characteristics of environmental data (e.g., type of distribution and skewness) are unknown a priori, we suggest using MLE based on gamma distribution, rROS and GROS. Copyright © 2015 Elsevier Ltd. All rights reserved.

Biomining of MoS2 with Peptide-based Smart Biomaterials.

PubMed

Cetinel, Sibel; Shen, Wei-Zheng; Aminpour, Maral; Bhomkar, Prasanna; Wang, Feng; Borujeny, Elham Rafie; Sharma, Kumakshi; Nayebi, Niloofar; Montemagno, Carlo

2018-02-20

Biomining of valuable metals using a target specific approach promises increased purification yields and decreased cost. Target specificity can be implemented with proteins/peptides, the biological molecules, responsible from various structural and functional pathways in living organisms by virtue of their specific recognition abilities towards both organic and inorganic materials. Phage display libraries are used to identify peptide biomolecules capable of specifically recognizing and binding organic/inorganic materials of interest with high affinities. Using combinatorial approaches, these molecular recognition elements can be converted into smart hybrid biomaterials and harnessed for biotechnological applications. Herein, we used a commercially available phage-display library to identify peptides with specific binding affinity to molybdenite (MoS 2 ) and used them to decorate magnetic NPs. These peptide-coupled NPs could capture MoS 2 under a variety of environmental conditions. The same batch of NPs could be re-used multiple times to harvest MoS 2 , clearly suggesting that this hybrid material was robust and recyclable. The advantages of this smart hybrid biomaterial with respect to its MoS 2 -binding specificity, robust performance under environmentally challenging conditions and its recyclability suggests its potential application in harvesting MoS 2 from tailing ponds and downstream mining processes.

Smoking and long-term labour market outcomes.

PubMed

Böckerman, Petri; Hyytinen, Ari; Kaprio, Jaakko

2015-07-01

To examine the long-term effects of smoking on labour market outcomes using twin data matched to register-based individual information on earnings. Twin data for Finnish men born 1945-1957 was used to remove the shared environmental and genetic factors. The results were subjected to extensive robustness testing. Lifetime cigarette consumption was measured by (cumulative) cigarette pack-years in early adulthood. The average of an individual's earnings (and, alternatively, taxable income) was measured over a subsequent 15-year period in later adulthood. Smokers have lower long-term income and earnings. For example, controlling for the shared environmental and genetic factors using the data on genetically identical twins, smoking is negatively associated with lifetime income (p=0.015). The negative association was also robust to the use of various covariates, such as education, health indicators and extraversion. Smoking is negatively related to long-term labour market outcomes. The provision of information about the indirect monetary costs of smoking may thus complement the policy efforts that aim at educating consumers about the health costs of smoking. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Toward Environmentally Robust Organic Electronics: Approaches and Applications.

PubMed

Lee, Eun Kwang; Lee, Moo Yeol; Park, Cheol Hee; Lee, Hae Rang; Oh, Joon Hak

2017-11-01

Recent interest in flexible electronics has led to a paradigm shift in consumer electronics, and the emergent development of stretchable and wearable electronics is opening a new spectrum of ubiquitous applications for electronics. Organic electronic materials, such as π-conjugated small molecules and polymers, are highly suitable for use in low-cost wearable electronic devices, and their charge-carrier mobilities have now exceeded that of amorphous silicon. However, their commercialization is minimal, mainly because of weaknesses in terms of operational stability, long-term stability under ambient conditions, and chemical stability related to fabrication processes. Recently, however, many attempts have been made to overcome such instabilities of organic electronic materials. Here, an overview is provided of the strategies developed for environmentally robust organic electronics to overcome the detrimental effects of various critical factors such as oxygen, water, chemicals, heat, and light. Additionally, molecular design approaches to π-conjugated small molecules and polymers that are highly stable under ambient and harsh conditions are explored; such materials will circumvent the need for encapsulation and provide a greater degree of freedom using simple solution-based device-fabrication techniques. Applications that are made possible through these strategies are highlighted. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mapping the natural variation in whole bone stiffness and strength across skeletal sites.

PubMed

Schlecht, Stephen H; Bigelow, Erin M R; Jepsen, Karl J

2014-10-01

Traits of the skeletal system are coordinately adjusted to establish mechanical homeostasis in response to genetic and environmental factors. Prior work demonstrated that this 'complex adaptive' process is not perfect, revealing a two-fold difference in whole bone stiffness of the tibia across a population. Robustness (specifically, total cross-sectional area relative to length) varies widely across skeletal sites and between sexes. However, it is unknown whether the natural variation in whole bone stiffness and strength also varies across skeletal sites and between men and women. We tested the hypotheses that: 1) all major long bones of the appendicular skeleton demonstrate inherent, systemic constraints in the degree to which morphological and compositional traits can be adjusted for a given robustness; and 2) these traits covary in a predictable manner independent of body size and robustness. We assessed the functional relationships among robustness, cortical area (Ct.Ar), cortical tissue mineral density (Ct.TMD), and bone strength index (BSI) across the long bones of the upper and lower limbs of 115 adult men and women. All bones showed a significant (p<0.001) positive regression between BSI and robustness after adjusting for body size, with slender bones being 1.7-2.3 times less stiff and strong in men and 1.3-2.8 times less stiff and strong in women compared to robust bones. Our findings are the first to document the natural inter-individual variation in whole bone stiffness and strength that exist within populations and that is predictable based on skeletal robustness for all major long bones. Documenting and further understanding this natural variation in strength may be critical for differentially diagnosing and treating skeletal fragility. Copyright © 2014 Elsevier Inc. All rights reserved.

Mapping the natural variation in whole bone stiffness and strength across skeletal sites

PubMed Central

Schlecht, Stephen H.; Bigelow, Erin M.R.; Jepsen, Karl J.

2016-01-01

Traits of the skeletal system are coordinately adjusted to establish mechanical homeostasis in response to genetic and environmental factors. Prior work demonstrated that this `complex adaptive' process is not perfect, revealing a two-fold difference in whole bone stiffness of the tibia across a population. Robustness (specifically, total cross-sectional area relative to length) varies widely across skeletal sites and between sexes. However, it is unknown whether the natural variation in whole bone stiffness and strength also varies across skeletal sites and between men and women. We tested the hypotheses that: 1) all major long bones of the appendicular skeleton demonstrate inherent, systemic constraints in the degree to which morphological and compositional traits can be adjusted for a given robustness; and 2) these traits covary in a predictable manner independent of body size and robustness. We assessed the functional relationships among robustness, cortical area (Ct.Ar), cortical tissue mineral density (Ct.TMD), and bone strength index (BSI) across the long bones of the upper and lower limbs of 115 adult men and women. All bones showed a significant (p < 0.001) positive regression between BSI and robustness after adjusting for body size, with slender bones being 1.7–2.3 times less stiff and strong in men and 1.3–2.8 times less stiff and strong in women compared to robust bones. Our findings are the first to document the natural inter-individual variation in whole bone stiffness and strength that exist within populations and that is predictable based on skeletal robustness for all major long bones. Documenting and further understanding this natural variation in strength may be critical for differentially diagnosing and treating skeletal fragility. PMID:24999223

What interventions increase commuter cycling? A systematic review.

PubMed

Stewart, Glenn; Anokye, Nana Kwame; Pokhrel, Subhash

2015-08-14

To identify interventions that will increase commuter cycling. All settings where commuter cycling might take place. Adults (aged 18+) in any country. Individual, group or environmental interventions including policies and infrastructure. A wide range of 'changes in commuter cycling' indicators, including frequency of cycling, change in workforce commuting mode, change in commuting population transport mode, use of infrastructure by defined populations and population modal shift. 12 studies from 6 countries (6 from the UK, 2 from Australia, 1 each from Sweden, Ireland, New Zealand and the USA) met the inclusion criteria. Of those, 2 studies were randomised control trials and the remainder preintervention and postintervention studies. The majority of studies (n=7) evaluated individual-based or group-based interventions and the rest environmental interventions. Individual-based or group-based interventions in 6/7 studies were found to increase commuter cycling of which the effect was significant in only 3/6 studies. Environmental interventions, however, had small but positive effects in much larger but more difficult to define populations. Almost all studies had substantial loss to follow-up. Despite commuter cycling prevalence varying widely between countries, robust evidence of what interventions will increase commuter cycling in low cycling prevalence nations is sparse. Wider environmental interventions that make cycling conducive appear to reach out to hard to define but larger populations. This could mean that environmental interventions, despite their small positive effects, have greater public health significance than individual-based or group-based measures because those interventions encourage a larger number of people to integrate physical activity into their everyday lives. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Priority screening of toxic chemicals and industry sectors in the U.S. toxics release inventory: a comparison of the life cycle impact-based and risk-based assessment tools developed by U.S. EPA.

PubMed

Lim, Seong-Rin; Lam, Carl W; Schoenung, Julie M

2011-09-01

Life Cycle Impact Assessment (LCIA) and Risk Assessment (RA) employ different approaches to evaluate toxic impact potential for their own general applications. LCIA is often used to evaluate toxicity potentials for corporate environmental management and RA is often used to evaluate a risk score for environmental policy in government. This study evaluates the cancer, non-cancer, and ecotoxicity potentials and risk scores of chemicals and industry sectors in the United States on the basis of the LCIA- and RA-based tools developed by U.S. EPA, and compares the priority screening of toxic chemicals and industry sectors identified with each method to examine whether the LCIA- and RA-based results lead to the same prioritization schemes. The Tool for the Reduction and Assessment of Chemical and other environmental Impacts (TRACI) is applied as an LCIA-based screening approach with a focus on air and water emissions, and the Risk-Screening Environmental Indicator (RSEI) is applied in equivalent fashion as an RA-based screening approach. The U.S. Toxic Release Inventory is used as the dataset for this analysis, because of its general applicability to a comprehensive list of chemical substances and industry sectors. Overall, the TRACI and RSEI results do not agree with each other in part due to the unavailability of characterization factors and toxic scores for select substances, but primarily because of their different evaluation approaches. Therefore, TRACI and RSEI should be used together both to support a more comprehensive and robust approach to screening of chemicals for environmental management and policy and to highlight substances that are found to be of concern from both perspectives. Copyright © 2011 Elsevier Ltd. All rights reserved.

What interventions increase commuter cycling? A systematic review

PubMed Central

Stewart, Glenn; Anokye, Nana Kwame; Pokhrel, Subhash

2015-01-01

Objective To identify interventions that will increase commuter cycling. Setting All settings where commuter cycling might take place. Participants Adults (aged 18+) in any country. Interventions Individual, group or environmental interventions including policies and infrastructure. Primary and secondary outcome measures A wide range of ‘changes in commuter cycling’ indicators, including frequency of cycling, change in workforce commuting mode, change in commuting population transport mode, use of infrastructure by defined populations and population modal shift. Results 12 studies from 6 countries (6 from the UK, 2 from Australia, 1 each from Sweden, Ireland, New Zealand and the USA) met the inclusion criteria. Of those, 2 studies were randomised control trials and the remainder preintervention and postintervention studies. The majority of studies (n=7) evaluated individual-based or group-based interventions and the rest environmental interventions. Individual-based or group-based interventions in 6/7 studies were found to increase commuter cycling of which the effect was significant in only 3/6 studies. Environmental interventions, however, had small but positive effects in much larger but more difficult to define populations. Almost all studies had substantial loss to follow-up. Conclusions Despite commuter cycling prevalence varying widely between countries, robust evidence of what interventions will increase commuter cycling in low cycling prevalence nations is sparse. Wider environmental interventions that make cycling conducive appear to reach out to hard to define but larger populations. This could mean that environmental interventions, despite their small positive effects, have greater public health significance than individual-based or group-based measures because those interventions encourage a larger number of people to integrate physical activity into their everyday lives. PMID:26275902

Life cycle assessment to compare the environmental impact of seven contemporary food waste management systems.

PubMed

Edwards, Joel; Othman, Maazuza; Crossin, Enda; Burn, Stewart

2018-01-01

Municipal food waste (FW) represents 35-45% of household residual waste in Australia, with the nation generating 1.6Tg annually. It is estimated that 91% of this FW ends up in landfill. This study used life cycle assessment to determine and compare the environmental impact of seven contemporary FW management systems for two real-life jurisdictions; incorporating the complete waste service and expanding the system to include inert and garden waste. Although, no system exhibited a best ranking across all impact categories, FW digestion based systems were all revealed to have a lower global warming potential than composting and landfilling systems. Mechanical biological treatment, anaerobic co-digestion, and home composting all demonstrated the lowest environmental impacts for two or more of the environmental impact categories assessed. The assessment included market and technological specific variables and uncertainties providing a framework for robust decision making at a municipality level. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

DETERMINING A ROBUST D-OPTIMAL DESIGN FOR TESTING FOR DEPARTURE FROM ADDITIVITY IN A MIXTURE OF FOUR PFAAS

EPA Science Inventory

Our objective was to determine an optimal experimental design for a mixture of perfluoroalkyl acids (PFAAs) that is robust to the assumption of additivity. Of particular focus to this research project is whether an environmentally relevant mixture of four PFAAs with long half-liv...

Real-time Bayesian anomaly detection in streaming environmental data

NASA Astrophysics Data System (ADS)

Hill, David J.; Minsker, Barbara S.; Amir, Eyal

2009-04-01

With large volumes of data arriving in near real time from environmental sensors, there is a need for automated detection of anomalous data caused by sensor or transmission errors or by infrequent system behaviors. This study develops and evaluates three automated anomaly detection methods using dynamic Bayesian networks (DBNs), which perform fast, incremental evaluation of data as they become available, scale to large quantities of data, and require no a priori information regarding process variables or types of anomalies that may be encountered. This study investigates these methods' abilities to identify anomalies in eight meteorological data streams from Corpus Christi, Texas. The results indicate that DBN-based detectors, using either robust Kalman filtering or Rao-Blackwellized particle filtering, outperform a DBN-based detector using Kalman filtering, with the former having false positive/negative rates of less than 2%. These methods were successful at identifying data anomalies caused by two real events: a sensor failure and a large storm.

Network Hubs Buffer Environmental Variation in Saccharomyces cerevisiae

PubMed Central

Levy, Sasha F; Siegal, Mark L

2008-01-01

Regulatory and developmental systems produce phenotypes that are robust to environmental and genetic variation. A gene product that normally contributes to this robustness is termed a phenotypic capacitor. When a phenotypic capacitor fails, for example when challenged by a harsh environment or mutation, the system becomes less robust and thus produces greater phenotypic variation. A functional phenotypic capacitor provides a mechanism by which hidden polymorphism can accumulate, whereas its failure provides a mechanism by which evolutionary change might be promoted. The primary example to date of a phenotypic capacitor is Hsp90, a molecular chaperone that targets a large set of signal transduction proteins. In both Drosophila and Arabidopsis, compromised Hsp90 function results in pleiotropic phenotypic effects dependent on the underlying genotype. For some traits, Hsp90 also appears to buffer stochastic variation, yet the relationship between environmental and genetic buffering remains an important unresolved question. We previously used simulations of knockout mutations in transcriptional networks to predict that many gene products would act as phenotypic capacitors. To test this prediction, we use high-throughput morphological phenotyping of individual yeast cells from single-gene deletion strains to identify gene products that buffer environmental variation in Saccharomyces cerevisiae. We find more than 300 gene products that, when absent, increase morphological variation. Overrepresented among these capacitors are gene products that control chromosome organization and DNA integrity, RNA elongation, protein modification, cell cycle, and response to stimuli such as stress. Capacitors have a high number of synthetic-lethal interactions but knockouts of these genes do not tend to cause severe decreases in growth rate. Each capacitor can be classified based on whether or not it is encoded by a gene with a paralog in the genome. Capacitors with a duplicate are highly connected in the protein–protein interaction network and show considerable divergence in expression from their paralogs. In contrast, capacitors encoded by singleton genes are part of highly interconnected protein clusters whose other members also tend to affect phenotypic variability or fitness. These results suggest that buffering and release of variation is a widespread phenomenon that is caused by incomplete functional redundancy at multiple levels in the genetic architecture. PMID:18986213

Improving the 'tool box' for robust industrial enzymes.

PubMed

Littlechild, J A

2017-05-01

The speed of sequencing of microbial genomes and metagenomes is providing an ever increasing resource for the identification of new robust biocatalysts with industrial applications for many different aspects of industrial biotechnology. Using 'natures catalysts' provides a sustainable approach to chemical synthesis of fine chemicals, general chemicals such as surfactants and new consumer-based materials such as biodegradable plastics. This provides a sustainable and 'green chemistry' route to chemical synthesis which generates no toxic waste and is environmentally friendly. In addition, enzymes can play important roles in other applications such as carbon dioxide capture, breakdown of food and other waste streams to provide a route to the concept of a 'circular economy' where nothing is wasted. The use of improved bioinformatic approaches and the development of new rapid enzyme activity screening methodology can provide an endless resource for new robust industrial biocatalysts.This mini-review will discuss several recent case studies where industrial enzymes of 'high priority' have been identified and characterised. It will highlight specific hydrolase enzymes and recent case studies which have been carried out within our group in Exeter.

Perfluorinated Alkyl Compounds: Challenges To Develop Robust And Reliable Methods

EPA Science Inventory

An increasing number of studies have been conducted to investigate the environmental distribution of perfluorinated alkyl compounds (PFCs), some of which are known to be toxic in laboratory studies. Despite growing public concerns, environmental monitoring data are still limited...

Robust Speech Processing & Recognition: Speaker ID, Language ID, Speech Recognition/Keyword Spotting, Diarization/Co-Channel/Environmental Characterization, Speaker State Assessment

DTIC Science & Technology

2015-10-01

Scoring, Gaussian Backend , etc.) as shown in Fig. 39. The methods in this domain also emphasized the ability to perform data purification for both...investigation using the same infrastructure was undertaken to explore Lombard effect “flavor” detection for improved speaker ID. The study The presence of...dimension selection and compared to a common N-gram frequency based selection. 2.1.2: Exploration on NN/DBN backend : Since Deep Neural Networks (DNN) have

Saigas on the brink: Multidisciplinary analysis of the factors influencing mass mortality events

PubMed Central

Kock, Richard A.; Orynbayev, Mukhit; Robinson, Sarah; Zuther, Steffen; Singh, Navinder J.; Beauvais, Wendy; Morgan, Eric R.; Kerimbayev, Aslan; Khomenko, Sergei; Martineau, Henny M.; Rystaeva, Rashida; Omarova, Zamira; Wolfs, Sara; Hawotte, Florent; Radoux, Julien; Milner-Gulland, Eleanor J.

2018-01-01

In 2015, more than 200,000 saiga antelopes died in 3 weeks in central Kazakhstan. The proximate cause of death is confirmed as hemorrhagic septicemia caused by the bacterium Pasteurella multocida type B, based on multiple strands of evidence. Statistical modeling suggests that there was unusually high relative humidity and temperature in the days leading up to the mortality event; temperature and humidity anomalies were also observed in two previous similar events in the same region. The modeled influence of environmental covariates is consistent with known drivers of hemorrhagic septicemia. Given the saiga population’s vulnerability to mass mortality and the likely exacerbation of climate-related and environmental stressors in the future, management of risks to population viability such as poaching and viral livestock disease is urgently needed, as well as robust ongoing veterinary surveillance. A multidisciplinary approach is needed to research mass mortality events under rapid environmental change. PMID:29376120

Advancing environmental risk assessment for transgenic biofeedstock crops

PubMed Central

Wolt, Jeffrey D

2009-01-01

Transgenic modification of plants is a key enabling technology for developing sustainable biofeedstocks for biofuels production. Regulatory decisions and the wider acceptance and development of transgenic biofeedstock crops are considered from the context of science-based risk assessment. The risk assessment paradigm for transgenic biofeedstock crops is fundamentally no different from that of current generation transgenic crops, except that the focus of the assessment must consider the unique attributes of a given biofeedstock crop and its environmental release. For currently envisioned biofeedstock crops, particular emphasis in risk assessment will be given to characterization of altered metabolic profiles and their implications relative to non-target environmental effects and food safety; weediness and invasiveness when plants are modified for abiotic stress tolerance or are domesticated; and aggregate risk when plants are platforms for multi-product production. Robust risk assessments for transgenic biofeedstock crops are case-specific, initiated through problem formulation, and use tiered approaches for risk characterization. PMID:19883509

Robust geostatistical analysis of spatial data

NASA Astrophysics Data System (ADS)

Papritz, Andreas; Künsch, Hans Rudolf; Schwierz, Cornelia; Stahel, Werner A.

2013-04-01

Most of the geostatistical software tools rely on non-robust algorithms. This is unfortunate, because outlying observations are rather the rule than the exception, in particular in environmental data sets. Outliers affect the modelling of the large-scale spatial trend, the estimation of the spatial dependence of the residual variation and the predictions by kriging. Identifying outliers manually is cumbersome and requires expertise because one needs parameter estimates to decide which observation is a potential outlier. Moreover, inference after the rejection of some observations is problematic. A better approach is to use robust algorithms that prevent automatically that outlying observations have undue influence. Former studies on robust geostatistics focused on robust estimation of the sample variogram and ordinary kriging without external drift. Furthermore, Richardson and Welsh (1995) proposed a robustified version of (restricted) maximum likelihood ([RE]ML) estimation for the variance components of a linear mixed model, which was later used by Marchant and Lark (2007) for robust REML estimation of the variogram. We propose here a novel method for robust REML estimation of the variogram of a Gaussian random field that is possibly contaminated by independent errors from a long-tailed distribution. It is based on robustification of estimating equations for the Gaussian REML estimation (Welsh and Richardson, 1997). Besides robust estimates of the parameters of the external drift and of the variogram, the method also provides standard errors for the estimated parameters, robustified kriging predictions at both sampled and non-sampled locations and kriging variances. Apart from presenting our modelling framework, we shall present selected simulation results by which we explored the properties of the new method. This will be complemented by an analysis a data set on heavy metal contamination of the soil in the vicinity of a metal smelter. Marchant, B.P. and Lark, R.M. 2007. Robust estimation of the variogram by residual maximum likelihood. Geoderma 140: 62-72. Richardson, A.M. and Welsh, A.H. 1995. Robust restricted maximum likelihood in mixed linear models. Biometrics 51: 1429-1439. Welsh, A.H. and Richardson, A.M. 1997. Approaches to the robust estimation of mixed models. In: Handbook of Statistics Vol. 15, Elsevier, pp. 343-384.

Robust Entrainment of Circadian Oscillators Requires Specific Phase Response Curves

PubMed Central

Pfeuty, Benjamin; Thommen, Quentin; Lefranc, Marc

2011-01-01

The circadian clocks keeping time in many living organisms rely on self-sustained biochemical oscillations entrained by external cues, such as light, to the 24-h cycle induced by Earth's rotation. However, environmental cues are unreliable due to the variability of habitats, weather conditions, or cue-sensing mechanisms among individuals. A tempting hypothesis is that circadian clocks have evolved so as to be robust to fluctuations in the signal that entrains them. To support this hypothesis, we analyze the synchronization behavior of weakly and periodically forced oscillators in terms of their phase response curve (PRC), which measures phase changes induced by a perturbation applied at different times of the cycle. We establish a general relationship between the robustness of key entrainment properties, such as stability and oscillator phase, on the one hand, and the shape of the PRC as characterized by a specific curvature or the existence of a dead zone, on the other hand. The criteria obtained are applied to computational models of circadian clocks and account for the disparate robustness properties of various forcing schemes. Finally, the analysis of PRCs measured experimentally in several organisms strongly suggests a case of convergent evolution toward an optimal strategy for maintaining a clock that is accurate and robust to environmental fluctuations. PMID:21641300

Distributed environmental control

NASA Technical Reports Server (NTRS)

Cleveland, Gary A.

1992-01-01

We present an architecture of distributed, independent control agents designed to work with the Computer Aided System Engineering and Analysis (CASE/A) simulation tool. CASE/A simulates behavior of Environmental Control and Life Support Systems (ECLSS). We describe a lattice of agents capable of distributed sensing and overcoming certain sensor and effector failures. We address how the architecture can achieve the coordinating functions of a hierarchical command structure while maintaining the robustness and flexibility of independent agents. These agents work between the time steps of the CASE/A simulation tool to arrive at command decisions based on the state variables maintained by CASE/A. Control is evaluated according to both effectiveness (e.g., how well temperature was maintained) and resource utilization (the amount of power and materials used).

Global Sensitivity Analysis of Environmental Models: Convergence, Robustness and Validation

NASA Astrophysics Data System (ADS)

Sarrazin, Fanny; Pianosi, Francesca; Khorashadi Zadeh, Farkhondeh; Van Griensven, Ann; Wagener, Thorsten

2015-04-01

Global Sensitivity Analysis aims to characterize the impact that variations in model input factors (e.g. the parameters) have on the model output (e.g. simulated streamflow). In sampling-based Global Sensitivity Analysis, the sample size has to be chosen carefully in order to obtain reliable sensitivity estimates while spending computational resources efficiently. Furthermore, insensitive parameters are typically identified through the definition of a screening threshold: the theoretical value of their sensitivity index is zero but in a sampling-base framework they regularly take non-zero values. There is little guidance available for these two steps in environmental modelling though. The objective of the present study is to support modellers in making appropriate choices, regarding both sample size and screening threshold, so that a robust sensitivity analysis can be implemented. We performed sensitivity analysis for the parameters of three hydrological models with increasing level of complexity (Hymod, HBV and SWAT), and tested three widely used sensitivity analysis methods (Elementary Effect Test or method of Morris, Regional Sensitivity Analysis, and Variance-Based Sensitivity Analysis). We defined criteria based on a bootstrap approach to assess three different types of convergence: the convergence of the value of the sensitivity indices, of the ranking (the ordering among the parameters) and of the screening (the identification of the insensitive parameters). We investigated the screening threshold through the definition of a validation procedure. The results showed that full convergence of the value of the sensitivity indices is not necessarily needed to rank or to screen the model input factors. Furthermore, typical values of the sample sizes that are reported in the literature can be well below the sample sizes that actually ensure convergence of ranking and screening.

Rapid detection of microbial cell abundance in aquatic systems

DOE PAGES

Rocha, Andrea M.; Yuan, Quan; Close, Dan M.; ...

2016-06-01

The detection and quantification of naturally occurring microbial cellular densities is an essential component of environmental systems monitoring. While there are a number of commonly utilized approaches for monitoring microbial abundance, capacitance-based biosensors represent a promising approach because of their low-cost and label-free detection of microbial cells, but are not as well characterized as more traditional methods. Here, we investigate the applicability of enhanced alternating current electrokinetics (ACEK) capacitive sensing as a new application for rapidly detecting and quantifying microbial cellular densities in cultured and environmentally sourced aquatic samples. ACEK capacitive sensor performance was evaluated using two distinct and dynamicmore » systems the Great Australian Bight and groundwater from the Oak Ridge Reservation in Oak Ridge, TN. Results demonstrate that ACEK capacitance-based sensing can accurately determine microbial cell counts throughout cellular concentrations typically encountered in naturally occurring microbial communities (10 3 – 10 6 cells/mL). A linear relationship was observed between cellular density and capacitance change correlations, allowing a simple linear curve fitting equation to be used for determining microbial abundances in unknown samples. As a result, this work provides a foundation for understanding the limits of capacitance-based sensing in natural environmental samples and supports future efforts focusing on evaluating the robustness ACEK capacitance-based within aquatic environments.« less

Rapid detection of microbial cell abundance in aquatic systems

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

Rocha, Andrea M.; Yuan, Quan; Close, Dan M.

The detection and quantification of naturally occurring microbial cellular densities is an essential component of environmental systems monitoring. While there are a number of commonly utilized approaches for monitoring microbial abundance, capacitance-based biosensors represent a promising approach because of their low-cost and label-free detection of microbial cells, but are not as well characterized as more traditional methods. Here, we investigate the applicability of enhanced alternating current electrokinetics (ACEK) capacitive sensing as a new application for rapidly detecting and quantifying microbial cellular densities in cultured and environmentally sourced aquatic samples. ACEK capacitive sensor performance was evaluated using two distinct and dynamicmore » systems the Great Australian Bight and groundwater from the Oak Ridge Reservation in Oak Ridge, TN. Results demonstrate that ACEK capacitance-based sensing can accurately determine microbial cell counts throughout cellular concentrations typically encountered in naturally occurring microbial communities (10 3 – 10 6 cells/mL). A linear relationship was observed between cellular density and capacitance change correlations, allowing a simple linear curve fitting equation to be used for determining microbial abundances in unknown samples. As a result, this work provides a foundation for understanding the limits of capacitance-based sensing in natural environmental samples and supports future efforts focusing on evaluating the robustness ACEK capacitance-based within aquatic environments.« less

Robustness, efficiency, and optimality in the Fenna-Matthews-Olson photosynthetic pigment-protein complex

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

Baker, Lewis A.; Habershon, Scott, E-mail: S.Habershon@warwick.ac.uk

Pigment-protein complexes (PPCs) play a central role in facilitating excitation energy transfer (EET) from light-harvesting antenna complexes to reaction centres in photosynthetic systems; understanding molecular organisation in these biological networks is key to developing better artificial light-harvesting systems. In this article, we combine quantum-mechanical simulations and a network-based picture of transport to investigate how chromophore organization and protein environment in PPCs impacts on EET efficiency and robustness. In a prototypical PPC model, the Fenna-Matthews-Olson (FMO) complex, we consider the impact on EET efficiency of both disrupting the chromophore network and changing the influence of (local and global) environmental dephasing. Surprisingly,more » we find a large degree of resilience to changes in both chromophore network and protein environmental dephasing, the extent of which is greater than previously observed; for example, FMO maintains EET when 50% of the constituent chromophores are removed, or when environmental dephasing fluctuations vary over two orders-of-magnitude relative to the in vivo system. We also highlight the fact that the influence of local dephasing can be strongly dependent on the characteristics of the EET network and the initial excitation; for example, initial excitations resulting in rapid coherent decay are generally insensitive to the environment, whereas the incoherent population decay observed following excitation at weakly coupled chromophores demonstrates a more pronounced dependence on dephasing rate as a result of the greater possibility of local exciton trapping. Finally, we show that the FMO electronic Hamiltonian is not particularly optimised for EET; instead, it is just one of many possible chromophore organisations which demonstrate a good level of EET transport efficiency following excitation at different chromophores. Overall, these robustness and efficiency characteristics are attributed to the highly connected nature of the chromophore network and the presence of multiple EET pathways, features which might easily be built into artificial photosynthetic systems.« less

Objective sampling design in a highly heterogeneous landscape - characterizing environmental determinants of malaria vector distribution in French Guiana, in the Amazonian region.

PubMed

Roux, Emmanuel; Gaborit, Pascal; Romaña, Christine A; Girod, Romain; Dessay, Nadine; Dusfour, Isabelle

2013-12-01

Sampling design is a key issue when establishing species inventories and characterizing habitats within highly heterogeneous landscapes. Sampling efforts in such environments may be constrained and many field studies only rely on subjective and/or qualitative approaches to design collection strategy. The region of Cacao, in French Guiana, provides an excellent study site to understand the presence and abundance of Anopheles mosquitoes, their species dynamics and the transmission risk of malaria across various environments. We propose an objective methodology to define a stratified sampling design. Following thorough environmental characterization, a factorial analysis of mixed groups allows the data to be reduced and non-collinear principal components to be identified while balancing the influences of the different environmental factors. Such components defined new variables which could then be used in a robust k-means clustering procedure. Then, we identified five clusters that corresponded to our sampling strata and selected sampling sites in each stratum. We validated our method by comparing the species overlap of entomological collections from selected sites and the environmental similarities of the same sites. The Morisita index was significantly correlated (Pearson linear correlation) with environmental similarity based on i) the balanced environmental variable groups considered jointly (p = 0.001) and ii) land cover/use (p-value < 0.001). The Jaccard index was significantly correlated with land cover/use-based environmental similarity (p-value = 0.001). The results validate our sampling approach. Land cover/use maps (based on high spatial resolution satellite images) were shown to be particularly useful when studying the presence, density and diversity of Anopheles mosquitoes at local scales and in very heterogeneous landscapes.

Objective sampling design in a highly heterogeneous landscape - characterizing environmental determinants of malaria vector distribution in French Guiana, in the Amazonian region

PubMed Central

2013-01-01

Background Sampling design is a key issue when establishing species inventories and characterizing habitats within highly heterogeneous landscapes. Sampling efforts in such environments may be constrained and many field studies only rely on subjective and/or qualitative approaches to design collection strategy. The region of Cacao, in French Guiana, provides an excellent study site to understand the presence and abundance of Anopheles mosquitoes, their species dynamics and the transmission risk of malaria across various environments. We propose an objective methodology to define a stratified sampling design. Following thorough environmental characterization, a factorial analysis of mixed groups allows the data to be reduced and non-collinear principal components to be identified while balancing the influences of the different environmental factors. Such components defined new variables which could then be used in a robust k-means clustering procedure. Then, we identified five clusters that corresponded to our sampling strata and selected sampling sites in each stratum. Results We validated our method by comparing the species overlap of entomological collections from selected sites and the environmental similarities of the same sites. The Morisita index was significantly correlated (Pearson linear correlation) with environmental similarity based on i) the balanced environmental variable groups considered jointly (p = 0.001) and ii) land cover/use (p-value << 0.001). The Jaccard index was significantly correlated with land cover/use-based environmental similarity (p-value = 0.001). Conclusions The results validate our sampling approach. Land cover/use maps (based on high spatial resolution satellite images) were shown to be particularly useful when studying the presence, density and diversity of Anopheles mosquitoes at local scales and in very heterogeneous landscapes. PMID:24289184

77 FR 38051 - EPA Activities To Promote Environmental Justice in the Permit Application Process

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-26

... (EPA). In 2011, EPA published Plan EJ 2014, the Agency's overarching strategy for advancing... robust community engagement strategies that recognize the value of community outreach. Pursuant to these strategies, facilities engage actively with the community through environmental initiatives, neighborhood...

A sensitive analytical procedure for monitoring acrylamide in environmental water samples by offline SPE-UPLC/MS/MS.

PubMed

Togola, Anne; Coureau, Charlotte; Guezennec, Anne-Gwenaëlle; Touzé, Solène

2015-05-01

The presence of acrylamide in natural systems is of concern from both environmental and health points of view. We developed an accurate and robust analytical procedure (offline solid phase extraction combined with UPLC/MS/MS) with a limit of quantification (20 ng L(-1)) compatible with toxicity threshold values. The optimized (considering the nature of extraction phases, sampling volumes, and solvent of elution) solid phase extraction (SPE) was validated according to ISO Standard ISO/IEC 17025 on groundwater, surface water, and industrial process water samples. Acrylamide is highly polar, which induces a high variability during the SPE step, therefore requiring the use of C(13)-labeled acrylamide as an internal standard to guarantee the accuracy and robustness of the method (uncertainty about 25 % (k = 2) at limit of quantification level). The specificity of the method and the stability of acrylamide were studied for these environmental media, and it was shown that the method is suitable for measuring acrylamide in environmental studies.

Comparative Evaluation of Veriflow®Listeria Species to USDA Culture-Based Method for the Detection of Listeria spp. in Food and Environmental Samples.

PubMed

Joelsson, Adam C; Terkhorn, Shawn P; Brown, Ashley S; Puri, Amrita; Pascal, Benjamin J; Gaudioso, Zara E; Siciliano, Nicholas A

2017-09-01

Veriflow® Listeria species (Veriflow LS) is a molecular-based assay for the presumptive detection of Listeria spp. from environmental surfaces (stainless steel, sealed concrete, plastic, and ceramic tile) and ready-to-eat (RTE) food matrixes (hot dogs and deli meat). The assay utilizes a PCR detection method coupled with a rapid, visual, flow-based assay that develops in 3 min post-PCR amplification and requires only a 24 h enrichment for maximum sensitivity. The Veriflow LS system eliminates the need for sample purification, gel electrophoresis, or fluorophore-based detection of target amplification and does not require complex data analysis. This Performance Tested MethodSM validation study demonstrated the ability of the Veriflow LS assay to detect low levels of artificially inoculated Listeria spp. in six distinct environmental and food matrixes. In each unpaired reference comparison study, probability of detection analysis indicated that there was no significant difference between the Veriflow LS method and the U.S. Department of Agriculture Food Safety and Inspection Service Microbiology Laboratory Guide Chapter 8.08 reference method. Fifty-one strains of various Listeria spp. were detected in the inclusivity study, and 35 nonspecific organisms went undetected in the exclusivity study. The study results show that the Veriflow LS is a sensitive, selective, and robust assay for the presumptive detection of Listeria spp. sampled from environmental surfaces (stainless steel, sealed concrete, plastic, and ceramic tile) and RTE food matrixes (hot dogs and deli meat).

Northern Russian chironomid-based modern summer temperature data set and inference models

NASA Astrophysics Data System (ADS)

Nazarova, Larisa; Self, Angela E.; Brooks, Stephen J.; van Hardenbroek, Maarten; Herzschuh, Ulrike; Diekmann, Bernhard

2015-11-01

West and East Siberian data sets and 55 new sites were merged based on the high taxonomic similarity, and the strong relationship between mean July air temperature and the distribution of chironomid taxa in both data sets compared with other environmental parameters. Multivariate statistical analysis of chironomid and environmental data from the combined data set consisting of 268 lakes, located in northern Russia, suggests that mean July air temperature explains the greatest amount of variance in chironomid distribution compared with other measured variables (latitude, longitude, altitude, water depth, lake surface area, pH, conductivity, mean January air temperature, mean July air temperature, and continentality). We established two robust inference models to reconstruct mean summer air temperatures from subfossil chironomids based on ecological and geographical approaches. The North Russian 2-component WA-PLS model (RMSEPJack = 1.35 °C, rJack2 = 0.87) can be recommended for application in palaeoclimatic studies in northern Russia. Based on distinctive chironomid fauna and climatic regimes of Kamchatka the Far East 2-component WAPLS model (RMSEPJack = 1.3 °C, rJack2 = 0.81) has potentially better applicability in Kamchatka.

Long fiber Bragg grating sensor interrogation using discrete-time microwave photonic filtering techniques.

PubMed

Ricchiuti, Amelia Lavinia; Barrera, David; Sales, Salvador; Thevenaz, Luc; Capmany, José

2013-11-18

A novel technique for interrogating photonic sensors based on long fiber Bragg gratings (FBGs) is presented and experimentally demonstrated, dedicated to detect the presence and the precise location of several spot events. The principle of operation is based on a technique used to analyze microwave photonics (MWP) filters. The long FBGs are used as quasi-distributed sensors. Several hot-spots can be detected along the FBG with a spatial accuracy under 0.5 mm using a modulator and a photo-detector (PD) with a modest bandwidth of less than 1 GHz. The proposed interrogation system is intrinsically robust against environmental changes.

Modeling the effects of trophy selection and environmental disturbance on a simulated population of African lions.

PubMed

Whitman, Karyl L; Starfield, Anthony M; Quadling, Henley; Packer, Craig

2007-06-01

Tanzania is a premier destination for trophy hunting of African lions (Panthera leo) and is home to the most extensive long-term study of unhunted lions. Thus, it provides a unique opportunity to apply data from a long-term field study to a conservation dilemma: How can a trophy-hunted species whose reproductive success is closely tied to social stability be harvested sustainably? We used an individually based, spatially explicit, stochastic model, parameterized with nearly 40 years of behavioral and demographic data on lions in the Serengeti, to examine the separate effects of trophy selection and environmental disturbance on the viability of a simulated lion population in response to annual harvesting. Female population size was sensitive to the harvesting of young males (> or = 3 years), whereas hunting represented a relatively trivial threat to population viability when the harvest was restricted to mature males (> or = 6 years). Overall model performance was robust to environmental disturbance and to errors in age assessment based on nose coloration as an index used to age potential trophies. Introducing an environmental disturbance did not eliminate the capacity to maintain a viable breeding population when harvesting only older males, and initially depleted populations recovered within 15-25 years after the disturbance to levels comparable to hunted populations that did not experience a catastrophic event. These results are consistent with empirical observations of lion resilience to environmental stochasticity.

Performance of vegetation indices from Landsat time series in deforestation monitoring

NASA Astrophysics Data System (ADS)

Schultz, Michael; Clevers, Jan G. P. W.; Carter, Sarah; Verbesselt, Jan; Avitabile, Valerio; Quang, Hien Vu; Herold, Martin

2016-10-01

The performance of Landsat time series (LTS) of eight vegetation indices (VIs) was assessed for monitoring deforestation across the tropics. Three sites were selected based on differing remote sensing observation frequencies, deforestation drivers and environmental factors. The LTS of each VI was analysed using the Breaks For Additive Season and Trend (BFAST) Monitor method to identify deforestation. A robust reference database was used to evaluate the performance regarding spatial accuracy, sensitivity to observation frequency and combined use of multiple VIs. The canopy cover sensitive Normalized Difference Fraction Index (NDFI) was the most accurate. Among those tested, wetness related VIs (Normalized Difference Moisture Index (NDMI) and the Tasselled Cap wetness (TCw)) were spatially more accurate than greenness related VIs (Normalized Difference Vegetation Index (NDVI) and Tasselled Cap greenness (TCg)). When VIs were fused on feature level, spatial accuracy was improved and overestimation of change reduced. NDVI and NDFI produced the most robust results when observation frequency varies.

The Cross-Correlation and Reshuffling Tests in Discerning Induced Seismicity

NASA Astrophysics Data System (ADS)

Schultz, Ryan; Telesca, Luciano

2018-05-01

In recent years, cases of newly emergent induced clusters have increased seismic hazard and risk in locations with social, environmental, and economic consequence. Thus, the need for a quantitative and robust means to discern induced seismicity has become a critical concern. This paper reviews a Matlab-based algorithm designed to quantify the statistical confidence between two time-series datasets. Similar to prior approaches, our method utilizes the cross-correlation to delineate the strength and lag of correlated signals. In addition, use of surrogate reshuffling tests allows for the dynamic testing against statistical confidence intervals of anticipated spurious correlations. We demonstrate the robust nature of our algorithm in a suite of synthetic tests to determine the limits of accurate signal detection in the presence of noise and sub-sampling. Overall, this routine has considerable merit in terms of delineating the strength of correlated signals, one of which includes the discernment of induced seismicity from natural.

Robust Depth Image Acquisition Using Modulated Pattern Projection and Probabilistic Graphical Models

PubMed Central

Kravanja, Jaka; Žganec, Mario; Žganec-Gros, Jerneja; Dobrišek, Simon; Štruc, Vitomir

2016-01-01

Depth image acquisition with structured light approaches in outdoor environments is a challenging problem due to external factors, such as ambient sunlight, which commonly affect the acquisition procedure. This paper presents a novel structured light sensor designed specifically for operation in outdoor environments. The sensor exploits a modulated sequence of structured light projected onto the target scene to counteract environmental factors and estimate a spatial distortion map in a robust manner. The correspondence between the projected pattern and the estimated distortion map is then established using a probabilistic framework based on graphical models. Finally, the depth image of the target scene is reconstructed using a number of reference frames recorded during the calibration process. We evaluate the proposed sensor on experimental data in indoor and outdoor environments and present comparative experiments with other existing methods, as well as commercial sensors. PMID:27775570

Color sensor and neural processor on one chip

NASA Astrophysics Data System (ADS)

Fiesler, Emile; Campbell, Shannon R.; Kempem, Lother; Duong, Tuan A.

1998-10-01

Low-cost, compact, and robust color sensor that can operate in real-time under various environmental conditions can benefit many applications, including quality control, chemical sensing, food production, medical diagnostics, energy conservation, monitoring of hazardous waste, and recycling. Unfortunately, existing color sensor are either bulky and expensive or do not provide the required speed and accuracy. In this publication we describe the design of an accurate real-time color classification sensor, together with preprocessing and a subsequent neural network processor integrated on a single complementary metal oxide semiconductor (CMOS) integrated circuit. This one-chip sensor and information processor will be low in cost, robust, and mass-producible using standard commercial CMOS processes. The performance of the chip and the feasibility of its manufacturing is proven through computer simulations based on CMOS hardware parameters. Comparisons with competing methodologies show a significantly higher performance for our device.

Multiple Leader Candidate and Competitive Position Allocation for Robust Formation against Member Robot Faults

PubMed Central

Kwon, Ji-Wook; Kim, Jin Hyo; Seo, Jiwon

2015-01-01

This paper proposes a Multiple Leader Candidate (MLC) structure and a Competitive Position Allocation (CPA) algorithm which can be applicable for various applications including environmental sensing. Unlike previous formation structures such as virtual-leader and actual-leader structures with position allocation including a rigid allocation and an optimization based allocation, the formation employing the proposed MLC structure and CPA algorithm is robust against the fault (or disappearance) of the member robots and reduces the entire cost. In the MLC structure, a leader of the entire system is chosen among leader candidate robots. The CPA algorithm is the decentralized position allocation algorithm that assigns the robots to the vertex of the formation via the competition of the adjacent robots. The numerical simulations and experimental results are included to show the feasibility and the performance of the multiple robot system employing the proposed MLC structure and the CPA algorithm. PMID:25954956

The Navigation Guide Systematic Review Methodology: A Rigorous and Transparent Method for Translating Environmental Health Science into Better Health Outcomes

PubMed Central

Sutton, Patrice

2014-01-01

Background: Synthesizing what is known about the environmental drivers of health is instrumental to taking prevention-oriented action. Methods of research synthesis commonly used in environmental health lag behind systematic review methods developed in the clinical sciences over the past 20 years. Objectives: We sought to develop a proof of concept of the “Navigation Guide,” a systematic and transparent method of research synthesis in environmental health. Discussion: The Navigation Guide methodology builds on best practices in research synthesis in evidence-based medicine and environmental health. Key points of departure from current methods of expert-based narrative review prevalent in environmental health include a prespecified protocol, standardized and transparent documentation including expert judgment, a comprehensive search strategy, assessment of “risk of bias,” and separation of the science from values and preferences. Key points of departure from evidence-based medicine include assigning a “moderate” quality rating to human observational studies and combining diverse evidence streams. Conclusions: The Navigation Guide methodology is a systematic and rigorous approach to research synthesis that has been developed to reduce bias and maximize transparency in the evaluation of environmental health information. Although novel aspects of the method will require further development and validation, our findings demonstrated that improved methods of research synthesis under development at the National Toxicology Program and under consideration by the U.S. Environmental Protection Agency are fully achievable. The institutionalization of robust methods of systematic and transparent review would provide a concrete mechanism for linking science to timely action to prevent harm. Citation: Woodruff TJ, Sutton P. 2014. The Navigation Guide systematic review methodology: a rigorous and transparent method for translating environmental health science into better health outcomes. Environ Health Perspect 122:1007–1014; http://dx.doi.org/10.1289/ehp.1307175 PMID:24968373

Female mating preferences determine system-level evolution in a gene network model.

PubMed

Fierst, Janna L

2013-06-01

Environmental patterns of directional, stabilizing and fluctuating selection can influence the evolution of system-level properties like evolvability and mutational robustness. Intersexual selection produces strong phenotypic selection and these dynamics may also affect the response to mutation and the potential for future adaptation. In order to to assess the influence of mating preferences on these evolutionary properties, I modeled a male trait and female preference determined by separate gene regulatory networks. I studied three sexual selection scenarios: sexual conflict, a Gaussian model of the Fisher process described in Lande (in Proc Natl Acad Sci 78(6):3721-3725, 1981) and a good genes model in which the male trait signalled his mutational condition. I measured the effects these mating preferences had on the potential for traits and preferences to evolve towards new states, and mutational robustness of both the phenotype and the individual's overall viability. All types of sexual selection increased male phenotypic robustness relative to a randomly mating population. The Fisher model also reduced male evolvability and mutational robustness for viability. Under good genes sexual selection, males evolved an increased mutational robustness for viability. Females choosing their mates is a scenario that is sufficient to create selective forces that impact genetic evolution and shape the evolutionary response to mutation and environmental selection. These dynamics will inevitably develop in any population where sexual selection is operating, and affect the potential for future adaptation.

Multi-criteria multi-stakeholder decision analysis using a fuzzy-stochastic approach for hydrosystem management

NASA Astrophysics Data System (ADS)

Subagadis, Y. H.; Schütze, N.; Grundmann, J.

2014-09-01

The conventional methods used to solve multi-criteria multi-stakeholder problems are less strongly formulated, as they normally incorporate only homogeneous information at a time and suggest aggregating objectives of different decision-makers avoiding water-society interactions. In this contribution, Multi-Criteria Group Decision Analysis (MCGDA) using a fuzzy-stochastic approach has been proposed to rank a set of alternatives in water management decisions incorporating heterogeneous information under uncertainty. The decision making framework takes hydrologically, environmentally, and socio-economically motivated conflicting objectives into consideration. The criteria related to the performance of the physical system are optimized using multi-criteria simulation-based optimization, and fuzzy linguistic quantifiers have been used to evaluate subjective criteria and to assess stakeholders' degree of optimism. The proposed methodology is applied to find effective and robust intervention strategies for the management of a coastal hydrosystem affected by saltwater intrusion due to excessive groundwater extraction for irrigated agriculture and municipal use. Preliminary results show that the MCGDA based on a fuzzy-stochastic approach gives useful support for robust decision-making and is sensitive to the decision makers' degree of optimism.

Additive Mixing and Conformal Coating of Noniridescent Structural Colors with Robust Mechanical Properties Fabricated by Atomization Deposition.

PubMed

Li, Qingsong; Zhang, Yafeng; Shi, Lei; Qiu, Huihui; Zhang, Suming; Qi, Ning; Hu, Jianchen; Yuan, Wei; Zhang, Xiaohua; Zhang, Ke-Qin

2018-04-24

Artificial structural colors based on short-range-ordered amorphous photonic structures (APSs) have attracted great scientific and industrial interest in recent years. However, the previously reported methods of self-assembling colloidal nanoparticles lack fine control of the APS coating and fixation on substrates and poorly realize three-dimensional (3D) conformal coatings for objects with irregular or highly curved surfaces. In this paper, atomization deposition of silica colloidal nanoparticles with poly(vinyl alcohol) as the additive is proposed to solve the above problems. By finely controlling the thicknesses of APS coatings, additive mixing of noniridescent structural colors is easily realized. Based on the intrinsic omnidirectional feature of atomization, a one-step 3D homogeneous conformal coating is also readily realized on various irregular or highly curved surfaces, including papers, resins, metal plates, ceramics, and flexible silk fabrics. The vivid coatings on silk fabrics by atomization deposition possess robust mechanical properties, which are confirmed by rubbing and laundering tests, showing great potential in developing an environmentally friendly coloring technique in the textile industry.

THE EFFECTS OF UNCERTAINTY ON ESTIMATING THE RELATIVE ENVIRONMENTAL QUALITY OF WATERSHEDS ACROSS A REGION

EPA Science Inventory

Landscape ecologists may be faced with ranking the relative environmental quality of watersheds across a region. The results show that watersheds in the best and the worst condition have rankings that are robust to uncertainty but intermediate watersheds may be difficult or impo...

ROBUST ESTIMATION OF MEAN AND VARIANCE USING ENVIRONMENTAL DATA SETS WITH BELOW DETECTION LIMIT OBSERVATIONS

EPA Science Inventory

Scientists, especially environmental scientists often encounter trace level concentrations that are typically reported as less than a certain limit of detection, L. Type 1, left-censored data arise when certain low values lying below L are ignored or unknown as they cannot be mea...

75 FR 26269 - Draft Programmatic Environmental Assessment for the Integrated Public Alert and Warning Program's...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-11

...] Draft Programmatic Environmental Assessment for the Integrated Public Alert and Warning Program's... from construction- related actions taken under the Integrated Public Alert and Warning Program (IPAWS... Order 13407, Public Alert and Warning System, by providing robust and survivable power generation, fuel...

Working Group on Virtual Data Integration

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

Williams, Dean N.

2016-03-07

This report is the outcome of a workshop commissioned by the U.S. Department of Energy’s (DOE) Climate and Environmental Sciences Division (CESD) to examine current and future data infrastructure requirements foundational for achieving CESD scientific mission goals in advancing a robust, predictive understanding of Earth’s climate and environmental systems.

Environmental Scanning: Assessing Local Business Training Needs.

ERIC Educational Resources Information Center

Clagett, Craig A.; Huntington, Robin B.

Environmental scanning (ES) is a formal process of assessing trends and forecasting events which can influence an institution so that the potential challenges and opportunities can be effectively anticipated during strategic planning activities. The goal of ES is the implementation of proactive, anticipatory policies that will be robust under a…

Modelling the influence of parental effects on gene-network evolution.

PubMed

Odorico, Andreas; Rünneburger, Estelle; Le Rouzic, Arnaud

2018-05-01

Understanding the importance of nongenetic heredity in the evolutionary process is a major topic in modern evolutionary biology. We modified a classical gene-network model by allowing parental transmission of gene expression and studied its evolutionary properties through individual-based simulations. We identified ontogenetic time (i.e. the time gene networks have to stabilize before being submitted to natural selection) as a crucial factor in determining the evolutionary impact of this phenotypic inheritance. Indeed, fast-developing organisms display enhanced adaptation and greater robustness to mutations when evolving in presence of nongenetic inheritance (NGI). In contrast, in our model, long development reduces the influence of the inherited state of the gene network. NGI thus had a negligible effect on the evolution of gene networks when the speed at which transcription levels reach equilibrium is not constrained. Nevertheless, simulations show that intergenerational transmission of the gene-network state negatively affects the evolution of robustness to environmental disturbances for either fast- or slow-developing organisms. Therefore, these results suggest that the evolutionary consequences of NGI might not be sought only in the way species respond to selection, but also on the evolution of emergent properties (such as environmental and genetic canalization) in complex genetic architectures. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

Geographical Genomics of Human Leukocyte Gene Expression Variation in Southern Morocco

PubMed Central

Idaghdour, Youssef; Czika, Wendy; Shianna, Kevin V.; Lee, S. Hong; Visscher, Peter M.; Martin, Hilary C.; Miclaus, Kelci; Jadallah, Sami J.; Goldstein, David B.; Wolfinger, Russell D.; Gibson, Greg

2009-01-01

Studies of the genetics of gene expression reveal expression SNPs that explain variation in transcript abundance. Here we address the robustness of eSNP associations to environmental geography and population structure in a comparison of 194 Arab and Amazigh individuals from a city and two villages in southern Morocco. Gene expression differed between pairs of locations for up to a third of all transcripts, with notable enrichment for ribosomal biosynthesis and oxidative phosphorylation. Robust associations were observed in the leukocyte samples with cis-eSNPs (P < 10−08) for 346 genes, and trans-eSNPs (P < 10−11) with 10 genes. All of these were consistent across the three sample locations and after controlling for ethnicity and relatedness. No evidence for large-effect trans-acting mediators of the pervasive environmental influence was found and instead genetic and environmental factors acted in a largely additive manner. PMID:19966804

On Motion Planning and Control of Multi-Link Lightweight Robotic Manipulators

NASA Technical Reports Server (NTRS)

Cetinkunt, Sabri

1987-01-01

A general gross and fine motion planning and control strategy is needed for lightweight robotic manipulator applications such as painting, welding, material handling, surface finishing, and spacecraft servicing. The control problem of lightweight manipulators is to perform fast, accurate, and robust motions despite the payload variations, structural flexibility, and other environmental disturbances. Performance of the rigid manipulator model based computed torque and decoupled joint control methods are determined and simulated for the counterpart flexible manipulators. A counterpart flexible manipulator is defined as a manipulator which has structural flexibility, in addition to having the same inertial, geometric, and actuation properties of a given rigid manipulator. An adaptive model following control (AMFC) algorithm is developed to improve the performance in speed, accuracy, and robustness. It is found that the AMFC improves the speed performance by a factor of two over the conventional non-adaptive control methods for given accuracy requirements while proving to be more robust with respect to payload variations. Yet there are clear limitations on the performance of AMFC alone as well, which are imposed by the arm flexibility. In the search to further improve speed performance while providing a desired accuracy and robustness, a combined control strategy is developed. Furthermore, the problem of switching from one control structure to another during the motion and implementation aspects of combined control are discussed.

Illumination Invariant Change Detection (iicd): from Earth to Mars

NASA Astrophysics Data System (ADS)

Wan, X.; Liu, J.; Qin, M.; Li, S. Y.

2018-04-01

Multi-temporal Earth Observation and Mars orbital imagery data with frequent repeat coverage provide great capability for planetary surface change detection. When comparing two images taken at different times of day or in different seasons for change detection, the variation of topographic shades and shadows caused by the change of sunlight angle can be so significant that it overwhelms the real object and environmental changes, making automatic detection unreliable. An effective change detection algorithm therefore has to be robust to the illumination variation. This paper presents our research on developing and testing an Illumination Invariant Change Detection (IICD) method based on the robustness of phase correlation (PC) to the variation of solar illumination for image matching. The IICD is based on two key functions: i) initial change detection based on a saliency map derived from pixel-wise dense PC matching and ii) change quantization which combines change type identification, motion estimation and precise appearance change identification. Experiment using multi-temporal Landsat 7 ETM+ satellite images, Rapid eye satellite images and Mars HiRiSE images demonstrate that our frequency based image matching method can reach sub-pixel accuracy and thus the proposed IICD method can effectively detect and precisely segment large scale change such as landslide as well as small object change such as Mars rover, under daily and seasonal sunlight changes.

Mass Spectrometric Quantification of N-Linked Glycans by Reference to Exogenous Standards.

PubMed

Mehta, Nickita; Porterfield, Mindy; Struwe, Weston B; Heiss, Christian; Azadi, Parastoo; Rudd, Pauline M; Tiemeyer, Michael; Aoki, Kazuhiro

2016-09-02

Environmental and metabolic processes shape the profile of glycoprotein glycans expressed by cells, whether in culture, developing tissues, or mature organisms. Quantitative characterization of glycomic changes associated with these conditions has been achieved historically by reductive coupling of oligosaccharides to various fluorophores following release from glycoprotein and subsequent HPLC or capillary electrophoretic separation. Such labeling-based approaches provide a robust means of quantifying glycan amount based on fluorescence yield. Mass spectrometry, on the other hand, has generally been limited to relative quantification in which the contribution of the signal intensity for an individual glycan is expressed as a percent of the signal intensity summed over the total profile. Relative quantification has been valuable for highlighting changes in glycan expression between samples; sensitivity is high, and structural information can be derived by fragmentation. We have investigated whether MS-based glycomics is amenable to absolute quantification by referencing signal intensities to well-characterized oligosaccharide standards. We report the qualification of a set of N-linked oligosaccharide standards by NMR, HPLC, and MS. We also demonstrate the dynamic range, sensitivity, and recovery from complex biological matrices for these standards in their permethylated form. Our results indicate that absolute quantification for MS-based glycomic analysis is reproducible and robust utilizing currently available glycan standards.

Optimal Diabatic Dynamics of Majoarana-based Topological Qubits

NASA Astrophysics Data System (ADS)

Seradjeh, Babak; Rahmani, Armin; Franz, Marcel

In topological quantum computing, unitary operations on qubits are performed by adiabatic braiding of non-Abelian quasiparticles such as Majorana zero modes and are protected from local environmental perturbations. This scheme requires slow operations. By using the Pontryagin's maximum principle, here we show the same quantum gates can be implemented in much shorter times through optimal diabatic pulses. While our fast diabatic gates no not enjoy topological protection, they provide significant practical advantages due to their optimal speed and remarkable robustness to calibration errors and noise. NSERC, CIfAR, NSF DMR- 1350663, BSF 2014345.

Modelling spatio-temporal variability of Mytilus edulis (L.) growth by forcing a dynamic energy budget model with satellite-derived environmental data

NASA Astrophysics Data System (ADS)

Thomas, Yoann; Mazurié, Joseph; Alunno-Bruscia, Marianne; Bacher, Cédric; Bouget, Jean-François; Gohin, Francis; Pouvreau, Stéphane; Struski, Caroline

2011-11-01

In order to assess the potential of various marine ecosystems for shellfish aquaculture and to evaluate their carrying capacities, there is a need to clarify the response of exploited species to environmental variations using robust ecophysiological models and available environmental data. For a large range of applications and comparison purposes, a non-specific approach based on 'generic' individual growth models offers many advantages. In this context, we simulated the response of blue mussel ( Mytilus edulis L.) to the spatio-temporal fluctuations of the environment in Mont Saint-Michel Bay (North Brittany) by forcing a generic growth model based on Dynamic Energy Budgets with satellite-derived environmental data (i.e. temperature and food). After a calibration step based on data from mussel growth surveys, the model was applied over nine years on a large area covering the entire bay. These simulations provide an evaluation of the spatio-temporal variability in mussel growth and also show the ability of the DEB model to integrate satellite-derived data and to predict spatial and temporal growth variability of mussels. Observed seasonal, inter-annual and spatial growth variations are well simulated. The large-scale application highlights the strong link between food and mussel growth. The methodology described in this study may be considered as a suitable approach to account for environmental effects (food and temperature variations) on physiological responses (growth and reproduction) of filter feeders in varying environments. Such physiological responses may then be useful for evaluating the suitability of coastal ecosystems for shellfish aquaculture.

Reciprocity Between Robustness of Period and Plasticity of Phase in Biological Clocks

NASA Astrophysics Data System (ADS)

Hatakeyama, Tetsuhiro S.; Kaneko, Kunihiko

2015-11-01

Circadian clocks exhibit the robustness of period and plasticity of phase against environmental changes such as temperature and nutrient conditions. Thus far, however, it is unclear how both are simultaneously achieved. By investigating distinct models of circadian clocks, we demonstrate reciprocity between robustness and plasticity: higher robustness in the period implies higher plasticity in the phase, where changes in period and in phase follow a linear relationship with a negative coefficient. The robustness of period is achieved by the adaptation on the limit cycle via a concentration change of a buffer molecule, whose temporal change leads to a phase shift following a shift of the limit-cycle orbit in phase space. Generality of reciprocity in clocks with the adaptation mechanism is confirmed with theoretical analysis of simple models, while biological significance is discussed.

Is CO2 emission a side effect of financial development? An empirical analysis for China.

PubMed

Hao, Yu; Zhang, Zong-Yong; Liao, Hua; Wei, Yi-Ming; Wang, Shuo

2016-10-01

Based on panel data for 29 Chinese provinces from 1995 to 2012, this paper explores the relationship between financial development and environmental quality in China. A comprehensive framework is utilized to estimate both the direct and indirect effects of financial development on CO 2 emissions in China using a carefully designed two-stage regression model. The first-difference and orthogonal-deviation Generalized Method of Moments (GMM) methods are used to control for potential endogeneity and introduce dynamics. To ensure the robustness of the estimations, two indicators measuring financial development-financial depth and financial efficiency-are used. The empirical results indicate that the direct effects of financial depth and financial efficiency on environmental quality are positive and negative, respectively. The indirect effects of both indicators are U shaped and dominate the shape of the total effects. These findings suggest that the influences of the financial development on environment depend on the level of economic development. At the early stage of economic growth, financial development is environmentally friendly. When the economy is highly developed, a higher level of financial development is harmful to the environmental quality.

From Environmental Sequences to Morphology: Observation and Characterisation of a Paulinellid Testate Amoeba (Micropyxidiella edaphonis gen. nov. sp. nov. Euglyphida, Paulinellidae) from Soil using Fluorescent in situ Hybridization.

PubMed

Tarnawski, Sonia-Estelle; Lara, Enrique

2015-05-01

High microbial diversity is revealed by environmental DNA surveys. However, nothing is known about the morphology and function of these potentially new organisms. In the course of an environmental soil diversity study, we found for the first time environmental sequences that reveal the presence of Paulinellidae (a mostly marine and marginally freshwater family of euglyphid testate amoebae) in samples of forest litter from different geographic origins. The new sequences form a basal, robust clade in the family. We used fluorescent in situ hybridization (FISH) to detect the organisms from which these sequences derived. We isolated the cells and documented them with light and scanning electron microscopy. Based on these observations, we described these organisms as Micropyxidiella edaphonis gen. nov. sp. nov. The organisms were very small testate amoebae (generally less than 10μm) with an irregular proteinaceous test. This suggests an unknown diversity in testate amoebae, and calls for extending this type of investigations to other protist groups which are known only as environmental DNA sequences. Copyright © 2015 Elsevier GmbH. All rights reserved.

The impact of environmental pollution on public health expenditure: dynamic panel analysis based on Chinese provincial data.

PubMed

Hao, Yu; Liu, Shuang; Lu, Zhi-Nan; Huang, Junbing; Zhao, Mingyuan

2018-05-01

In recent years, along with rapid economic growth, China's environmental problems have become increasingly prominent. At the same time, the level of China's pollution has been growing rapidly, which has caused huge damages to the residents' health. In this regard, the public health expenditure ballooned as the environmental quality deteriorated in China. In this study, the effect of environmental pollution on residents' health expenditure is empirically investigated by employing the first-order difference generalized method of moments (GMM) method to control for potential endogeneity. Using a panel data of Chinese provinces for the period of 1998-2015, this study found that the environmental pollution (represented by SO 2 and soot emissions) would indeed lead to the increase in the medical expenses of Chinese residents. At the current stage of economic development, an increase in SO 2 and soot emissions per capita would push up the public health expenditure per capita significantly. The estimation results are quite robust for different types of regression specifications and different combinations of control variables. Some social and economic variables such as public services and education may also have remarkable influences on residential medical expenses through different channels.

Life cycle assessment of overhead and underground primary power distribution.

PubMed

Bumby, Sarah; Druzhinina, Ekaterina; Feraldi, Rebe; Werthmann, Danae; Geyer, Roland; Sahl, Jack

2010-07-15

Electrical power can be distributed in overhead or underground systems, both of which generate a variety of environmental impacts at all stages of their life cycles. While there is considerable literature discussing the trade-offs between both systems in terms of aesthetics, safety, cost, and reliability, environmental assessments are relatively rare and limited to power cable production and end-of-life management. This paper assesses environmental impacts from overhead and underground medium voltage power distribution systems as they are currently built and managed by Southern California Edison (SCE). It uses process-based life cycle assessment (LCA) according to ISO 14044 (2006) and SCE-specific primary data to the extent possible. Potential environmental impacts have been calculated using a wide range of midpoint indicators, and robustness of the results has been investigated through sensitivity analysis of the most uncertain and potentially significant parameters. The studied underground system has higher environmental impacts in all indicators and for all parameter values, mostly due to its higher material intensity. For both systems and all indicators the majority of impact occurs during cable production. Promising strategies for impact reduction are thus cable failure rate reduction for overhead and cable lifetime extension for underground systems.

Optimal dynamic water allocation: Irrigation extractions and environmental tradeoffs in the Murray River, Australia

NASA Astrophysics Data System (ADS)

Grafton, R. Quentin; Chu, Hoang Long; Stewardson, Michael; Kompas, Tom

2011-12-01

A key challenge in managing semiarid basins, such as in the Murray-Darling in Australia, is to balance the trade-offs between the net benefits of allocating water for irrigated agriculture, and other uses, versus the costs of reduced surface flows for the environment. Typically, water planners do not have the tools to optimally and dynamically allocate water among competing uses. We address this problem by developing a general stochastic, dynamic programming model with four state variables (the drought status, the current weather, weather correlation, and current storage) and two controls (environmental release and irrigation allocation) to optimally allocate water between extractions and in situ uses. The model is calibrated to Australia's Murray River that generates: (1) a robust qualitative result that "pulse" or artificial flood events are an optimal way to deliver environmental flows over and above conveyance of base flows; (2) from 2001 to 2009 a water reallocation that would have given less to irrigated agriculture and more to environmental flows would have generated between half a billion and over 3 billion U.S. dollars in overall economic benefits; and (3) water markets increase optimal environmental releases by reducing the losses associated with reduced water diversions.

Are exposure predictions, used for the prioritization of pharmaceuticals in the environment, fit for purpose?

USGS Publications Warehouse

Burns, Emily E.; Thomas-Oates, Jane; Kolpin, Dana W.; Furlong, Edward T.; Boxall, Alistair B.A.

2017-01-01

Prioritization methodologies are often used for identifying those pharmaceuticals that pose the greatest risk to the natural environment and to focus laboratory testing or environmental monitoring toward pharmaceuticals of greatest concern. Risk-based prioritization approaches, employing models to derive exposure concentrations, are commonly used, but the reliability of these models is unclear. The present study evaluated the accuracy of exposure models commonly used for pharmaceutical prioritization. Targeted monitoring was conducted for 95 pharmaceuticals in the Rivers Foss and Ouse in the City of York (UK). Predicted environmental concentration (PEC) ranges were estimated based on localized prescription, hydrological data, reported metabolism, and wastewater treatment plant (WWTP) removal rates, and were compared with measured environmental concentrations (MECs). For the River Foss, PECs, obtained using highest metabolism and lowest WWTP removal, were similar to MECs. In contrast, this trend was not observed for the River Ouse, possibly because of pharmaceutical inputs unaccounted for by our modeling. Pharmaceuticals were ranked by risk based on either MECs or PECs. With 2 exceptions (dextromethorphan and diphenhydramine), risk ranking based on both MECs and PECs produced similar results in the River Foss. Overall, these findings indicate that PECs may well be appropriate for prioritization of pharmaceuticals in the environment when robust and local data on the system of interest are available and reflective of most source inputs. 

Random Forest-Based Approach for Maximum Power Point Tracking of Photovoltaic Systems Operating under Actual Environmental Conditions.

PubMed

Shareef, Hussain; Mutlag, Ammar Hussein; Mohamed, Azah

2017-01-01

Many maximum power point tracking (MPPT) algorithms have been developed in recent years to maximize the produced PV energy. These algorithms are not sufficiently robust because of fast-changing environmental conditions, efficiency, accuracy at steady-state value, and dynamics of the tracking algorithm. Thus, this paper proposes a new random forest (RF) model to improve MPPT performance. The RF model has the ability to capture the nonlinear association of patterns between predictors, such as irradiance and temperature, to determine accurate maximum power point. A RF-based tracker is designed for 25 SolarTIFSTF-120P6 PV modules, with the capacity of 3 kW peak using two high-speed sensors. For this purpose, a complete PV system is modeled using 300,000 data samples and simulated using the MATLAB/SIMULINK package. The proposed RF-based MPPT is then tested under actual environmental conditions for 24 days to validate the accuracy and dynamic response. The response of the RF-based MPPT model is also compared with that of the artificial neural network and adaptive neurofuzzy inference system algorithms for further validation. The results show that the proposed MPPT technique gives significant improvement compared with that of other techniques. In addition, the RF model passes the Bland-Altman test, with more than 95 percent acceptability.

Comparative Evaluation of Veriflow® Listeria monocytogenes to USDA and AOAC Culture Based Methods for the Detection of Listeria monocytogenes in Food.

PubMed

Joelsson, Adam C; Brown, Ashley S; Puri, Amrita; Keough, Martin P; Gaudioso, Zara E; Siciliano, Nicholas A; Snook, Adam E

2015-01-01

Veriflow® Listeria monocytogenes (LM) is a molecular based assay for the presumptive detection of Listeria monocytogenes from environmental surfaces, dairy, and ready-to-eat (RTE) food matrixes (hot dogs and deli meat). The assay utilizes a PCR detection method coupled with a rapid, visual, flow-based assay that develops in 3 min post PCR amplification and requires only 24 h of enrichment for maximum sensitivity. The Veriflow LM system eliminates the need for sample purification, gel electrophoresis, or fluorophore-based detection of target amplification, and does not require complex data analysis. This Performance Tested Method(SM) validation study demonstrated the ability of the Veriflow LM method to detect low levels of artificially inoculated L. monocytogenes in seven distinct environmental and food matrixes. In each unpaired reference comparison study, probability of detection analysis indicated no significant difference between the Veriflow LM method and the U.S. Department of Agriculture, Food Safety and Inspection Service Microbiology Laboratory Guidebook 8.08 or AOAC 993.12 reference method. Fifty strains of L. monocytogenes were detected in the inclusivity study, while 39 nonspecific organisms were undetected in the exclusivity study. The study results show that Veriflow LM is a sensitive, selective, and robust assay for the presumptive detection of L. monocytogenes sampled from environmental, dairy, or RTE (hot dogs and deli meat) food matrixes.

Random Forest-Based Approach for Maximum Power Point Tracking of Photovoltaic Systems Operating under Actual Environmental Conditions

PubMed Central

Shareef, Hussain; Mohamed, Azah

2017-01-01

Many maximum power point tracking (MPPT) algorithms have been developed in recent years to maximize the produced PV energy. These algorithms are not sufficiently robust because of fast-changing environmental conditions, efficiency, accuracy at steady-state value, and dynamics of the tracking algorithm. Thus, this paper proposes a new random forest (RF) model to improve MPPT performance. The RF model has the ability to capture the nonlinear association of patterns between predictors, such as irradiance and temperature, to determine accurate maximum power point. A RF-based tracker is designed for 25 SolarTIFSTF-120P6 PV modules, with the capacity of 3 kW peak using two high-speed sensors. For this purpose, a complete PV system is modeled using 300,000 data samples and simulated using the MATLAB/SIMULINK package. The proposed RF-based MPPT is then tested under actual environmental conditions for 24 days to validate the accuracy and dynamic response. The response of the RF-based MPPT model is also compared with that of the artificial neural network and adaptive neurofuzzy inference system algorithms for further validation. The results show that the proposed MPPT technique gives significant improvement compared with that of other techniques. In addition, the RF model passes the Bland–Altman test, with more than 95 percent acceptability. PMID:28702051

A fast, robust and tunable synthetic gene oscillator.

PubMed

Stricker, Jesse; Cookson, Scott; Bennett, Matthew R; Mather, William H; Tsimring, Lev S; Hasty, Jeff

2008-11-27

One defining goal of synthetic biology is the development of engineering-based approaches that enable the construction of gene-regulatory networks according to 'design specifications' generated from computational modelling. This approach provides a systematic framework for exploring how a given regulatory network generates a particular phenotypic behaviour. Several fundamental gene circuits have been developed using this approach, including toggle switches and oscillators, and these have been applied in new contexts such as triggered biofilm development and cellular population control. Here we describe an engineered genetic oscillator in Escherichia coli that is fast, robust and persistent, with tunable oscillatory periods as fast as 13 min. The oscillator was designed using a previously modelled network architecture comprising linked positive and negative feedback loops. Using a microfluidic platform tailored for single-cell microscopy, we precisely control environmental conditions and monitor oscillations in individual cells through multiple cycles. Experiments reveal remarkable robustness and persistence of oscillations in the designed circuit; almost every cell exhibited large-amplitude fluorescence oscillations throughout observation runs. The oscillatory period can be tuned by altering inducer levels, temperature and the media source. Computational modelling demonstrates that the key design principle for constructing a robust oscillator is a time delay in the negative feedback loop, which can mechanistically arise from the cascade of cellular processes involved in forming a functional transcription factor. The positive feedback loop increases the robustness of the oscillations and allows for greater tunability. Examination of our refined model suggested the existence of a simplified oscillator design without positive feedback, and we construct an oscillator strain confirming this computational prediction.

Development and evaluation of a hand tracker using depth images captured from an overhead perspective.

PubMed

Czarnuch, Stephen; Mihailidis, Alex

2015-03-27

We present the development and evaluation of a robust hand tracker based on single overhead depth images for use in the COACH, an assistive technology for people with dementia. The new hand tracker was designed to overcome limitations experienced by the COACH in previous clinical trials. We train a random decision forest classifier using ∼5000 manually labeled, unbalanced, training images. Hand positions from the classifier are translated into task actions based on proximity to environmental objects. Tracker performance is evaluated using a large set of ∼24 000 manually labeled images captured from 41 participants in a fully-functional washroom, and compared to the system's previous colour-based hand tracker. Precision and recall were 0.994 and 0.938 for the depth tracker compared to 0.981 and 0.822 for the colour tracker with the current data, and 0.989 and 0.466 in the previous study. The improved tracking performance supports integration of the depth-based tracker into the COACH toward unsupervised, real-world trials. Implications for Rehabilitation The COACH is an intelligent assistive technology that can enable people with cognitive disabilities to stay at home longer, supporting the concept of aging-in-place. Automated prompting systems, a type of intelligent assistive technology, can help to support the independent completion of activities of daily living, increasing the independence of people with cognitive disabilities while reducing the burden of care experienced by caregivers. Robust motion tracking using depth imaging supports the development of intelligent assistive technologies like the COACH. Robust motion tracking also has application to other forms of assistive technologies including gaming, human-computer interaction and automated assessments.

VARS-TOOL: A Comprehensive, Efficient, and Robust Sensitivity Analysis Toolbox

NASA Astrophysics Data System (ADS)

Razavi, S.; Sheikholeslami, R.; Haghnegahdar, A.; Esfahbod, B.

2016-12-01

VARS-TOOL is an advanced sensitivity and uncertainty analysis toolbox, applicable to the full range of computer simulation models, including Earth and Environmental Systems Models (EESMs). The toolbox was developed originally around VARS (Variogram Analysis of Response Surfaces), which is a general framework for Global Sensitivity Analysis (GSA) that utilizes the variogram/covariogram concept to characterize the full spectrum of sensitivity-related information, thereby providing a comprehensive set of "global" sensitivity metrics with minimal computational cost. VARS-TOOL is unique in that, with a single sample set (set of simulation model runs), it generates simultaneously three philosophically different families of global sensitivity metrics, including (1) variogram-based metrics called IVARS (Integrated Variogram Across a Range of Scales - VARS approach), (2) variance-based total-order effects (Sobol approach), and (3) derivative-based elementary effects (Morris approach). VARS-TOOL is also enabled with two novel features; the first one being a sequential sampling algorithm, called Progressive Latin Hypercube Sampling (PLHS), which allows progressively increasing the sample size for GSA while maintaining the required sample distributional properties. The second feature is a "grouping strategy" that adaptively groups the model parameters based on their sensitivity or functioning to maximize the reliability of GSA results. These features in conjunction with bootstrapping enable the user to monitor the stability, robustness, and convergence of GSA with the increase in sample size for any given case study. VARS-TOOL has been shown to achieve robust and stable results within 1-2 orders of magnitude smaller sample sizes (fewer model runs) than alternative tools. VARS-TOOL, available in MATLAB and Python, is under continuous development and new capabilities and features are forthcoming.

SoundProof: A Smartphone Platform for Wireless Monitoring of Wildlife and Environment

NASA Astrophysics Data System (ADS)

Lukac, M.; Monibi, M.; Lane, M. L.; Howell, L.; Ramanathan, N.; Borker, A.; McKown, M.; Croll, D.; Terschy, B.

2011-12-01

We are developing an open-source, low-cost wildlife and environmental monitoring solution based on Android smartphones. Using a smartphone instead of a traditional microcontroller or single board computer has several advantages: smartphones are single integrated devices with multiple radios and a battery; they have a robust software interface which enables customization; and are field-tested by millions of users daily. Consequently, smartphones can improve the cost, configurability, and real-time access to data for environmental monitoring, ultimately replacing existing monitoring solutions which are proprietary, difficult to customize, expensive, and require labor-intensive maintenance. While smartphones can radically change environmental and wildlife monitoring, there are a number of technical challenges to address. We present our smartphone-based platform, SoundProof, discuss the challenges of building an autonomous system based on Android phones, and our ongoing efforts to enable environmental monitoring. Our system is built using robust off-the-shelf hardware and mature open-source software where available, to increase scalability and ease of installation. Key features include: * High-quality acoustic signal collection from external microphones to monitor wildlife populations. * Real-time data access, remote programming, and configuration of the field sensor via wireless cellular or WiFi channels, accessible from a website. * Waterproof packaging and solar charger setup for long-term field deployments. * Rich instrumentation of the end-to-end system to quickly identify and debug problems. * Supplementary mesh networking system with long-range wireless antennae to provide coverage when no cell network is available. We have deployed this system to monitor Rufous Crowned Sparrows on Anacapa Island, Chinese Crested Turns on the Matsu Islands in Taiwan, and Ashy Storm Petrels on South East Farallon Island. We have testbeds at two UC Natural Reserves to field-test new or exploratory features before deployment. Side-by-side validation data collected in the field using SoundProof and state-of-the-art wildlife monitoring solutions, including the Cornell ARU and Wildlife Acoustic's Songmeter, demonstrate that acoustic signals collected with cellphones provide sufficient data integrity for measuring the success of bird conservation efforts, measuring bird relative abundance and detecting elusive species. We are extending this platform to numerous other areas of environmental monitoring. Recent developments such as the Android Open Accessory, the IOIO Board, MicroBridge, Amarino, and Cellbots enable microcontrollers to talk with Android applications, making it affordable and feasible to extend our platform to operate with the most common sensors.

Robust digital image watermarking using distortion-compensated dither modulation

NASA Astrophysics Data System (ADS)

Li, Mianjie; Yuan, Xiaochen

2018-04-01

In this paper, we propose a robust feature extraction based digital image watermarking method using Distortion- Compensated Dither Modulation (DC-DM). Our proposed local watermarking method provides stronger robustness and better flexibility than traditional global watermarking methods. We improve robustness by introducing feature extraction and DC-DM method. To extract the robust feature points, we propose a DAISY-based Robust Feature Extraction (DRFE) method by employing the DAISY descriptor and applying the entropy calculation based filtering. The experimental results show that the proposed method achieves satisfactory robustness under the premise of ensuring watermark imperceptibility quality compared to other existing methods.

Comparison of linear and nonlinear programming approaches for "worst case dose" and "minmax" robust optimization of intensity-modulated proton therapy dose distributions.

PubMed

Zaghian, Maryam; Cao, Wenhua; Liu, Wei; Kardar, Laleh; Randeniya, Sharmalee; Mohan, Radhe; Lim, Gino

2017-03-01

Robust optimization of intensity-modulated proton therapy (IMPT) takes uncertainties into account during spot weight optimization and leads to dose distributions that are resilient to uncertainties. Previous studies demonstrated benefits of linear programming (LP) for IMPT in terms of delivery efficiency by considerably reducing the number of spots required for the same quality of plans. However, a reduction in the number of spots may lead to loss of robustness. The purpose of this study was to evaluate and compare the performance in terms of plan quality and robustness of two robust optimization approaches using LP and nonlinear programming (NLP) models. The so-called "worst case dose" and "minmax" robust optimization approaches and conventional planning target volume (PTV)-based optimization approach were applied to designing IMPT plans for five patients: two with prostate cancer, one with skull-based cancer, and two with head and neck cancer. For each approach, both LP and NLP models were used. Thus, for each case, six sets of IMPT plans were generated and assessed: LP-PTV-based, NLP-PTV-based, LP-worst case dose, NLP-worst case dose, LP-minmax, and NLP-minmax. The four robust optimization methods behaved differently from patient to patient, and no method emerged as superior to the others in terms of nominal plan quality and robustness against uncertainties. The plans generated using LP-based robust optimization were more robust regarding patient setup and range uncertainties than were those generated using NLP-based robust optimization for the prostate cancer patients. However, the robustness of plans generated using NLP-based methods was superior for the skull-based and head and neck cancer patients. Overall, LP-based methods were suitable for the less challenging cancer cases in which all uncertainty scenarios were able to satisfy tight dose constraints, while NLP performed better in more difficult cases in which most uncertainty scenarios were hard to meet tight dose limits. For robust optimization, the worst case dose approach was less sensitive to uncertainties than was the minmax approach for the prostate and skull-based cancer patients, whereas the minmax approach was superior for the head and neck cancer patients. The robustness of the IMPT plans was remarkably better after robust optimization than after PTV-based optimization, and the NLP-PTV-based optimization outperformed the LP-PTV-based optimization regarding robustness of clinical target volume coverage. In addition, plans generated using LP-based methods had notably fewer scanning spots than did those generated using NLP-based methods. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Designing monitoring programs for chemicals of emerging concern in potable reuse--what to include and what not to include?

PubMed

Drewes, J E; Anderson, P; Denslow, N; Olivieri, A; Schlenk, D; Snyder, S A; Maruya, K A

2013-01-01

This study discussed a proposed process to prioritize chemicals for reclaimed water monitoring programs, selection of analytical methods required for their quantification, toxicological relevance of chemicals of emerging concern regarding human health, and related issues. Given that thousands of chemicals are potentially present in reclaimed water and that information about those chemicals is rapidly evolving, a transparent, science-based framework was developed to guide prioritization of which compounds of emerging concern (CECs) should be included in reclaimed water monitoring programs. The recommended framework includes four steps: (1) compile environmental concentrations (e.g., measured environmental concentration or MEC) of CECs in the source water for reuse projects; (2) develop a monitoring trigger level (MTL) for each of these compounds (or groups thereof) based on toxicological relevance; (3) compare the environmental concentration (e.g., MEC) to the MTL; CECs with a MEC/MTL ratio greater than 1 should be prioritized for monitoring, compounds with a ratio less than '1' should only be considered if they represent viable treatment process performance indicators; and (4) screen the priority list to ensure that a commercially available robust analytical method is available for that compound.

Addressing location uncertainties in GPS-based activity monitoring: A methodological framework

PubMed Central

Wan, Neng; Lin, Ge; Wilson, Gaines J.

2016-01-01

Location uncertainty has been a major barrier in information mining from location data. Although the development of electronic and telecommunication equipment has led to an increased amount and refined resolution of data about individuals’ spatio-temporal trajectories, the potential of such data, especially in the context of environmental health studies, has not been fully realized due to the lack of methodology that addresses location uncertainties. This article describes a methodological framework for deriving information about people’s continuous activities from individual-collected Global Positioning System (GPS) data, which is vital for a variety of environmental health studies. This framework is composed of two major methods that address critical issues at different stages of GPS data processing: (1) a fuzzy classification method for distinguishing activity patterns; and (2) a scale-adaptive method for refining activity locations and outdoor/indoor environments. Evaluation of this framework based on smartphone-collected GPS data indicates that it is robust to location errors and is able to generate useful information about individuals’ life trajectories. PMID:28943777

A spectral water index based on visual bands

NASA Astrophysics Data System (ADS)

Basaeed, Essa; Bhaskar, Harish; Al-Mualla, Mohammed

2013-10-01

Land-water segmentation is an important preprocessing step in a number of remote sensing applications such as target detection, environmental monitoring, and map updating. A Normalized Optical Water Index (NOWI) is proposed to accurately discriminate between land and water regions in multi-spectral satellite imagery data from DubaiSat-1. NOWI exploits the spectral characteristics of water content (using visible bands) and uses a non-linear normalization procedure that renders strong emphasize on small changes in lower brightness values whilst guaranteeing that the segmentation process remains image-independent. The NOWI representation is validated through systematic experiments, evaluated using robust metrics, and compared against various supervised classification algorithms. Analysis has indicated that NOWI has the advantages that it: a) is a pixel-based method that requires no global knowledge of the scene under investigation, b) can be easily implemented in parallel processing, c) is image-independent and requires no training, d) works in different environmental conditions, e) provides high accuracy and efficiency, and f) works directly on the input image without any form of pre-processing.

SU-E-J-212: Identifying Bones From MRI: A Dictionary Learnign and Sparse Regression Approach

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

Ruan, D; Yang, Y; Cao, M

2014-06-01

Purpose: To develop an efficient and robust scheme to identify bony anatomy based on MRI-only simulation images. Methods: MRI offers important soft tissue contrast and functional information, yet its lack of correlation to electron-density has placed it as an auxiliary modality to CT in radiotherapy simulation and adaptation. An effective scheme to identify bony anatomy is an important first step towards MR-only simulation/treatment paradigm and would satisfy most practical purposes. We utilize a UTE acquisition sequence to achieve visibility of the bone. By contrast to manual + bulk or registration-to identify bones, we propose a novel learning-based approach for improvedmore » robustness to MR artefacts and environmental changes. Specifically, local information is encoded with MR image patch, and the corresponding label is extracted (during training) from simulation CT aligned to the UTE. Within each class (bone vs. nonbone), an overcomplete dictionary is learned so that typical patches within the proper class can be represented as a sparse combination of the dictionary entries. For testing, an acquired UTE-MRI is divided to patches using a sliding scheme, where each patch is sparsely regressed against both bone and nonbone dictionaries, and subsequently claimed to be associated with the class with the smaller residual. Results: The proposed method has been applied to the pilot site of brain imaging and it has showed general good performance, with dice similarity coefficient of greater than 0.9 in a crossvalidation study using 4 datasets. Importantly, it is robust towards consistent foreign objects (e.g., headset) and the artefacts relates to Gibbs and field heterogeneity. Conclusion: A learning perspective has been developed for inferring bone structures based on UTE MRI. The imaging setting is subject to minimal motion effects and the post-processing is efficient. The improved efficiency and robustness enables a first translation to MR-only routine. The scheme generalizes to multiple tissue classes.« less

MPLEx: a Robust and Universal Protocol for Single-Sample Integrative Proteomic, Metabolomic, and Lipidomic Analyses

PubMed Central

Nakayasu, Ernesto S.; Nicora, Carrie D.; Sims, Amy C.; Burnum-Johnson, Kristin E.; Kim, Young-Mo; Kyle, Jennifer E.; Matzke, Melissa M.; Shukla, Anil K.; Chu, Rosalie K.; Schepmoes, Athena A.; Jacobs, Jon M.; Baric, Ralph S.; Webb-Robertson, Bobbie-Jo; Smith, Richard D.

2016-01-01

ABSTRACT Integrative multi-omics analyses can empower more effective investigation and complete understanding of complex biological systems. Despite recent advances in a range of omics analyses, multi-omic measurements of the same sample are still challenging and current methods have not been well evaluated in terms of reproducibility and broad applicability. Here we adapted a solvent-based method, widely applied for extracting lipids and metabolites, to add proteomics to mass spectrometry-based multi-omics measurements. The metabolite, protein, and lipid extraction (MPLEx) protocol proved to be robust and applicable to a diverse set of sample types, including cell cultures, microbial communities, and tissues. To illustrate the utility of this protocol, an integrative multi-omics analysis was performed using a lung epithelial cell line infected with Middle East respiratory syndrome coronavirus, which showed the impact of this virus on the host glycolytic pathway and also suggested a role for lipids during infection. The MPLEx method is a simple, fast, and robust protocol that can be applied for integrative multi-omic measurements from diverse sample types (e.g., environmental, in vitro, and clinical). IMPORTANCE In systems biology studies, the integration of multiple omics measurements (i.e., genomics, transcriptomics, proteomics, metabolomics, and lipidomics) has been shown to provide a more complete and informative view of biological pathways. Thus, the prospect of extracting different types of molecules (e.g., DNAs, RNAs, proteins, and metabolites) and performing multiple omics measurements on single samples is very attractive, but such studies are challenging due to the fact that the extraction conditions differ according to the molecule type. Here, we adapted an organic solvent-based extraction method that demonstrated broad applicability and robustness, which enabled comprehensive proteomics, metabolomics, and lipidomics analyses from the same sample. Author Video: An author video summary of this article is available. PMID:27822525

Survival of Cryptosporidium parvum oocysts under various environmental pressures.

PubMed Central

Robertson, L J; Campbell, A T; Smith, H V

1992-01-01

The survival of various isolates of Cryptosporidium parvum oocysts under a range of environmental pressures including freezing, desiccation, and water treatment processes and in physical environments commonly associated with oocysts such as feces and various water types was monitored. Oocyst viability was assessed by in vitro excystation and by a viability assay based on the exclusion or inclusion of two fluorogenic vital dyes. Although desiccation was found to be lethal, a small proportion of oocysts were able to withstand exposure to temperatures as low as -22 degrees C. The water treatment processes investigated did not affect the survival of oocysts when pH was corrected. However, contact with lime, ferric sulfate, or alum had a significant impact on oocyst survival if the pH was not corrected. Oocysts demonstrated longevity in all water types investigated, including seawater, and when in contact with feces were considered to develop an enhanced impermeability to small molecules which might increase the robustness of the oocysts when exposed to environmental pressures. PMID:1482175

Strategic Environmental Assessment of Greenhouse Gas Mitigation Options in the Canadian Agricultural Sector

NASA Astrophysics Data System (ADS)

Noble, Bram F.; Christmas, Lisa M.

2008-01-01

This article presents a methodological framework for strategic environmental assessment (SEA) application. The overall objective is to demonstrate SEA as a systematic and structured policy, plan, and program (PPP) decision support tool. In order to accomplish this objective, a stakeholder-based SEA application to greenhouse gas (GHG) mitigation policy options in Canadian agriculture is presented. Using a mail-out impact assessment exercise, agricultural producers and nonproducers from across the Canadian prairie region were asked to evaluate five competing GHG mitigation options against 13 valued environmental components (VECs). Data were analyzed using multi-criteria and exploratory analytical techniques. The results suggest considerable variation in perceived impacts and GHG mitigation policy preferences, suggesting that a blanket policy approach to GHG mitigation will create gainers and losers based on soil type and associate cropping and on-farm management practices. It is possible to identify a series of regional greenhouse gas mitigation programs that are robust, socially meaningful, and operationally relevant to both agricultural producers and policy decision makers. The assessment demonstrates the ability of SEA to address, in an operational sense, environmental problems that are characterized by conflicting interests and competing objectives and alternatives. A structured and systematic SEA methodology provides the necessary decision support framework for the consideration of impacts, and allows for PPPs to be assessed based on a much broader set of properties, objectives, criteria, and constraints whereas maintaining rigor and accountability in the assessment process.

Developing a robust wireless sensor network structure for environmental sensing

NASA Astrophysics Data System (ADS)

Zhang, Z.; Oroza, C.; Glaser, S. D.; Bales, R. C.; Conklin, M. H.

2013-12-01

The American River Hydrologic Observatory is being strategically deployed as a real-time ground-based measurement network that delivers accurate and timely information on snow conditions and other hydrologic attributes with a previously unheard of granularity of time and space. The basin-scale network involves 18 sub-networks set out at physiographically representative locations spanning the seasonally snow-covered half of the 5000 km2 American river basin. Each sub-network, covering about a 1-km2 area, consists of 10 wirelessly networked sensing nodes that continuously measure and telemeter temperature, and snow depth; plus selected locations are equipped with sensors for relative humidity, solar radiation, and soil moisture at several depths. The sensor locations were chosen to maximize the variance sampled for snow depth within the basin. Network design and deployment involves an iterative but efficient process. After sensor-station locations are determined, a robust network of interlinking sensor stations and signal repeaters must be constructed to route sensor data to a central base station with a two-way communicable data uplink. Data can then be uploaded from site to remote servers in real time through satellite and cell modems. Signal repeaters are placed for robustness of a self-healing network with redundant signal paths to the base station. Manual, trial-and-error heuristic approaches for node placement are inefficient and labor intensive. In that approach field personnel must restructure the network in real time and wait for new network statistics to be calculated at the base station before finalizing a placement, acting without knowledge of the global topography or overall network structure. We show how digital elevation plus high-definition aerial photographs to give foliage coverage can optimize planning of signal repeater placements and guarantee a robust network structure prior to the physical deployment. We can also 'stress test' the final network by simulating the failure of an individual node and investigating the effect and the self-healing ability of the stressed network. The resulting sensor network can survive temporary service interruption from a small subset of signal repeaters and sensor stations. The robustness and the resilient of the network performance ensure the integrity of the dataset and the real-time transmissibility during harsh conditions.

Ensuring food security with lower environmental costs under intensive agricultural land use patterns: A case study from China.

PubMed

Qi, Xiaoxing; Wang, Raymond Yu; Li, Jianchun; Zhang, Tao; Liu, Liming; He, Yanling

2018-05-01

Rapid population growth and environmental deterioration make ensuring food security with lower environmental costs fundamental to realizing sustainable development in China and other developing countries. The conceptual framework used in this paper integrates the major consequences of intensive agricultural land use and the diverse objectives of policymakers and farmers. It also offers an operational approach, based on farmers' diverse performance in grain production and farmland productivity, to assess food production and environmental impacts under foci-differentiated scenarios. Using data from farmer household surveys, soil surveys, land use images, and statistical yearbooks, this approach was tested using a regional case in China. The results indicate that, among all farmer types, the medium-scale farmers had a better comprehensive performance for grain production for yield, fertilizer and pesticide inputs, labor productivity, and sustainability. Therefore, grain yields can be increased and environmental costs reduced simultaneously through the use of policy instruments that encourage the transformation of trapped farmers into medium-scale farmers and balancing the proportion of single and double cropped rice. In addition, and in order to reduce grain losses caused by natural disasters and to prevent environmental degradation, robust policy measures should be developed to avoid the currently predominant cropping patterns that erode biodiversity. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Fault-Tolerant Radiation-Robust Mass Storage Concept for Highly Scaled Flash Memory

NASA Astrophysics Data System (ADS)

Fuchs, Cristian M.; Trinitis, Carsten; Appel, Nicolas; Langer, Martin

2015-09-01

Future spacemissions will require vast amounts of data to be stored and processed aboard spacecraft. While satisfying operational mission requirements, storage systems must guarantee data integrity and recover damaged data throughout the mission. NAND-flash memories have become popular for space-borne high performance mass memory scenarios, though future storage concepts will rely upon highly scaled flash or other memory technologies. With modern flash memory, single bit erasure coding and RAID based concepts are insufficient. Thus, a fully run-time configurable, high performance, dependable storage concept, requiring a minimal set of logic or software. The solution is based on composite erasure coding and can be adjusted for altered mission duration or changing environmental conditions.

Modeling global mangrove soil carbon stocks: filling the gaps in coastal environments

NASA Astrophysics Data System (ADS)

Rovai, A.; Twilley, R.

2017-12-01

We provide an overview of contemporaneous global mangrove soil organic carbon (SOC) estimates, focusing on a framework to explain disproportionate differences among observed data as a way to improve global estimates. This framework is based on a former conceptual model, the coastal environmental setting, in contrast to the more popular latitude-based hypotheses largely believed to explain hemispheric variation in mangrove ecosystem properties. To demonstrate how local and regional estimates of SOC linked to coastal environmental settings can render more realistic global mangrove SOC extrapolations we combined published and unpublished data, yielding a total of 106 studies, reporting on 552 sites from 43 countries. These sites were classified into distinct coastal environmental setting types according to two concurrent worldwide typology of nearshore coastal systems classifications. Mangrove SOC density varied substantially across coastal environmental settings, ranging from 14.9 ± 0.8 in river dominated (deltaic) soils to 53.9 ± 1.6 mg cm-3 (mean ± SE) in karstic coastlines. Our findings reveal striking differences between published values and contemporary global mangrove SOC extrapolation based on country-level mean reference values, particularly for karstic-dominated coastlines where mangrove SOC stocks have been underestimated by up to 50%. Correspondingly, climate-based global estimates predicted lower mangrove SOC density values (32-41 mg C cm-3) for mangroves in karstic environments, differing from published (21-126 mg C cm-3) and unpublished (47-58 mg C cm-3) values. Moreover, climate-based projections yielded higher SOC density values (27-70 mg C cm-3) for river-dominated mangroves compared to lower ranges reported in the literature (11-24 mg C cm-3). We argue that this inconsistent reporting of SOC stock estimates between river-dominated and karstic coastal environmental settings is likely due to the omission of geomorphological and geophysical environmental drivers, which control C storage in coastal wetlands. We encourage the science community more close utilize coastal environmental settings and new inventories of geomorphological typologies to build more robust estimates of local and regional estimates of SOC that can be extrapolated to global C estimates.

A hybrid Bayesian network approach for trade-offs between environmental flows and agricultural water using dynamic discretization

NASA Astrophysics Data System (ADS)

Xue, Jie; Gui, Dongwei; Lei, Jiaqiang; Sun, Huaiwei; Zeng, Fanjiang; Feng, Xinlong

2017-12-01

Agriculture and the eco-environment are increasingly competing for water. The extension of intensive farmland for ensuring food security has resulted in excessive water exploitation by agriculture. Consequently, this has led to a lack of water supply in natural ecosystems. This paper proposes a trade-off framework to coordinate the water-use conflict between agriculture and the eco-environment, based on economic compensation for irrigation stakeholders. A hybrid Bayesian network (HBN) is developed to implement the framework, including: (a) agricultural water shortage assessments after meeting environmental flows; (b) water-use tradeoff analysis between agricultural irrigation and environmental flows using the HBN; and (c) quantification of the agricultural economic compensation for different irrigation stakeholders. The constructed HBN is computed by dynamic discretization, which is a more robust and accurate propagation algorithm than general static discretization. A case study of the Qira oasis area in Northwest China demonstrates that the water trade-off based on economic compensation depends on the available water supply and environmental flows at different levels. Agricultural irrigation water extracted for grain crops should be preferentially guaranteed to ensure food security, in spite of higher economic compensation in other cash crops' irrigation for water coordination. Updating water-saving engineering and adopting drip irrigation technology in agricultural facilities after satisfying environmental flows would greatly relieve agricultural water shortage and save the economic compensation for different irrigation stakeholders. The approach in this study can be easily applied in water-stressed areas worldwide for dealing with water competition.

Can people catastrophize barriers? An exploratory analysis of the association between pain catastrophizing and perceptions of environmental factors.

PubMed

Ravesloot, Craig; Berendts, Cathy; Schiwal, Alex

2017-01-01

Measurement of the environment is taking on increased importance for understanding variability in participation. Most measures of the environment use subjective ratings, yet little is known about how people appraise the environment. /Hypothesis: We conducted this post-hoc study to examine whether or not catastrophizing, an important variable for understanding how pain contributes to disability, may be related to ratings of the environment. We hypothesized higher pain catastrophizing scores would be associated with greater environmental barriers and fewer facilitators. Individuals with functional impairments (N = 525) were recruited from a population-based random sample of households in a small western city in the United States to complete a paper-based survey about their health and community living experiences. We conducted exploratory regression analyses to investigate associations with environmental factor ratings. We found substantial associations between pain catastrophizing and both environmental barriers and personal factor problems after controlling for demographics, participation assessed by community trips per week, health conditions, impairment and pain level. The models accounted for 28% of the variance in environmental factor ratings and 52% of the variability personal factor ratings. We also present odds ratios for the association between personal characteristics and the likelihood of endorsing EF and PF. A variety of individual characteristics are associated with ratings of both environmental and personal factors that impact participation. Among these, pain catastrophizing is a robust predictor of EF and PF ratings which suggests future research designed specifically to test this relationship may generate useful results for developing interventions to increase participation. Copyright © 2016 Elsevier Inc. All rights reserved.

Calcium-magnesium Aluminosilicate (CMAS) Interactions with Advanced Environmental Barrier Coating Material

NASA Technical Reports Server (NTRS)

Wiesner, Valerie L.; Bansal, Narottam P.

2015-01-01

Particulates, like sand and volcanic ash, threaten the development of robust environmental barrier coatings (EBCs) that protect next-generation silicon-based ceramic matrix composite (CMC) turbine engine components from harsh combustion environments during service. The siliceous particulates transform into molten glassy deposits of calcium-magnesium aluminosilicate (CMAS) when ingested by an aircraft engine operating at temperatures above 1200C. In this study, a sample of desert sand was melted into CMAS glass to evaluate high-temperature interactions between the sand glass and an advanced EBC material. Desert sand glass was added to the surface of hot-pressed EBC substrates, which were then heated in air at temperatures ranging from 1200C to 1500C. Scanning electron microscopy and X-ray energy-dispersive spectroscopy were used to evaluate microstructure and phase compositions of specimens and the CMASEBC interface after heat treatments.

Optical Measurements for Intelligent Aerospace Propulsion

NASA Technical Reports Server (NTRS)

Mercer, Carolyn R.

2003-01-01

There is growing interest in applying intelligent technologies to aerospace propulsion systems to reap expected benefits in cost, performance, and environmental compliance. Cost benefits span the engine life cycle from development, operations, and maintenance. Performance gains are anticipated in reduced fuel consumption, increased thrust-toweight ratios, and operability. Environmental benefits include generating fewer pollutants and less noise. Critical enabling technologies to realize these potential benefits include sensors, actuators, logic, electronics, materials, and structures. For propulsion applications, the challenge is to increase the robustness of these technologies so that they can withstand harsh temperatures, vibrations, and grime while providing extremely reliable performance. This paper addresses the role that optical metrology is playing in providing solutions to these challenges. Optics for ground-based testing (development cycle), flight sensing (operations), and inspection (maintenance) are described. Opportunities for future work are presented.

A general procedure to generate models for urban environmental-noise pollution using feature selection and machine learning methods.

PubMed

Torija, Antonio J; Ruiz, Diego P

2015-02-01

The prediction of environmental noise in urban environments requires the solution of a complex and non-linear problem, since there are complex relationships among the multitude of variables involved in the characterization and modelling of environmental noise and environmental-noise magnitudes. Moreover, the inclusion of the great spatial heterogeneity characteristic of urban environments seems to be essential in order to achieve an accurate environmental-noise prediction in cities. This problem is addressed in this paper, where a procedure based on feature-selection techniques and machine-learning regression methods is proposed and applied to this environmental problem. Three machine-learning regression methods, which are considered very robust in solving non-linear problems, are used to estimate the energy-equivalent sound-pressure level descriptor (LAeq). These three methods are: (i) multilayer perceptron (MLP), (ii) sequential minimal optimisation (SMO), and (iii) Gaussian processes for regression (GPR). In addition, because of the high number of input variables involved in environmental-noise modelling and estimation in urban environments, which make LAeq prediction models quite complex and costly in terms of time and resources for application to real situations, three different techniques are used to approach feature selection or data reduction. The feature-selection techniques used are: (i) correlation-based feature-subset selection (CFS), (ii) wrapper for feature-subset selection (WFS), and the data reduction technique is principal-component analysis (PCA). The subsequent analysis leads to a proposal of different schemes, depending on the needs regarding data collection and accuracy. The use of WFS as the feature-selection technique with the implementation of SMO or GPR as regression algorithm provides the best LAeq estimation (R(2)=0.94 and mean absolute error (MAE)=1.14-1.16 dB(A)). Copyright © 2014 Elsevier B.V. All rights reserved.

Robust geostatistical analysis of spatial data

NASA Astrophysics Data System (ADS)

Papritz, A.; Künsch, H. R.; Schwierz, C.; Stahel, W. A.

2012-04-01

Most of the geostatistical software tools rely on non-robust algorithms. This is unfortunate, because outlying observations are rather the rule than the exception, in particular in environmental data sets. Outlying observations may results from errors (e.g. in data transcription) or from local perturbations in the processes that are responsible for a given pattern of spatial variation. As an example, the spatial distribution of some trace metal in the soils of a region may be distorted by emissions of local anthropogenic sources. Outliers affect the modelling of the large-scale spatial variation, the so-called external drift or trend, the estimation of the spatial dependence of the residual variation and the predictions by kriging. Identifying outliers manually is cumbersome and requires expertise because one needs parameter estimates to decide which observation is a potential outlier. Moreover, inference after the rejection of some observations is problematic. A better approach is to use robust algorithms that prevent automatically that outlying observations have undue influence. Former studies on robust geostatistics focused on robust estimation of the sample variogram and ordinary kriging without external drift. Furthermore, Richardson and Welsh (1995) [2] proposed a robustified version of (restricted) maximum likelihood ([RE]ML) estimation for the variance components of a linear mixed model, which was later used by Marchant and Lark (2007) [1] for robust REML estimation of the variogram. We propose here a novel method for robust REML estimation of the variogram of a Gaussian random field that is possibly contaminated by independent errors from a long-tailed distribution. It is based on robustification of estimating equations for the Gaussian REML estimation. Besides robust estimates of the parameters of the external drift and of the variogram, the method also provides standard errors for the estimated parameters, robustified kriging predictions at both sampled and unsampled locations and kriging variances. The method has been implemented in an R package. Apart from presenting our modelling framework, we shall present selected simulation results by which we explored the properties of the new method. This will be complemented by an analysis of the Tarrawarra soil moisture data set [3].

Effect of environmental conditions on the relationship between solar-induced fluorescence and gross primary productivity at an OzFlux grassland site

NASA Astrophysics Data System (ADS)

Verma, Manish; Schimel, David; Evans, Bradley; Frankenberg, Christian; Beringer, Jason; Drewry, Darren T.; Magney, Troy; Marang, Ian; Hutley, Lindsay; Moore, Caitlin; Eldering, Annmarie

2017-03-01

Recent studies have utilized coarse spatial and temporal resolution remotely sensed solar-induced fluorescence (SIF) for modeling terrestrial gross primary productivity (GPP) at regional scales. Although these studies have demonstrated the potential of SIF, there have been concerns about the ecophysiological basis of the relationship between SIF and GPP in different environmental conditions. Launched in 2014, the Orbiting Carbon Observatory-2 (OCO-2) has enabled fine-scale (1.3 by 2.5 km) retrievals of SIF that are comparable with measurements recorded at eddy covariance towers. In this study, we examine the effect of environmental conditions on the relationship of OCO-2 SIF with tower GPP over the course of a growing season at a well-characterized natural grassland site. Combining OCO-2 SIF and eddy covariance tower data with a canopy radiative transfer and an ecosystem model, we also assess the potential of OCO-2 SIF to constrain the estimates of Vcmax, one of the most important parameters in ecosystem models. Based on the results, we suggest that although environmental conditions play a role in determining the nature of relationship between SIF and GPP, overall, the linear relationship is more robust at ecosystem scale than the theory based on leaf-level processes might suggest. Our study also shows that the ability of SIF to constrain Vcmax is weak at the selected site.

Evolution of robust circadian clocks in Drosophila melanogaster populations reared in constant dark for over 330 generations

NASA Astrophysics Data System (ADS)

Shindey, Radhika; Varma, Vishwanath; Nikhil, K. L.; Sharma, Vijay Kumar

2016-10-01

Robustness is considered to be an important feature of biological systems which may evolve when the functionality of a trait is associated with higher fitness across multiple environmental conditions. Thus, the ability to maintain stable biological phenotypes across environments is thought to be of adaptive value. Previously, we have reported higher intrinsic activity levels (activity levels of free-running rhythm in constant darkness) and power of rhythm (as assessed by amplitude of the periodogram) in Drosophila melanogaster populations (stocks) reared in constant darkness (DD stocks) as compared to those reared in constant light (LL stocks) and 12:12-h light-dark cycles (LD stocks) for over 19 years (˜330 generations). In the current study, we intended to examine whether the enhanced levels of activity observed in DD stocks persist under various environments such as photoperiods, ambient temperatures, non-24-h light-dark (LD) cycles, and semi-natural conditions (SN). We found that DD stocks largely retain their phenotype of enhanced activity levels across most of the above-mentioned environments suggesting the evolution of robust circadian clocks in DD stocks. Furthermore, we compared the peak activity levels of the three stocks across different environmental conditions relative to their peaks in constant darkness and found that the change in peak activity levels upon entrainment was not significantly different across the three stocks for any of the examined environmental conditions. This suggests that the enhancement of activity levels in DD stocks is not due to differential sensitivity to environment. Thus, these results suggest that rearing in constant darkness (DD) leads to evolution of robust circadian clocks suggesting a possible adaptive value of possessing such rhythms under constant dark environments.

The Role of Design-of-Experiments in Managing Flow in Compact Air Vehicle Inlets

NASA Technical Reports Server (NTRS)

Anderson, Bernhard H.; Miller, Daniel N.; Gridley, Marvin C.; Agrell, Johan

2003-01-01

It is the purpose of this study to demonstrate the viability and economy of Design-of-Experiments methodologies to arrive at microscale secondary flow control array designs that maintain optimal inlet performance over a wide range of the mission variables and to explore how these statistical methods provide a better understanding of the management of flow in compact air vehicle inlets. These statistical design concepts were used to investigate the robustness properties of low unit strength micro-effector arrays. Low unit strength micro-effectors are micro-vanes set at very low angles-of-incidence with very long chord lengths. They were designed to influence the near wall inlet flow over an extended streamwise distance, and their advantage lies in low total pressure loss and high effectiveness in managing engine face distortion. The term robustness is used in this paper in the same sense as it is used in the industrial problem solving community. It refers to minimizing the effects of the hard-to-control factors that influence the development of a product or process. In Robustness Engineering, the effects of the hard-to-control factors are often called noise , and the hard-to-control factors themselves are referred to as the environmental variables or sometimes as the Taguchi noise variables. Hence Robust Optimization refers to minimizing the effects of the environmental or noise variables on the development (design) of a product or process. In the management of flow in compact inlets, the environmental or noise variables can be identified with the mission variables. Therefore this paper formulates a statistical design methodology that minimizes the impact of variations in the mission variables on inlet performance and demonstrates that these statistical design concepts can lead to simpler inlet flow management systems.

Evolution of robust circadian clocks in Drosophila melanogaster populations reared in constant dark for over 330 generations.

PubMed

Shindey, Radhika; Varma, Vishwanath; Nikhil, K L; Sharma, Vijay Kumar

2016-10-01

Robustness is considered to be an important feature of biological systems which may evolve when the functionality of a trait is associated with higher fitness across multiple environmental conditions. Thus, the ability to maintain stable biological phenotypes across environments is thought to be of adaptive value. Previously, we have reported higher intrinsic activity levels (activity levels of free-running rhythm in constant darkness) and power of rhythm (as assessed by amplitude of the periodogram) in Drosophila melanogaster populations (stocks) reared in constant darkness (DD stocks) as compared to those reared in constant light (LL stocks) and 12:12-h light-dark cycles (LD stocks) for over 19 years (∼330 generations). In the current study, we intended to examine whether the enhanced levels of activity observed in DD stocks persist under various environments such as photoperiods, ambient temperatures, non-24-h light-dark (LD) cycles, and semi-natural conditions (SN). We found that DD stocks largely retain their phenotype of enhanced activity levels across most of the above-mentioned environments suggesting the evolution of robust circadian clocks in DD stocks. Furthermore, we compared the peak activity levels of the three stocks across different environmental conditions relative to their peaks in constant darkness and found that the change in peak activity levels upon entrainment was not significantly different across the three stocks for any of the examined environmental conditions. This suggests that the enhancement of activity levels in DD stocks is not due to differential sensitivity to environment. Thus, these results suggest that rearing in constant darkness (DD) leads to evolution of robust circadian clocks suggesting a possible adaptive value of possessing such rhythms under constant dark environments.

Flood risk assessment and robust management under deep uncertainty: Application to Dhaka City

NASA Astrophysics Data System (ADS)

Mojtahed, Vahid; Gain, Animesh Kumar; Giupponi, Carlo

2014-05-01

The socio-economic changes as well as climatic changes have been the main drivers of uncertainty in environmental risk assessment and in particular flood. The level of future uncertainty that researchers face when dealing with problems in a future perspective with focus on climate change is known as Deep Uncertainty (also known as Knightian uncertainty), since nobody has already experienced and undergone those changes before and our knowledge is limited to the extent that we have no notion of probabilities, and therefore consolidated risk management approaches have limited potential.. Deep uncertainty is referred to circumstances that analysts and experts do not know or parties to decision making cannot agree on: i) the appropriate models describing the interaction among system variables, ii) probability distributions to represent uncertainty about key parameters in the model 3) how to value the desirability of alternative outcomes. The need thus emerges to assist policy-makers by providing them with not a single and optimal solution to the problem at hand, such as crisp estimates for the costs of damages of natural hazards considered, but instead ranges of possible future costs, based on the outcomes of ensembles of assessment models and sets of plausible scenarios. Accordingly, we need to substitute optimality as a decision criterion with robustness. Under conditions of deep uncertainty, the decision-makers do not have statistical and mathematical bases to identify optimal solutions, while instead they should prefer to implement "robust" decisions that perform relatively well over all conceivable outcomes out of all future unknown scenarios. Under deep uncertainty, analysts cannot employ probability theory or other statistics that usually can be derived from observed historical data and therefore, we turn to non-statistical measures such as scenario analysis. We construct several plausible scenarios with each scenario being a full description of what may happen in future and based on a meaningful synthesis of parameters' values with control of their correlations for maintaining internal consistencies. This paper aims at incorporating a set of data mining and sampling tools to assess uncertainty of model outputs under future climatic and socio-economic changes for Dhaka city and providing a decision support system for robust flood management and mitigation policies. After constructing an uncertainty matrix to identify the main sources of uncertainty for Dhaka City, we identify several hazard and vulnerability maps based on future climatic and socio-economic scenarios. The vulnerability of each flood management alternative under different set of scenarios is determined and finally the robustness of each plausible solution considered is defined based on the above assessment.

An Approach to Risk-Based Design Incorporating Damage Tolerance Analyses

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.; Glaessgen, Edward H.; Sleight, David W.

2002-01-01

Incorporating risk-based design as an integral part of spacecraft development is becoming more and more common. Assessment of uncertainties associated with design parameters and environmental aspects such as loading provides increased knowledge of the design and its performance. Results of such studies can contribute to mitigating risk through a system-level assessment. Understanding the risk of an event occurring, the probability of its occurrence, and the consequences of its occurrence can lead to robust, reliable designs. This paper describes an approach to risk-based structural design incorporating damage-tolerance analysis. The application of this approach to a candidate Earth-entry vehicle is described. The emphasis of the paper is on describing an approach for establishing damage-tolerant structural response inputs to a system-level probabilistic risk assessment.

Per- and Polyfluoroalkyl Substances (PFAS): Sampling ...

EPA Pesticide Factsheets

Per- and polyfluoroalkyl substances (PFAS) are a large group of manufactured compounds used in a variety of industries, such as aerospace, automotive, textiles, and electronics, and are used in some food packaging and firefighting materials. For example, they may be used to make products more resistant to stains, grease and water. In the environment, some PFAS break down very slowly, if at all, allowing bioaccumulation (concentration) to occur in humans and wildlife. Some have been found to be toxic to laboratory animals, producing reproductive, developmental, and systemic effects in laboratory tests. EPA's methods for analyzing PFAS in environmental media are in various stages of development. This technical brief summarizes the work being done to develop robust analytical methods for groundwater, surface water, wastewater, and solids, including soils, sediments, and biosolids. The U.S. Environmental Protection Agency’s (EPA) methods for analyzing PFAS in environmental media are in various stages of development. EPA is working to develop robust analytical methods for groundwater, surface water, wastewater, and solids, including soils, sediments, and biosolids.

Using adaptive processes and adverse outcome pathways to develop meaningful, robust, and actionable environmental monitoring programs.

PubMed

Arciszewski, Tim J; Munkittrick, Kelly R; Scrimgeour, Garry J; Dubé, Monique G; Wrona, Fred J; Hazewinkel, Rod R

2017-09-01

The primary goals of environmental monitoring are to indicate whether unexpected changes related to development are occurring in the physical, chemical, and biological attributes of ecosystems and to inform meaningful management intervention. Although achieving these objectives is conceptually simple, varying scientific and social challenges often result in their breakdown. Conceptualizing, designing, and operating programs that better delineate monitoring, management, and risk assessment processes supported by hypothesis-driven approaches, strong inference, and adverse outcome pathways can overcome many of the challenges. Generally, a robust monitoring program is characterized by hypothesis-driven questions associated with potential adverse outcomes and feedback loops informed by data. Specifically, key and basic features are predictions of future observations (triggers) and mechanisms to respond to success or failure of those predictions (tiers). The adaptive processes accelerate or decelerate the effort to highlight and overcome ignorance while preventing the potentially unnecessary escalation of unguided monitoring and management. The deployment of the mutually reinforcing components can allow for more meaningful and actionable monitoring programs that better associate activities with consequences. Integr Environ Assess Manag 2017;13:877-891. © 2017 The Authors. Integrated Environmental Assessment and Management Published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC). © 2017 The Authors. Integrated Environmental Assessment and Management Published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Robust reinforcement learning.

PubMed

Morimoto, Jun; Doya, Kenji

2005-02-01

This letter proposes a new reinforcement learning (RL) paradigm that explicitly takes into account input disturbance as well as modeling errors. The use of environmental models in RL is quite popular for both offline learning using simulations and for online action planning. However, the difference between the model and the real environment can lead to unpredictable, and often unwanted, results. Based on the theory of H(infinity) control, we consider a differential game in which a "disturbing" agent tries to make the worst possible disturbance while a "control" agent tries to make the best control input. The problem is formulated as finding a min-max solution of a value function that takes into account the amount of the reward and the norm of the disturbance. We derive online learning algorithms for estimating the value function and for calculating the worst disturbance and the best control in reference to the value function. We tested the paradigm, which we call robust reinforcement learning (RRL), on the control task of an inverted pendulum. In the linear domain, the policy and the value function learned by online algorithms coincided with those derived analytically by the linear H(infinity) control theory. For a fully nonlinear swing-up task, RRL achieved robust performance with changes in the pendulum weight and friction, while a standard reinforcement learning algorithm could not deal with these changes. We also applied RRL to the cart-pole swing-up task, and a robust swing-up policy was acquired.

Fast, cheap and in control: spectral imaging with handheld devices

NASA Astrophysics Data System (ADS)

Gooding, Edward A.; Deutsch, Erik R.; Huehnerhoff, Joseph; Hajian, Arsen R.

2017-05-01

Remote sensing has moved out of the laboratory and into the real world. Instruments using reflection or Raman imaging modalities become faster, cheaper and more powerful annually. Enabling technologies include virtual slit spectrometer design, high power multimode diode lasers, fast open-loop scanning systems, low-noise IR-sensitive array detectors and low-cost computers with touchscreen interfaces. High-volume manufacturing assembles these components into inexpensive portable or handheld devices that make possible sophisticated decision-making based on robust data analytics. Examples include threat, hazmat and narcotics detection; remote gas sensing; biophotonic screening; environmental remediation and a host of other applications.

Highly birefringent suspended-core photonic microcells for refractive-index sensing

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

Wang, Chao; The Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen 518057; Jin, Wa

2014-08-11

An in-line photonic microcell with a highly birefringent suspended microfiber core is fabricated by locally heating and pressurizing selected air-holes of an endless single mode photonic crystal fiber. The microfiber core has rhombus-like cross-sectional geometry and could achieve a high birefringence of up to 10{sup −2}. The microfiber core is fixed at the center of the microcell by thin struts attached to an outer jacket tube, which protects and isolates the microfiber from environmental contaminations. Highly sensitive and robust refractive index sensors based on such microcells are experimentally demonstrated.

Robust Control Design for Systems With Probabilistic Uncertainty

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.

2005-01-01

This paper presents a reliability- and robustness-based formulation for robust control synthesis for systems with probabilistic uncertainty. In a reliability-based formulation, the probability of violating design requirements prescribed by inequality constraints is minimized. In a robustness-based formulation, a metric which measures the tendency of a random variable/process to cluster close to a target scalar/function is minimized. A multi-objective optimization procedure, which combines stability and performance requirements in time and frequency domains, is used to search for robustly optimal compensators. Some of the fundamental differences between the proposed strategy and conventional robust control methods are: (i) unnecessary conservatism is eliminated since there is not need for convex supports, (ii) the most likely plants are favored during synthesis allowing for probabilistic robust optimality, (iii) the tradeoff between robust stability and robust performance can be explored numerically, (iv) the uncertainty set is closely related to parameters with clear physical meaning, and (v) compensators with improved robust characteristics for a given control structure can be synthesized.

Critical bounds on noise and SNR for robust estimation of real-time brain activity from functional near infra-red spectroscopy.

PubMed

Aqil, Muhammad; Jeong, Myung Yung

2018-04-24

The robust characterization of real-time brain activity carries potential for many applications. However, the contamination of measured signals by various instrumental, environmental, and physiological sources of noise introduces a substantial amount of signal variance and, consequently, challenges real-time estimation of contributions from underlying neuronal sources. Functional near infra-red spectroscopy (fNIRS) is an emerging imaging modality whose real-time potential is yet to be fully explored. The objectives of the current study are to (i) validate a time-dependent linear model of hemodynamic responses in fNIRS, and (ii) test the robustness of this approach against measurement noise (instrumental and physiological) and mis-specification of the hemodynamic response basis functions (amplitude, latency, and duration). We propose a linear hemodynamic model with time-varying parameters, which are estimated (adapted and tracked) using a dynamic recursive least square algorithm. Owing to the linear nature of the activation model, the problem of achieving robust convergence to an accurate estimation of the model parameters is recast as a problem of parameter error stability around the origin. We show that robust convergence of the proposed method is guaranteed in the presence of an acceptable degree of model misspecification and we derive an upper bound on noise under which reliable parameters can still be inferred. We also derived a lower bound on signal-to-noise-ratio over which the reliable parameters can still be inferred from a channel/voxel. Whilst here applied to fNIRS, the proposed methodology is applicable to other hemodynamic-based imaging technologies such as functional magnetic resonance imaging. Copyright © 2018 Elsevier Inc. All rights reserved.

A rapidly-reversible absorptive and emissive vapochromic Pt(II) pincer-based chemical sensor

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

Bryant, M. J.; Skelton, J. M.; Hatcher, L. E.

Selective, robust and cost-effective chemical sensors for detecting small volatile-organic compounds (VOCs) have widespread applications in industry, healthcare and environmental monitoring. Here we design a Pt(II) pincer-Type material with selective absorptive and emissive responses to methanol and water. The yellow anhydrous form converts reversibly on a subsecond timescale to a red hydrate in the presence of parts-per-Thousand levels of atmospheric water vapour. Exposure to methanol induces a similarly-rapid and reversible colour change to a blue methanol solvate. Stable smart coatings on glass demonstrate robust switching over 10 4 cycles, and flexible microporous polymer membranes incorporating microcrystals of the complex showmore » identical vapochromic behaviour. The rapid vapochromic response can be rationalised from the crystal structure, and in combination with quantum-chemical modelling, we provide a complete microscopic picture of the switching mechanism. We discuss how this multiscale design approach can be used to obtain new compounds with tailored VOC selectivity and spectral responses.« less

Robust output feedback stabilization for a flexible marine riser system.

PubMed

Zhao, Zhijia; Liu, Yu; Guo, Fang

2017-12-06

The aim of this paper is to develop a boundary control for the vibration reduction of a flexible marine riser system in the presence of parametric uncertainties and system states obtained inaccurately. To this end, an adaptive output feedback boundary control is proposed to suppress the riser's vibration fusing with observer-based backstepping, high-gain observers and robust adaptive control theory. In addition, the parameter adaptive laws are designed to compensate for the system parametric uncertainties, and the disturbance observer is introduced to mitigate the effects of external environmental disturbance. The uniformly bounded stability of the closed-loop system is achieved through rigorous Lyapunov analysis without any discretisation or simplification of the dynamics in the time and space, and the state observer error is ensured to exponentially converge to zero as time grows to infinity. In the end, the simulation and comparison studies are carried out to illustrate the performance of the proposed control under the proper choice of the design parameters. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

A rapidly-reversible absorptive and emissive vapochromic Pt(II) pincer-based chemical sensor

DOE PAGES

Bryant, M. J.; Skelton, J. M.; Hatcher, L. E.; ...

2017-11-27

Selective, robust and cost-effective chemical sensors for detecting small volatile-organic compounds (VOCs) have widespread applications in industry, healthcare and environmental monitoring. Here we design a Pt(II) pincer-Type material with selective absorptive and emissive responses to methanol and water. The yellow anhydrous form converts reversibly on a subsecond timescale to a red hydrate in the presence of parts-per-Thousand levels of atmospheric water vapour. Exposure to methanol induces a similarly-rapid and reversible colour change to a blue methanol solvate. Stable smart coatings on glass demonstrate robust switching over 10 4 cycles, and flexible microporous polymer membranes incorporating microcrystals of the complex showmore » identical vapochromic behaviour. The rapid vapochromic response can be rationalised from the crystal structure, and in combination with quantum-chemical modelling, we provide a complete microscopic picture of the switching mechanism. We discuss how this multiscale design approach can be used to obtain new compounds with tailored VOC selectivity and spectral responses.« less

Macro to microfluidics system for biological environmental monitoring.

PubMed

Delattre, Cyril; Allier, Cédric P; Fouillet, Yves; Jary, Dorothée; Bottausci, Frederic; Bouvier, Denis; Delapierre, Guillaume; Quinaud, Manuelle; Rival, Arnaud; Davoust, Laurent; Peponnet, Christine

2012-01-01

Biological environmental monitoring (BEM) is a growing field of research which challenges both microfluidics and system automation. The aim is to develop a transportable system with analysis throughput which satisfies the requirements: (i) fully autonomous, (ii) complete protocol integration from sample collection to final analysis, (iii) detection of diluted molecules or biological species in a large real life environmental sample volume, (iv) robustness and (v) flexibility and versatility. This paper discusses all these specifications in order to define an original fluidic architecture based on three connected modules, a sampling module, a sample preparation module and a detection module. The sample preparation module highly concentrates on the pathogens present in a few mL samples of complex and unknown solutions and purifies the pathogens' nucleic acids into a few μL of a controlled buffer. To do so, a two-step concentration protocol based on magnetic beads is automated in a reusable macro-to-micro fluidic system. The detection module is a PCR based miniaturized platform using digital microfluidics, where reactions are performed in 64 nL droplets handled by electrowetting on dielectric (EWOD) actuation. The design and manufacture of the two modules are reported as well as their respective performances. To demonstrate the integration of the complete protocol in the same system, first results of pathogen detection are shown. Copyright © 2012 Elsevier B.V. All rights reserved.

Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots.

PubMed

Duarte, Miguel; Costa, Vasco; Gomes, Jorge; Rodrigues, Tiago; Silva, Fernando; Oliveira, Sancho Moura; Christensen, Anders Lyhne

2016-01-01

Swarm robotics is a promising approach for the coordination of large numbers of robots. While previous studies have shown that evolutionary robotics techniques can be applied to obtain robust and efficient self-organized behaviors for robot swarms, most studies have been conducted in simulation, and the few that have been conducted on real robots have been confined to laboratory environments. In this paper, we demonstrate for the first time a swarm robotics system with evolved control successfully operating in a real and uncontrolled environment. We evolve neural network-based controllers in simulation for canonical swarm robotics tasks, namely homing, dispersion, clustering, and monitoring. We then assess the performance of the controllers on a real swarm of up to ten aquatic surface robots. Our results show that the evolved controllers transfer successfully to real robots and achieve a performance similar to the performance obtained in simulation. We validate that the evolved controllers display key properties of swarm intelligence-based control, namely scalability, flexibility, and robustness on the real swarm. We conclude with a proof-of-concept experiment in which the swarm performs a complete environmental monitoring task by combining multiple evolved controllers.

Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots

PubMed Central

Duarte, Miguel; Costa, Vasco; Gomes, Jorge; Rodrigues, Tiago; Silva, Fernando; Oliveira, Sancho Moura; Christensen, Anders Lyhne

2016-01-01

Swarm robotics is a promising approach for the coordination of large numbers of robots. While previous studies have shown that evolutionary robotics techniques can be applied to obtain robust and efficient self-organized behaviors for robot swarms, most studies have been conducted in simulation, and the few that have been conducted on real robots have been confined to laboratory environments. In this paper, we demonstrate for the first time a swarm robotics system with evolved control successfully operating in a real and uncontrolled environment. We evolve neural network-based controllers in simulation for canonical swarm robotics tasks, namely homing, dispersion, clustering, and monitoring. We then assess the performance of the controllers on a real swarm of up to ten aquatic surface robots. Our results show that the evolved controllers transfer successfully to real robots and achieve a performance similar to the performance obtained in simulation. We validate that the evolved controllers display key properties of swarm intelligence-based control, namely scalability, flexibility, and robustness on the real swarm. We conclude with a proof-of-concept experiment in which the swarm performs a complete environmental monitoring task by combining multiple evolved controllers. PMID:26999614

Glacier surface velocity estimation in the West Kunlun Mountain range from L-band ALOS/PALSAR images using modified synthetic aperture radar offset-tracking procedure

NASA Astrophysics Data System (ADS)

Ruan, Zhixing; Guo, Huadong; Liu, Guang; Yan, Shiyong

2014-01-01

Glacier movement is closely related to changes in climatic, hydrological, and geological factors. However, detecting glacier surface flow velocity with conventional ground surveys is challenging. Remote sensing techniques, especially synthetic aperture radar (SAR), provide regular observations covering larger-scale glacier regions. Glacier surface flow velocity in the West Kunlun Mountains using modified offset-tracking techniques based on ALOS/PALSAR images is estimated. Three maps of glacier flow velocity for the period 2007 to 2010 are derived from procedures of offset detection using cross correlation in the Fourier domain and global offset elimination of thin plate smooth splines. Our results indicate that, on average, winter glacier motion on the North Slope is 1 cm/day faster than on the South Slope-a result which corresponds well with the local topography. The performance of our method as regards the reliability of extracted displacements and the robustness of this algorithm are discussed. The SAR-based offset tracking is proven to be reliable and robust, making it possible to investigate comprehensive glacier movement and its response mechanism to environmental change.

Are exposure predictions, used for the prioritization of pharmaceuticals in the environment, fit for purpose?

PubMed

Burns, Emily E; Thomas-Oates, Jane; Kolpin, Dana W; Furlong, Edward T; Boxall, Alistair B A

2017-10-01

Prioritization methodologies are often used for identifying those pharmaceuticals that pose the greatest risk to the natural environment and to focus laboratory testing or environmental monitoring toward pharmaceuticals of greatest concern. Risk-based prioritization approaches, employing models to derive exposure concentrations, are commonly used, but the reliability of these models is unclear. The present study evaluated the accuracy of exposure models commonly used for pharmaceutical prioritization. Targeted monitoring was conducted for 95 pharmaceuticals in the Rivers Foss and Ouse in the City of York (UK). Predicted environmental concentration (PEC) ranges were estimated based on localized prescription, hydrological data, reported metabolism, and wastewater treatment plant (WWTP) removal rates, and were compared with measured environmental concentrations (MECs). For the River Foss, PECs, obtained using highest metabolism and lowest WWTP removal, were similar to MECs. In contrast, this trend was not observed for the River Ouse, possibly because of pharmaceutical inputs unaccounted for by our modeling. Pharmaceuticals were ranked by risk based on either MECs or PECs. With 2 exceptions (dextromethorphan and diphenhydramine), risk ranking based on both MECs and PECs produced similar results in the River Foss. Overall, these findings indicate that PECs may well be appropriate for prioritization of pharmaceuticals in the environment when robust and local data on the system of interest are available and reflective of most source inputs. Environ Toxicol Chem 2017;36:2823-2832. © 2017 SETAC. © 2017 SETAC.

Suboptimal evolutionary novel environments promote singular altered gravity responses of transcriptome during Drosophila metamorphosis

PubMed Central

2013-01-01

Background Previous experiments have shown that the reduced gravity aboard the International Space Station (ISS) causes important alterations in Drosophila gene expression. These changes were shown to be intimately linked to environmental space-flight related constraints. Results Here, we use an array of different techniques for ground-based simulation of microgravity effects to assess the effect of suboptimal environmental conditions on the gene expression of Drosophila in reduced gravity. A global and integrative analysis, using “gene expression dynamics inspector” (GEDI) self-organizing maps, reveals different degrees in the responses of the transcriptome when using different environmental conditions or microgravity/hypergravity simulation devices. Although the genes that are affected are different in each simulation technique, we find that the same gene ontology groups, including at least one large multigene family related with behavior, stress response or organogenesis, are over represented in each case. Conclusions These results suggest that the transcriptome as a whole can be finely tuned to gravity force. In optimum environmental conditions, the alteration of gravity has only mild effects on gene expression but when environmental conditions are far from optimal, the gene expression must be tuned greatly and effects become more robust, probably linked to the lack of experience of organisms exposed to evolutionary novel environments such as a gravitational free one. PMID:23806134

Comparative Evaluation of Veriflow® Salmonella Species to USDA and FDA Culture-Based Methods for the Detection of Salmonella spp. in Food and Environmental Samples.

PubMed

Puri, Amrita; Joelsson, Adam C; Terkhorn, Shawn P; Brown, Ashley S; Gaudioso, Zara E; Siciliano, Nicholas A

2017-09-01

Veriflow® Salmonella species (Veriflow SS) is a molecular-based assay for the presumptive detection of Salmonella spp. from environmental surfaces (stainless steel, sealed concrete, plastic, and ceramic tile), dairy (2% milk), raw meat (20% fat ground beef), chicken carcasses, and ready-to-eat (RTE) food (hot dogs). The assay utilizes a PCR detection method coupled with a rapid, visual, flow-based assay that develops in 3 min post-PCR amplification and requires only an 18 h enrichment for maximum sensitivity. The Veriflow SS system eliminates the need for sample purification, gel electrophoresis, or fluorophore-based detection of target amplification and does not require complex data analysis. This Performance Tested MethodSM validation study demonstrated the ability of the Veriflow SS method to detect low levels of artificially inoculated or naturally occurring Salmonella spp. in eight distinct environmental and food matrixes. In each reference comparison study, probability of detection analysis indicated that there was no significant difference between the Veriflow SS method and the U.S. Department of Agriculture Food Safety and Inspection Service Microbiology Laboratory Guidebook Chapter 4.06 and the U.S. Food and Drug Administration Bacteriological Analytical Manual Chapter 5 reference methods. A total of 104 Salmonella strains were detected in the inclusivity study, and 35 nonspecific organisms went undetected in the exclusivity study. The study results show that the Veriflow SS method is a sensitive, selective, and robust assay for the presumptive detection of Salmonella spp. sampled from environmental surfaces (stainless steel, sealed concrete, plastic, and ceramic tile), dairy (2% milk), raw meat (20% fat ground beef), chicken carcasses, and RTE food (hot dogs).

Quantitative proteomics and network analysis of SSA1 and SSB1 deletion mutants reveals robustness of chaperone HSP70 network in Saccharomyces cerevisiae

PubMed Central

Jarnuczak, Andrew F.; Eyers, Claire E.; Schwartz, Jean‐Marc; Grant, Christopher M.

2015-01-01

Molecular chaperones play an important role in protein homeostasis and the cellular response to stress. In particular, the HSP70 chaperones in yeast mediate a large volume of protein folding through transient associations with their substrates. This chaperone interaction network can be disturbed by various perturbations, such as environmental stress or a gene deletion. Here, we consider deletions of two major chaperone proteins, SSA1 and SSB1, from the chaperone network in Sacchromyces cerevisiae. We employ a SILAC‐based approach to examine changes in global and local protein abundance and rationalise our results via network analysis and graph theoretical approaches. Although the deletions result in an overall increase in intracellular protein content, correlated with an increase in cell size, this is not matched by substantial changes in individual protein concentrations. Despite the phenotypic robustness to deletion of these major hub proteins, it cannot be simply explained by the presence of paralogues. Instead, network analysis and a theoretical consideration of folding workload suggest that the robustness to perturbation is a product of the overall network structure. This highlights how quantitative proteomics and systems modelling can be used to rationalise emergent network properties, and how the HSP70 system can accommodate the loss of major hubs. PMID:25689132

Offspring ADHD as a risk factor for parental marital problems: controls for genetic and environmental confounds.

PubMed

Schermerhorn, Alice C; D'Onofrio, Brian M; Slutske, Wendy S; Emery, Robert E; Turkheimer, Eric; Harden, K Paige; Heath, Andrew C; Martin, Nicholas G

2012-12-01

Previous studies have found that child attention-deficit/hyperactivity disorder (ADHD) is associated with more parental marital problems. However, the reasons for this association are unclear. The association might be due to genetic or environmental confounds that contribute to both marital problems and ADHD. Data were drawn from the Australian Twin Registry, including 1,296 individual twins, their spouses, and offspring. We studied adult twins who were discordant for offspring ADHD.Using a discordant twin pairs design, we examined the extent to which genetic and environmental confounds,as well as measured parental and offspring characteristics, explain the ADHD-marital problems association. Offspring ADHD predicted parental divorce and marital conflict. The associations were also robust when comparing differentially exposed identical twins to control for unmeasured genetic and environmental factors, when controlling for measured maternal and paternal psychopathology,when restricting the sample based on timing of parental divorce and ADHD onset, and when controlling for other forms of offspring psychopathology. Each of these controls rules out alternative explanations for the association. The results of the current study converge with those of prior research in suggesting that factors directly associated with offspring ADHD increase parental marital problems.

Environmental stress, ageing and glial cell senescence: a novel mechanistic link to Parkinson’s disease?

PubMed Central

Chinta, Shankar J; Lieu, Christopher A; DeMaria, Marco; Laberge, Remi-Martin; Campisi, Judith; Andersen, Julie K

2013-01-01

Exposure to environmental toxins is associated with a variety of age-related diseases including cancer and neurodegeneration. For example, in Parkinson’s disease (PD), chronic environmental exposure to certain toxins has been linked to the age-related development of neuropathology. Neuronal damage is believed to involve the induction of neuroinflammatory events as a consequence of glial cell activation. Cellular senescence is a potent anti-cancer mechanism that occurs in a number of proliferative cell types and causes the arrest of proliferation of cells at risk of malignant transformation following exposure to potentially oncogenic stimuli. With age, senescent cells accumulate and express a senescence-associated secretory phenotype (SASP; i.e. the robust secretion of many inflammatory cytokines, growth factors and proteases). Whereas cell senescence in peripheral tissues has been causally linked to a number of age-related pathologies, little is known about the induction of cellular senescence and the SASP in the brain. Based on recently reported findings, we propose that environmental stressors associated with PD may act in part by eliciting senescence and the SASP within non-neuronal glial cells in the ageing brain, thus contributing to the characteristic decline in neuronal integrity that occurs in this disorder. PMID:23600398

Offspring ADHD as a Risk Factor for Parental Marital Problems: Controls for Genetic and Environmental Confounds

PubMed Central

Schermerhorn, Alice C.; D’Onofrio, Brian M.; Slutske, Wendy S.; Emery, Robert E.; Turkheimer, Eric; Harden, K. Paige; Heath, Andrew C.; Martin, Nicholas G.

2013-01-01

Background Previous studies have found that child attention-deficit/hyperactivity disorder (ADHD) is associated with more parental marital problems. The reasons for this association are unclear, however. The association might be due to genetic or environmental confounds that contribute to both marital problems and ADHD. Method Data were drawn from the Australian Twin Registry, including 1296 individual twins, their spouses, and offspring. We studied adult twins who were discordant for offspring ADHD. Using a discordant twin pairs design, we examined the extent to which genetic and environmental confounds, as well as measured parental and offspring characteristics, explain the ADHD-marital problems association. Results Offspring ADHD predicted parental divorce and marital conflict. The associations were also robust when comparing differentially exposed identical twins to control for unmeasured genetic and environmental factors, when controlling for measured maternal and paternal psychopathology, when restricting the sample based on timing of parental divorce and ADHD onset, and when controlling for other forms of offspring psychopathology. Each of these controls rules out alternative explanations for the association. Conclusion The results of the current study converge with those of prior research in suggesting that factors directly associated with offspring ADHD increase parental marital problems. PMID:22958575

Robust detection of rare species using environmental DNA: The importance of primer specificity

Treesearch

Taylor M. Wilcox; Kevin S. McKelvey; Michael K. Young; Stephen F. Jane; Winsor H. Lowe; Andrew R. Whiteley; Michael K. Schwartz

2013-01-01

Environmental DNA (eDNA) is being rapidly adopted as a tool to detect rare animals. Quantitative PCR (qPCR) using probebased chemistries may represent a particularly powerful tool because of the method's sensitivity, specificity, and potential to quantify target DNA. However, there has been little work understanding the performance of these assays in the presence...

Are There Shared Environmental Influences on Attention-Deficit/Hyperactivity Disorder? Reply to Wood, Buitelaar, Rijsdijk, Asherson, and Kunsti (2010)

ERIC Educational Resources Information Center

Burt, S. Alexandra

2010-01-01

A recent large-scale meta-analysis of twin and adoption studies indicated that shared environmental influences make important contributions to most forms of child and adolescent psychopathology (Burt, 2009b). The sole exception to this robust pattern of results was observed for attention-deficit/hyperactivity disorder (ADHD), which appeared to be…

Toward more robust projections of forest landscape dynamics under novel environmental conditions: embedding PnET within LANDIS-II

Treesearch

A. De Bruijn; E.J. Gustafson; B.R. Sturtevant; J.R. Foster; B.R. Miranda; N.I. Lichti; D.F. Jacobs

2014-01-01

Ecological models built on phenomenological relationships and behavior of the past may not be robustunder novel conditions of the future because global changes are producing environmental conditions that forests have not experienced historically. We developed a new succession extension for the LANDIS-II forest landscape model, PnET-Succession, to simulate forest growth...

Robust Membranes for Sustainable Wastewater Treatment by Forward Osmosis in FOBs

DTIC Science & Technology

2017-05-09

the Department of Defense Strategic Environmental Research and Development Program (SERDP). The publication of this report does not indicate...CT 06511 9. SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR’S ACRONYM(S) Strategic Environmental Research and...strategies, in-situ fabrication and post -fabrication membrane modification. In-situ fabrication modification involves fabrication of a polyamide selective

Alcohol Outlet Density, Drinking Contexts and Intimate Partner Violence: A Review of Environmental Risk Factors

ERIC Educational Resources Information Center

Cunradi, Carol B.; Mair, Christina; Todd, Michael

2014-01-01

Alcohol use is a robust predictor of intimate partner violence (IPV). A critical barrier to progress in preventing alcohol-related IPV is that little is known about how an individual's specific drinking contexts (where, how often, and with whom one drinks) are related to IPV, or how these contexts are affected by environmental characteristics,…

Formation of dominant mode by evolution in biological systems

NASA Astrophysics Data System (ADS)

Furusawa, Chikara; Kaneko, Kunihiko

2018-04-01

A reduction in high-dimensional phenotypic states to a few degrees of freedom is essential to understand biological systems. Here, we show evolutionary robustness causes such reduction which restricts possible phenotypic changes in response to a variety of environmental conditions. First, global protein expression changes in Escherichia coli after various environmental perturbations were shown to be proportional across components, across different types of environmental conditions. To examine if such dimension reduction is a result of evolution, we analyzed a cell model—with a huge number of components, that reproduces itself via a catalytic reaction network—and confirmed that common proportionality in the concentrations of all components is shaped through evolutionary processes. We found that the changes in concentration across all components in response to environmental and evolutionary changes are constrained to the changes along a one-dimensional major axis, within a huge-dimensional state space. On the basis of these observations, we propose a theory in which such constraints in phenotypic changes are achieved both by evolutionary robustness and plasticity and formulate this proposition in terms of dynamical systems. Accordingly, broad experimental and numerical results on phenotypic changes caused by evolution and adaptation are coherently explained.

Robust optimization modelling with applications to industry and environmental problems

NASA Astrophysics Data System (ADS)

Chaerani, Diah; Dewanto, Stanley P.; Lesmana, Eman

2017-10-01

Robust Optimization (RO) modeling is one of the existing methodology for handling data uncertainty in optimization problem. The main challenge in this RO methodology is how and when we can reformulate the robust counterpart of uncertain problems as a computationally tractable optimization problem or at least approximate the robust counterpart by a tractable problem. Due to its definition the robust counterpart highly depends on how we choose the uncertainty set. As a consequence we can meet this challenge only if this set is chosen in a suitable way. The development on RO grows fast, since 2004, a new approach of RO called Adjustable Robust Optimization (ARO) is introduced to handle uncertain problems when the decision variables must be decided as a ”wait and see” decision variables. Different than the classic Robust Optimization (RO) that models decision variables as ”here and now”. In ARO, the uncertain problems can be considered as a multistage decision problem, thus decision variables involved are now become the wait and see decision variables. In this paper we present the applications of both RO and ARO. We present briefly all results to strengthen the importance of RO and ARO in many real life problems.

Life-cycle assessment of the municipal solid waste management system in Hangzhou, China (EASEWASTE).

PubMed

Zhao, Yan; Wang, Hong-Tao; Lu, Wen-Jing; Damgaard, Anders; Christensen, Thomas H

2009-06-01

With the purpose of assessing the environmental impacts and benefits of the current municipal solid waste management system and two modified systems, EASEWASTE, a life-cycle-based model, was used to evaluate the waste system of Hangzhou city in China. An integrated model was established, including waste generation, collection, transportation, treatment, disposal and accompanying external processes. The results showed that CH(4) released from landfilling was the primary pollutant contributing to global warming, and HCl and NH(3) from incineration contributed most to acidification. Material recycling and incineration with energy recovery were important because of the induced savings in material production based on virgin materials and in energy production based on coal combustion. A modified system in which waste is transported to the nearest incinerators would be relatively better than the current system, mainly due to the decrease of pollution from landfilled waste and the increase in energy production from waste avoiding energy production by traditional power plants. A ban on free plastic bags for shopping was shown to reduce most environmental impacts due to saved oil resources and other materials used in producing the plastic bags. Sensitivity analysis confirmed the robustness of the results. LCA methodology and a model like EASEWASTE are very suitable for evaluating the overall environmental consequences, and can be used for decision support and strategic planning in developing countries such as China where pollution control has become increasingly important with the rapid increase of waste generation as well as the increasing public awareness of environmental protection.

Robust control of combustion instabilities

NASA Astrophysics Data System (ADS)

Hong, Boe-Shong

Several interactive dynamical subsystems, each of which has its own time-scale and physical significance, are decomposed to build a feedback-controlled combustion- fluid robust dynamics. On the fast-time scale, the phenomenon of combustion instability is corresponding to the internal feedback of two subsystems: acoustic dynamics and flame dynamics, which are parametrically dependent on the slow-time-scale mean-flow dynamics controlled for global performance by a mean-flow controller. This dissertation constructs such a control system, through modeling, analysis and synthesis, to deal with model uncertainties, environmental noises and time- varying mean-flow operation. Conservation law is decomposed as fast-time acoustic dynamics and slow-time mean-flow dynamics, served for synthesizing LPV (linear parameter varying)- L2-gain robust control law, in which a robust observer is embedded for estimating and controlling the internal status, while achieving trade- offs among robustness, performances and operation. The robust controller is formulated as two LPV-type Linear Matrix Inequalities (LMIs), whose numerical solver is developed by finite-element method. Some important issues related to physical understanding and engineering application are discussed in simulated results of the control system.

Recognition and characterization of unstructured environmental sounds

NASA Astrophysics Data System (ADS)

Chu, Selina

2011-12-01

Environmental sounds are what we hear everyday, or more generally sounds that surround us ambient or background audio. Humans utilize both vision and hearing to respond to their surroundings, a capability still quite limited in machine processing. The first step toward achieving multimodal input applications is the ability to process unstructured audio and recognize audio scenes (or environments). Such ability would have applications in content analysis and mining of multimedia data or improving robustness in context aware applications through multi-modality, such as in assistive robotics, surveillances, or mobile device-based services. The goal of this thesis is on the characterization of unstructured environmental sounds for understanding and predicting the context surrounding of an agent or device. Most research on audio recognition has focused primarily on speech and music. Less attention has been paid to the challenges and opportunities for using audio to characterize unstructured audio. My research focuses on investigating challenging issues in characterizing unstructured environmental audio and to develop novel algorithms for modeling the variations of the environment. The first step in building a recognition system for unstructured auditory environment was to investigate on techniques and audio features for working with such audio data. We begin by performing a study that explore suitable features and the feasibility of designing an automatic environment recognition system using audio information. In my initial investigation to explore the feasibility of designing an automatic environment recognition system using audio information, I have found that traditional recognition and feature extraction for audio were not suitable for environmental sound, as they lack any type of structures, unlike those of speech and music which contain formantic and harmonic structures, thus dispelling the notion that traditional speech and music recognition techniques can simply be used for realistic environmental sound. Natural unstructured environment sounds contain a large variety of sounds, which are in fact noise-like and are not effectively modeled by Mel-frequency cepstral coefficients (MFCCs) or other commonly-used audio features, e.g. energy, zero-crossing, etc. Due to the lack of appropriate features that is suitable for environmental audio and to achieve a more effective representation, I proposed a specialized feature extraction algorithm for environmental sounds that utilizes the matching pursuit (MP) algorithm to learn the inherent structure of each type of sounds, which we called MP-features. MP-features have shown to capture and represent sounds from different sources and different ranges, where frequency domain features (e.g., MFCCs) fail and can be advantageous when combining with MFCCs to improve the overall performance. The third component leads to our investigation on modeling and detecting the background audio. One of the goals of this research is to characterize an environment. Since many events would blend into the background, I wanted to look for a way to achieve a general model for any particular environment. Once we have an idea of the background, it will enable us to identify foreground events even if we havent seen these events before. Therefore, the next step is to investigate into learning the audio background model for each environment type, despite the occurrences of different foreground events. In this work, I presented a framework for robust audio background modeling, which includes learning the models for prediction, data knowledge and persistent characteristics of the environment. This approach has the ability to model the background and detect foreground events as well as the ability to verify whether the predicted background is indeed the background or a foreground event that protracts for a longer period of time. In this work, I also investigated the use of a semi-supervised learning technique to exploit and label new unlabeled audio data. The final components of my thesis will involve investigating on learning sound structures for generalization and applying the proposed ideas to context aware applications. The inherent nature of environmental sound is noisy and contains relatively large amounts of overlapping events between different environments. Environmental sounds contain large variances even within a single environment type, and frequently, there are no divisible or clear boundaries between some types. Traditional methods of classification are generally not robust enough to handle classes with overlaps. This audio, hence, requires representation by complex models. Using deep learning architecture provides a way to obtain a generative model-based method for classification. Specifically, I considered the use of Deep Belief Networks (DBNs) to model environmental audio and investigate its applicability with noisy data to improve robustness and generalization. A framework was proposed using composite-DBNs to discover high-level representations and to learn a hierarchical structure for different acoustic environments in a data-driven fashion. Experimental results on real data sets demonstrate its effectiveness over traditional methods with over 90% accuracy on recognition for a high number of environmental sound types.

Magnetic detection of mercuric ion using giant magnetoresistance-based biosensing system.

PubMed

Wang, Wei; Wang, Yi; Tu, Liang; Klein, Todd; Feng, Yinglong; Li, Qin; Wang, Jian-Ping

2014-04-15

We have demonstrated a novel sensing strategy employing a giant magnetoresistance (GMR) biosensor and DNA chemistry for the detection of mercuric ion (Hg(2+)). This assay takes advantages of high sensitivity and real-time signal readout of GMR biosensor and high selectivity of thymine-thymine (T-T) pair for Hg(2+). The assay has a detection limit of 10 nM in both buffer and natural water, which is the maximum mercury level in drinking water regulated by U.S. Environmental Protection Agency (EPA). The magnitude of the dynamic range for Hg(2+) detection is up to three orders (10 nM to 10 μM). Herein, GMR sensing technology is first introduced into a pollutant monitoring area. It can be foreseen that the GMR biosensor could become a robust contender in the areas of environmental monitoring and food safety testing.

Sensitivity Analysis of earth and environmental models: a systematic review to guide scientific advancement

NASA Astrophysics Data System (ADS)

Wagener, Thorsten; Pianosi, Francesca

2016-04-01

Sensitivity Analysis (SA) investigates how the variation in the output of a numerical model can be attributed to variations of its input factors. SA is increasingly being used in earth and environmental modelling for a variety of purposes, including uncertainty assessment, model calibration and diagnostic evaluation, dominant control analysis and robust decision-making. Here we provide some practical advice regarding best practice in SA and discuss important open questions based on a detailed recent review of the existing body of work in SA. Open questions relate to the consideration of input factor interactions, methods for factor mapping and the formal inclusion of discrete factors in SA (for example for model structure comparison). We will analyse these questions using relevant examples and discuss possible ways forward. We aim at stimulating the discussion within the community of SA developers and users regarding the setting of good practices and on defining priorities for future research.

Molecular Mechanisms and Management of a Cutaneous Inflammatory Disorder: Psoriasis

PubMed Central

Cho, Dae Ho; Park, Hyun Jeong

2017-01-01

Psoriasis is a complex chronic inflammatory cutaneous disorder. To date, robust molecular mechanisms of psoriasis have been reported. Among diverse aberrant immunopathogenetic mechanisms, the current model emphasizes the role of Th1 and the IL-23/Th17 axis, skin-resident immune cells and major signal transduction pathways involved in psoriasis. The multiple genetic risk loci for psoriasis have been rapidly revealed with the advent of a novel technology. Moreover, identifying epigenetic modifications could bridge the gap between genetic and environmental risk factors in psoriasis. This review will provide a better understanding of the pathogenesis of psoriasis by unraveling the complicated interplay among immunological abnormalities, genetic risk foci, epigenetic modification and environmental factors of psoriasis. With advances in molecular biology, diverse new targets are under investigation to manage psoriasis. The recent advances in treatment modalities for psoriasis based on targeted molecules are also discussed. PMID:29232931

Full circumpolar migration ensures evolutionary unity in the Emperor penguin.

PubMed

Cristofari, Robin; Bertorelle, Giorgio; Ancel, André; Benazzo, Andrea; Le Maho, Yvon; Ponganis, Paul J; Stenseth, Nils Chr; Trathan, Phil N; Whittington, Jason D; Zanetti, Enrico; Zitterbart, Daniel P; Le Bohec, Céline; Trucchi, Emiliano

2016-06-14

Defining reliable demographic models is essential to understand the threats of ongoing environmental change. Yet, in the most remote and threatened areas, models are often based on the survey of a single population, assuming stationarity and independence in population responses. This is the case for the Emperor penguin Aptenodytes forsteri, a flagship Antarctic species that may be at high risk continent-wide before 2100. Here, using genome-wide data from the whole Antarctic continent, we reveal that this top-predator is organized as one single global population with a shared demography since the late Quaternary. We refute the view of the local population as a relevant demographic unit, and highlight that (i) robust extinction risk estimations are only possible by including dispersal rates and (ii) colony-scaled population size is rather indicative of local stochastic events, whereas the species' response to global environmental change is likely to follow a shared evolutionary trajectory.

Full circumpolar migration ensures evolutionary unity in the Emperor penguin

PubMed Central

Cristofari, Robin; Bertorelle, Giorgio; Ancel, André; Benazzo, Andrea; Le Maho, Yvon; Ponganis, Paul J.; Stenseth, Nils Chr; Trathan, Phil N.; Whittington, Jason D.; Zanetti, Enrico; Zitterbart, Daniel P.; Le Bohec, Céline; Trucchi, Emiliano

2016-01-01

Defining reliable demographic models is essential to understand the threats of ongoing environmental change. Yet, in the most remote and threatened areas, models are often based on the survey of a single population, assuming stationarity and independence in population responses. This is the case for the Emperor penguin Aptenodytes forsteri, a flagship Antarctic species that may be at high risk continent-wide before 2100. Here, using genome-wide data from the whole Antarctic continent, we reveal that this top-predator is organized as one single global population with a shared demography since the late Quaternary. We refute the view of the local population as a relevant demographic unit, and highlight that (i) robust extinction risk estimations are only possible by including dispersal rates and (ii) colony-scaled population size is rather indicative of local stochastic events, whereas the species' response to global environmental change is likely to follow a shared evolutionary trajectory. PMID:27296726

Socio-Environmental Resilience and Complex Urban Systems Modeling

NASA Astrophysics Data System (ADS)

Deal, Brian; Petri, Aaron; Pan, Haozhi; Goldenberg, Romain; Kalantari, Zahra; Cvetkovic, Vladimir

2017-04-01

The increasing pressure of climate change has inspired two normative agendas; socio-technical transitions and socio-ecological resilience, both sharing a complex-systems epistemology (Gillard et al. 2016). Socio-technical solutions include a continuous, massive data gathering exercise now underway in urban places under the guise of developing a 'smart'(er) city. This has led to the creation of data-rich environments where large data sets have become central to monitoring and forming a response to anomalies. Some have argued that these kinds of data sets can help in planning for resilient cities (Norberg and Cumming 2008; Batty 2013). In this paper, we focus on a more nuanced, ecologically based, socio-environmental perspective of resilience planning that is often given less consideration. Here, we broadly discuss (and model) the tightly linked, mutually influenced, social and biophysical subsystems that are critical for understanding urban resilience. We argue for the need to incorporate these sub system linkages into the resilience planning lexicon through the integration of systems models and planning support systems. We make our case by first providing a context for urban resilience from a socio-ecological and planning perspective. We highlight the data needs for this type of resilient planning and compare it to currently collected data streams in various smart city efforts. This helps to define an approach for operationalizing socio-environmental resilience planning using robust systems models and planning support systems. For this, we draw from our experiences in coupling a spatio-temporal land use model (the Landuse Evolution and impact Assessment Model (LEAM)) with water quality and quantity models in Stockholm Sweden. We describe the coupling of these systems models using a robust Planning Support System (PSS) structural framework. We use the coupled model simulations and PSS to analyze the connection between urban land use transformation (social) and water (environmental) systems within the context of planning for a more resilient Stockholm. This work shows that complex urban systems models can help bridge the divide between socio-technological and socio-environmental systems knowledge and achieving resilient urban areas.

TyPol - a new methodology for organic compounds clustering based on their molecular characteristics and environmental behavior.

PubMed

Servien, Rémi; Mamy, Laure; Li, Ziang; Rossard, Virginie; Latrille, Eric; Bessac, Fabienne; Patureau, Dominique; Benoit, Pierre

2014-09-01

Following legislation, the assessment of the environmental risks of 30000-100000 chemical substances is required for their registration dossiers. However, their behavior in the environment and their transfer to environmental components such as water or atmosphere are studied for only a very small proportion of the chemical in laboratory tests or monitoring studies because it is time-consuming and/or cost prohibitive. Therefore, the objective of this work was to develop a new methodology, TyPol, to classify organic compounds, and their degradation products, according to both their behavior in the environment and their molecular properties. The strategy relies on partial least squares analysis and hierarchical clustering. The calculation of molecular descriptors is based on an in silico approach, and the environmental endpoints (i.e. environmental parameters) are extracted from several available databases and literature. The classification of 215 organic compounds inputted in TyPol for this proof-of-concept study showed that the combination of some specific molecular descriptors could be related to a particular behavior in the environment. TyPol also provided an analysis of similarities (or dissimilarities) between organic compounds and their degradation products. Among the 24 degradation products that were inputted, 58% were found in the same cluster as their parents. The robustness of the method was tested and shown to be good. TyPol could help to predict the environmental behavior of a "new" compound (parent compound or degradation product) from its affiliation to one cluster, but also to select representative substances from a large data set in order to answer some specific questions regarding their behavior in the environment. Copyright © 2014 Elsevier Ltd. All rights reserved.

Fractionating dead reckoning: role of the compass, odometer, logbook, and home base establishment in spatial orientation

NASA Astrophysics Data System (ADS)

Wallace, Douglas G.; Martin, Megan M.; Winter, Shawn S.

2008-06-01

Rats use multiple sources of information to maintain spatial orientation. Although previous work has focused on rats’ use of environmental cues, a growing number of studies have demonstrated that rats also use self-movement cues to organize navigation. This review examines the extent that kinematic analysis of naturally occurring behavior has provided insight into processes that mediate dead-reckoning-based navigation. This work supports a role for separate systems in processing self-movement cues that converge on the hippocampus. The compass system is involved in deriving directional information from self-movement cues; whereas, the odometer system is involved in deriving distance information from self-movement cues. The hippocampus functions similar to a logbook in that outward path unique information from the compass and odometer is used to derive the direction and distance of a path to the point at which movement was initiated. Finally, home base establishment may function to reset this system after each excursion and anchor environmental cues to self-movement cues. The combination of natural behaviors and kinematic analysis has proven to be a robust paradigm to investigate the neural basis of spatial orientation.

Fractionating dead reckoning: role of the compass, odometer, logbook, and home base establishment in spatial orientation

PubMed Central

Martin, Megan M.; Winter, Shawn S.

2008-01-01

Rats use multiple sources of information to maintain spatial orientation. Although previous work has focused on rats' use of environmental cues, a growing number of studies have demonstrated that rats also use self-movement cues to organize navigation. This review examines the extent that kinematic analysis of naturally occurring behavior has provided insight into processes that mediate dead-reckoning-based navigation. This work supports a role for separate systems in processing self-movement cues that converge on the hippocampus. The compass system is involved in deriving directional information from self-movement cues; whereas, the odometer system is involved in deriving distance information from self-movement cues. The hippocampus functions similar to a logbook in that outward path unique information from the compass and odometer is used to derive the direction and distance of a path to the point at which movement was initiated. Finally, home base establishment may function to reset this system after each excursion and anchor environmental cues to self-movement cues. The combination of natural behaviors and kinematic analysis has proven to be a robust paradigm to investigate the neural basis of spatial orientation. PMID:18553065

Variation in tibial functionality and fracture susceptibility among healthy, young adults arises from the acquisition of biologically distinct sets of traits.

PubMed

Jepsen, Karl J; Evans, Rachel; Negus, Charles H; Gagnier, Joel J; Centi, Amanda; Erlich, Tomer; Hadid, Amir; Yanovich, Ran; Moran, Daniel S

2013-06-01

Physiological systems like bone respond to many genetic and environmental factors by adjusting traits in a highly coordinated, compensatory manner to establish organ-level function. To be mechanically functional, a bone should be sufficiently stiff and strong to support physiological loads. Factors impairing this process are expected to compromise strength and increase fracture risk. We tested the hypotheses that individuals with reduced stiffness relative to body size will show an increased risk of fracturing and that reduced strength arises from the acquisition of biologically distinct sets of traits (ie, different combinations of morphological and tissue-level mechanical properties). We assessed tibial functionality retrospectively for 336 young adult women and men engaged in military training, and calculated robustness (total area/bone length), cortical area (Ct.Ar), and tissue-mineral density (TMD). These three traits explained 69% to 72% of the variation in tibial stiffness (p < 0.0001). Having reduced stiffness relative to body size (body weight × bone length) was associated with odds ratios of 1.5 (95% confidence interval [CI], 0.5-4.3) and 7.0 (95% CI, 2.0-25.1) for women and men, respectively, for developing a stress fracture based on radiography and scintigraphy. K-means cluster analysis was used to segregate men and women into subgroups based on robustness, Ct.Ar, and TMD adjusted for body size. Stiffness varied 37% to 42% among the clusters (p < 0.0001, ANOVA). For men, 78% of stress fracture cases segregated to three clusters (p < 0.03, chi-square). Clusters showing reduced function exhibited either slender tibias with the expected Ct.Ar and TMD relative to body size and robustness (ie, well-adapted bones) or robust tibias with reduced residuals for Ct.Ar or TMD relative to body size and robustness (ie, poorly adapted bones). Thus, we show there are multiple biomechanical and thus biological pathways leading to reduced function and increased fracture risk. Our results have important implications for developing personalized preventative diagnostics and treatments. Copyright © 2013 American Society for Bone and Mineral Research.

Managing Acute Behavioural Disturbances in the Emergency Department Using the Environment, Policies and Practices: A Systematic Review.

PubMed

Weiland, Tracey J; Ivory, Sean; Hutton, Jennie

2017-06-01

Effective strategies for managing acute behavioural disturbances (ABDs) within emergency departments (EDs) are needed given their rising occurrence and negative impact on safety, psychological wellbeing, and staff turnover. Non-pharmacological interventions for ABD management generally fall into four categories: environmental modifications; policies; practice changes; and education. Our objective was to systematically review the efficacy of strategies for ABD management within EDs that involved changes to environment, architecture, policy and practice. We performed systematic searches of CINAHL Plus with Full Text, PsycINFO, MEDLINE, and EMBASE, as well as reference lists of relevant review articles to identify relevant studies published between January 1985 - April 2016. We included studies written in English, which reported management of behavioural disturbances in adults associated with the ED through the use of environmental modifiers (including seclusion, restraint, specialised rooms, architectural changes), policy, and practice-based interventions excepting education-only interventions. Efficacy outcomes of interest included incidence, severity, and duration of ABD, incidence of injuries, staff absenteeism, restraint use, restraint duration, and staff and patient perceptions. Two reviewers independently screened titles and abstracts, and assessed the relevancy and eligibility of studies based on full-text articles. Two authors independently appraised included studies. A narrative synthesis of findings was undertaken. Studies reporting interventions for managing ABDs within the ED are limited in number and quality. The level of evidence for efficacy is low, requiring caution in conclusions. While there is preliminary evidence for environmental change in the form of specialised behavioural rooms, security upgrades and ED modifications, these are not supported by evidence from controlled studies. Many of these "common sense" environmental changes recommended in many guidelines have been widely implemented in EDs. There is an unambiguous gap in the literature regarding the efficacy of interventions for ABD management in EDs involving environmental, policy or practice-based changes. With growing demand on EDs, and with increasing numbers of ABDs, identification of robust evidence-based interventions for safe and effective ABD management is vital.

Airborne Transducer Integrity under Operational Environment for Structural Health Monitoring

PubMed Central

Salmanpour, Mohammad Saleh; Sharif Khodaei, Zahra; Aliabadi, Mohammad Hossein

2016-01-01

This paper investigates the robustness of permanently mounted transducers used in airborne structural health monitoring systems, when exposed to the operational environment. Typical airliners operate in a range of conditions, hence, structural health monitoring (SHM) transducer robustness and integrity must be demonstrated for these environments. A set of extreme temperature, altitude and vibration environment test profiles are developed using the existing Radio Technical Commission for Aeronautics (RTCA)/DO-160 test methods. Commercially available transducers and manufactured versions bonded to carbon fibre reinforced polymer (CFRP) composite materials are tested. It was found that the DuraAct transducer is robust to environmental conditions tested, while the other transducer types degrade under the same conditions. PMID:27973450

Building a robust vehicle detection and classification module

NASA Astrophysics Data System (ADS)

Grigoryev, Anton; Khanipov, Timur; Koptelov, Ivan; Bocharov, Dmitry; Postnikov, Vassily; Nikolaev, Dmitry

2015-12-01

The growing adoption of intelligent transportation systems (ITS) and autonomous driving requires robust real-time solutions for various event and object detection problems. Most of real-world systems still cannot rely on computer vision algorithms and employ a wide range of costly additional hardware like LIDARs. In this paper we explore engineering challenges encountered in building a highly robust visual vehicle detection and classification module that works under broad range of environmental and road conditions. The resulting technology is competitive to traditional non-visual means of traffic monitoring. The main focus of the paper is on software and hardware architecture, algorithm selection and domain-specific heuristics that help the computer vision system avoid implausible answers.

Selective robust optimization: A new intensity-modulated proton therapy optimization strategy

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

Li, Yupeng; Niemela, Perttu; Siljamaki, Sami

2015-08-15

Purpose: To develop a new robust optimization strategy for intensity-modulated proton therapy as an important step in translating robust proton treatment planning from research to clinical applications. Methods: In selective robust optimization, a worst-case-based robust optimization algorithm is extended, and terms of the objective function are selectively computed from either the worst-case dose or the nominal dose. Two lung cancer cases and one head and neck cancer case were used to demonstrate the practical significance of the proposed robust planning strategy. The lung cancer cases had minimal tumor motion less than 5 mm, and, for the demonstration of the methodology,more » are assumed to be static. Results: Selective robust optimization achieved robust clinical target volume (CTV) coverage and at the same time increased nominal planning target volume coverage to 95.8%, compared to the 84.6% coverage achieved with CTV-based robust optimization in one of the lung cases. In the other lung case, the maximum dose in selective robust optimization was lowered from a dose of 131.3% in the CTV-based robust optimization to 113.6%. Selective robust optimization provided robust CTV coverage in the head and neck case, and at the same time improved controls over isodose distribution so that clinical requirements may be readily met. Conclusions: Selective robust optimization may provide the flexibility and capability necessary for meeting various clinical requirements in addition to achieving the required plan robustness in practical proton treatment planning settings.« less

Smart Growth Self-Assessment for Rural Communities

EPA Pesticide Factsheets

Tool to help small towns and rural communities assess their existing policies, plans, codes, and zoning regulations to determine how well they work to create healthy, environmentally resilient, and economically robust places.

The MPLEx Protocol for Multi-omic Analyses of Soil Samples

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

Nicora, Carrie D.; Burnum-Johnson, Kristin E.; Nakayasu, Ernesto S.

Mass spectrometry (MS)-based integrated metaproteomic, metabolomic and lipidomic (multi-omic) studies are transforming our ability to understand and characterize microbial communities in environmental and biological systems. These measurements are even enabling enhanced analyses of complex soil microbial communities, which are the most complex microbial systems known to date. Multi-omic analyses, however, do have sample preparation challenges since separate extractions are typically needed for each omic study, thereby greatly amplifying the preparation time and amount of sample required. To address this limitation, a 3-in-1 method for simultaneous metabolite, protein, and lipid extraction (MPLEx) from the exact same soil sample was created bymore » adapting a solvent-based approach. This MPLEx protocol has proven to be simple yet robust for many sample types and even when utilized for limited quantities of complex soil samples. The MPLEx method also greatly enabled the rapid multi-omic measurements needed to gain a better understanding of the members of each microbial community, while evaluating the changes taking place upon biological and environmental perturbations.« less

A Distributed Model for Stressors Monitoring Based on Environmental Smart Sensors.

PubMed

de Ramón-Fernández, Alberto; Ruiz-Fernández, Daniel; Marcos-Jorquera, Diego; Gilart-Iglesias, Virgilio

2018-06-14

Nowadays, in many countries, stress is becoming a problem that increasingly affects the health of people. Suffering stress continuously can lead to serious behavioral disorders such as anxiety or depression. Every person, in his daily routine, can face many factors which can contribute to increase his stress level. This paper describes a flexible and distributed model to monitor environmental variables associated with stress, which provides adaptability to any environment in an agile way. This model was designed to transform stress environmental variables in value added information (key stress indicator) and to provide it to external systems, in both proactive and reactive mode. Thus, this value-added information will assist organizations and users in a personalized way helping in the detection and prevention of acute stress cases. Our proposed model is supported by an architecture that achieves the features above mentioned, in addition to interoperability, robustness, scalability, autonomy, efficient, low cost and consumption, and information availability in real time. Finally, a prototype of the system was implemented, allowing the validation of the proposal in different environments at the University of Alicante.

Systematic review and consensus guidelines for environmental sampling of Burkholderia pseudomallei.

PubMed

Limmathurotsakul, Direk; Dance, David A B; Wuthiekanun, Vanaporn; Kaestli, Mirjam; Mayo, Mark; Warner, Jeffrey; Wagner, David M; Tuanyok, Apichai; Wertheim, Heiman; Yoke Cheng, Tan; Mukhopadhyay, Chiranjay; Puthucheary, Savithiri; Day, Nicholas P J; Steinmetz, Ivo; Currie, Bart J; Peacock, Sharon J

2013-01-01

Burkholderia pseudomallei, a Tier 1 Select Agent and the cause of melioidosis, is a Gram-negative bacillus present in the environment in many tropical countries. Defining the global pattern of B. pseudomallei distribution underpins efforts to prevent infection, and is dependent upon robust environmental sampling methodology. Our objective was to review the literature on the detection of environmental B. pseudomallei, update the risk map for melioidosis, and propose international consensus guidelines for soil sampling. An international working party (Detection of Environmental Burkholderia pseudomallei Working Party (DEBWorP)) was formed during the VIth World Melioidosis Congress in 2010. PubMed (January 1912 to December 2011) was searched using the following MeSH terms: pseudomallei or melioidosis. Bibliographies were hand-searched for secondary references. The reported geographical distribution of B. pseudomallei in the environment was mapped and categorized as definite, probable, or possible. The methodology used for detecting environmental B. pseudomallei was extracted and collated. We found that global coverage was patchy, with a lack of studies in many areas where melioidosis is suspected to occur. The sampling strategies and bacterial identification methods used were highly variable, and not all were robust. We developed consensus guidelines with the goals of reducing the probability of false-negative results, and the provision of affordable and 'low-tech' methodology that is applicable in both developed and developing countries. The proposed consensus guidelines provide the basis for the development of an accurate and comprehensive global map of environmental B. pseudomallei.

MIPs as Tools in Environmental Biotechnology.

PubMed

Mattiasson, Bo

2015-01-01

Molecular imprints are potentially fantastic constructions. They are selective, robust, and nonbiodegradable if produced from stable polymers. A range of different applications has been presented, everything from separation of enantiomers, via adsorbents for sample preparation before analysis to applications in wastewater treatment. This chapter deals with molecularly imprinted polymers (MIPs) as tools in environmental biotechnology, a field that has the potential to become very important in the future.

The robust corrective action priority-an improved approach for selecting competing corrective actions in FMEA based on principle of robust design

NASA Astrophysics Data System (ADS)

Sutrisno, Agung; Gunawan, Indra; Vanany, Iwan

2017-11-01

In spite of being integral part in risk - based quality improvement effort, studies improving quality of selection of corrective action priority using FMEA technique are still limited in literature. If any, none is considering robustness and risk in selecting competing improvement initiatives. This study proposed a theoretical model to select risk - based competing corrective action by considering robustness and risk of competing corrective actions. We incorporated the principle of robust design in counting the preference score among corrective action candidates. Along with considering cost and benefit of competing corrective actions, we also incorporate the risk and robustness of corrective actions. An example is provided to represent the applicability of the proposed model.

Combined use of SAR and optical data for environmental assessments around refugee camps in semiarid landscapes

NASA Astrophysics Data System (ADS)

Braun, A.; Hochschild, V.

2015-04-01

Over 15 million people were officially considered as refugees in the year 2012 and another 28 million as internally displaced people (IDPs). Natural disasters, climatic and environmental changes, violent regional conflicts and population growth force people to migrate in all parts of this world. This trend is likely to continue in the near future, as political instabilities increase and land degradation progresses. EO4HumEn aims at developing operational services to support humanitarian operations during crisis situations by means of dedicated geo-spatial information products derived from Earth observation and GIS data. The goal is to develop robust, automated methods of image analysis routines for population estimation, identification of potential groundwater extraction sites and monitoring the environmental impact of refugee/IDP camps. This study investigates the combination of satellite SAR data with optical sensors and elevation information for the assessment of the environmental conditions around refugee camps. In order to estimate their impact on land degradation, land cover classifications are required which target dynamic landscapes. We performed a land use / land cover classification based on a random forest algorithm and 39 input prediction rasters based on Landsat 8 data and additional layers generated from radar texture and elevation information. The overall accuracy was 92.9 %, while optical data had the highest impact on the final classification. By analysing all combinations of the three input datasets we additionally estimated their impact on single classification outcomes and land cover classes.

Advanced Computational Framework for Environmental Management ZEM, Version 1.x

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

Vesselinov, Velimir V.; O'Malley, Daniel; Pandey, Sachin

2016-11-04

Typically environmental management problems require analysis of large and complex data sets originating from concurrent data streams with different data collection frequencies and pedigree. These big data sets require on-the-fly integration into a series of models with different complexity for various types of model analyses where the data are applied as soft and hard model constraints. This is needed to provide fast iterative model analyses based on the latest available data to guide decision-making. Furthermore, the data and model are associated with uncertainties. The uncertainties are probabilistic (e.g. measurement errors) and non-probabilistic (unknowns, e.g. alternative conceptual models characterizing site conditions).more » To address all of these issues, we have developed an integrated framework for real-time data and model analyses for environmental decision-making called ZEM. The framework allows for seamless and on-the-fly integration of data and modeling results for robust and scientifically-defensible decision-making applying advanced decision analyses tools such as Bayesian- Information-Gap Decision Theory (BIG-DT). The framework also includes advanced methods for optimization that are capable of dealing with a large number of unknown model parameters, and surrogate (reduced order) modeling capabilities based on support vector regression techniques. The framework is coded in Julia, a state-of-the-art high-performance programing language (http://julialang.org). The ZEM framework is open-source and can be applied to any environmental management site. The framework will be open-source and released under GPL V3 license.« less

Exploration of the Hypothalamic-Pituitary-Adrenal Axis to Improve Animal Welfare by Means of Genetic Selection: Lessons from the South African Merino

PubMed Central

Hough, Denise; Swart, Pieter; Cloete, Schalk

2013-01-01

Simple Summary Breeding sheep that are robust and easily managed may be beneficial for both animal welfare and production. Sheep that are more readily able to adapt to stressful situations and a wide variety of environmental conditions are likely to have more resources available for a higher expression of their production potential. This review explores the utilization of one of the stress response pathways, namely the hypothalamic-pituitary-adrenal axis, to locate potential sites where genetic markers might be identified that contribute to sheep robustness. A South African Merino breeding programme is used to demonstrate the potential benefits of this approach. Abstract It is a difficult task to improve animal production by means of genetic selection, if the environment does not allow full expression of the animal’s genetic potential. This concept may well be the future for animal welfare, because it highlights the need to incorporate traits related to production and robustness, simultaneously, to reach sustainable breeding goals. This review explores the identification of potential genetic markers for robustness within the hypothalamic-pituitary-adrenal axis (HPAA), since this axis plays a vital role in the stress response. If genetic selection for superior HPAA responses to stress is possible, then it ought to be possible to breed robust and easily managed genotypes that might be able to adapt to a wide range of environmental conditions whilst expressing a high production potential. This approach is explored in this review by means of lessons learnt from research on Merino sheep, which were divergently selected for their multiple rearing ability. These two selection lines have shown marked differences in reproduction, production and welfare, which makes this breeding programme ideal to investigate potential genetic markers of robustness. The HPAA function is explored in detail to elucidate where such genetic markers are likely to be found. PMID:26487412

Robust Methods for Moderation Analysis with a Two-Level Regression Model.

PubMed

Yang, Miao; Yuan, Ke-Hai

2016-01-01

Moderation analysis has many applications in social sciences. Most widely used estimation methods for moderation analysis assume that errors are normally distributed and homoscedastic. When these assumptions are not met, the results from a classical moderation analysis can be misleading. For more reliable moderation analysis, this article proposes two robust methods with a two-level regression model when the predictors do not contain measurement error. One method is based on maximum likelihood with Student's t distribution and the other is based on M-estimators with Huber-type weights. An algorithm for obtaining the robust estimators is developed. Consistent estimates of standard errors of the robust estimators are provided. The robust approaches are compared against normal-distribution-based maximum likelihood (NML) with respect to power and accuracy of parameter estimates through a simulation study. Results show that the robust approaches outperform NML under various distributional conditions. Application of the robust methods is illustrated through a real data example. An R program is developed and documented to facilitate the application of the robust methods.

MicroRNA function in Drosophila melanogaster.

PubMed

Carthew, Richard W; Agbu, Pamela; Giri, Ritika

2017-05-01

Over the last decade, microRNAs have emerged as critical regulators in the expression and function of animal genomes. This review article discusses the relationship between microRNA-mediated regulation and the biology of the fruit fly Drosophila melanogaster. We focus on the roles that microRNAs play in tissue growth, germ cell development, hormone action, and the development and activity of the central nervous system. We also discuss the ways in which microRNAs affect robustness. Many gene regulatory networks are robust; they are relatively insensitive to the precise values of reaction constants and concentrations of molecules acting within the networks. MicroRNAs involved in robustness appear to be nonessential under uniform conditions used in conventional laboratory experiments. However, the robust functions of microRNAs can be revealed when environmental or genetic variation otherwise has an impact on developmental outcomes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Guaranteeing robustness of structural condition monitoring to environmental variability

NASA Astrophysics Data System (ADS)

Van Buren, Kendra; Reilly, Jack; Neal, Kyle; Edwards, Harry; Hemez, François

2017-01-01

Advances in sensor deployment and computational modeling have allowed significant strides to be recently made in the field of Structural Health Monitoring (SHM). One widely used SHM strategy is to perform a vibration analysis where a model of the structure's pristine (undamaged) condition is compared with vibration response data collected from the physical structure. Discrepancies between model predictions and monitoring data can be interpreted as structural damage. Unfortunately, multiple sources of uncertainty must also be considered in the analysis, including environmental variability, unknown model functional forms, and unknown values of model parameters. Not accounting for these sources of uncertainty can lead to false-positives or false-negatives in the structural condition assessment. To manage the uncertainty, we propose a robust SHM methodology that combines three technologies. A time series algorithm is trained using "baseline" data to predict the vibration response, compare predictions to actual measurements collected on a potentially damaged structure, and calculate a user-defined damage indicator. The second technology handles the uncertainty present in the problem. An analysis of robustness is performed to propagate this uncertainty through the time series algorithm and obtain the corresponding bounds of variation of the damage indicator. The uncertainty description and robustness analysis are both inspired by the theory of info-gap decision-making. Lastly, an appropriate "size" of the uncertainty space is determined through physical experiments performed in laboratory conditions. Our hypothesis is that examining how the uncertainty space changes throughout time might lead to superior diagnostics of structural damage as compared to only monitoring the damage indicator. This methodology is applied to a portal frame structure to assess if the strategy holds promise for robust SHM. (Publication approved for unlimited, public release on October-28-2015, LA-UR-15-28442, unclassified.)

A Novel Multi-Sensor Environmental Perception Method Using Low-Rank Representation and a Particle Filter for Vehicle Reversing Safety

PubMed Central

Zhang, Zutao; Li, Yanjun; Wang, Fubing; Meng, Guanjun; Salman, Waleed; Saleem, Layth; Zhang, Xiaoliang; Wang, Chunbai; Hu, Guangdi; Liu, Yugang

2016-01-01

Environmental perception and information processing are two key steps of active safety for vehicle reversing. Single-sensor environmental perception cannot meet the need for vehicle reversing safety due to its low reliability. In this paper, we present a novel multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. The proposed system consists of four main steps, namely multi-sensor environmental perception, information fusion, target recognition and tracking using low-rank representation and a particle filter, and vehicle reversing speed control modules. First of all, the multi-sensor environmental perception module, based on a binocular-camera system and ultrasonic range finders, obtains the distance data for obstacles behind the vehicle when the vehicle is reversing. Secondly, the information fusion algorithm using an adaptive Kalman filter is used to process the data obtained with the multi-sensor environmental perception module, which greatly improves the robustness of the sensors. Then the framework of a particle filter and low-rank representation is used to track the main obstacles. The low-rank representation is used to optimize an objective particle template that has the smallest L-1 norm. Finally, the electronic throttle opening and automatic braking is under control of the proposed vehicle reversing control strategy prior to any potential collisions, making the reversing control safer and more reliable. The final system simulation and practical testing results demonstrate the validity of the proposed multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. PMID:27294931

A Novel Multi-Sensor Environmental Perception Method Using Low-Rank Representation and a Particle Filter for Vehicle Reversing Safety.

PubMed

Zhang, Zutao; Li, Yanjun; Wang, Fubing; Meng, Guanjun; Salman, Waleed; Saleem, Layth; Zhang, Xiaoliang; Wang, Chunbai; Hu, Guangdi; Liu, Yugang

2016-06-09

Environmental perception and information processing are two key steps of active safety for vehicle reversing. Single-sensor environmental perception cannot meet the need for vehicle reversing safety due to its low reliability. In this paper, we present a novel multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. The proposed system consists of four main steps, namely multi-sensor environmental perception, information fusion, target recognition and tracking using low-rank representation and a particle filter, and vehicle reversing speed control modules. First of all, the multi-sensor environmental perception module, based on a binocular-camera system and ultrasonic range finders, obtains the distance data for obstacles behind the vehicle when the vehicle is reversing. Secondly, the information fusion algorithm using an adaptive Kalman filter is used to process the data obtained with the multi-sensor environmental perception module, which greatly improves the robustness of the sensors. Then the framework of a particle filter and low-rank representation is used to track the main obstacles. The low-rank representation is used to optimize an objective particle template that has the smallest L-1 norm. Finally, the electronic throttle opening and automatic braking is under control of the proposed vehicle reversing control strategy prior to any potential collisions, making the reversing control safer and more reliable. The final system simulation and practical testing results demonstrate the validity of the proposed multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety.

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

Cox, S.; Katz, J.; Wurtenberger, L.

Low emission development strategies (LEDS) articulate economy-wide policies and implementation plans designed to enable a country to meet its long-term development objectives while reducing greenhouse gas emissions. A development impact assessment tool was developed to inform an analytically robust and transparent prioritization of LEDS actions based on their economic, social, and environmental impacts. The graphical tool helps policymakers communicate the development impacts of LEDS options and identify actions that help meet both emissions reduction and development goals. This paper summarizes the adaptation and piloting of the tool in Kenya and Montenegro. The paper highlights strengths of the tool and discussesmore » key needs for improving it.« less

Development of Temperature Sensitive Paints for the Detection of Small Temperature Differences

NASA Technical Reports Server (NTRS)

Oglesby, Donald M.; Upchurch, Billy T.; Sealey, Bradley S.; Leighty, Bradley D.; Burkett, Cecil G., Jr.; Jalali, Amir

1997-01-01

Temperature sensitive paints (TSP s) have recently been used to detect small temperature differences on aerodynamic model surfaces. These types of applications impose stringent performance requirements on a paint system. The TSP s must operate over a broad temperature range, must be physically robust (cannot chip or peel), must be polishable to at least the smoothness of the model surface, and must have sufficient sensitivity to detect small temperature differences. TSP coatings based on the use of metal complexes in polymer binders were developed at NASA Langley Research Center which meet most of the requirements for detection of small temperature differences under severe environmental conditions.

Further Investigation Into the Use of Laser Surface Preparation of Ti-6Al-4V Alloy for Adhesive Bonding

NASA Technical Reports Server (NTRS)

Palmieri, Frank L.; Crow, Allison; Zetterberg, Anna; Hopkins, John; Wohl, Christopher J.; Connell, John W.; Belcher, Tony; Blohowiak, Kay Y.

2014-01-01

Adhesive bonding offers many advantages over mechanical fastening, but requires robust materials and processing methodologies before it can be incorporated in primary structures for aerospace applications. Surface preparation is widely recognized as one of the key steps to producing robust and predictable bonds. This report documents an ongoing investigation of a surface preparation technique based on Nd:YAG laser ablation as a replacement for the chemical etch and/or abrasive processes currently applied to Ti-6Al-4V alloys. Laser ablation imparts both topographical and chemical changes to a surface that can lead to increased bond durability. A laser based process provides an alternative to chemical-immersion, manual abrasion, and grit blast process steps which are expensive, hazardous, environmentally unfriendly, and less precise. In addition, laser ablation is amenable to process automation, which can improve reproducibility to meet quality standards for surface preparation. An update on work involving adhesive property testing, surface characterization, surface stability, and the effect of laser surface treatment on fatigue behavior is presented. Based on the tests conducted, laser surface treatment is a viable replacement for the immersion chemical surface treatment processes. Testing also showed that the fatigue behavior of the Ti-6Al-4V alloy is comparable for surfaces treated with either laser ablation or chemical surface treatment.

Robust estimates of environmental effects on population vital rates: an integrated capture–recapture model of seasonal brook trout growth, survival and movement in a stream network

USGS Publications Warehouse

Letcher, Benjamin H.; Schueller, Paul; Bassar, Ronald D.; Nislow, Keith H.; Coombs, Jason A.; Sakrejda, Krzysztof; Morrissey, Michael; Sigourney, Douglas B.; Whiteley, Andrew R.; O'Donnell, Matthew J.; Dubreuil, Todd L.

2015-01-01

Modelling the effects of environmental change on populations is a key challenge for ecologists, particularly as the pace of change increases. Currently, modelling efforts are limited by difficulties in establishing robust relationships between environmental drivers and population responses.We developed an integrated capture–recapture state-space model to estimate the effects of two key environmental drivers (stream flow and temperature) on demographic rates (body growth, movement and survival) using a long-term (11 years), high-resolution (individually tagged, sampled seasonally) data set of brook trout (Salvelinus fontinalis) from four sites in a stream network. Our integrated model provides an effective context within which to estimate environmental driver effects because it takes full advantage of data by estimating (latent) state values for missing observations, because it propagates uncertainty among model components and because it accounts for the major demographic rates and interactions that contribute to annual survival.We found that stream flow and temperature had strong effects on brook trout demography. Some effects, such as reduction in survival associated with low stream flow and high temperature during the summer season, were consistent across sites and age classes, suggesting that they may serve as robust indicators of vulnerability to environmental change. Other survival effects varied across ages, sites and seasons, indicating that flow and temperature may not be the primary drivers of survival in those cases. Flow and temperature also affected body growth rates; these responses were consistent across sites but differed dramatically between age classes and seasons. Finally, we found that tributary and mainstem sites responded differently to variation in flow and temperature.Annual survival (combination of survival and body growth across seasons) was insensitive to body growth and was most sensitive to flow (positive) and temperature (negative) in the summer and fall.These observations, combined with our ability to estimate the occurrence, magnitude and direction of fish movement between these habitat types, indicated that heterogeneity in response may provide a mechanism providing potential resilience to environmental change. Given that the challenges we faced in our study are likely to be common to many intensive data sets, the integrated modelling approach could be generally applicable and useful.

Robust estimates of environmental effects on population vital rates: an integrated capture-recapture model of seasonal brook trout growth, survival and movement in a stream network.

PubMed

Letcher, Benjamin H; Schueller, Paul; Bassar, Ronald D; Nislow, Keith H; Coombs, Jason A; Sakrejda, Krzysztof; Morrissey, Michael; Sigourney, Douglas B; Whiteley, Andrew R; O'Donnell, Matthew J; Dubreuil, Todd L

2015-03-01

Modelling the effects of environmental change on populations is a key challenge for ecologists, particularly as the pace of change increases. Currently, modelling efforts are limited by difficulties in establishing robust relationships between environmental drivers and population responses. We developed an integrated capture-recapture state-space model to estimate the effects of two key environmental drivers (stream flow and temperature) on demographic rates (body growth, movement and survival) using a long-term (11 years), high-resolution (individually tagged, sampled seasonally) data set of brook trout (Salvelinus fontinalis) from four sites in a stream network. Our integrated model provides an effective context within which to estimate environmental driver effects because it takes full advantage of data by estimating (latent) state values for missing observations, because it propagates uncertainty among model components and because it accounts for the major demographic rates and interactions that contribute to annual survival. We found that stream flow and temperature had strong effects on brook trout demography. Some effects, such as reduction in survival associated with low stream flow and high temperature during the summer season, were consistent across sites and age classes, suggesting that they may serve as robust indicators of vulnerability to environmental change. Other survival effects varied across ages, sites and seasons, indicating that flow and temperature may not be the primary drivers of survival in those cases. Flow and temperature also affected body growth rates; these responses were consistent across sites but differed dramatically between age classes and seasons. Finally, we found that tributary and mainstem sites responded differently to variation in flow and temperature. Annual survival (combination of survival and body growth across seasons) was insensitive to body growth and was most sensitive to flow (positive) and temperature (negative) in the summer and fall. These observations, combined with our ability to estimate the occurrence, magnitude and direction of fish movement between these habitat types, indicated that heterogeneity in response may provide a mechanism providing potential resilience to environmental change. Given that the challenges we faced in our study are likely to be common to many intensive data sets, the integrated modelling approach could be generally applicable and useful. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

Distributed Aviation Concepts and Technologies

NASA Technical Reports Server (NTRS)

Moore, Mark D.

2008-01-01

Aviation has experienced one hundred years of evolution, resulting in the current air transportation system dominated by commercial airliners in a hub and spoke infrastructure. While the first fifty years involved disruptive technologies that required frequent vehicle adaptation, the second fifty years produced a stable evolutionary optimization of decreasing costs with increasing safety. This optimization has resulted in traits favoring a centralized service model with high vehicle productivity and cost efficiency. However, it may also have resulted in a system that is not sufficiently robust to withstand significant system disturbances. Aviation is currently facing rapid change from issues such as environmental damage, terrorism threat, congestion and capacity limitations, and cost of energy. Currently, these issues are leading to a loss of service for weaker spoke markets. These catalysts and a lack of robustness could result in a loss of service for much larger portions of the aviation market. The impact of other competing transportation services may be equally important as casual factors of change. Highway system forecasts indicate a dramatic slow down as congestion reaches a point of non-linearly increasing delay. In the next twenty-five years, there is the potential for aviation to transform itself into a more robust, scalable, adaptive, secure, safe, affordable, convenient, efficient and environmentally friendly system. To achieve these characteristics, the new system will likely be based on a distributed model that enables more direct services. Short range travel is already demonstrating itself to be inefficient with a centralized model, providing opportunities for emergent distributed services through air-taxi models. Technologies from the on-demand revolution in computers and communications are now available as major drivers for aviation on-demand adaptation. Other technologies such as electric propulsion are currently transforming the automobile industry, and will also significantly alter the functionality of future distributed aviation concepts. Many hurdles exist, including technology, regulation, and perception. Aviation has an inherent governmental role not present in other recent on-demand transformations, which may pose a risk of curtailing aviation democratization .

Management applications of discontinuity theory

EPA Science Inventory

1.Human impacts on the environment are multifaceted and can occur across distinct spatiotemporal scales. Ecological responses to environmental change are therefore difficult to predict, and entail large degrees of uncertainty. Such uncertainty requires robust tools for management...

Social-ecological resilience and law

USGS Publications Warehouse

Garmestani, Ahjond S.; Allen, Craig R.

2014-01-01

Environmental law envisions ecological systems as existing in an equilibrium state, reinforcing a rigid legal framework unable to absorb rapid environmental changes and innovations in sustainability. For the past four decades, “resilience theory,” which embraces uncertainty and nonlinear dynamics in complex adaptive systems, has provided a robust, invaluable foundation for sound environmental management. Reforming American law to incorporate this knowledge is the key to sustainability. This volume features top legal and resilience scholars speaking on resilience theory and its legal applications to climate change, biodiversity, national parks, and water law.

Jobs and the environment: An overview

NASA Astrophysics Data System (ADS)

Goodstein, Eban

1996-05-01

This paper provides an overview of economic research on the relationship between environmental protection and employment. The paper addresses, first, the impact of existing regulation on overall employment rates, shutdowns and layoffs, and regulation-induced capital flight from developed countries. Second, the paper provides a framework for evaluating claims that, over the longer run, environmental protection measures will boost overall employment and provide the foundation for a robust, sustainable economy.

Learning consensus in adversarial environments

NASA Astrophysics Data System (ADS)

Vamvoudakis, Kyriakos G.; García Carrillo, Luis R.; Hespanha, João. P.

2013-05-01

This work presents a game theory-based consensus problem for leaderless multi-agent systems in the presence of adversarial inputs that are introducing disturbance to the dynamics. Given the presence of enemy components and the possibility of malicious cyber attacks compromising the security of networked teams, a position agreement must be reached by the networked mobile team based on environmental changes. The problem is addressed under a distributed decision making framework that is robust to possible cyber attacks, which has an advantage over centralized decision making in the sense that a decision maker is not required to access information from all the other decision makers. The proposed framework derives three tuning laws for every agent; one associated with the cost, one associated with the controller, and one with the adversarial input.

A year 2003 conceptual model for the U.S. telecommunications infrastructure.

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

Cox, Roger Gary; Reinert, Rhonda K.

2003-12-01

To model the telecommunications infrastructure and its role and robustness to shocks, we must characterize the business and engineering of telecommunications systems in the year 2003 and beyond. By analogy to environmental systems modeling, we seek to develop a 'conceptual model' for telecommunications. Here, the conceptual model is a list of high-level assumptions consistent with the economic and engineering architectures of telecommunications suppliers and customers, both today and in the near future. We describe the present engineering architectures of the most popular service offerings, and describe the supplier markets in some detail. We also develop a characterization of the customermore » base for telecommunications services and project its likely response to disruptions in service, base-lining such conjectures against observed behaviors during 9/11.« less

A Versatile and Scalable Approach toward Robust Superhydrophobic Porous Materials with Excellent Absorbency and Flame Retardancy

NASA Astrophysics Data System (ADS)

Ruan, Changping; Shen, Mengxia; Ren, Xiaoyan; Ai, Kelong; Lu, Lehui

2016-08-01

The frequent oil spillages and the industrial discharge of organic contaminants have not only created severe environmental and ecological crises, but also cause a risk of fire and explosion. These environmental and safety issues emphasize the urgent need for materials that possess superior sorption capability and less flammability and thus can effectively and safely clean up the floating oils and water-insoluble organic compounds. Here we present the successful hydrophobic modification of the flame retardant melamine sponge with a commercial fluorosilicone, by using a facile one-step solvent-free approach and demonstrate that the resultant superhydrophobic sponge not only exhibits extraordinary absorption efficiency (including high capacity, superior selectivity, good recyclability, and simple recycling routes), but also retains excellent flame retardancy and robust stability. In comparison to conventional methods, which usually utilize massive organic solvents, the present approach does not involve any complicated process or sophisticated equipment nor generates any waste liquids, and thus is a more labor-saving, environment-friendly, energy-efficient and cost-effective strategy for the hydrophobic modification. Taking into account the critical role of hydrophobic porous materials, especially in the field of environmental remediation, the approach presented herein would be highly valuable for environmental remediation and industrial applications.

A Versatile and Scalable Approach toward Robust Superhydrophobic Porous Materials with Excellent Absorbency and Flame Retardancy

PubMed Central

Ruan, Changping; Shen, Mengxia; Ren, Xiaoyan; Ai, Kelong; Lu, Lehui

2016-01-01

The frequent oil spillages and the industrial discharge of organic contaminants have not only created severe environmental and ecological crises, but also cause a risk of fire and explosion. These environmental and safety issues emphasize the urgent need for materials that possess superior sorption capability and less flammability and thus can effectively and safely clean up the floating oils and water-insoluble organic compounds. Here we present the successful hydrophobic modification of the flame retardant melamine sponge with a commercial fluorosilicone, by using a facile one-step solvent-free approach and demonstrate that the resultant superhydrophobic sponge not only exhibits extraordinary absorption efficiency (including high capacity, superior selectivity, good recyclability, and simple recycling routes), but also retains excellent flame retardancy and robust stability. In comparison to conventional methods, which usually utilize massive organic solvents, the present approach does not involve any complicated process or sophisticated equipment nor generates any waste liquids, and thus is a more labor-saving, environment-friendly, energy-efficient and cost-effective strategy for the hydrophobic modification. Taking into account the critical role of hydrophobic porous materials, especially in the field of environmental remediation, the approach presented herein would be highly valuable for environmental remediation and industrial applications. PMID:27501762

Holistic Assessment and Ethical Disputation on a New Trend in Solid Biofuels.

PubMed

Hašková, Simona

2017-04-01

A new trend in the production technology of solid biof uels has appeared. There is a wide consensus that most solid biofuels will be produced according to the new production methods within a few years. Numerous samples were manufactured from agro-residues according to conventional methods as well as new methods. Robust analyses that reviewed the hygienic, environmental, financial and ethical aspects were performed. The hygienic and environmental aspect was assessed by robust chemical and technical analyses. The financial aspect was assessed by energy cost breakdown. The ethical point of view was built on the above stated findings, the survey questionnaire and critical discussion with the literature. It is concluded that the new production methods are significantly favourable from both the hygienic and environmental points of view. Financial indicators do not allow the expressing of any preference. Regarding the ethical aspect, it is concluded that the new methods are beneficial in terms of environmental responsibility. However, it showed that most of the customers that took part in the survey are price oriented and therefore they tend to prefer the cheaper-conventional alternative. In the long term it can be assumed that expansion of the new technology and competition among manufacturers will reduce the costs.

Variable fidelity robust optimization of pulsed laser orbital debris removal under epistemic uncertainty

NASA Astrophysics Data System (ADS)

Hou, Liqiang; Cai, Yuanli; Liu, Jin; Hou, Chongyuan

2016-04-01

A variable fidelity robust optimization method for pulsed laser orbital debris removal (LODR) under uncertainty is proposed. Dempster-shafer theory of evidence (DST), which merges interval-based and probabilistic uncertainty modeling, is used in the robust optimization. The robust optimization method optimizes the performance while at the same time maximizing its belief value. A population based multi-objective optimization (MOO) algorithm based on a steepest descent like strategy with proper orthogonal decomposition (POD) is used to search robust Pareto solutions. Analytical and numerical lifetime predictors are used to evaluate the debris lifetime after the laser pulses. Trust region based fidelity management is designed to reduce the computational cost caused by the expensive model. When the solutions fall into the trust region, the analytical model is used to reduce the computational cost. The proposed robust optimization method is first tested on a set of standard problems and then applied to the removal of Iridium 33 with pulsed lasers. It will be shown that the proposed approach can identify the most robust solutions with minimum lifetime under uncertainty.

Nuclear Magnetic Resonance Spectroscopy-Based Identification of Yeast.

PubMed

Himmelreich, Uwe; Sorrell, Tania C; Daniel, Heide-Marie

2017-01-01

Rapid and robust high-throughput identification of environmental, industrial, or clinical yeast isolates is important whenever relatively large numbers of samples need to be processed in a cost-efficient way. Nuclear magnetic resonance (NMR) spectroscopy generates complex data based on metabolite profiles, chemical composition and possibly on medium consumption, which can not only be used for the assessment of metabolic pathways but also for accurate identification of yeast down to the subspecies level. Initial results on NMR based yeast identification where comparable with conventional and DNA-based identification. Potential advantages of NMR spectroscopy in mycological laboratories include not only accurate identification but also the potential of automated sample delivery, automated analysis using computer-based methods, rapid turnaround time, high throughput, and low running costs.We describe here the sample preparation, data acquisition and analysis for NMR-based yeast identification. In addition, a roadmap for the development of classification strategies is given that will result in the acquisition of a database and analysis algorithms for yeast identification in different environments.

Research on Robustness of Tree-based P2P Streaming

NASA Astrophysics Data System (ADS)

Chu, Chen; Yan, Jinyao; Ding, Kuangzheng; Wang, Xi

Research on P2P streaming media is a hot topic in the area of Internet technology. It has emerged as a promising technique. This new paradigm brings a number of unique advantages such as scalability, resilience and also effectiveness in coping with dynamics and heterogeneity. However, There are also many problems in P2P streaming media systems using traditional tree-based topology such as the bandwidth limits between parents and child nodes; node's joining or leaving has a great effect on robustness of tree-based topology. This paper will introduce a method of measuring the robustness of tree-based topology: using network measurement, we observe and record the bandwidth between all the nodes, analyses the correlation between all the sibling flows, measure the robustness of tree-based topology. And the result shows that in the Tree-based topology, the different links which have similar routing paths would share the bandwidth bottleneck, reduce the robustness of the Tree-based topology.

Robust model predictive control for constrained continuous-time nonlinear systems

NASA Astrophysics Data System (ADS)

Sun, Tairen; Pan, Yongping; Zhang, Jun; Yu, Haoyong

2018-02-01

In this paper, a robust model predictive control (MPC) is designed for a class of constrained continuous-time nonlinear systems with bounded additive disturbances. The robust MPC consists of a nonlinear feedback control and a continuous-time model-based dual-mode MPC. The nonlinear feedback control guarantees the actual trajectory being contained in a tube centred at the nominal trajectory. The dual-mode MPC is designed to ensure asymptotic convergence of the nominal trajectory to zero. This paper extends current results on discrete-time model-based tube MPC and linear system model-based tube MPC to continuous-time nonlinear model-based tube MPC. The feasibility and robustness of the proposed robust MPC have been demonstrated by theoretical analysis and applications to a cart-damper springer system and a one-link robot manipulator.

Measuring spatial and temporal Ca2+ signals in Arabidopsis plants.

PubMed

Zhu, Xiaohong; Taylor, Aaron; Zhang, Shenyu; Zhang, Dayong; Feng, Ying; Liang, Gaimei; Zhu, Jian-Kang

2014-09-02

Developmental and environmental cues induce Ca(2+) fluctuations in plant cells. Stimulus-specific spatial-temporal Ca(2+) patterns are sensed by cellular Ca(2+) binding proteins that initiate Ca(2+) signaling cascades. However, we still know little about how stimulus specific Ca(2+) signals are generated. The specificity of a Ca(2+) signal may be attributed to the sophisticated regulation of the activities of Ca(2+) channels and/or transporters in response to a given stimulus. To identify these cellular components and understand their functions, it is crucial to use systems that allow a sensitive and robust recording of Ca(2+) signals at both the tissue and cellular levels. Genetically encoded Ca(2+) indicators that are targeted to different cellular compartments have provided a platform for live cell confocal imaging of cellular Ca(2+) signals. Here we describe instructions for the use of two Ca(2+) detection systems: aequorin based FAS (film adhesive seedlings) luminescence Ca(2+) imaging and case12 based live cell confocal fluorescence Ca(2+) imaging. Luminescence imaging using the FAS system provides a simple, robust and sensitive detection of spatial and temporal Ca(2+) signals at the tissue level, while live cell confocal imaging using Case12 provides simultaneous detection of cytosolic and nuclear Ca(2+) signals at a high resolution.

Opening a band gap without breaking lattice symmetry: a new route toward robust graphene-based nanoelectronics.

PubMed

Kou, Liangzhi; Hu, Feiming; Yan, Binghai; Frauenheim, Thomas; Chen, Changfeng

2014-07-07

Developing graphene-based nanoelectronics hinges on opening a band gap in the electronic structure of graphene, which is commonly achieved by breaking the inversion symmetry of the graphene lattice via an electric field (gate bias) or asymmetric doping of graphene layers. Here we introduce a new design strategy that places a bilayer graphene sheet sandwiched between two cladding layers of materials that possess strong spin-orbit coupling (e.g., Bi2Te3). Our ab initio and tight-binding calculations show that a proximity enhanced spin-orbit coupling effect opens a large (44 meV) band gap in bilayer graphene without breaking its lattice symmetry, and the band gap can be effectively tuned by an interlayer stacking pattern and significantly enhanced by interlayer compression. The feasibility of this quantum-well structure is demonstrated by recent experimental realization of high-quality heterojunctions between graphene and Bi2Te3, and this design also conforms to existing fabrication techniques in the semiconductor industry. The proposed quantum-well structure is expected to be especially robust since it does not require an external power supply to open and maintain a band gap, and the cladding layers provide protection against environmental degradation of the graphene layer in its device applications.

Quantitative proteomics and network analysis of SSA1 and SSB1 deletion mutants reveals robustness of chaperone HSP70 network in Saccharomyces cerevisiae.

PubMed

Jarnuczak, Andrew F; Eyers, Claire E; Schwartz, Jean-Marc; Grant, Christopher M; Hubbard, Simon J

2015-09-01

Molecular chaperones play an important role in protein homeostasis and the cellular response to stress. In particular, the HSP70 chaperones in yeast mediate a large volume of protein folding through transient associations with their substrates. This chaperone interaction network can be disturbed by various perturbations, such as environmental stress or a gene deletion. Here, we consider deletions of two major chaperone proteins, SSA1 and SSB1, from the chaperone network in Sacchromyces cerevisiae. We employ a SILAC-based approach to examine changes in global and local protein abundance and rationalise our results via network analysis and graph theoretical approaches. Although the deletions result in an overall increase in intracellular protein content, correlated with an increase in cell size, this is not matched by substantial changes in individual protein concentrations. Despite the phenotypic robustness to deletion of these major hub proteins, it cannot be simply explained by the presence of paralogues. Instead, network analysis and a theoretical consideration of folding workload suggest that the robustness to perturbation is a product of the overall network structure. This highlights how quantitative proteomics and systems modelling can be used to rationalise emergent network properties, and how the HSP70 system can accommodate the loss of major hubs. © 2015 The Authors. PROTEOMICS published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

A kriging metamodel-assisted robust optimization method based on a reverse model

NASA Astrophysics Data System (ADS)

Zhou, Hui; Zhou, Qi; Liu, Congwei; Zhou, Taotao

2018-02-01

The goal of robust optimization methods is to obtain a solution that is both optimum and relatively insensitive to uncertainty factors. Most existing robust optimization approaches use outer-inner nested optimization structures where a large amount of computational effort is required because the robustness of each candidate solution delivered from the outer level should be evaluated in the inner level. In this article, a kriging metamodel-assisted robust optimization method based on a reverse model (K-RMRO) is first proposed, in which the nested optimization structure is reduced into a single-loop optimization structure to ease the computational burden. Ignoring the interpolation uncertainties from kriging, K-RMRO may yield non-robust optima. Hence, an improved kriging-assisted robust optimization method based on a reverse model (IK-RMRO) is presented to take the interpolation uncertainty of kriging metamodel into consideration. In IK-RMRO, an objective switching criterion is introduced to determine whether the inner level robust optimization or the kriging metamodel replacement should be used to evaluate the robustness of design alternatives. The proposed criterion is developed according to whether or not the robust status of the individual can be changed because of the interpolation uncertainties from the kriging metamodel. Numerical and engineering cases are used to demonstrate the applicability and efficiency of the proposed approach.

Performance Testing of Best Management Practices

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) lacks robust data documenting the performance of best Management practices (BMPs) regarding stormwater management, and a clear understanding of the performance changes associated with conditions. By generating these data, The Nation...

Evolution of robustness to damage in artificial 3-dimensional development.

PubMed

Joachimczak, Michał; Wróbel, Borys

2012-09-01

GReaNs is an Artificial Life platform we have built to investigate the general principles that guide evolution of multicellular development and evolution of artificial gene regulatory networks. The embryos develop in GReaNs in a continuous 3-dimensional (3D) space with simple physics. The developmental trajectories are indirectly encoded in linear genomes. The genomes are not limited in size and determine the topology of gene regulatory networks that are not limited in the number of nodes. The expression of the genes is continuous and can be modified by adding environmental noise. In this paper we evolved development of structures with a specific shape (an ellipsoid) and asymmetrical pattering (a 3D pattern inspired by the French flag problem), and investigated emergence of the robustness to damage in development and the emergence of the robustness to noise. Our results indicate that both types of robustness are related, and that including noise during evolution promotes higher robustness to damage. Interestingly, we have observed that some evolved gene regulatory networks rely on noise for proper behaviour. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Uncertainty in the response of terrestrial carbon sink to environmental drivers undermines carbon-climate feedback predictions

DOE PAGES

Huntzinger, D. N.; Michalak, A. M.; Schwalm, C.; ...

2017-07-06

Terrestrial ecosystems play a vital role in regulating the accumulation of carbon (C) in the atmosphere. Understanding the factors controlling land C uptake is critical for reducing uncertainties in projections of future climate. The relative importance of changing climate, rising atmospheric CO 2, and other factors, however, remains unclear despite decades of research. Here, we use an ensemble of land models to show that models disagree on the primary driver of cumulative C uptake for 85% of vegetated land area. Disagreement is largest in model sensitivity to rising atmospheric CO 2 which shows almost twice the variability in cumulative landmore » uptake since 1901 (1 s.d. of 212.8 PgC vs. 138.5 PgC, respectively). We find that variability in CO 2 and temperature sensitivity is attributable, in part, to their compensatory effects on C uptake, whereby comparable estimates of C uptake can arise by invoking different sensitivities to key environmental conditions. Conversely, divergent estimates of C uptake can occur despite being based on the same environmental sensitivities. Together, these findings imply an important limitation to the predictability of C cycling and climate under unprecedented environmental conditions. We suggest that the carbon modeling community prioritize a probabilistic multi-model approach to generate more robust C cycle projections.« less

Uncertainty in the response of terrestrial carbon sink to environmental drivers undermines carbon-climate feedback predictions

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

Huntzinger, D. N.; Michalak, A. M.; Schwalm, C.

2017-07-06

Terrestrial ecosystems play a vital role in regulating the accumulation of carbon (C) in the atmosphere. Understanding the factors controlling land C uptake is critical for reducing uncertainties in projections of future climate. The relative importance of changing climate, rising atmospheric CO2, and other factors, however, remains unclear despite decades of research. Here, we use an ensemble of land models to show that models disagree on the primary driver of cumulative C uptake for 85% of vegetated land area. Disagreement is largest in model sensitivity to rising atmospheric CO2 which shows almost twice the variability in cumulative land uptake sincemore » 1901 (1 s.d. of 212.8 PgC vs. 138.5 PgC, respectively). We find that variability in CO2 and temperature sensitivity is attributable, in part, to their compensatory effects on C uptake, whereby comparable estimates of C uptake can arise by invoking different sensitivities to key environmental conditions. Conversely, divergent estimates of C uptake can occur despite being based on the same environmental sensitivities. Together, these findings imply an important limitation to the predictability of C cycling and climate under unprecedented environmental conditions. We suggest that the carbon modeling community prioritize a probabilistic multi-model approach to generate more robust C cycle projections.« less

Uncertainty in the response of terrestrial carbon sink to environmental drivers undermines carbon-climate feedback predictions

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

Huntzinger, D. N.; Michalak, A. M.; Schwalm, C.

Terrestrial ecosystems play a vital role in regulating the accumulation of carbon (C) in the atmosphere. Understanding the factors controlling land C uptake is critical for reducing uncertainties in projections of future climate. The relative importance of changing climate, rising atmospheric CO 2, and other factors, however, remains unclear despite decades of research. Here, we use an ensemble of land models to show that models disagree on the primary driver of cumulative C uptake for 85% of vegetated land area. Disagreement is largest in model sensitivity to rising atmospheric CO 2 which shows almost twice the variability in cumulative landmore » uptake since 1901 (1 s.d. of 212.8 PgC vs. 138.5 PgC, respectively). We find that variability in CO 2 and temperature sensitivity is attributable, in part, to their compensatory effects on C uptake, whereby comparable estimates of C uptake can arise by invoking different sensitivities to key environmental conditions. Conversely, divergent estimates of C uptake can occur despite being based on the same environmental sensitivities. Together, these findings imply an important limitation to the predictability of C cycling and climate under unprecedented environmental conditions. We suggest that the carbon modeling community prioritize a probabilistic multi-model approach to generate more robust C cycle projections.« less

Evaluating environmental impacts of alternative construction waste management approaches using supply-chain-linked life-cycle analysis.

PubMed

Kucukvar, Murat; Egilmez, Gokhan; Tatari, Omer

2014-06-01

Waste management in construction is critical for the sustainable treatment of building-related construction and demolition (C&D) waste materials, and recycling of these wastes has been considered as one of the best strategies in minimization of C&D debris. However, recycling of C&D materials may not always be a feasible strategy for every waste type and therefore recycling and other waste treatment strategies should be supported by robust decision-making models. With the aim of assessing the net carbon, energy, and water footprints of C&D recycling and other waste management alternatives, a comprehensive economic input-output-based hybrid life-cycle assessment model is developed by tracing all of the economy-wide supply-chain impacts of three waste management strategies: recycling, landfilling, and incineration. Analysis results showed that only the recycling of construction materials provided positive environmental footprint savings in terms of carbon, energy, and water footprints. Incineration is a better option as a secondary strategy after recycling for water and energy footprint categories, whereas landfilling is found to be as slightly better strategy when carbon footprint is considered as the main focus of comparison. In terms of construction materials' environmental footprint, nonferrous metals are found to have a significant environmental footprint reduction potential if recycled. © The Author(s) 2014.

Multidisciplinary life cycle metrics and tools for green buildings.

PubMed

Helgeson, Jennifer F; Lippiatt, Barbara C

2009-07-01

Building sector stakeholders need compelling metrics, tools, data, and case studies to support major investments in sustainable technologies. Proponents of green building widely claim that buildings integrating sustainable technologies are cost effective, but often these claims are based on incomplete, anecdotal evidence that is difficult to reproduce and defend. The claims suffer from 2 main weaknesses: 1) buildings on which claims are based are not necessarily "green" in a science-based, life cycle assessment (LCA) sense and 2) measures of cost effectiveness often are not based on standard methods for measuring economic worth. Yet, the building industry demands compelling metrics to justify sustainable building designs. The problem is hard to solve because, until now, neither methods nor robust data supporting defensible business cases were available. The US National Institute of Standards and Technology (NIST) Building and Fire Research Laboratory is beginning to address these needs by developing metrics and tools for assessing the life cycle economic and environmental performance of buildings. Economic performance is measured with the use of standard life cycle costing methods. Environmental performance is measured by LCA methods that assess the "carbon footprint" of buildings, as well as 11 other sustainability metrics, including fossil fuel depletion, smog formation, water use, habitat alteration, indoor air quality, and effects on human health. Carbon efficiency ratios and other eco-efficiency metrics are established to yield science-based measures of the relative worth, or "business cases," for green buildings. Here, the approach is illustrated through a realistic building case study focused on different heating, ventilation, air conditioning technology energy efficiency. Additionally, the evolution of the Building for Environmental and Economic Sustainability multidisciplinary team and future plans in this area are described.

Life-cycle and cost of goods assessment of fed-batch and perfusion-based manufacturing processes for mAbs.

PubMed

Bunnak, Phumthep; Allmendinger, Richard; Ramasamy, Sri V; Lettieri, Paola; Titchener-Hooker, Nigel J

2016-09-01

Life-cycle assessment (LCA) is an environmental assessment tool that quantifies the environmental impact associated with a product or a process (e.g., water consumption, energy requirements, and solid waste generation). While LCA is a standard approach in many commercial industries, its application has not been exploited widely in the bioprocessing sector. To contribute toward the design of more cost-efficient, robust and environmentally-friendly manufacturing process for monoclonal antibodies (mAbs), a framework consisting of an LCA and economic analysis combined with a sensitivity analysis of manufacturing process parameters and a production scale-up study is presented. The efficiency of the framework is demonstrated using a comparative study of the two most commonly used upstream configurations for mAb manufacture, namely fed-batch (FB) and perfusion-based processes. Results obtained by the framework are presented using a range of visualization tools, and indicate that a standard perfusion process (with a pooling duration of 4 days) has similar cost of goods than a FB process but a larger environmental footprint because it consumed 35% more water, demanded 17% more energy, and emitted 17% more CO 2 than the FB process. Water consumption was the most important impact category, especially when scaling-up the processes, as energy was required to produce process water and water-for-injection, while CO 2 was emitted from energy generation. The sensitivity analysis revealed that the perfusion process can be made more environmentally-friendly than the FB process if the pooling duration is extended to 8 days. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1324-1335, 2016. © 2016 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers.

Systematic Review and Consensus Guidelines for Environmental Sampling of Burkholderia pseudomallei

PubMed Central

Limmathurotsakul, Direk; Dance, David A. B.; Wuthiekanun, Vanaporn; Kaestli, Mirjam; Mayo, Mark; Warner, Jeffrey; Wagner, David M.; Tuanyok, Apichai; Wertheim, Heiman; Yoke Cheng, Tan; Mukhopadhyay, Chiranjay; Puthucheary, Savithiri; Day, Nicholas P. J.; Steinmetz, Ivo; Currie, Bart J.; Peacock, Sharon J.

2013-01-01

Background Burkholderia pseudomallei, a Tier 1 Select Agent and the cause of melioidosis, is a Gram-negative bacillus present in the environment in many tropical countries. Defining the global pattern of B. pseudomallei distribution underpins efforts to prevent infection, and is dependent upon robust environmental sampling methodology. Our objective was to review the literature on the detection of environmental B. pseudomallei, update the risk map for melioidosis, and propose international consensus guidelines for soil sampling. Methods/Principal Findings An international working party (Detection of Environmental Burkholderia pseudomallei Working Party (DEBWorP)) was formed during the VIth World Melioidosis Congress in 2010. PubMed (January 1912 to December 2011) was searched using the following MeSH terms: pseudomallei or melioidosis. Bibliographies were hand-searched for secondary references. The reported geographical distribution of B. pseudomallei in the environment was mapped and categorized as definite, probable, or possible. The methodology used for detecting environmental B. pseudomallei was extracted and collated. We found that global coverage was patchy, with a lack of studies in many areas where melioidosis is suspected to occur. The sampling strategies and bacterial identification methods used were highly variable, and not all were robust. We developed consensus guidelines with the goals of reducing the probability of false-negative results, and the provision of affordable and ‘low-tech’ methodology that is applicable in both developed and developing countries. Conclusions/Significance The proposed consensus guidelines provide the basis for the development of an accurate and comprehensive global map of environmental B. pseudomallei. PMID:23556010

A hybrid solution approach for a multi-objective closed-loop logistics network under uncertainty

NASA Astrophysics Data System (ADS)

Mehrbod, Mehrdad; Tu, Nan; Miao, Lixin

2015-06-01

The design of closed-loop logistics (forward and reverse logistics) has attracted growing attention with the stringent pressures of customer expectations, environmental concerns and economic factors. This paper considers a multi-product, multi-period and multi-objective closed-loop logistics network model with regard to facility expansion as a facility location-allocation problem, which more closely approximates real-world conditions. A multi-objective mixed integer nonlinear programming formulation is linearized by defining new variables and adding new constraints to the model. By considering the aforementioned model under uncertainty, this paper develops a hybrid solution approach by combining an interactive fuzzy goal programming approach and robust counterpart optimization based on three well-known robust counterpart optimization formulations. Finally, this paper compares the results of the three formulations using different test scenarios and parameter-sensitive analysis in terms of the quality of the final solution, CPU time, the level of conservatism, the degree of closeness to the ideal solution, the degree of balance involved in developing a compromise solution, and satisfaction degree.

Mussel-Inspired Fabrication of Konjac Glucomannan/Poly (Lactic Acid) Cryogels with Enhanced Thermal and Mechanical Properties

PubMed Central

Wang, Lin; Mu, Ruo-Jun; Gong, Jingni; Ni, Yongsheng; Hong, Xin; Pang, Jie; Wu, Chunhua

2017-01-01

Three-dimensional nanofibers cryogels (NFCs) with both thermally-tolerant and mechanically-robust properties have potential for wide application in biomedical or food areas; however, creating such NFCs has proven to be extremely challenging. In this study, konjac glucomannan (KGM)/poly (lactic acid) (PLA)-based novel NFCs were prepared by the incorporation of the mussel-inspired protein polydopamine (PDA) via a facile and environmentally-friendly electrospinning and freeze-shaping technique. The obtained KGM/PLA/PDA (KPP) NFCs were characterized by field emission scanning electron microscopy (FE-SEM), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) and compressive and tensile test. The results showed that the hierarchical cellular structure and physicochemical properties of KPP NFCs were dependent on the incorporation of PDA content. Moreover, the strong intermolecular hydrogen bond interactions among KGM, PLA and PDA also gave KPP NFCs high thermostability and mechanically-robust properties. Thus, this study developed a simple approach to fabricate multifunctional NFCs with significant potential for biomedical or food application. PMID:29258196

A phase-stepped point diffraction interferometer using liquid crystals

NASA Technical Reports Server (NTRS)

Mercer, Carolyn R.; Creath, Katherine; Rashidnia, Nasser

1995-01-01

A new instrument, the liquid crystal point diffraction interferometer (LCPDI), has been developed for the measurement of phase objects. This instrument maintains the compact, robust design of Linnik's point diffraction interferometer (PDI) and adds to it phase stepping capability for quantitative interferogram analysis. The result is a compact, simple to align, environmentally insensitive interferometer capable of accurately measuring optical wavefronts with high data density and with automated data reduction. The design of the LCPDI is briefly discussed. An algorithm is presented for eliminating phase measurement error caused by object beam intensity variation from frame-to-frame. The LCPDI is demonstrated by measuring the temperature distribution across a heated chamber filled with silicone oil. The measured results are compared to independently measured results and show excellent agreement with them. It is expected that this instrument will have application in the fluid sciences as a diagnostic tool, particularly in space based applications where autonomy, robustness, and compactness are desirable qualities. It should also be useful for the testing of optical elements, provided a master is available for comparison.

Solving the Puzzle of Recruitment and Retention-Strategies for Building a Robust Clinical and Translational Research Workforce.

PubMed

Nearing, Kathryn A; Hunt, Cerise; Presley, Jessica H; Nuechterlein, Bridget M; Moss, Marc; Manson, Spero M

2015-10-01

This paper is the first in a five-part series on the clinical and translational science educational pipeline and presents strategies to support recruitment and retention to create diverse pathways into clinical and translational research (CTR). The strategies address multiple levels or contexts of persistence decisions and include: (1) creating a seamless pipeline by forming strategic partnerships to achieve continuity of support for scholars and collective impact; (2) providing meaningful research opportunities to support identity formation as a scientist and sustain motivation to pursue and persist in CTR careers; (3) fostering an environment for effective mentorship and peer support to promote academic and social integration; (4) advocating for institutional policies to alleviate environmental pull factors; and, (5) supporting program evaluation-particularly, the examination of longitudinal outcomes. By combining institutional policies that promote a culture and climate for diversity with quality, evidence-based programs and integrated networks of support, we can create the environment necessary for diverse scholars to progress successfully and efficiently through the pipeline to achieve National Institutes of Health's vision of a robust CTR workforce. © 2015 Wiley Periodicals, Inc.

Enhanced robust fractional order proportional-plus-integral controller based on neural network for velocity control of permanent magnet synchronous motor.

PubMed

Zhang, Bitao; Pi, YouGuo

2013-07-01

The traditional integer order proportional-integral-differential (IO-PID) controller is sensitive to the parameter variation or/and external load disturbance of permanent magnet synchronous motor (PMSM). And the fractional order proportional-integral-differential (FO-PID) control scheme based on robustness tuning method is proposed to enhance the robustness. But the robustness focuses on the open-loop gain variation of controlled plant. In this paper, an enhanced robust fractional order proportional-plus-integral (ERFOPI) controller based on neural network is proposed. The control law of the ERFOPI controller is acted on a fractional order implement function (FOIF) of tracking error but not tracking error directly, which, according to theory analysis, can enhance the robust performance of system. Tuning rules and approaches, based on phase margin, crossover frequency specification and robustness rejecting gain variation, are introduced to obtain the parameters of ERFOPI controller. And the neural network algorithm is used to adjust the parameter of FOIF. Simulation and experimental results show that the method proposed in this paper not only achieve favorable tracking performance, but also is robust with regard to external load disturbance and parameter variation. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Convolutional Neural Network-Based Finger-Vein Recognition Using NIR Image Sensors

PubMed Central

Hong, Hyung Gil; Lee, Min Beom; Park, Kang Ryoung

2017-01-01

Conventional finger-vein recognition systems perform recognition based on the finger-vein lines extracted from the input images or image enhancement, and texture feature extraction from the finger-vein images. In these cases, however, the inaccurate detection of finger-vein lines lowers the recognition accuracy. In the case of texture feature extraction, the developer must experimentally decide on a form of the optimal filter for extraction considering the characteristics of the image database. To address this problem, this research proposes a finger-vein recognition method that is robust to various database types and environmental changes based on the convolutional neural network (CNN). In the experiments using the two finger-vein databases constructed in this research and the SDUMLA-HMT finger-vein database, which is an open database, the method proposed in this research showed a better performance compared to the conventional methods. PMID:28587269

Convolutional Neural Network-Based Finger-Vein Recognition Using NIR Image Sensors.

PubMed

Hong, Hyung Gil; Lee, Min Beom; Park, Kang Ryoung

2017-06-06

Conventional finger-vein recognition systems perform recognition based on the finger-vein lines extracted from the input images or image enhancement, and texture feature extraction from the finger-vein images. In these cases, however, the inaccurate detection of finger-vein lines lowers the recognition accuracy. In the case of texture feature extraction, the developer must experimentally decide on a form of the optimal filter for extraction considering the characteristics of the image database. To address this problem, this research proposes a finger-vein recognition method that is robust to various database types and environmental changes based on the convolutional neural network (CNN). In the experiments using the two finger-vein databases constructed in this research and the SDUMLA-HMT finger-vein database, which is an open database, the method proposed in this research showed a better performance compared to the conventional methods.

Robust Guar Gum/Cellulose Nanofibrils Multilayer Films with Good Barrier Properties.

PubMed

Dai, Lei; Long, Zhu; Chen, Jie; An, Xingye; Cheng, Dong; Khan, Avik; Ni, Yonghao

2017-02-15

The pursuit of sustainable functional materials requires development of materials based on renewable resources and efficient fabrication methods. Hereby, we fabricated all-polysaccharides multilayer films using cationic guar gum (CGG) and anionic cellulose nanofibrils (i.e., TEMPO-oxidized cellulose nanofibrils, TOCNs) through a layer-by-layer casting method. This technique is based on alternate depositions of oppositely charged water-based CGG and TOCNs onto laminated films. The resultant polyelectrolyte multilayer films were transparent, ductile, and strong. More importantly, the self-standing films exhibited excellent gas (water vapor and oxygen) and oil barrier performances. Another outstanding feature of these resultant films was their resistance to various organic solvents including methanol, acetone, N,N-dimethylacetamide (DMAc) and tetrahydrofuran (THF). The proposed film fabrication process is environmentally benign, cost-effective, and easy to scale-up. The developed CGG/TOCNs multilayer films can be used as a renewable material for industrial applications such as packaging.

The Wireless Sensor Network (WSN) Based Coal Ash Impoundments Safety Monitoring System

NASA Astrophysics Data System (ADS)

Sun, E. J.; Nieto, A.; Zhang, X. K.

2017-01-01

Coal ash impoundments are inevitable production of the coal-fired power plants. All coal ash impoundments in North Carolina USA that tested for groundwater contamination are leaking toxic heavy metals and other pollutants. Coal ash impoundments are toxic sources of dangerous pollutants that pose a danger to human and environmental health if the toxins spread to adjacent surface waters and drinking water wells. Coal ash impoundments failures accidents resulted in serious water contamination along with toxic heavy metals. To improve the design and stability of coal ash impoundments, the Development of a Coal Ash Impoundment Safety Monitoring System (CAISM) was proposed based on the implementation of a wireless sensor network (WSN) with the ability to monitor the stability of coal ash impoundments, water level, and saturation levels on-demand and remotely. The monitoring system based on a robust Ad-hoc network could be adapted to different safety conditions.

Optimization-Based Robust Nonlinear Control

DTIC Science & Technology

2006-08-01

ABSTRACT New control algorithms were developed for robust stabilization of nonlinear dynamical systems . Novel, linear matrix inequality-based synthesis...was to further advance optimization-based robust nonlinear control design, for general nonlinear systems (especially in discrete time ), for linear...Teel, IEEE Transactions on Control Systems Technology, vol. 14, no. 3, p. 398-407, May 2006. 3. "A unified framework for input-to-state stability in

Polyvinylidene Fluoride Micropore Membranes as Solid-Phase Extraction Disk for Preconcentration of Nanoparticulate Silver in Environmental Waters.

PubMed

Zhou, Xiao-Xia; Lai, Yu-Jian; Liu, Rui; Li, Sha-Sha; Xu, Jing-Wen; Liu, Jing-Fu

2017-12-05

Efficient separation and preconcentration of trace nanoparticulate silver (NAg) from large-volume environmental waters is a prerequisite for reliable analysis and therefore understanding the environmental processes of silver nanoparticles (AgNPs). Herein, we report the novel use of polyvinylidene fluoride (PVDF) filter membrane for disk-based solid phase extraction (SPE) of NAg in 1 L of water samples with the disk-based SPE system, which consists of a syringe pump and a syringe filter holder to embed the filter membrane. While the PVDF membrane can selectively adsorb NAg in the presence of Ag + , aqueous solution of 2% (m/v) FL-70 is found to efficiently elute NAg. Analysis of NAg is performed following optimization of filter membrane and elution conditions with an enrichment factor of 1000. Additionally, transmission electron microscopy (TEM), UV-vis spectroscopy, and size-exclusion chromatography coupled with ICP-MS (SEC-ICP-MS) analysis showed that the extraction gives rise to no change in NAg size or shape, making this method attractive for practical applications. Furthermore, feasibility of the protocol is verified by applying it to extract NAg in four real waters with recoveries of 62.2-80.2% at 0.056-0.58 μg/L spiked levels. This work will facilitate robust studies of trace NAg transformation and their hazard assessments in the environment.

Ensembles of novelty detection classifiers for structural health monitoring using guided waves

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

Dib, Gerges; Karpenko, Oleksii; Koricho, Ermias

Guided wave structural health monitoring uses sparse sensor networks embedded in sophisticated structures for defect detection and characterization. The biggest challenge of those sensor networks is developing robust techniques for reliable damage detection under changing environmental and operating conditions. To address this challenge, we develop a novelty classifier for damage detection based on one class support vector machines. We identify appropriate features for damage detection and introduce a feature aggregation method which quadratically increases the number of available training observations.We adopt a two-level voting scheme by using an ensemble of classifiers and predictions. Each classifier is trained on a differentmore » segment of the guided wave signal, and each classifier makes an ensemble of predictions based on a single observation. Using this approach, the classifier can be trained using a small number of baseline signals. We study the performance using monte-carlo simulations of an analytical model and data from impact damage experiments on a glass fiber composite plate.We also demonstrate the classifier performance using two types of baseline signals: fixed and rolling baseline training set. The former requires prior knowledge of baseline signals from all environmental and operating conditions, while the latter does not and leverages the fact that environmental and operating conditions vary slowly over time and can be modeled as a Gaussian process.« less

Implementation Science for the Environment.

PubMed

Hering, Janet G

2018-05-15

The establishment of the field of implementation science was motivated by the understanding that medical and health research alone is insufficient to generate better health outcomes. With strong support from funding agencies for medical research, implementation science promotes the application of a structured framework or model in the implementation of research-based results, specifically evidence-based practices (EBPs). Furthermore, explicit consideration is given to the context of EBP implementation (i.e., socio-economic, political, cultural, and institutional factors that could affect the implementation process). Finally, implementation is monitored in a robust and rigorous way. Today, the field of implementation science supports conferences and professional societies as well as one dedicated journal and numerous others with related content. The goal of these various activities is to reduce the estimated, average "bench to bedside" time lag of 17 years for uptake of EBPs from health research into routine practice. Despite similar time lags and impediments to uptake in the environmental domain, a parallel field of implementation science for the environment has not (yet) emerged. Although some parallels in needs and opportunities can easily be drawn between the health and environmental domains, a detailed mapping exercise is needed to understand which aspects of implementation science could be applied in the environmental domain either directly or in a modified form. This would allow an accelerated development of implementation science for the environment.

Adaptive Critic Nonlinear Robust Control: A Survey.

PubMed

Wang, Ding; He, Haibo; Liu, Derong

2017-10-01

Adaptive dynamic programming (ADP) and reinforcement learning are quite relevant to each other when performing intelligent optimization. They are both regarded as promising methods involving important components of evaluation and improvement, at the background of information technology, such as artificial intelligence, big data, and deep learning. Although great progresses have been achieved and surveyed when addressing nonlinear optimal control problems, the research on robustness of ADP-based control strategies under uncertain environment has not been fully summarized. Hence, this survey reviews the recent main results of adaptive-critic-based robust control design of continuous-time nonlinear systems. The ADP-based nonlinear optimal regulation is reviewed, followed by robust stabilization of nonlinear systems with matched uncertainties, guaranteed cost control design of unmatched plants, and decentralized stabilization of interconnected systems. Additionally, further comprehensive discussions are presented, including event-based robust control design, improvement of the critic learning rule, nonlinear H ∞ control design, and several notes on future perspectives. By applying the ADP-based optimal and robust control methods to a practical power system and an overhead crane plant, two typical examples are provided to verify the effectiveness of theoretical results. Overall, this survey is beneficial to promote the development of adaptive critic control methods with robustness guarantee and the construction of higher level intelligent systems.

Preparatory steps for a robust dynamic model for organically bound tritium dynamics in agricultural crops

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

Melintescu, A.; Galeriu, D.; Diabate, S.

2015-03-15

The processes involved in tritium transfer in crops are complex and regulated by many feedback mechanisms. A full mechanistic model is difficult to develop due to the complexity of the processes involved in tritium transfer and environmental conditions. First, a review of existing models (ORYZA2000, CROPTRIT and WOFOST) presenting their features and limits, is made. Secondly, the preparatory steps for a robust model are discussed, considering the role of dry matter and photosynthesis contribution to the OBT (Organically Bound Tritium) dynamics in crops.

Hunters of the Ice Age: The biology of Upper Paleolithic people.

PubMed

Holt, Brigitte M; Formicola, Vincenzo

2008-01-01

The Upper Paleolithic represents both the phase during which anatomically modern humans appeared and the climax of hunter-gatherer cultures. Demographic expansion into new areas that took place during this period and the diffusion of burial practices resulted in an unprecedented number of well-preserved human remains. This skeletal record, dovetailed with archeological, environmental, and chronological contexts, allows testing of hypotheses regarding biological processes at the population level. In this article, we review key studies about the biology of Upper Paleolithic populations based primarily on European samples, but integrating information from other areas of the Old World whenever possible. Data about cranial morphology, skeletal robusticity, stature, body proportions, health status, diet, physical activity, and genetics are evaluated in Late Pleistocene climatic and cultural contexts. Various lines of evidence delineate the Last Glacial Maximum (LGM) as a critical phase in the biological and cultural evolution of Upper Paleolithic populations. The LGM, a long phase of climatic deterioration culminating around 20,000 BP, had a profound impact on the environment, lifestyle, and behavior of human groups. Some of these effects are recorded in aspects of skeletal biology of these populations. Groups living before and after the LGM, Early Upper Paleolithic (EUP) and Late Upper Paleolithic (LUP), respectively, differ significantly in craniofacial dimensions, stature, robusticity, and body proportions. While paleopathological and stable isotope data suggest good health status throughout the Upper Paleolithic, some stress indicators point to a slight decline in quality of life in LUP populations. The intriguing and unexpected incidence of individuals affected by congenital disorders probably indicates selective burial practices for these abnormal individuals. While some of the changes observed can be explained through models of biocultural or environmental adaptation (e.g., decreased lower limb robusticity following decreased mobility; changes in body proportions along with climatic change), others are more difficult to explain. For instance, craniodental and upper limb robusticity show complex evolutionary patterns that do not always correspond to expectations. In addition, the marked decline in stature and the mosaic nature of change in body proportions still await clarifications. These issues, as well as systematic analysis of specific pathologies and possible relationships between genetic lineages, population movements and cultural complexes, should be among the goals of future research.

Dimpled ball grid array process development for space flight applications

NASA Technical Reports Server (NTRS)

Barr, S. L.; Mehta, A.

2000-01-01

A 472 dimpled ball grid array (D-BGA) package has not been used in past space flight environments, therefore it was necessary to develop a process that would yield robust and reliable solder joints. The process developing assembly, inspection and rework techniques, were verified by conducting environmental tests. Since the 472 D-BGA packages passed the above environmental tests within the specifications, the process was successfully developed for space flight electronics.

Living Membranes as Environmental Detectors

DTIC Science & Technology

2016-02-19

followed. Initial studies were conducted for 30 days of storage at room temperature and 4⁰C. Results indicate that the living membrane is stable...4⁰C or room temperature in wet or lyophilized form. Freeze-dried mat Wet pellicle 4oC RT 4oC RT Figure 13: Stability of RFP Living Membrane...physically robust format able to withstand extremes of temperature , humidity, and other environmental variables The living membrane systems under

Robust tracking of respiratory rate in high-dynamic range scenes using mobile thermal imaging

PubMed Central

Cho, Youngjun; Julier, Simon J.; Marquardt, Nicolai; Bianchi-Berthouze, Nadia

2017-01-01

The ability to monitor the respiratory rate, one of the vital signs, is extremely important for the medical treatment, healthcare and fitness sectors. In many situations, mobile methods, which allow users to undertake everyday activities, are required. However, current monitoring systems can be obtrusive, requiring users to wear respiration belts or nasal probes. Alternatively, contactless digital image sensor based remote-photoplethysmography (PPG) can be used. However, remote PPG requires an ambient source of light, and does not work properly in dark places or under varying lighting conditions. Recent advances in thermographic systems have shrunk their size, weight and cost, to the point where it is possible to create smart-phone based respiration rate monitoring devices that are not affected by lighting conditions. However, mobile thermal imaging is challenged in scenes with high thermal dynamic ranges (e.g. due to the different environmental temperature distributions indoors and outdoors). This challenge is further amplified by general problems such as motion artifacts and low spatial resolution, leading to unreliable breathing signals. In this paper, we propose a novel and robust approach for respiration tracking which compensates for the negative effects of variations in the ambient temperature and motion artifacts and can accurately extract breathing rates in highly dynamic thermal scenes. The approach is based on tracking the nostril of the user and using local temperature variations to infer inhalation and exhalation cycles. It has three main contributions. The first is a novel Optimal Quantization technique which adaptively constructs a color mapping of absolute temperature to improve segmentation, classification and tracking. The second is the Thermal Gradient Flow method that computes thermal gradient magnitude maps to enhance the accuracy of the nostril region tracking. Finally, we introduce the Thermal Voxel method to increase the reliability of the captured respiration signals compared to the traditional averaging method. We demonstrate the extreme robustness of our system to track the nostril-region and measure the respiratory rate by evaluating it during controlled respiration exercises in high thermal dynamic scenes (e.g. strong correlation (r = 0.9987) with the ground truth from the respiration-belt sensor). We also demonstrate how our algorithm outperformed standard algorithms in settings with different amounts of environmental thermal changes and human motion. We open the tracked ROI sequences of the datasets collected for these studies (i.e. under both controlled and unconstrained real-world settings) to the community to foster work in this area. PMID:29082079

Robust tracking of respiratory rate in high-dynamic range scenes using mobile thermal imaging.

PubMed

Cho, Youngjun; Julier, Simon J; Marquardt, Nicolai; Bianchi-Berthouze, Nadia

2017-10-01

The ability to monitor the respiratory rate, one of the vital signs, is extremely important for the medical treatment, healthcare and fitness sectors. In many situations, mobile methods, which allow users to undertake everyday activities, are required. However, current monitoring systems can be obtrusive, requiring users to wear respiration belts or nasal probes. Alternatively, contactless digital image sensor based remote-photoplethysmography (PPG) can be used. However, remote PPG requires an ambient source of light, and does not work properly in dark places or under varying lighting conditions. Recent advances in thermographic systems have shrunk their size, weight and cost, to the point where it is possible to create smart-phone based respiration rate monitoring devices that are not affected by lighting conditions. However, mobile thermal imaging is challenged in scenes with high thermal dynamic ranges (e.g. due to the different environmental temperature distributions indoors and outdoors). This challenge is further amplified by general problems such as motion artifacts and low spatial resolution, leading to unreliable breathing signals. In this paper, we propose a novel and robust approach for respiration tracking which compensates for the negative effects of variations in the ambient temperature and motion artifacts and can accurately extract breathing rates in highly dynamic thermal scenes. The approach is based on tracking the nostril of the user and using local temperature variations to infer inhalation and exhalation cycles. It has three main contributions. The first is a novel Optimal Quantization technique which adaptively constructs a color mapping of absolute temperature to improve segmentation, classification and tracking. The second is the Thermal Gradient Flow method that computes thermal gradient magnitude maps to enhance the accuracy of the nostril region tracking. Finally, we introduce the Thermal Voxel method to increase the reliability of the captured respiration signals compared to the traditional averaging method. We demonstrate the extreme robustness of our system to track the nostril-region and measure the respiratory rate by evaluating it during controlled respiration exercises in high thermal dynamic scenes (e.g. strong correlation (r = 0.9987) with the ground truth from the respiration-belt sensor). We also demonstrate how our algorithm outperformed standard algorithms in settings with different amounts of environmental thermal changes and human motion. We open the tracked ROI sequences of the datasets collected for these studies (i.e. under both controlled and unconstrained real-world settings) to the community to foster work in this area.

Optimizing Standard Sequential Extraction Protocol With Lake And Ocean Sediments

EPA Science Inventory

The environmental mobility/availability behavior of radionuclides in soils and sediments depends on their speciation. Experiments have been carried out to develop a simple but robust radionuclide sequential extraction method for identification of radionuclide partitioning in sed...

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

DOE PAGES

Sippel, Sebastian; Lange, Holger; Mahecha, Miguel D.; ...

2016-10-20

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observedmore » and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. Here we demonstrate that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics.« less

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

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

Sippel, Sebastian; Lange, Holger; Mahecha, Miguel D.

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observedmore » and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. Here we demonstrate that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics.« less

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

PubMed Central

Sippel, Sebastian; Mahecha, Miguel D.; Hauhs, Michael; Bodesheim, Paul; Kaminski, Thomas; Gans, Fabian; Rosso, Osvaldo A.

2016-01-01

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observed and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. We demonstrate here that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics. PMID:27764187

Near Real Time Detection and Tracking of the EYJAFJÖLL (iceland) Ash Cloud by the RST (robust Satellite Technique) Approach

NASA Astrophysics Data System (ADS)

Tramutoli, V.; Filizzola, C.; Marchese, F.; Paciello, R.; Pergola, N.; Sannazzaro, F.

2010-12-01

Volcanic ash clouds, besides to be an environmental issue, represent a serious problem for air traffic and an important economic threat for aviation companies. During the recent volcanic crisis due to the April-May 2010 eruption of Eyjafjöll (Iceland), ash clouds became a real problem for common citizens as well: during the first days of the eruption thousands of flights were cancelled disrupting hundred of thousands of passengers. Satellite remote sensing confirmed to be a crucial tool for monitoring this kind of events, spreading for thousands of kilometres with a very rapid space-time dynamics. Especially weather satellites, thanks to their high temporal resolution, may furnish a fundamental contribution, providing frequently updated information. However, in this particular case ash cloud was accompanied by a sudden and significant emission of water vapour, due to the ice melting of Eyjafjallajökull glacier, making satellite ash detection and discrimination very hard, especially in the first few days of the eruption, exactly when accurate information were mostly required in order to support emergency management. Among the satellite-based techniques for near real-time detection and tracking of ash clouds, the RST (Robust Satellite Technique) approach, formerly named RAT - Robust AVHRR Technique, has been long since proposed, demonstrating high performances both in terms of reliability and sensitivity. In this paper, results achieved by using RST-based detection schemes, applied during the Eyjafjöll eruption were presented. MSG-SEVIRI (Meteosat Second Generation - Spinning Enhanced and Visible Infrared Imager) records, with a temporal sampling of 15 minutes, were used applying a standard as well as an advanced RST configuration, which includes the use of SO2 absorption band together with TIR and MIR channels. Main outcomes, limits and possible future improvements were also discussed.

Quality Scalability Aware Watermarking for Visual Content.

PubMed

Bhowmik, Deepayan; Abhayaratne, Charith

2016-11-01

Scalable coding-based content adaptation poses serious challenges to traditional watermarking algorithms, which do not consider the scalable coding structure and hence cannot guarantee correct watermark extraction in media consumption chain. In this paper, we propose a novel concept of scalable blind watermarking that ensures more robust watermark extraction at various compression ratios while not effecting the visual quality of host media. The proposed algorithm generates scalable and robust watermarked image code-stream that allows the user to constrain embedding distortion for target content adaptations. The watermarked image code-stream consists of hierarchically nested joint distortion-robustness coding atoms. The code-stream is generated by proposing a new wavelet domain blind watermarking algorithm guided by a quantization based binary tree. The code-stream can be truncated at any distortion-robustness atom to generate the watermarked image with the desired distortion-robustness requirements. A blind extractor is capable of extracting watermark data from the watermarked images. The algorithm is further extended to incorporate a bit-plane discarding-based quantization model used in scalable coding-based content adaptation, e.g., JPEG2000. This improves the robustness against quality scalability of JPEG2000 compression. The simulation results verify the feasibility of the proposed concept, its applications, and its improved robustness against quality scalable content adaptation. Our proposed algorithm also outperforms existing methods showing 35% improvement. In terms of robustness to quality scalable video content adaptation using Motion JPEG2000 and wavelet-based scalable video coding, the proposed method shows major improvement for video watermarking.

Research on Intelligent Interface in Double-front Work Machines

NASA Astrophysics Data System (ADS)

Kamezaki, Mitsuhiro; Iwata, Hiroyasu; Sugano, Shigeki

This paper proposes a work state identification method with full independent of work environmental conditions and operator skill levels for construction machinery. Advanced operated-work machines, which have been designed for complicated tasks, require intelligent systems that can provide the quantitative work analysis needed to determine effective work procedures and that can provide operational and cognitive support for operators. Construction work environments are extremely complicated, however, and this makes state identification, which is a key technology for an intelligent system, difficult. We therefore defined primitive static states (PSS) that are determined using on-off information for the lever inputs and manipulator loads for each part of the grapple and front and that are completely independent of the various environmental conditions and variation in operator skill level that can cause an incorrect work state identification. To confirm the usefulness of PSS, we performed experiments with a demolition task by using our virtual reality simulator. We confirmed that PSS could robustly and accurately identify the work states and that untrained skills could be easily inferred from the results of PSS-based work analysis. We also confirmed in skill-training experiments that advice information based on PSS-based skill analysis greatly improved operator's work performance. We thus confirmed that PSS can adequately identify work states and are useful for work analysis and skill improvement.

Impact-acoustics inspection of tile-wall bonding integrity via wavelet transform and hidden Markov models

NASA Astrophysics Data System (ADS)

Luk, B. L.; Liu, K. P.; Tong, F.; Man, K. F.

2010-05-01

The impact-acoustics method utilizes different information contained in the acoustic signals generated by tapping a structure with a small metal object. It offers a convenient and cost-efficient way to inspect the tile-wall bonding integrity. However, the existence of the surface irregularities will cause abnormal multiple bounces in the practical inspection implementations. The spectral characteristics from those bounces can easily be confused with the signals obtained from different bonding qualities. As a result, it will deteriorate the classic feature-based classification methods based on frequency domain. Another crucial difficulty posed by the implementation is the additive noise existing in the practical environments that may also cause feature mismatch and false judgment. In order to solve this problem, the work described in this paper aims to develop a robust inspection method that applies model-based strategy, and utilizes the wavelet domain features with hidden Markov modeling. It derives a bonding integrity recognition approach with enhanced immunity to surface roughness as well as the environmental noise. With the help of the specially designed artificial sample slabs, experiments have been carried out with impact acoustic signals contaminated by real environmental noises acquired under practical inspection background. The results are compared with those using classic method to demonstrate the effectiveness of the proposed method.

Proposal of an environmental performance index to assess solid waste treatment technologies.

PubMed

Coelho, Hosmanny Mauro Goulart; Lange, Liséte Celina; Coelho, Lineker Max Goulart

2012-07-01

Although the concern with sustainable development and environment protection has considerably grown in the last years it is noted that the majority of decision making models and tools are still either excessively tied to economic aspects or geared to the production process. Moreover, existing models focus on the priority steps of solid waste management, beyond waste energy recovery and disposal. So, in order to help the lack of models and tools aiming at the waste treatment and final disposal, a new concept is proposed: the Cleaner Treatment, which is based on the Cleaner Production principles. This paper focuses on the development and validation of the Cleaner Treatment Index (CTI), to assess environmental performance of waste treatment technologies based on the Cleaner Treatment concept. The index is formed by aggregation (summation or product) of several indicators that consists in operational parameters. The weights of the indicator were established by Delphi Method and Brazilian Environmental Laws. In addition, sensitivity analyses were carried out comparing both aggregation methods. Finally, index validation was carried out by applying the CTI to 10 waste-to-energy plants data. From sensitivity analysis and validation results it is possible to infer that summation model is the most suitable aggregation method. For summation method, CTI results were superior to 0.5 (in a scale from 0 to 1) for most facilities evaluated. So, this study demonstrates that CTI is a simple and robust tool to assess and compare the environmental performance of different treatment plants being an excellent quantitative tool to support Cleaner Treatment implementation. Copyright © 2012 Elsevier Ltd. All rights reserved.

Epigenetic Mechanisms of Transmission of Metabolic Disease across Generations.

PubMed

Sales, Vicencia Micheline; Ferguson-Smith, Anne C; Patti, Mary-Elizabeth

2017-03-07

Both human and animal studies indicate that environmental exposures experienced during early life can robustly influence risk for adult disease. Moreover, environmental exposures experienced by parents during either intrauterine or postnatal life can also influence the health of their offspring, thus initiating a cycle of disease risk across generations. In this Perspective, we focus on epigenetic mechanisms in germ cells, including DNA methylation, histone modification, and non-coding RNAs, which collectively may provide a non-genetic molecular legacy of prior environmental exposures and influence transcriptional regulation, developmental trajectories, and adult disease risk in offspring. Copyright © 2017 Elsevier Inc. All rights reserved.

Image segmentation-based robust feature extraction for color image watermarking

NASA Astrophysics Data System (ADS)

Li, Mianjie; Deng, Zeyu; Yuan, Xiaochen

2018-04-01

This paper proposes a local digital image watermarking method based on Robust Feature Extraction. The segmentation is achieved by Simple Linear Iterative Clustering (SLIC) based on which an Image Segmentation-based Robust Feature Extraction (ISRFE) method is proposed for feature extraction. Our method can adaptively extract feature regions from the blocks segmented by SLIC. This novel method can extract the most robust feature region in every segmented image. Each feature region is decomposed into low-frequency domain and high-frequency domain by Discrete Cosine Transform (DCT). Watermark images are then embedded into the coefficients in the low-frequency domain. The Distortion-Compensated Dither Modulation (DC-DM) algorithm is chosen as the quantization method for embedding. The experimental results indicate that the method has good performance under various attacks. Furthermore, the proposed method can obtain a trade-off between high robustness and good image quality.

Surveying Europe's Only Cave-Dwelling Chordate Species (Proteus anguinus) Using Environmental DNA.

PubMed

Vörös, Judit; Márton, Orsolya; Schmidt, Benedikt R; Gál, Júlia Tünde; Jelić, Dušan

2017-01-01

In surveillance of subterranean fauna, especially in the case of rare or elusive aquatic species, traditional techniques used for epigean species are often not feasible. We developed a non-invasive survey method based on environmental DNA (eDNA) to detect the presence of the red-listed cave-dwelling amphibian, Proteus anguinus, in the caves of the Dinaric Karst. We tested the method in fifteen caves in Croatia, from which the species was previously recorded or expected to occur. We successfully confirmed the presence of P. anguinus from ten caves and detected the species for the first time in five others. Using a hierarchical occupancy model we compared the availability and detection probability of eDNA of two water sampling methods, filtration and precipitation. The statistical analysis showed that both availability and detection probability depended on the method and estimates for both probabilities were higher using filter samples than for precipitation samples. Combining reliable field and laboratory methods with robust statistical modeling will give the best estimates of species occurrence.

Alcohol Consumption and Long-Term Labor Market Outcomes.

PubMed

Böckerman, Petri; Hyytinen, Ari; Maczulskij, Terhi

2017-03-01

This paper examines whether alcohol consumption is related to long-term labor market outcomes. We use twin data for Finnish men and women matched to register-based individual information on employment and earnings. The twin data allow us to account for the shared environmental and genetic factors. The quantity of alcohol consumption was measured by weekly average consumption using self-reported data from three surveys (1975, 1981 and 1990). The average of an individual's employment months and earnings were measured in adulthood over the period 1990-2009. The models that account for the shared environmental and genetic factors reveal that former drinkers and heavy drinkers both have almost 20% lower earnings compared with moderate drinkers. On average, former drinkers work annually approx. 1 month less over the 20-year observation period. These associations are robust to the use of covariates, such as education, pre-existing health endowment and smoking. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Effects of seagrass bed removal for tourism purposes in a Mauritian bay.

PubMed

Daby, D

2003-01-01

Stresses and shocks are increasing on the main natural assets in Mauritius (Western Indian Ocean) by tourism (marine-based) development activities. Seagrasses are removed by hotels in the belief that they are unsightly or harbour organisms causing injury to bathers. Environmental changes (e.g. sediment characteristics and infauna distribution, water quality, seagrass biomass) resulting from clearing of a seagrass bed to create an aesthetically pleasant swimming zone for clients of a hotel were monitored during June 2000-July 2001, and compared to conditions prevailing in an adjacent undisturbed area. Key observations in the disturbed area were: highly turbid water overlying a destabilized lagoon seabed, complete loss of sediment infauna, and dramatic dry weight biomass declines (e.g. 72 and 65% in S. isoetifolium and H. uninervis, respectively). Such disruptions draw-down resilience rendering the marine habitats less robust and more vulnerable to environmental change and extreme events, with higher risks of chaos and ecological collapse, and constitute a major threat to the industry itself.

Determination of traces of 237Np in environmental samples by ICP-MS after separation using TOA extraction chromatography.

PubMed

Ji, Y Q; Li, J Y; Luo, S G; Wu, T; Liu, J L

2001-09-01

A simple, rapid, cost-efficient, and robust method for separation of 237Np with an extraction chromatographic column (TOA: tri-n-octylamine on Teflon powder) is outlined in detail and further improved for direct ICP-MS analysis. The column efficiently retained 237Np in 2 mol L(-1) HNO3 medium and all of the 237Np was easily eluted with 0.02 mol L(-1) oxalic acid in 0.16 mol L(-1) HNO3 at 95 degrees C. The separated solutions were free from most matrix elements and were aspirated into the ICP-MS directly. The decontamination factor for 238U is more than 10(4). The instrumental detection limit for 237Np was 0.46 pg mL(-1), which corresponds to 1.2 x 10(-5) Bq mL(-1). The method is more rapid than traditional radiometric techniques. It is also considered to be more suitable for environmental monitoring than existing methods based on TOA.

Synthetic biology and regulatory networks: where metabolic systems biology meets control engineering

PubMed Central

He, Fei; Murabito, Ettore; Westerhoff, Hans V.

2016-01-01

Metabolic pathways can be engineered to maximize the synthesis of various products of interest. With the advent of computational systems biology, this endeavour is usually carried out through in silico theoretical studies with the aim to guide and complement further in vitro and in vivo experimental efforts. Clearly, what counts is the result in vivo, not only in terms of maximal productivity but also robustness against environmental perturbations. Engineering an organism towards an increased production flux, however, often compromises that robustness. In this contribution, we review and investigate how various analytical approaches used in metabolic engineering and synthetic biology are related to concepts developed by systems and control engineering. While trade-offs between production optimality and cellular robustness have already been studied diagnostically and statically, the dynamics also matter. Integration of the dynamic design aspects of control engineering with the more diagnostic aspects of metabolic, hierarchical control and regulation analysis is leading to the new, conceptual and operational framework required for the design of robust and productive dynamic pathways. PMID:27075000

The Environmental Control and Life Support System (ECLSS) advanced automation project

NASA Technical Reports Server (NTRS)

Dewberry, Brandon S.; Carnes, Ray

1990-01-01

The objective of the environmental control and life support system (ECLSS) Advanced Automation Project is to influence the design of the initial and evolutionary Space Station Freedom Program (SSFP) ECLSS toward a man-made closed environment in which minimal flight and ground manpower is needed. Another objective includes capturing ECLSS design and development knowledge future missions. Our approach has been to (1) analyze the SSFP ECLSS, (2) envision as our goal a fully automated evolutionary environmental control system - an augmentation of the baseline, and (3) document the advanced software systems, hooks, and scars which will be necessary to achieve this goal. From this analysis, prototype software is being developed, and will be tested using air and water recovery simulations and hardware subsystems. In addition, the advanced software is being designed, developed, and tested using automation software management plan and lifecycle tools. Automated knowledge acquisition, engineering, verification and testing tools are being used to develop the software. In this way, we can capture ECLSS development knowledge for future use develop more robust and complex software, provide feedback to the knowledge based system tool community, and ensure proper visibility of our efforts.

MinION Nanopore Sequencing Enables Correlation between Resistome Phenotype and Genotype of Coliform Bacteria in Municipal Sewage.

PubMed

Xia, Yu; Li, An-Dong; Deng, Yu; Jiang, Xiao-Tao; Li, Li-Guan; Zhang, Tong

2017-01-01

Wastewater treatment plants (WWTPs) functioned as the intersection between the human society and nature environment, are receiving increasingly more attention on risk assessment of the acquisition of environmental antibiotic resistance genes (ARGs) by pathogenetic populations during treatment. However, because of the general lack of robust resistome profiling methods, genotype, and resistance phenotype is still poorly correlated in human pathogens of sewage samples. Here we applied MinION sequencing to quantify the resistance genes of multiple antibiotic resistant (MAR) coliform bacteria, a common indicator for human enteric pathogens in sewage samples. Our pipeline could deliver the results within 30 h from sample collection and the resistome quantification was consistent to that based on the Illumina platform. Additionally, the long nanopore reads not only enabled a simultaneous identification of the carrier populations of ARGs detected, but also facilitated the genome reconstruction of a representative MAR strain, from which we identified an instance of chromosomal integration of environmental resistance gene obtained by plasmid exchange with a porcine pathogen. This study demonstrated the utilization of MinION sequencing in quick monitoring and simultaneous phylogenetic tracking of environmental ARGs to address potential health risk associated with them.

MinION Nanopore Sequencing Enables Correlation between Resistome Phenotype and Genotype of Coliform Bacteria in Municipal Sewage

PubMed Central

Xia, Yu; Li, An-Dong; Deng, Yu; Jiang, Xiao-Tao; Li, Li-Guan; Zhang, Tong

2017-01-01

Wastewater treatment plants (WWTPs) functioned as the intersection between the human society and nature environment, are receiving increasingly more attention on risk assessment of the acquisition of environmental antibiotic resistance genes (ARGs) by pathogenetic populations during treatment. However, because of the general lack of robust resistome profiling methods, genotype, and resistance phenotype is still poorly correlated in human pathogens of sewage samples. Here we applied MinION sequencing to quantify the resistance genes of multiple antibiotic resistant (MAR) coliform bacteria, a common indicator for human enteric pathogens in sewage samples. Our pipeline could deliver the results within 30 h from sample collection and the resistome quantification was consistent to that based on the Illumina platform. Additionally, the long nanopore reads not only enabled a simultaneous identification of the carrier populations of ARGs detected, but also facilitated the genome reconstruction of a representative MAR strain, from which we identified an instance of chromosomal integration of environmental resistance gene obtained by plasmid exchange with a porcine pathogen. This study demonstrated the utilization of MinION sequencing in quick monitoring and simultaneous phylogenetic tracking of environmental ARGs to address potential health risk associated with them. PMID:29163399

Molecular ecological network analyses.

PubMed

Deng, Ye; Jiang, Yi-Huei; Yang, Yunfeng; He, Zhili; Luo, Feng; Zhou, Jizhong

2012-05-30

Understanding the interaction among different species within a community and their responses to environmental changes is a central goal in ecology. However, defining the network structure in a microbial community is very challenging due to their extremely high diversity and as-yet uncultivated status. Although recent advance of metagenomic technologies, such as high throughout sequencing and functional gene arrays, provide revolutionary tools for analyzing microbial community structure, it is still difficult to examine network interactions in a microbial community based on high-throughput metagenomics data. Here, we describe a novel mathematical and bioinformatics framework to construct ecological association networks named molecular ecological networks (MENs) through Random Matrix Theory (RMT)-based methods. Compared to other network construction methods, this approach is remarkable in that the network is automatically defined and robust to noise, thus providing excellent solutions to several common issues associated with high-throughput metagenomics data. We applied it to determine the network structure of microbial communities subjected to long-term experimental warming based on pyrosequencing data of 16 S rRNA genes. We showed that the constructed MENs under both warming and unwarming conditions exhibited topological features of scale free, small world and modularity, which were consistent with previously described molecular ecological networks. Eigengene analysis indicated that the eigengenes represented the module profiles relatively well. In consistency with many other studies, several major environmental traits including temperature and soil pH were found to be important in determining network interactions in the microbial communities examined. To facilitate its application by the scientific community, all these methods and statistical tools have been integrated into a comprehensive Molecular Ecological Network Analysis Pipeline (MENAP), which is open-accessible now (http://ieg2.ou.edu/MENA). The RMT-based molecular ecological network analysis provides powerful tools to elucidate network interactions in microbial communities and their responses to environmental changes, which are fundamentally important for research in microbial ecology and environmental microbiology.

Self Calibrated Wireless Distributed Environmental Sensory Networks

PubMed Central

Fishbain, Barak; Moreno-Centeno, Erick

2016-01-01

Recent advances in sensory and communication technologies have made Wireless Distributed Environmental Sensory Networks (WDESN) technically and economically feasible. WDESNs present an unprecedented tool for studying many environmental processes in a new way. However, the WDESNs’ calibration process is a major obstacle in them becoming the common practice. Here, we present a new, robust and efficient method for aggregating measurements acquired by an uncalibrated WDESN, and producing accurate estimates of the observed environmental variable’s true levels rendering the network as self-calibrated. The suggested method presents novelty both in group-decision-making and in environmental sensing as it offers a most valuable tool for distributed environmental monitoring data aggregation. Applying the method on an extensive real-life air-pollution dataset showed markedly more accurate results than the common practice and the state-of-the-art. PMID:27098279

A simple SDS-PAGE protein pattern from pitcher secretions as a new tool to distinguish Nepenthes species (Nepenthaceae).

PubMed

Biteau, Flore; Nisse, Estelle; Miguel, Sissi; Hannewald, Paul; Bazile, Vincent; Gaume, Laurence; Mignard, Benoit; Hehn, Alain; Bourgaud, Frederic

2013-12-01

Carnivorous plants have always fascinated scientists because these plants are able to attract, capture, and digest animal prey using their remarkable traps that contain digestive secretions. Nepenthes is one of the largest genera of carnivorous plants, with 120 species described thus far. Despite an outstanding diversity of trap designs, many species are often confused with each other and remain difficult to classify because they resemble pitchers or of the occurrence of interspecific hybrids. Here, we propose a new method to easily distinguish Nepenthes species based on a SDS PAGE protein pattern analysis of their pitcher secretions. Intraspecific comparisons were performed among specimens growing in different environmental conditions to ascertain the robustness of this method. Our results show that, at the juvenile stage and in the absence of prey in the pitcher, an examined species is characterized by a specific and stable profile, whatever the environmental conditions. The method we describe here can be used as a reliable tool to easily distinguish between Nepenthes species and to help with potential identification based on the species-specific protein pattern of their pitcher secretions, which is complementary to the monograph information.

Towards generalised reference condition models for environmental assessment: a case study on rivers in Atlantic Canada.

PubMed

Armanini, D G; Monk, W A; Carter, L; Cote, D; Baird, D J

2013-08-01

Evaluation of the ecological status of river sites in Canada is supported by building models using the reference condition approach. However, geography, data scarcity and inter-operability constraints have frustrated attempts to monitor national-scale status and trends. This issue is particularly true in Atlantic Canada, where no ecological assessment system is currently available. Here, we present a reference condition model based on the River Invertebrate Prediction and Classification System approach with regional-scale applicability. To achieve this, we used biological monitoring data collected from wadeable streams across Atlantic Canada together with freely available, nationally consistent geographic information system (GIS) environmental data layers. For the first time, we demonstrated that it is possible to use data generated from different studies, even when collected using different sampling methods, to generate a robust predictive model. This model was successfully generated and tested using GIS-based rather than local habitat variables and showed improved performance when compared to a null model. In addition, ecological quality ratio data derived from the model responded to observed stressors in a test dataset. Implications for future large-scale implementation of river biomonitoring using a standardised approach with global application are presented.

Impact of water depth on the distribution of iGDGTs in the surface sediments from the northern South China Sea: applicability of TEX86 in marginal seas

NASA Astrophysics Data System (ADS)

Chen, Jiali; Hu, Pengju; Li, Xing; Yang, Yang; Song, Jinming; Li, Xuegang; Yuan, Huamao; Li, Ning; Lü, Xiaoxia

2018-03-01

The TEX 86 H paleothermometer on the base of isoprenoid glycerol dialkyl glycerol tetraethers (iGDGTs) has been widely applied to various marine settings to reconstruct past sea surface temperatures (SSTs). However, it remains uncertain how well this proxy reconstructs SSTs in marginal seas. In this study, we analyze the environmental factors governing distribution of iGDGTs in surface sediments to assess the applicability of TEX 86 H paleothermometer in the South China Sea (SCS). Individual iGDGT concentrations increase gradually eastwards. Redundancy analysis based on the relative abundance of an individual iGDGT compound and environmental parameters suggests that water depth is the most influential factor to the distribution of iGDGTs, because thaumarchaeota communities are water-depth dependent. Interestingly, the SST difference (Δ T) between TEX 86 H derived temperature and remote-sensing SST is less than 1°C in sediments with water depth>200 m, indicating that TEX 86 H was the robust proxy to trace the paleo-SST in the region if water depth is greater than 200 m.

Anthropometric geography applied to the analysis of socioeconomic disparities: cohort trends and spatial patterns of height and robustness in 20th-century Spain.

PubMed

Camara, Antonio D; Roman, Joan Garcia

2015-11-01

Anthropometrics have been widely used to study the influence of environmental factors on health and nutritional status. In contrast, anthropometric geography has not often been employed to approximate the dynamics of spatial disparities associated with socioeconomic and demographic changes. Spain exhibited intense disparity and change during the middle decades of the 20 th century, with the result that the life courses of the corresponding cohorts were associated with diverse environmental conditions. This was also true of the Spanish territories. This paper presents insights concerning the relationship between socioeconomic changes and living conditions by combining the analysis of cohort trends and the anthropometric cartography of height and physical build. This analysis is conducted for Spanish male cohorts born 1934-1973 that were recorded in the Spanish military statistics. This information is interpreted in light of region-level data on GDP and infant mortality. Our results show an anthropometric convergence across regions that, nevertheless, did not substantially modify the spatial patterns of robustness, featuring primarily robust northeastern regions and weak Central-Southern regions. These patterns persisted until the 1990s (cohorts born during the 1970s). For the most part, anthropometric disparities were associated with socioeconomic disparities, although the former lessened over time to a greater extent than the latter. Interestingly, the various anthropometric indicators utilized here do not point to the same conclusions. Some discrepancies between height and robustness patterns have been found that moderate the statements from the analysis of cohort height alone regarding the level and evolution of living conditions across Spanish regions.

Extending the Distributed Lag Model framework to handle chemical mixtures.

PubMed

Bello, Ghalib A; Arora, Manish; Austin, Christine; Horton, Megan K; Wright, Robert O; Gennings, Chris

2017-07-01

Distributed Lag Models (DLMs) are used in environmental health studies to analyze the time-delayed effect of an exposure on an outcome of interest. Given the increasing need for analytical tools for evaluation of the effects of exposure to multi-pollutant mixtures, this study attempts to extend the classical DLM framework to accommodate and evaluate multiple longitudinally observed exposures. We introduce 2 techniques for quantifying the time-varying mixture effect of multiple exposures on an outcome of interest. Lagged WQS, the first technique, is based on Weighted Quantile Sum (WQS) regression, a penalized regression method that estimates mixture effects using a weighted index. We also introduce Tree-based DLMs, a nonparametric alternative for assessment of lagged mixture effects. This technique is based on the Random Forest (RF) algorithm, a nonparametric, tree-based estimation technique that has shown excellent performance in a wide variety of domains. In a simulation study, we tested the feasibility of these techniques and evaluated their performance in comparison to standard methodology. Both methods exhibited relatively robust performance, accurately capturing pre-defined non-linear functional relationships in different simulation settings. Further, we applied these techniques to data on perinatal exposure to environmental metal toxicants, with the goal of evaluating the effects of exposure on neurodevelopment. Our methods identified critical neurodevelopmental windows showing significant sensitivity to metal mixtures. Copyright © 2017 Elsevier Inc. All rights reserved.

Ecosystem oceanography for global change in fisheries.

PubMed

Cury, Philippe Maurice; Shin, Yunne-Jai; Planque, Benjamin; Durant, Joël Marcel; Fromentin, Jean-Marc; Kramer-Schadt, Stephanie; Stenseth, Nils Christian; Travers, Morgane; Grimm, Volker

2008-06-01

Overexploitation and climate change are increasingly causing unanticipated changes in marine ecosystems, such as higher variability in fish recruitment and shifts in species dominance. An ecosystem-based approach to fisheries attempts to address these effects by integrating populations, food webs and fish habitats at different scales. Ecosystem models represent indispensable tools to achieve this objective. However, a balanced research strategy is needed to avoid overly complex models. Ecosystem oceanography represents such a balanced strategy that relates ecosystem components and their interactions to climate change and exploitation. It aims at developing realistic and robust models at different levels of organisation and addressing specific questions in a global change context while systematically exploring the ever-increasing amount of biological and environmental data.

Wirelessly Interrogated Position or Displacement Sensors

NASA Technical Reports Server (NTRS)

Woodard, Stanley E.; Taylor, Bryant D.

2007-01-01

Two simple position or displacement sensors based on inductance-capacitance resonant circuits have been conceived. These sensors are both powered and interrogated without use of wires and without making contact with other objects. Instead, excitation and interrogation are accomplished by means of a magnetic-field-response recorder. Both of the present position or displacement sensors consist essentially of variable rectangular parallel-plate capacitors electrically connected in series with fixed inductors. Simple inductance-capacitance circuits of the type used in these sensors are inherently robust; their basic mode of operation does not depend on maintenance of specific environmental conditions. Hence, these sensors can be used under such harsh conditions as cryogenic temperatures, high pressures, and radioactivity.

Additively Manufactured IN718 Components with Wirelessly Powered and Interrogated Embedded Sensing

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

Attridge, Paul; Bajekal, Sanjay; Klecka, Michael

A methodology is described for embedding commercial-off-the-shelf sensors together with wireless communication and power circuit elements using direct laser metal sintered additively manufactured components. Physics based models of the additive manufacturing processes and sensor/wireless level performance models guided the design and embedment processes. A combination of cold spray deposition and laser engineered net shaping was used to fashion the transmitter/receiving elements and embed the sensors, thereby providing environmental protection and component robustness/survivability for harsh conditions. By design, this complement of analog and digital sensors were wirelessly powered and interrogated using a health and utilization monitoring system; enabling real-time, in situmore » prognostics and diagnostics.« less

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.

Implementation of Multi-Agent Object Attention System Based on Biologically Inspired Attractor Selection

NASA Astrophysics Data System (ADS)

Hashimoto, Ryoji; Matsumura, Tomoya; Nozato, Yoshihiro; Watanabe, Kenji; Onoye, Takao

A multi-agent object attention system is proposed, which is based on biologically inspired attractor selection model. Object attention is facilitated by using a video sequence and a depth map obtained through a compound-eye image sensor TOMBO. Robustness of the multi-agent system over environmental changes is enhanced by utilizing the biological model of adaptive response by attractor selection. To implement the proposed system, an efficient VLSI architecture is employed with reducing enormous computational costs and memory accesses required for depth map processing and multi-agent attractor selection process. According to the FPGA implementation result of the proposed object attention system, which is accomplished by using 7,063 slices, 640×512 pixel input images can be processed in real-time with three agents at a rate of 9fps in 48MHz operation.

Fabrication and Qualification of Coated Chip-on-Board Technology for Miniaturized Space Systems

NASA Technical Reports Server (NTRS)

Maurer, R. H.; Le, B. Q.; Nhan, E.; Lew, A. L.; Darrin, M. Ann Garrison

1997-01-01

The results of a study carried out in order to manufacture and verify the quality of chip-on-board (COB) packaging technology are presented. The COB, designed for space applications, was tested under environmental stresses, temperature cycling, and temperature-humidity-bias. Both robustness in space applications and in environmental protection on the ground-complete reliability without hermeticity were searched for. The epoxy-parylene combinations proved to be superior to other materials tested.

Approaches in highly parameterized inversion—PEST++ Version 3, a Parameter ESTimation and uncertainty analysis software suite optimized for large environmental models

USGS Publications Warehouse

Welter, David E.; White, Jeremy T.; Hunt, Randall J.; Doherty, John E.

2015-09-18

The PEST++ Version 3 software suite can be compiled for Microsoft Windows®4 and Linux®5 operating systems; the source code is available in a Microsoft Visual Studio®6 2013 solution; Linux Makefiles are also provided. PEST++ Version 3 continues to build a foundation for an open-source framework capable of producing robust and efficient parameter estimation tools for large environmental models.

Risk, Robustness and Water Resources Planning Under Uncertainty

NASA Astrophysics Data System (ADS)

Borgomeo, Edoardo; Mortazavi-Naeini, Mohammad; Hall, Jim W.; Guillod, Benoit P.

2018-03-01

Risk-based water resources planning is based on the premise that water managers should invest up to the point where the marginal benefit of risk reduction equals the marginal cost of achieving that benefit. However, this cost-benefit approach may not guarantee robustness under uncertain future conditions, for instance under climatic changes. In this paper, we expand risk-based decision analysis to explore possible ways of enhancing robustness in engineered water resources systems under different risk attitudes. Risk is measured as the expected annual cost of water use restrictions, while robustness is interpreted in the decision-theoretic sense as the ability of a water resource system to maintain performance—expressed as a tolerable risk of water use restrictions—under a wide range of possible future conditions. Linking risk attitudes with robustness allows stakeholders to explicitly trade-off incremental increases in robustness with investment costs for a given level of risk. We illustrate the framework through a case study of London's water supply system using state-of-the -art regional climate simulations to inform the estimation of risk and robustness.

An enhanced inertial navigation system based on a low-cost IMU and laser scanner

NASA Astrophysics Data System (ADS)

Kim, Hyung-Soon; Baeg, Seung-Ho; Yang, Kwang-Woong; Cho, Kuk; Park, Sangdeok

2012-06-01

This paper describes an enhanced fusion method for an Inertial Navigation System (INS) based on a 3-axis accelerometer sensor, a 3-axis gyroscope sensor and a laser scanner. In GPS-denied environments, indoor or dense forests, a pure INS odometry is available for estimating the trajectory of a human or robot. However it has a critical implementation problem: a drift error of velocity, position and heading angles. Commonly the problem can be solved by fusing visual landmarks, a magnetometer or radio beacons. These methods are not robust in diverse environments: darkness, fog or sunlight, an unstable magnetic field and an environmental obstacle. We propose to overcome the drift problem using an Iterative Closest Point (ICP) scan matching algorithm with a laser scanner. This system consists of three parts. The first is the INS. It estimates attitude, velocity, position based on a 6-axis Inertial Measurement Unit (IMU) with both 'Heuristic Reduction of Gyro Drift' (HRGD) and 'Heuristic Reduction of Velocity Drift' (HRVD) methods. A frame-to-frame ICP matching algorithm for estimating position and attitude by laser scan data is the second. The third is an extended kalman filter method for multi-sensor data fusing: INS and Laser Range Finder (LRF). The proposed method is simple and robust in diverse environments, so we could reduce the drift error efficiently. We confirm the result comparing an odometry of the experimental result with ICP and LRF aided-INS in a long corridor.

Uniting statistical and individual-based approaches for animal movement modelling.

PubMed

Latombe, Guillaume; Parrott, Lael; Basille, Mathieu; Fortin, Daniel

2014-01-01

The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems.

Uniting Statistical and Individual-Based Approaches for Animal Movement Modelling

PubMed Central

Latombe, Guillaume; Parrott, Lael; Basille, Mathieu; Fortin, Daniel

2014-01-01

The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems. PMID:24979047

Dynamic linear models using the Kalman filter for early detection and early warning of malaria outbreaks

NASA Astrophysics Data System (ADS)

Merkord, C. L.; Liu, Y.; DeVos, M.; Wimberly, M. C.

2015-12-01

Malaria early detection and early warning systems are important tools for public health decision makers in regions where malaria transmission is seasonal and varies from year to year with fluctuations in rainfall and temperature. Here we present a new data-driven dynamic linear model based on the Kalman filter with time-varying coefficients that are used to identify malaria outbreaks as they occur (early detection) and predict the location and timing of future outbreaks (early warning). We fit linear models of malaria incidence with trend and Fourier form seasonal components using three years of weekly malaria case data from 30 districts in the Amhara Region of Ethiopia. We identified past outbreaks by comparing the modeled prediction envelopes with observed case data. Preliminary results demonstrated the potential for improved accuracy and timeliness over commonly-used methods in which thresholds are based on simpler summary statistics of historical data. Other benefits of the dynamic linear modeling approach include robustness to missing data and the ability to fit models with relatively few years of training data. To predict future outbreaks, we started with the early detection model for each district and added a regression component based on satellite-derived environmental predictor variables including precipitation data from the Tropical Rainfall Measuring Mission (TRMM) and land surface temperature (LST) and spectral indices from the Moderate Resolution Imaging Spectroradiometer (MODIS). We included lagged environmental predictors in the regression component of the model, with lags chosen based on cross-correlation of the one-step-ahead forecast errors from the first model. Our results suggest that predictions of future malaria outbreaks can be improved by incorporating lagged environmental predictors.

Towards a universal trait-based model of terrestrial primary production

NASA Astrophysics Data System (ADS)

Wang, H.; Prentice, I. C.; Cornwell, W.; Keenan, T. F.; Davis, T.; Wright, I. J.; Evans, B. J.; Peng, C.

2015-12-01

Systematic variations of plant traits along environmental gradients have been observed for decades. For example, the tendencies of leaf nitrogen per unit area to increase, and of the leaf-internal to ambient CO2 concentration ratio (ci:ca) to decrease, with aridity are well established. But ecosystem models typically represent trait variation based purely on empirical relationships, or on untested conjectures, or not at all. Neglect of quantitative trait variation and its adapative significance probably contributes to the persistent large uncertainties among models in predicting the response of the carbon cycle to environmental change. However, advances in ecological theory and the accumulation of extensive data sets during recent decades suggest that theoretically based and testable predictions of trait variation could be achieved. Based on well-established ecophysiological principles and consideration of the adaptive significance of traits, we propose universal relationships between photosynthetic traits (ci:ca, carbon fixation capacity, and the ratio of electron transport capacity to carbon fixation capacity) and primary environmental variables, which capture observed trait variations both within and between plant functional types. Moreover, incorporating these traits into the standard model of C3photosynthesis allows gross primary production (GPP) of natural vegetation to be predicted by a single equation with just two free parameters, which can be estimated from independent observations. The resulting model performs as well as much more complex models. Our results provide a fresh perspective with potentially high reward: the possibility of a deeper understanding of the relationships between plant traits and environment, simpler and more robust and reliable representation of land processes in Earth system models, and thus improved predictability for biosphere-atmosphere interactions and climate feedbacks.

Development of environmental impact monitoring protocol for offshore carbon capture and storage (CCS): A biological perspective

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

Kim, Hyewon, E-mail: hyewon@ldeo.columbia.edu; Kim, Yong Hoon, E-mail: Yong.Kim@rpsgroup.com; Kang, Seong-Gil, E-mail: kangsg@kriso.re.kr

Offshore geologic storage of carbon dioxide (CO{sub 2}), known as offshore carbon capture and sequestration (CCS), has been under active investigation as a safe, effective mitigation option for reducing CO{sub 2} levels from anthropogenic fossil fuel burning and climate change. Along with increasing trends in implementation plans and related logistics on offshore CCS, thorough risk assessment (i.e. environmental impact monitoring) needs to be conducted to evaluate potential risks, such as CO{sub 2} gas leakage at injection sites. Gas leaks from offshore CCS may affect the physiology of marine organisms and disrupt certain ecosystem functions, thereby posing an environmental risk. Here,more » we synthesize current knowledge on environmental impact monitoring of offshore CCS with an emphasis on biological aspects and provide suggestions for better practice. Based on our critical review of preexisting literatures, this paper: 1) discusses key variables sensitive to or indicative of gas leakage by summarizing physico-chemical and ecological variables measured from previous monitoring cruises on offshore CCS; 2) lists ecosystem and organism responses to a similar environmental condition to CO{sub 2} leakage and associated impacts, such as ocean acidification and hypercapnia, to predict how they serve as responsive indicators of short- and long-term gas exposure, and 3) discusses the designs of the artificial gas release experiments in fields and the best model simulation to produce realistic leakage scenarios in marine ecosystems. Based on our analysis, we suggest that proper incorporation of biological aspects will provide successful and robust long-term monitoring strategies with earlier detection of gas leakage, thus reducing the risks associated with offshore CCS. - Highlights: • This paper synthesizes the current knowledge on environmental impact monitoring of offshore Carbon Capture and Sequestration (CCS). • Impacts of CO{sub 2} leakage (ocean acidification, hypercapnia) on marine organisms and ecosystems are discussed. • Insights and recommendations on EIA monitoring for CCS operations are proposed specifically in marine ecosystem perspective.« less

Proposal of an environmental performance index to assess solid waste treatment technologies

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

Goulart Coelho, Hosmanny Mauro, E-mail: hosmanny@hotmail.com; Lange, Lisete Celina; Coelho, Lineker Max Goulart

2012-07-15

Highlights: Black-Right-Pointing-Pointer Proposal of a new concept in waste management: Cleaner Treatment. Black-Right-Pointing-Pointer Development of an index to assess quantitatively waste treatment technologies. Black-Right-Pointing-Pointer Delphi Method was carried out so as to define environmental indicators. Black-Right-Pointing-Pointer Environmental performance evaluation of waste-to-energy plants. - Abstract: Although the concern with sustainable development and environment protection has considerably grown in the last years it is noted that the majority of decision making models and tools are still either excessively tied to economic aspects or geared to the production process. Moreover, existing models focus on the priority steps of solid waste management, beyond wastemore » energy recovery and disposal. So, in order to help the lack of models and tools aiming at the waste treatment and final disposal, a new concept is proposed: the Cleaner Treatment, which is based on the Cleaner Production principles. This paper focuses on the development and validation of the Cleaner Treatment Index (CTI), to assess environmental performance of waste treatment technologies based on the Cleaner Treatment concept. The index is formed by aggregation (summation or product) of several indicators that consists in operational parameters. The weights of the indicator were established by Delphi Method and Brazilian Environmental Laws. In addition, sensitivity analyses were carried out comparing both aggregation methods. Finally, index validation was carried out by applying the CTI to 10 waste-to-energy plants data. From sensitivity analysis and validation results it is possible to infer that summation model is the most suitable aggregation method. For summation method, CTI results were superior to 0.5 (in a scale from 0 to 1) for most facilities evaluated. So, this study demonstrates that CTI is a simple and robust tool to assess and compare the environmental performance of different treatment plants being an excellent quantitative tool to support Cleaner Treatment implementation.« less

Development of Advanced Thermal and Environmental Barrier Coatings Using a High-Heat-Flux Testing Approach

NASA Technical Reports Server (NTRS)

Zhu, Dongming; Miller, Robert A.

2003-01-01

The development of low conductivity, robust thermal and environmental barrier coatings requires advanced testing techniques that can accurately and effectively evaluate coating thermal conductivity and cyclic resistance at very high surface temperatures (up to 1700 C) under large thermal gradients. In this study, a laser high-heat-flux test approach is established for evaluating advanced low conductivity, high temperature capability thermal and environmental barrier coatings under the NASA Ultra Efficient Engine Technology (UEET) program. The test approach emphasizes the real-time monitoring and assessment of the coating thermal conductivity, which initially rises under the steady-state high temperature thermal gradient test due to coating sintering, and later drops under the cyclic thermal gradient test due to coating cracking/delamination. The coating system is then evaluated based on damage accumulation and failure after the combined steady-state and cyclic thermal gradient tests. The lattice and radiation thermal conductivity of advanced ceramic coatings can also be evaluated using laser heat-flux techniques. The external radiation resistance of the coating is assessed based on the measured specimen temperature response under a laser- heated intense radiation-flux source. The coating internal radiation contribution is investigated based on the measured apparent coating conductivity increases with the coating surface test temperature under large thermal gradient test conditions. Since an increased radiation contribution is observed at these very high surface test temperatures, by varying the laser heat-flux and coating average test temperature, the complex relation between the lattice and radiation conductivity as a function of surface and interface test temperature may be derived.

A fuzzy stochastic framework for managing hydro-environmental and socio-economic interactions under uncertainty

NASA Astrophysics Data System (ADS)

Subagadis, Yohannes Hagos; Schütze, Niels; Grundmann, Jens

2014-05-01

An amplified interconnectedness between a hydro-environmental and socio-economic system brings about profound challenges of water management decision making. In this contribution, we present a fuzzy stochastic approach to solve a set of decision making problems, which involve hydrologically, environmentally, and socio-economically motivated criteria subjected to uncertainty and ambiguity. The proposed methodological framework combines objective and subjective criteria in a decision making procedure for obtaining an acceptable ranking in water resources management alternatives under different type of uncertainty (subjective/objective) and heterogeneous information (quantitative/qualitative) simultaneously. The first step of the proposed approach involves evaluating the performance of alternatives with respect to different types of criteria. The ratings of alternatives with respect to objective and subjective criteria are evaluated by simulation-based optimization and fuzzy linguistic quantifiers, respectively. Subjective and objective uncertainties related to the input information are handled through linking fuzziness and randomness together. Fuzzy decision making helps entail the linguistic uncertainty and a Monte Carlo simulation process is used to map stochastic uncertainty. With this framework, the overall performance of each alternative is calculated using an Order Weighted Averaging (OWA) aggregation operator accounting for decision makers' experience and opinions. Finally, ranking is achieved by conducting pair-wise comparison of management alternatives. This has been done on the basis of the risk defined by the probability of obtaining an acceptable ranking and mean difference in total performance for the pair of management alternatives. The proposed methodology is tested in a real-world hydrosystem, to find effective and robust intervention strategies for the management of a coastal aquifer system affected by saltwater intrusion due to excessive groundwater extraction for irrigated agriculture and municipal use. The results show that the approach gives useful support for robust decision-making and is sensitive to the decision makers' degree of optimism.

Miniaturised Space Payloads for Outdoor Environmental Applications

NASA Astrophysics Data System (ADS)

de Souza, P. A.

2012-12-01

The need for portable, robust and acurate sensors has increased in recent years resulting from industrial and environmental needs. This paper describes a number of applications of engineering copies of those Moessbauer spectrometers (MIMOS II) used by Mars Exploration Rovers, and the use of portable XRF spectrometers in the analysis of heavy metals in sediments. MIMOS II has been applied in the characterisation of Fe-bearing phases in airborne particles in industrialised urban centres, The results have allowed an identification of sources or air pollution in near-real-time. The results help to combine production parameters with pollution impact in the urban area. MIMOS II became a powerful tool because its constructive requirements to flight has produced a robust, power efficient, miniaturised, and light. On the limitation side, the technique takes sometime to produce a good result and the instrument requires a radioactive source to operate. MIMOS II Team has reported a new generation of this instrument incorporating a XRF spectrometer using the radioactive source to generate fluorescence emissions from sample. The author, and its research group, adapted a portable XRF spectrometer to an autonomous underwater vehicle (AUV) and conducted heavy metals survey in sediments across the Derwent Estuary in Tasmania, Australia. The AUV lands on suitable locations underwater, makes the chemical analysis and decide based on the result to move to a closer location, should high concentration of chemicals of interest be found, or to another distant location otherwise. Beyond environmental applications, these instruments were applied in archaeology and in industrial process control.oessbauer spectra recorded on airborne particles (Total Suspended Particles) collected at Ilha do Boi, VItoria, ES, Brazil. SIRO's Autonomous Underwater Vehicle carring a miniaturised XRF spectrometer for underwater chemistry. Students involved in this Project: Mr Jeremy Breen and Mr Andrew Davie. Collaborators: Dr. Greg Timms (CSIRO) and Dr. Robert Ollington (UTAS). This AUV us 1.2m long.

“Smart” Materials Based on Cellulose: A Review of the Preparations, Properties, and Applications

PubMed Central

Qiu, Xiaoyun; Hu, Shuwen

2013-01-01

Cellulose is the most abundant biomass material in nature, and possesses some promising properties, such as mechanical robustness, hydrophilicity, biocompatibility, and biodegradability. Thus, cellulose has been widely applied in many fields. “Smart” materials based on cellulose have great advantages—especially their intelligent behaviors in reaction to environmental stimuli—and they can be applied to many circumstances, especially as biomaterials. This review aims to present the developments of “smart” materials based on cellulose in the last decade, including the preparations, properties, and applications of these materials. The preparations of “smart” materials based on cellulose by chemical modifications and physical incorporating/blending were reviewed. The responsiveness to pH, temperature, light, electricity, magnetic fields, and mechanical forces, etc. of these “smart” materials in their different forms such as copolymers, nanoparticles, gels, and membranes were also reviewed, and the applications as drug delivery systems, hydrogels, electronic active papers, sensors, shape memory materials and smart membranes, etc. were also described in this review. PMID:28809338

Stakeholder value-linked sustainability assessment: Evaluating remedial alternatives for the Portland Harbor Superfund Site, Portland, Oregon, USA.

PubMed

Apitz, Sabine E; Fitzpatrick, Anne G; McNally, Amanda; Harrison, David; Coughlin, Conor; Edwards, Deborah A

2018-01-01

Regulatory decisions on remediation should consider affected communities' needs and values, and how these might be impacted by remedial options; this process requires that diverse stakeholders are able to engage in a transparent consideration of value trade-offs and of the distribution of risks and benefits associated with remedial actions and outcomes. The Stakeholder Values Assessment (SVA) tool was developed to evaluate remedial impacts on environmental quality, economic viability, and social equity in the context of stakeholder values and priorities. Stakeholder values were linked to the pillars of sustainability and also to a range of metrics to evaluate how sediment remediation affects these values. Sediment remedial alternatives proposed by the US Environmental Protection Agency (USEPA) for the Portland Harbor Superfund Site were scored for each metric, based upon data provided in published feasibility study (FS) documents. Metric scores were aggregated to generate scores for each value; these were then aggregated to generate scores for each pillar of sustainability. In parallel, the inferred priorities (in terms of regional remediation, restoration, planning, and development) of diverse stakeholder groups (SGs) were used to evaluate the sensitivity and robustness of the values-based sustainability assessment to diverse SG priorities. This approach, which addresses social indicators of impact and then integrates them with indicators of environmental and economic impacts, goes well beyond the Comprehensive Environmental Response, Compensation and Liability Act's (CERCLA) 9 criteria for evaluating remedial alternatives because it evaluates how remedial alternatives might be ranked in terms of the diverse values and priorities of stakeholders. This approach identified trade-offs and points of potential contention, providing a systematic, semiquantitative, transparent valuation tool that can be used in community engagement. Integr Environ Assess Manag 2018;14:43-62. © 2017 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC). © 2017 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Integrating malaria surveillance with climate data for outbreak detection and forecasting: the EPIDEMIA system.

PubMed

Merkord, Christopher L; Liu, Yi; Mihretie, Abere; Gebrehiwot, Teklehaymanot; Awoke, Worku; Bayabil, Estifanos; Henebry, Geoffrey M; Kassa, Gebeyaw T; Lake, Mastewal; Wimberly, Michael C

2017-02-23

Early indication of an emerging malaria epidemic can provide an opportunity for proactive interventions. Challenges to the identification of nascent malaria epidemics include obtaining recent epidemiological surveillance data, spatially and temporally harmonizing this information with timely data on environmental precursors, applying models for early detection and early warning, and communicating results to public health officials. Automated web-based informatics systems can provide a solution to these problems, but their implementation in real-world settings has been limited. The Epidemic Prognosis Incorporating Disease and Environmental Monitoring for Integrated Assessment (EPIDEMIA) computer system was designed and implemented to integrate disease surveillance with environmental monitoring in support of operational malaria forecasting in the Amhara region of Ethiopia. A co-design workshop was held with computer scientists, epidemiological modelers, and public health partners to develop an initial list of system requirements. Subsequent updates to the system were based on feedback obtained from system evaluation workshops and assessments conducted by a steering committee of users in the public health sector. The system integrated epidemiological data uploaded weekly by the Amhara Regional Health Bureau with remotely-sensed environmental data freely available from online archives. Environmental data were acquired and processed automatically by the EASTWeb software program. Additional software was developed to implement a public health interface for data upload and download, harmonize the epidemiological and environmental data into a unified database, automatically update time series forecasting models, and generate formatted reports. Reporting features included district-level control charts and maps summarizing epidemiological indicators of emerging malaria outbreaks, environmental risk factors, and forecasts of future malaria risk. Successful implementation and use of EPIDEMIA is an important step forward in the use of epidemiological and environmental informatics systems for malaria surveillance. Developing software to automate the workflow steps while remaining robust to continual changes in the input data streams was a key technical challenge. Continual stakeholder involvement throughout design, implementation, and operation has created a strong enabling environment that will facilitate the ongoing development, application, and testing of the system.

Robust Inference of Risks of Large Portfolios

PubMed Central

Fan, Jianqing; Han, Fang; Liu, Han; Vickers, Byron

2016-01-01

We propose a bootstrap-based robust high-confidence level upper bound (Robust H-CLUB) for assessing the risks of large portfolios. The proposed approach exploits rank-based and quantile-based estimators, and can be viewed as a robust extension of the H-CLUB procedure (Fan et al., 2015). Such an extension allows us to handle possibly misspecified models and heavy-tailed data, which are stylized features in financial returns. Under mixing conditions, we analyze the proposed approach and demonstrate its advantage over H-CLUB. We further provide thorough numerical results to back up the developed theory, and also apply the proposed method to analyze a stock market dataset. PMID:27818569

Robust optimization in lung treatment plans accounting for geometric uncertainty.

PubMed

Zhang, Xin; Rong, Yi; Morrill, Steven; Fang, Jian; Narayanasamy, Ganesh; Galhardo, Edvaldo; Maraboyina, Sanjay; Croft, Christopher; Xia, Fen; Penagaricano, Jose

2018-05-01

Robust optimization generates scenario-based plans by a minimax optimization method to find optimal scenario for the trade-off between target coverage robustness and organ-at-risk (OAR) sparing. In this study, 20 lung cancer patients with tumors located at various anatomical regions within the lungs were selected and robust optimization photon treatment plans including intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) plans were generated. The plan robustness was analyzed using perturbed doses with setup error boundary of ±3 mm in anterior/posterior (AP), ±3 mm in left/right (LR), and ±5 mm in inferior/superior (IS) directions from isocenter. Perturbed doses for D 99 , D 98 , and D 95 were computed from six shifted isocenter plans to evaluate plan robustness. Dosimetric study was performed to compare the internal target volume-based robust optimization plans (ITV-IMRT and ITV-VMAT) and conventional PTV margin-based plans (PTV-IMRT and PTV-VMAT). The dosimetric comparison parameters were: ITV target mean dose (D mean ), R 95 (D 95 /D prescription ), Paddick's conformity index (CI), homogeneity index (HI), monitor unit (MU), and OAR doses including lung (D mean , V 20 Gy and V 15 Gy ), chest wall, heart, esophagus, and maximum cord doses. A comparison of optimization results showed the robust optimization plan had better ITV dose coverage, better CI, worse HI, and lower OAR doses than conventional PTV margin-based plans. Plan robustness evaluation showed that the perturbed doses of D 99 , D 98 , and D 95 were all satisfied at least 99% of the ITV to received 95% of prescription doses. It was also observed that PTV margin-based plans had higher MU than robust optimization plans. The results also showed robust optimization can generate plans that offer increased OAR sparing, especially for normal lungs and OARs near or abutting the target. Weak correlation was found between normal lung dose and target size, and no other correlation was observed in this study. © 2018 University of Arkansas for Medical Sciences. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

A UNIFYING CONCEPT FOR ASSESSING TOXICOLOGICAL INTERACTIONS: CHANGES IN SLOPE

EPA Science Inventory

Robust statistical methods are important to the evaluation of interactions among chemicals in a mixture. However, different concepts of interaction as applied to the statistical analysis of chemical mixture toxicology data or as used in environmental risk assessment often can ap...

ROBUSTNESS OF SIGNALING GRADIENT IN DROSOPHILA WING IMAGINAL DISC

PubMed Central

Lei, Jinzhi; Wan, Frederic Y. M.; Lander, Arthur D.; Nie, Qing

2012-01-01

Quasi-stable gradients of signaling protein molecules (known as morphogens or ligands) bound to cell receptors are known to be responsible for differential cell signaling and gene expressions. From these follow different stable cell fates and visually patterned tissues in biological development. Recent studies have shown that the relevant basic biological processes yield gradients that are sensitive to small changes in system characteristics (such as expression level of morphogens or receptors) or environmental conditions (such as temperature changes). Additional biological activities must play an important role in the high level of robustness observed in embryonic patterning for example. It is natural to attribute observed robustness to various type of feedback control mechanisms. However, our own simulation studies have shown that feedback control is neither necessary nor sufficient for robustness of the morphogen decapentaplegic (Dpp) gradient in wing imaginal disc of Drosophilas. Furthermore, robustness can be achieved by substantial binding of the signaling morphogen Dpp with nonsignaling cell surface bound molecules (such as heparan sulfate proteoglygans) and degrading the resulting complexes at a sufficiently rapid rate. The present work provides a theoretical basis for the results of our numerical simulation studies. PMID:24098092

Recurrence quantification analysis to characterize cyclical components of environmental elemental exposures during fetal and postnatal development

PubMed Central

Austin, Christine; Gennings, Chris; Tammimies, Kristiina; Bölte, Sven; Arora, Manish

2017-01-01

Environmental exposures to essential and toxic elements may alter health trajectories, depending on the timing, intensity, and mixture of exposures. In epidemiologic studies, these factors are typically analyzed as a function of elemental concentrations in biological matrices measured at one or more points in time. Such an approach, however, fails to account for the temporal cyclicity in the metabolism of environmental chemicals, which if perturbed may lead to adverse health outcomes. Here, we conceptualize and apply a non-linear method–recurrence quantification analysis (RQA)–to quantify cyclical components of prenatal and early postnatal exposure profiles for elements essential to normal development, including Zn, Mn, Mg, and Ca, and elements associated with deleterious health effects or narrow tolerance ranges, including Pb, As, and Cr. We found robust evidence of cyclical patterns in the metabolic profiles of nutrient elements, which we validated against randomized twin-surrogate time-series, and further found that nutrient dynamical properties differ from those of Cr, As, and Pb. Furthermore, we extended this approach to provide a novel method of quantifying dynamic interactions between two environmental exposures. To achieve this, we used cross-recurrence quantification analysis (CRQA), and found that elemental nutrient-nutrient interactions differed from those involving toxicants. These rhythmic regulatory interactions, which we characterize in two geographically distinct cohorts, have not previously been uncovered using traditional regression-based approaches, and may provide a critical unit of analysis for environmental and dietary exposures in epidemiological studies. PMID:29112980

Chemical speciation of heavy metals by surface-enhanced Raman scattering spectroscopy: identification and quantification of inorganic- and methyl-mercury in water

NASA Astrophysics Data System (ADS)

Guerrini, Luca; Rodriguez-Loureiro, Ignacio; Correa-Duarte, Miguel A.; Lee, Yih Hong; Ling, Xing Yi; García de Abajo, F. Javier; Alvarez-Puebla, Ramon A.

2014-06-01

Chemical speciation of heavy metals has become extremely important in environmental and analytical research because of the strong dependence that toxicity, environmental mobility, persistence and bioavailability of these pollutants have on their specific chemical forms. Novel nano-optical-based detection strategies, capable of overcoming the intrinsic limitations of well-established analytic methods for the quantification of total metal ion content, have been reported, but the speciation of different chemical forms has not yet been achieved. Here, we report the first example of a SERS-based sensor for chemical speciation of toxic metal ions in water at trace levels. Specifically, the inorganic Hg2+ and the more toxicologically relevant methylmercury (CH3Hg+) are selected as analytical targets. The sensing platform consists of a self-assembled monolayer of 4-mercaptopyridine (MPY) on highly SERS-active and robust hybrid plasmonic materials formed by a dense layer of interacting gold nanoparticles anchored onto polystyrene microbeads. The co-ordination of Hg2+ and CH3Hg+ to the nitrogen atom of the MPY ring yields characteristic changes in the vibrational SERS spectra of the organic chemoreceptor that can be qualitatively and quantitatively correlated to the presence of the two different mercury forms.Chemical speciation of heavy metals has become extremely important in environmental and analytical research because of the strong dependence that toxicity, environmental mobility, persistence and bioavailability of these pollutants have on their specific chemical forms. Novel nano-optical-based detection strategies, capable of overcoming the intrinsic limitations of well-established analytic methods for the quantification of total metal ion content, have been reported, but the speciation of different chemical forms has not yet been achieved. Here, we report the first example of a SERS-based sensor for chemical speciation of toxic metal ions in water at trace levels. Specifically, the inorganic Hg2+ and the more toxicologically relevant methylmercury (CH3Hg+) are selected as analytical targets. The sensing platform consists of a self-assembled monolayer of 4-mercaptopyridine (MPY) on highly SERS-active and robust hybrid plasmonic materials formed by a dense layer of interacting gold nanoparticles anchored onto polystyrene microbeads. The co-ordination of Hg2+ and CH3Hg+ to the nitrogen atom of the MPY ring yields characteristic changes in the vibrational SERS spectra of the organic chemoreceptor that can be qualitatively and quantitatively correlated to the presence of the two different mercury forms. Electronic supplementary information (ESI) available: Representative TEM and ESEM images of AuNPs and PS@Au particles. Optical extinction spectra of AuNPs and PS@Au suspensions. SERS spectra of unmodified PS@Au suspension before and after the addition of CH3Hg+. SERS spectra of PS@Au-MPY upon addition of several metal solutions. Detailed SERS study of the MPY response to high concentration of CH3Hg+. See DOI: 10.1039/c4nr01464b

The developmental genetics of biological robustness

PubMed Central

Mestek Boukhibar, Lamia; Barkoulas, Michalis

2016-01-01

Background Living organisms are continuously confronted with perturbations, such as environmental changes that include fluctuations in temperature and nutrient availability, or genetic changes such as mutations. While some developmental systems are affected by such challenges and display variation in phenotypic traits, others continue consistently to produce invariable phenotypes despite perturbation. This ability of a living system to maintain an invariable phenotype in the face of perturbations is termed developmental robustness. Biological robustness is a phenomenon observed across phyla, and studying its mechanisms is central to deciphering the genotype–phenotype relationship. Recent work in yeast, animals and plants has shown that robustness is genetically controlled and has started to reveal the underlying mechinisms behind it. Scope and Conclusions Studying biological robustness involves focusing on an important property of developmental traits, which is the phenotypic distribution within a population. This is often neglected because the vast majority of developmental biology studies instead focus on population aggregates, such as trait averages. By drawing on findings in animals and yeast, this Viewpoint considers how studies on plant developmental robustness may benefit from strict definitions of what is the developmental system of choice and what is the relevant perturbation, and also from clear distinctions between gene effects on the trait mean and the trait variance. Recent advances in quantitative developmental biology and high-throughput phenotyping now allow the design of targeted genetic screens to identify genes that amplify or restrict developmental trait variance and to study how variation propagates across different phenotypic levels in biological systems. The molecular characterization of more quantitative trait loci affecting trait variance will provide further insights into the evolution of genes modulating developmental robustness. The study of robustness mechanisms in closely related species will address whether mechanisms of robustness are evolutionarily conserved. PMID:26292993

Comparisons of Robustness and Sensitivity between Cancer and Normal Cells by Microarray Data

PubMed Central

Chu, Liang-Hui; Chen, Bor-Sen

2008-01-01

Robustness is defined as the ability to uphold performance in face of perturbations and uncertainties, and sensitivity is a measure of the system deviations generated by perturbations to the system. While cancer appears as a robust but fragile system, few computational and quantitative evidences demonstrate robustness tradeoffs in cancer. Microarrays have been widely applied to decipher gene expression signatures in human cancer research, and quantification of global gene expression profiles facilitates precise prediction and modeling of cancer in systems biology. We provide several efficient computational methods based on system and control theory to compare robustness and sensitivity between cancer and normal cells by microarray data. Measurement of robustness and sensitivity by linear stochastic model is introduced in this study, which shows oscillations in feedback loops of p53 and demonstrates robustness tradeoffs that cancer is a robust system with some extreme fragilities. In addition, we measure sensitivity of gene expression to perturbations in other gene expression and kinetic parameters, discuss nonlinear effects in feedback loops of p53 and extend our method to robustness-based cancer drug design. PMID:19259409

Efficient Robust Optimization of Metal Forming Processes using a Sequential Metamodel Based Strategy

NASA Astrophysics Data System (ADS)

Wiebenga, J. H.; Klaseboer, G.; van den Boogaard, A. H.

2011-08-01

The coupling of Finite Element (FE) simulations to mathematical optimization techniques has contributed significantly to product improvements and cost reductions in the metal forming industries. The next challenge is to bridge the gap between deterministic optimization techniques and the industrial need for robustness. This paper introduces a new and generally applicable structured methodology for modeling and solving robust optimization problems. Stochastic design variables or noise variables are taken into account explicitly in the optimization procedure. The metamodel-based strategy is combined with a sequential improvement algorithm to efficiently increase the accuracy of the objective function prediction. This is only done at regions of interest containing the optimal robust design. Application of the methodology to an industrial V-bending process resulted in valuable process insights and an improved robust process design. Moreover, a significant improvement of the robustness (>2σ) was obtained by minimizing the deteriorating effects of several noise variables. The robust optimization results demonstrate the general applicability of the robust optimization strategy and underline the importance of including uncertainty and robustness explicitly in the numerical optimization procedure.

A scoring mechanism for the rank aggregation of network robustness

NASA Astrophysics Data System (ADS)

Yazdani, Alireza; Dueñas-Osorio, Leonardo; Li, Qilin

2013-10-01

To date, a number of metrics have been proposed to quantify inherent robustness of network topology against failures. However, each single metric usually only offers a limited view of network vulnerability to different types of random failures and targeted attacks. When applied to certain network configurations, different metrics rank network topology robustness in different orders which is rather inconsistent, and no single metric fully characterizes network robustness against different modes of failure. To overcome such inconsistency, this work proposes a multi-metric approach as the basis of evaluating aggregate ranking of network topology robustness. This is based on simultaneous utilization of a minimal set of distinct robustness metrics that are standardized so to give way to a direct comparison of vulnerability across networks with different sizes and configurations, hence leading to an initial scoring of inherent topology robustness. Subsequently, based on the inputs of initial scoring a rank aggregation method is employed to allocate an overall ranking of robustness to each network topology. A discussion is presented in support of the presented multi-metric approach and its applications to more realistically assess and rank network topology robustness.

Robust consensus algorithm for multi-agent systems with exogenous disturbances under convergence conditions

NASA Astrophysics Data System (ADS)

Jiang, Yulian; Liu, Jianchang; Tan, Shubin; Ming, Pingsong

2014-09-01

In this paper, a robust consensus algorithm is developed and sufficient conditions for convergence to consensus are proposed for a multi-agent system (MAS) with exogenous disturbances subject to partial information. By utilizing H∞ robust control, differential game theory and a design-based approach, the consensus problem of the MAS with exogenous bounded interference is resolved and the disturbances are restrained, simultaneously. Attention is focused on designing an H∞ robust controller (the robust consensus algorithm) based on minimisation of our proposed rational and individual cost functions according to goals of the MAS. Furthermore, sufficient conditions for convergence of the robust consensus algorithm are given. An example is employed to demonstrate that our results are effective and more capable to restrain exogenous disturbances than the existing literature.

(Q)SARs to predict environmental toxicities: current status and future needs.

PubMed

Cronin, Mark T D

2017-03-22

The current state of the art of (Quantitative) Structure-Activity Relationships ((Q)SARs) to predict environmental toxicity is assessed along with recommendations to develop these models further. The acute toxicity of compounds acting by the non-polar narcotic mechanism of action can be well predicted, however other approaches, including read-across, may be required for compounds acting by specific mechanisms of action. The chronic toxicity of compounds to environmental species is more difficult to predict from (Q)SARs, with robust data sets and more mechanistic information required. In addition, the toxicity of mixtures is little addressed by (Q)SAR approaches. Developments in environmental toxicology including Adverse Outcome Pathways (AOPs) and omics responses should be utilised to develop better, more mechanistically relevant, (Q)SAR models.

Robust Global Image Registration Based on a Hybrid Algorithm Combining Fourier and Spatial Domain Techniques

DTIC Science & Technology

2012-09-01

Robust global image registration based on a hybrid algorithm combining Fourier and spatial domain techniques Peter N. Crabtree, Collin Seanor...00-00-2012 to 00-00-2012 4. TITLE AND SUBTITLE Robust global image registration based on a hybrid algorithm combining Fourier and spatial domain...demonstrate performance of a hybrid algorithm . These results are from analysis of a set of images of an ISO 12233 [12] resolution chart captured in the

Advanced Ceramic Matrix Composites (CMCs) for High Temperature Applications

NASA Technical Reports Server (NTRS)

Singh, M.

2005-01-01

Advanced ceramic matrix composites (CMCs) are enabling materials for a number of demanding applications in aerospace, energy, and nuclear industries. In the aerospace systems, these materials are being considered for applications in hot sections of jet engines such as the combustor liner, vanes, nozzle components, nose cones, leading edges of reentry vehicles, and space propulsion components. Applications in the energy and environmental industries include radiant heater tubes, heat exchangers, heat recuperators, gas and diesel particulate filters, and components for land based turbines for power generation. These materials are also being considered for use in the first wall and blanket components of fusion reactors. In the last few years, a number of CMC components have been developed and successfully tested for various aerospace and ground based applications. However, a number of challenges still remain slowing the wide scale implementation of these materials. They include robust fabrication and manufacturing, assembly and integration, coatings, property modeling and life prediction, design codes and databases, repair and refurbishment, and cost. Fabrication of net and complex shape components with high density and tailorable matrix properties is quite expensive, and even then various desirable properties are not achievable. In this presentation, a number of examples of successful CMC component development and testing will be provided. In addition, critical need for robust manufacturing, joining and assembly technologies in successful implementation of these systems will be discussed.

A robust damage-detection technique with environmental variability combining time-series models with principal components

NASA Astrophysics Data System (ADS)

Lakshmi, K.; Rama Mohan Rao, A.

2014-10-01

In this paper, a novel output-only damage-detection technique based on time-series models for structural health monitoring in the presence of environmental variability and measurement noise is presented. The large amount of data obtained in the form of time-history response is transformed using principal component analysis, in order to reduce the data size and thereby improve the computational efficiency of the proposed algorithm. The time instant of damage is obtained by fitting the acceleration time-history data from the structure using autoregressive (AR) and AR with exogenous inputs time-series prediction models. The probability density functions (PDFs) of damage features obtained from the variances of prediction errors corresponding to references and healthy current data are found to be shifting from each other due to the presence of various uncertainties such as environmental variability and measurement noise. Control limits using novelty index are obtained using the distances of the peaks of the PDF curves in healthy condition and used later for determining the current condition of the structure. Numerical simulation studies have been carried out using a simply supported beam and also validated using an experimental benchmark data corresponding to a three-storey-framed bookshelf structure proposed by Los Alamos National Laboratory. Studies carried out in this paper clearly indicate the efficiency of the proposed algorithm for damage detection in the presence of measurement noise and environmental variability.

Development and validation of an ELISA kit for the detection of ricin toxins from biological specimens and environmental samples.

PubMed

Chen, Hsiao Ying; Tran, Hung; Foo, Ling Yann; Sew, Tracey Wenhui; Loke, Weng Keong

2014-08-01

Ricin is a toxin that can be easily extracted from seeds of Ricinus communis plants. Ricin is considered to be a major bio-threat as it can be freely and easily acquired in large quantities. A deliberate release of such toxin in civilian populations would very likely overwhelm existing public health systems, resulting in public fear and social unrest. There is currently no commercially available or FDA-approved prophylaxis such as vaccines, or therapeutic antitoxins or antidotes, available for ricin intoxication. Patient treatment is typically supportive care based on symptoms, often designed to reinforce the body's natural response. This paper describes the development and validation of a robust ELISA test kit, which can be used to screen for ricin in biological specimens such as whole blood and faeces. Faecal specimens are shown in this study to have better diagnostic sensitivity and a wider diagnostic window compared to whole blood. From these results, it is concluded that faeces is the most suitable clinical specimen for diagnosis of ricin poisoning via the oral route. The ELISA test kit can also detect ricin in environmental samples. An advantage of this ELISA kit over other commercial off-the-shelf (COTS) detection kits currently on the market that are developed to screen environmental samples only is its ability to diagnose ricin poisoning from clinical specimens as well as detect ricin from environmental samples.

Would environmental pollution affect home prices? An empirical study based on China's key cities.

PubMed

Hao, Yu; Zheng, Shaoqing

2017-11-01

With the development of China's economy, the problem of environmental pollution has become increasingly more serious, affecting the sustained and healthy development of Chinese cities and the willingness of residents to invest in fixed assets. In this paper, a panel data set of 70 of China's key cities from 2003 to 2014 is used to study the effect of environmental pollution on home prices in China's key cities. In addition to the static panel data regression model, this paper uses the generalized method of moments (GMM) to control for the potential endogeneity and introduce the dynamics. To ensure the robustness of the research results, this paper uses four typical pollutants: per capita volume of SO 2 emissions, industrial soot (dust) emissions, industrial wastewater discharge, and industrial chemical oxygen demand discharge. The analysis shows that environmental pollution does have a negative impact on home prices, and the magnitude of this effect is dependent on the level of economic development. When GDP per capita increases, the size of the negative impact on home prices tends to reduce. Industrial soot (dust) has the greatest impact, and the impact of industrial wastewater is relatively small. It is also found that some other social and economic factors, including greening, public transport, citizen income, fiscal situation, loans, FDI, and population density, have positive effects on home prices, but the effect of employment on home prices is relatively weak.

Steroid hormones in environmental matrices: extraction method comparison.

PubMed

Andaluri, Gangadhar; Suri, Rominder P S; Graham, Kendon

2017-11-09

The U.S. Environmental Protection Agency (EPA) has developed methods for the analysis of steroid hormones in water, soil, sediment, and municipal biosolids by HRGC/HRMS (EPA Method 1698). Following the guidelines provided in US-EPA Method 1698, the extraction methods were validated with reagent water and applied to municipal wastewater, surface water, and municipal biosolids using GC/MS/MS for the analysis of nine most commonly detected steroid hormones. This is the first reported comparison of the separatory funnel extraction (SFE), continuous liquid-liquid extraction (CLLE), and Soxhlet extraction methods developed by the U.S. EPA. Furthermore, a solid phase extraction (SPE) method was also developed in-house for the extraction of steroid hormones from aquatic environmental samples. This study provides valuable information regarding the robustness of the different extraction methods. Statistical analysis of the data showed that SPE-based methods provided better recovery efficiencies and lower variability of the steroid hormones followed by SFE. The analytical methods developed in-house for extraction of biosolids showed a wide recovery range; however, the variability was low (≤ 7% RSD). Soxhlet extraction and CLLE are lengthy procedures and have been shown to provide highly variably recovery efficiencies. The results of this study are guidance for better sample preparation strategies in analytical methods for steroid hormone analysis, and SPE adds to the choice in environmental sample analysis.

Policy Directions Addressing the Public Health Impact of Climate Change in South Korea: The Climate-change Health Adaptation and Mitigation Program

PubMed Central

Shin, Yong Seung

2012-01-01

Climate change, caused by global warming, is increasingly recognized as a major threat to mankind's survival. Climate change concurrently has both direct and modifying influences on environmental, social, and public health systems undermining human health as a whole. Environmental health policy-makers need to make use of political and technological alternatives to address these ramifying effects. The objective of this paper is to review public health policy in Korea, as well as internationally, particularly as it relates to climate change health adaptation and mitigation programs (such as C-CHAMP of Korea), in order to assess and elicit directions for a robust environmental health policy that is adaptive to the health impacts of climate change. In Korea, comprehensive measures to prevent or mitigate overall health effects are limited, and the diffusion of responsibility among various government departments makes consistency in policy execution very difficult. This paper proposes integration, synergy, and utilization as the three core principles of policy direction for the assessment and adaptation to the health impacts of climate change. For specific action plans, we suggest policy making based on scientifically integrated health impact assessments and the prioritization of environmental factors in climate change; the development of practical and technological tools that support policy decisions by making their political implementation more efficient; and customized policy development that deals with the vulnerability of local communities. PMID:23256088

Thermal Gradient Cyclic Behavior of a Thermal/Environmental Barrier Coating System on SiC/SiC Ceramic Matrix Composites

NASA Technical Reports Server (NTRS)

Zhu, Dongming; Lee, Kang N.; Miller, Robert A.

2002-01-01

Thermal barrier and environmental barrier coatings (TBCs and EBCs) will play a crucial role in future advanced gas turbine engines because of their ability to significantly extend the temperature capability of the ceramic matrix composite (CMC) engine components in harsh combustion environments. In order to develop high performance, robust coating systems for effective thermal and environmental protection of the engine components, appropriate test approaches for evaluating the critical coating properties must be established. In this paper, a laser high-heat-flux, thermal gradient approach for testing the coatings will be described. Thermal cyclic behavior of plasma-sprayed coating systems, consisting of ZrO2-8wt%Y2O3 thermal barrier and NASA Enabling Propulsion Materials (EPM) Program developed mullite+BSAS/Si type environmental barrier coatings on SiC/SiC ceramic matrix composites, was investigated under thermal gradients using the laser heat-flux rig in conjunction with the furnace thermal cyclic tests in water-vapor environments. The coating sintering and interface damage were assessed by monitoring the real-time thermal conductivity changes during the laser heat-flux tests and by examining the microstructural changes after the tests. The coating failure mechanisms are discussed based on the cyclic test results and are correlated to the sintering, creep, and thermal stress behavior under simulated engine temperature and heat flux conditions.

Policy Directions Addressing the Public Health Impact of Climate Change in South Korea: The Climate-change Health Adaptation and Mitigation Program.

PubMed

Shin, Yong Seung; Ha, Jongsik

2012-01-01

Climate change, caused by global warming, is increasingly recognized as a major threat to mankind's survival. Climate change concurrently has both direct and modifying influences on environmental, social, and public health systems undermining human health as a whole. Environmental health policy-makers need to make use of political and technological alternatives to address these ramifying effects. The objective of this paper is to review public health policy in Korea, as well as internationally, particularly as it relates to climate change health adaptation and mitigation programs (such as C-CHAMP of Korea), in order to assess and elicit directions for a robust environmental health policy that is adaptive to the health impacts of climate change. In Korea, comprehensive measures to prevent or mitigate overall health effects are limited, and the diffusion of responsibility among various government departments makes consistency in policy execution very difficult. This paper proposes integration, synergy, and utilization as the three core principles of policy direction for the assessment and adaptation to the health impacts of climate change. For specific action plans, we suggest policy making based on scientifically integrated health impact assessments and the prioritization of environmental factors in climate change; the development of practical and technological tools that support policy decisions by making their political implementation more efficient; and customized policy development that deals with the vulnerability of local communities.

Environmental Detection of Clandestine Nuclear Weapon Programs

NASA Astrophysics Data System (ADS)

Kemp, R. Scott

2016-06-01

Environmental sensing of nuclear activities has the potential to detect nuclear weapon programs at early stages, deter nuclear proliferation, and help verify nuclear accords. However, no robust system of detection has been deployed to date. This can be variously attributed to high costs, technical limitations in detector technology, simple countermeasures, and uncertainty about the magnitude or behavior of potential signals. In this article, current capabilities and promising opportunities are reviewed. Systematic research in a variety of areas could improve prospects for detecting covert nuclear programs, although the potential for countermeasures suggests long-term verification of nuclear agreements will need to rely on methods other than environmental sensing.

EU Water Governance: Striking the Right Balance between Regulatory Flexibility and Enforcement?

EPA Science Inventory

Considering the challenges and threats currently facing water management and the exacerbation of uncertainty by climate change, the need for flexible yet robust and legitimate environmental regulation is evident. The European Union took a novel approach toward sustainable water r...

EFFECTS OF INSTILLED COMBUSTION-DERIVED ENVIRONMENTAL PARTICLES IN SPONTANEOUSLY HYPERTENSIVE RATS. PART 1: CARDIOVASCULAR RESPONSES

EPA Science Inventory

Epidemiological studies have reported a robust correlation between levels of ambient particulate matter (PM) and the incidence of morbidity and mortality, particularly among persons with cardiopulmonary disease. While similar effects have been demonstrated in animals, the mechan...

MEASUREMENT OF AMMONIA EMISSIONS FROM MECHANICALLY VENTILATED POULTRY HOUSES USING MULTIPATH TUNABLE DIODE LASER SPECTROSCOPY

EPA Science Inventory

Ammonia emissions from mechanically ventilated poultry operations are an important environmental concern. Open Path Tunable Diode Laser Absorption Spectroscopy has emerged as a robust real-time method for gas phase measurement of ammonia concentrations in agricultural settings. ...

Early Stages of the Evolution of Life: a Cybernetic Approach

NASA Astrophysics Data System (ADS)

Melkikh, Alexey V.; Seleznev, Vladimir D.

2008-08-01

Early stages of the evolution of life are considered in terms of control theory. A model is proposed for the transport of substances in a protocell possessing the property of robustness with regard to changes in the environmental concentration of a substance.

Early stages of the evolution of life: a cybernetic approach.

PubMed

Melkikh, Alexey V; Seleznev, Vladimir D

2008-08-01

Early stages of the evolution of life are considered in terms of control theory. A model is proposed for the transport of substances in a protocell possessing the property of robustness with regard to changes in the environmental concentration of a substance.

Encapsulated silicene: A robust large-gap topological insulator

DOE PAGES

Kou, Liangzhi; Ma, Yandong; Yan, Binghai; ...

2015-08-20

The quantum spin Hall (QSH) effect predicted in silicene has raised exciting prospects of new device applications compatible with current microelectronic technology. Efforts to explore this novel phenomenon, however, have been impeded by fundamental challenges imposed by silicene’s small topologically nontrivial band gap and fragile electronic properties susceptible to environmental degradation effects. Here we propose a strategy to circumvent these challenges by encapsulating silicene between transition-metal dichalcogenides (TMDCs) layers. First-principles calculations show that such encapsulated silicene exhibit a two-orders-of-magnitude enhancement in its nontrivial band gap, which is driven by the strong spin–orbit coupling effect in TMDCs via the proximity effect.more » Moreover, the cladding TMDCs layers also shield silicene from environmental gases that are detrimental to the QSH state in free-standing silicene. In conclusion, the encapsulated silicene represents a novel two-dimensional topological insulator with a robust nontrivial band gap suitable for room-temperature applications, which has significant implications for innovative QSH device design and fabrication.« less

Noise suppression methods for robust speech processing

NASA Astrophysics Data System (ADS)

Boll, S. F.; Ravindra, H.; Randall, G.; Armantrout, R.; Power, R.

1980-05-01

Robust speech processing in practical operating environments requires effective environmental and processor noise suppression. This report describes the technical findings and accomplishments during this reporting period for the research program funded to develop real time, compressed speech analysis synthesis algorithms whose performance in invariant under signal contamination. Fulfillment of this requirement is necessary to insure reliable secure compressed speech transmission within realistic military command and control environments. Overall contributions resulting from this research program include the understanding of how environmental noise degrades narrow band, coded speech, development of appropriate real time noise suppression algorithms, and development of speech parameter identification methods that consider signal contamination as a fundamental element in the estimation process. This report describes the current research and results in the areas of noise suppression using the dual input adaptive noise cancellation using the short time Fourier transform algorithms, articulation rate change techniques, and a description of an experiment which demonstrated that the spectral subtraction noise suppression algorithm can improve the intelligibility of 2400 bps, LPC 10 coded, helicopter speech by 10.6 point.

Mechanically robust, electrically conductive ultralow-density carbon nanotube-based aerogels

DOEpatents

Worsley, Marcus A; Baumann, Theodore F; Satcher, Jr., Joe H

2014-04-01

A method of making a mechanically robust, electrically conductive ultralow-density carbon nanotube-based aerogel, including the steps of dispersing nanotubes in an aqueous media or other media to form a suspension, adding reactants and catalyst to the suspension to create a reaction mixture, curing the reaction mixture to form a wet gel, drying the wet gel to produce a dry gel, and pyrolyzing the dry gel to produce the mechanically robust, electrically conductive ultralow-density carbon nanotube-based aerogel. The aerogel is mechanically robust, electrically conductive, and ultralow-density, and is made of a porous carbon material having 5 to 95% by weight carbon nanotubes and 5 to 95% carbon binder.

Mechanically robust, electrically conductive ultralow-density carbon nanotube-based aerogels

DOEpatents

Worsley, Marcus A.; Baumann, Theodore F.; Satcher, Jr, Joe H.

2016-07-05

A method of making a mechanically robust, electrically conductive ultralow-density carbon nanotube-based aerogel, including the steps of dispersing nanotubes in an aqueous media or other media to form a suspension, adding reactants and catalyst to the suspension to create a reaction mixture, curing the reaction mixture to form a wet gel, drying the wet gel to produce a dry gel, and pyrolyzing the dry gel to produce the mechanically robust, electrically conductive ultralow-density carbon nanotube-based aerogel. The aerogel is mechanically robust, electrically conductive, and ultralow-density, and is made of a porous carbon material having 5 to 95% by weight carbon nanotubes and 5 to 95% carbon binder.

Environmental Quality and Aquatic Invertebrate Metrics Relationships at Patagonian Wetlands Subjected to Livestock Grazing Pressures.

PubMed

Epele, Luis Beltrán; Miserendino, María Laura

2015-01-01

Livestock grazing can compromise the biotic integrity and health of wetlands, especially in remotes areas like Patagonia, which provide habitat for several endemic terrestrial and aquatic species. Understanding the effects of these land use practices on invertebrate communities can help prevent the deterioration of wetlands and provide insights for restoration. In this contribution, we assessed the responses of 36 metrics based on the structural and functional attributes of invertebrates (130 taxa) at 30 Patagonian wetlands that were subject to different levels of livestock grazing intensity. These levels were categorized as low, medium and high based on eight features (livestock stock densities plus seven wetland measurements). Significant changes in environmental features were detected across the gradient of wetlands, mainly related to pH, conductivity, and nutrient values. Regardless of rainfall gradient, symptoms of eutrophication were remarkable at some highly disturbed sites. Seven invertebrate metrics consistently and accurately responded to livestock grazing on wetlands. All of them were negatively related to increased levels of grazing disturbance, with the number of insect families appearing as the most robust measure. A multivariate approach (RDA) revealed that invertebrate metrics were significantly affected by environmental variables related to water quality: in particular, pH, conductivity, dissolved oxygen, nutrient concentrations, and the richness and coverage of aquatic plants. Our results suggest that the seven aforementioned metrics could be used to assess ecological quality in the arid and semi-arid wetlands of Patagonia, helping to ensure the creation of protected areas and their associated ecological services.

A Low-Power Wireless Image Sensor Node with Noise-Robust Moving Object Detection and a Region-of-Interest Based Rate Controller

DTIC Science & Technology

2017-03-01

A Low- Power Wireless Image Sensor Node with Noise-Robust Moving Object Detection and a Region-of-Interest Based Rate Controller Jong Hwan Ko...Atlanta, GA 30332 USA Contact Author Email: jonghwan.ko@gatech.edu Abstract: This paper presents a low- power wireless image sensor node for...present a low- power wireless image sensor node with a noise-robust moving object detection and region-of-interest based rate controller [Fig. 1]. The

Robust stochastic fuzzy possibilistic programming for environmental decision making under uncertainty.

PubMed

Zhang, Xiaodong; Huang, Guo H; Nie, Xianghui

2009-12-20

Nonpoint source (NPS) water pollution is one of serious environmental issues, especially within an agricultural system. This study aims to propose a robust chance-constrained fuzzy possibilistic programming (RCFPP) model for water quality management within an agricultural system, where solutions for farming area, manure/fertilizer application amount, and livestock husbandry size under different scenarios are obtained and interpreted. Through improving upon the existing fuzzy possibilistic programming, fuzzy robust programming and chance-constrained programming approaches, the RCFPP can effectively reflect the complex system features under uncertainty, where implications of water quality/quantity restrictions for achieving regional economic development objectives are studied. By delimiting the uncertain decision space through dimensional enlargement of the original fuzzy constraints, the RCFPP enhances the robustness of the optimization processes and resulting solutions. The results of the case study indicate that useful information can be obtained through the proposed RCFPP model for providing feasible decision schemes for different agricultural activities under different scenarios (combinations of different p-necessity and p(i) levels). A p-necessity level represents the certainty or necessity degree of the imprecise objective function, while a p(i) level means the probabilities at which the constraints will be violated. A desire to acquire high agricultural income would decrease the certainty degree of the event that maximization of the objective be satisfied, and potentially violate water management standards; willingness to accept low agricultural income will run into the risk of potential system failure. The decision variables under combined p-necessity and p(i) levels were useful for the decision makers to justify and/or adjust the decision schemes for the agricultural activities through incorporation of their implicit knowledge. The results also suggest that this developed approach is applicable to many practical problems where fuzzy and probabilistic distribution information simultaneously exist.

Anthropometric geography applied to the analysis of socioeconomic disparities: cohort trends and spatial patterns of height and robustness in 20th-century Spain

PubMed Central

Camara, Antonio D.; Roman, Joan Garcia

2014-01-01

Anthropometrics have been widely used to study the influence of environmental factors on health and nutritional status. In contrast, anthropometric geography has not often been employed to approximate the dynamics of spatial disparities associated with socioeconomic and demographic changes. Spain exhibited intense disparity and change during the middle decades of the 20th century, with the result that the life courses of the corresponding cohorts were associated with diverse environmental conditions. This was also true of the Spanish territories. This paper presents insights concerning the relationship between socioeconomic changes and living conditions by combining the analysis of cohort trends and the anthropometric cartography of height and physical build. This analysis is conducted for Spanish male cohorts born 1934–1973 that were recorded in the Spanish military statistics. This information is interpreted in light of region-level data on GDP and infant mortality. Our results show an anthropometric convergence across regions that, nevertheless, did not substantially modify the spatial patterns of robustness, featuring primarily robust northeastern regions and weak Central-Southern regions. These patterns persisted until the 1990s (cohorts born during the 1970s). For the most part, anthropometric disparities were associated with socioeconomic disparities, although the former lessened over time to a greater extent than the latter. Interestingly, the various anthropometric indicators utilized here do not point to the same conclusions. Some discrepancies between height and robustness patterns have been found that moderate the statements from the analysis of cohort height alone regarding the level and evolution of living conditions across Spanish regions. PMID:26640422

Epidemiological information is key when interpreting whole genome sequence data – lessons learned from a large Legionella pneumophila outbreak in Warstein, Germany, 2013

PubMed Central

Petzold, Markus; Prior, Karola; Moran-Gilad, Jacob; Harmsen, Dag; Lück, Christian

2017-01-01

Introduction Whole genome sequencing (WGS) is increasingly used in Legionnaires’ disease (LD) outbreak investigations, owing to its higher resolution than sequence-based typing, the gold standard typing method for Legionella pneumophila, in the analysis of endemic strains. Recently, a gene-by-gene typing approach based on 1,521 core genes called core genome multilocus sequence typing (cgMLST) was described that enables a robust and standardised typing of L. pneumophila. Methods: We applied this cgMLST scheme to isolates obtained during the largest outbreak of LD reported so far in Germany. In this outbreak, the epidemic clone ST345 had been isolated from patients and four different environmental sources. In total 42 clinical and environmental isolates were retrospectively typed. Results: Epidemiologically unrelated ST345 isolates were clearly distinguishable from the epidemic clone. Remarkably, epidemic isolates split up into two distinct clusters, ST345-A and ST345-B, each respectively containing a mix of clinical and epidemiologically-related environmental samples. Discussion/conclusion: The outbreak was therefore likely caused by both variants of the single sequence type, which pre-existed in the environmental reservoirs. The two clusters differed by 40 alleles located in two neighbouring genomic regions of ca 42 and 26 kb. Additional analysis supported horizontal gene transfer of the two regions as responsible for the difference between the variants. Both regions comprise virulence genes and have previously been reported to be involved in recombination events. This corroborates the notion that genomic outbreak investigations should always take epidemiological information into consideration when making inferences. Overall, cgMLST proved helpful in disentangling the complex genomic epidemiology of the outbreak. PMID:29162202

The impact of area-based initiatives on physical activity trends in deprived areas; a quasi-experimental evaluation of the Dutch District Approach.

PubMed

Kramer, Daniëlle; Droomers, Mariël; Jongeneel-Grimen, Birthe; Wingen, Marleen; Stronks, Karien; Kunst, Anton E

2014-03-11

Numerous area-based initiatives (ABIs) have been implemented in deprived neighbourhoods across Europe. These large-scale initiatives aim to tackle the socio-economic and environmental problems in these areas that might influence physical activity (PA). There is little robust evidence of their impact on PA. This study aimed to assess the impact of a Dutch ABI called the District Approach on trends in leisure-time PA in deprived districts. Repeated cross-sectional data on 48401 adults across the Netherlands were obtained from the Integrated Survey on Household Living Conditions (POLS) 2004-2011. 1517 of these adults resided in deprived target districts and 46884 adults resided elsewhere in the Netherlands. In a quasi-experimental interrupted time-series design, multilevel logistic regression analyses were performed to assess trends in leisure-time walking, cycling, and sports before and during the intervention. Trends in deprived target districts were compared with trends in various control groups. The role of the intensity of environmental interventions was also assessed. Deprived target districts showed a significantly positive change in walking trend between the pre-intervention and intervention period. The trend change in the deprived target districts was significantly larger compared to the rest of the Netherlands, but not compared to other deprived districts. For cycling and sports, neither deprived districts nor control districts showed a significant trend change. For all leisure-time PA outcomes, trend changes were not related to the intensity of environmental interventions in the deprived target districts. Some evidence was found to suggest that ABIs like the District Approach have a positive impact on leisure-time PA in deprived districts, regardless of the intensity of environmental interventions.

The impact of area-based initiatives on physical activity trends in deprived areas; a quasi-experimental evaluation of the Dutch District Approach

PubMed Central

2014-01-01

Background Numerous area-based initiatives (ABIs) have been implemented in deprived neighbourhoods across Europe. These large-scale initiatives aim to tackle the socio-economic and environmental problems in these areas that might influence physical activity (PA). There is little robust evidence of their impact on PA. This study aimed to assess the impact of a Dutch ABI called the District Approach on trends in leisure-time PA in deprived districts. Methods Repeated cross-sectional data on 48401 adults across the Netherlands were obtained from the Integrated Survey on Household Living Conditions (POLS) 2004–2011. 1517 of these adults resided in deprived target districts and 46884 adults resided elsewhere in the Netherlands. In a quasi-experimental interrupted time-series design, multilevel logistic regression analyses were performed to assess trends in leisure-time walking, cycling, and sports before and during the intervention. Trends in deprived target districts were compared with trends in various control groups. The role of the intensity of environmental interventions was also assessed. Results Deprived target districts showed a significantly positive change in walking trend between the pre-intervention and intervention period. The trend change in the deprived target districts was significantly larger compared to the rest of the Netherlands, but not compared to other deprived districts. For cycling and sports, neither deprived districts nor control districts showed a significant trend change. For all leisure-time PA outcomes, trend changes were not related to the intensity of environmental interventions in the deprived target districts. Conclusion Some evidence was found to suggest that ABIs like the District Approach have a positive impact on leisure-time PA in deprived districts, regardless of the intensity of environmental interventions. PMID:24612770

Epidemiological information is key when interpreting whole genome sequence data - lessons learned from a large Legionella pneumophila outbreak in Warstein, Germany, 2013.

PubMed

Petzold, Markus; Prior, Karola; Moran-Gilad, Jacob; Harmsen, Dag; Lück, Christian

2017-11-01

IntroductionWhole genome sequencing (WGS) is increasingly used in Legionnaires' disease (LD) outbreak investigations, owing to its higher resolution than sequence-based typing, the gold standard typing method for Legionella pneumophila, in the analysis of endemic strains. Recently, a gene-by-gene typing approach based on 1,521 core genes called core genome multilocus sequence typing (cgMLST) was described that enables a robust and standardised typing of L. pneumophila . Methods : We applied this cgMLST scheme to isolates obtained during the largest outbreak of LD reported so far in Germany. In this outbreak, the epidemic clone ST345 had been isolated from patients and four different environmental sources. In total 42 clinical and environmental isolates were retrospectively typed. Results : Epidemiologically unrelated ST345 isolates were clearly distinguishable from the epidemic clone. Remarkably, epidemic isolates split up into two distinct clusters, ST345-A and ST345-B, each respectively containing a mix of clinical and epidemiologically-related environmental samples. Discussion/conclusion : The outbreak was therefore likely caused by both variants of the single sequence type, which pre-existed in the environmental reservoirs. The two clusters differed by 40 alleles located in two neighbouring genomic regions of ca 42 and 26 kb. Additional analysis supported horizontal gene transfer of the two regions as responsible for the difference between the variants. Both regions comprise virulence genes and have previously been reported to be involved in recombination events. This corroborates the notion that genomic outbreak investigations should always take epidemiological information into consideration when making inferences. Overall, cgMLST proved helpful in disentangling the complex genomic epidemiology of the outbreak.

Identification of dust outbreaks on infrared MSG-SEVIRI data by using a Robust Satellite Technique (RST)

NASA Astrophysics Data System (ADS)

Sannazzaro, Filomena; Filizzola, Carolina; Marchese, Francesco; Corrado, Rosita; Paciello, Rossana; Mazzeo, Giuseppe; Pergola, Nicola; Tramutoli, Valerio

2014-01-01

Dust storms are meteorological phenomena of great interest for scientific community because of their potential impact on climate changes, for the risk that may pose to human health and due to other issues as desertification processes and reduction of the agricultural production. Satellite remote sensing, thanks to global coverage, high frequency of observation and low cost data, may highly contribute in monitoring these phenomena, provided that proper detection methods are used. In this work, the known Robust Satellite Techniques (RST) multitemporal approach, used for studying and monitoring several natural/environmental hazards, is tested on some important dust events affecting Mediterranean region in May 2004 and Arabian Peninsula in February 2008. To perform this study, data provided by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) have been processed, comparing the generated dust maps to some independent satellite-based aerosol products. Outcomes of this work show that the RST technique can be profitably used for detecting dust outbreaks from space, providing information also about areas characterized by a different probability of dust presence. They encourage further improvements of this technique in view of its possible implementation in the framework of operational warning systems.

Electrostatic doping as a source for robust ferromagnetism at the interface between antiferromagnetic cobalt oxides

PubMed Central

Li, Zi-An; Fontaíña-Troitiño, N.; Kovács, A.; Liébana-Viñas, S.; Spasova, M.; Dunin-Borkowski, R. E.; Müller, M.; Doennig, D.; Pentcheva, R.; Farle, M.; Salgueiriño, V.

2015-01-01

Polar oxide interfaces are an important focus of research due to their novel functionality which is not available in the bulk constituents. So far, research has focused mainly on heterointerfaces derived from the perovskite structure. It is important to extend our understanding of electronic reconstruction phenomena to a broader class of materials and structure types. Here we report from high-resolution transmission electron microscopy and quantitative magnetometry a robust – above room temperature (Curie temperature TC ≫ 300 K) – environmentally stable- ferromagnetically coupled interface layer between the antiferromagnetic rocksalt CoO core and a 2–4 nm thick antiferromagnetic spinel Co3O4 surface layer in octahedron-shaped nanocrystals. Density functional theory calculations with an on-site Coulomb repulsion parameter identify the origin of the experimentally observed ferromagnetic phase as a charge transfer process (partial reduction) of Co3+ to Co2+ at the CoO/Co3O4 interface, with Co2+ being in the low spin state, unlike the high spin state of its counterpart in CoO. This finding may serve as a guideline for designing new functional nanomagnets based on oxidation resistant antiferromagnetic transition metal oxides. PMID:25613569

Electrostatic doping as a source for robust ferromagnetism at the interface between antiferromagnetic cobalt oxides.

PubMed

Li, Zi-An; Fontaíña-Troitiño, N; Kovács, A; Liébana-Viñas, S; Spasova, M; Dunin-Borkowski, R E; Müller, M; Doennig, D; Pentcheva, R; Farle, M; Salgueiriño, V

2015-01-23

Polar oxide interfaces are an important focus of research due to their novel functionality which is not available in the bulk constituents. So far, research has focused mainly on heterointerfaces derived from the perovskite structure. It is important to extend our understanding of electronic reconstruction phenomena to a broader class of materials and structure types. Here we report from high-resolution transmission electron microscopy and quantitative magnetometry a robust – above room temperature (Curie temperature TC ≫ 300 K) – environmentally stable- ferromagnetically coupled interface layer between the antiferromagnetic rocksalt CoO core and a 2-4 nm thick antiferromagnetic spinel Co3O4 surface layer in octahedron-shaped nanocrystals. Density functional theory calculations with an on-site Coulomb repulsion parameter identify the origin of the experimentally observed ferromagnetic phase as a charge transfer process (partial reduction) of Co(3+) to Co(2+) at the CoO/Co3O4 interface, with Co(2+) being in the low spin state, unlike the high spin state of its counterpart in CoO. This finding may serve as a guideline for designing new functional nanomagnets based on oxidation resistant antiferromagnetic transition metal oxides.

Instantaneous, Simple, and Reversible Revealing of Invisible Patterns Encrypted in Robust Hollow Sphere Colloidal Photonic Crystals.

PubMed

Zhong, Kuo; Li, Jiaqi; Liu, Liwang; Van Cleuvenbergen, Stijn; Song, Kai; Clays, Koen

2018-05-04

The colors of photonic crystals are based on their periodic crystalline structure. They show clear advantages over conventional chromophores for many applications, mainly due to their anti-photobleaching and responsiveness to stimuli. More specifically, combining colloidal photonic crystals and invisible patterns is important in steganography and watermarking for anticounterfeiting applications. Here a convenient way to imprint robust invisible patterns in colloidal crystals of hollow silica spheres is presented. While these patterns remain invisible under static environmental humidity, even up to near 100% relative humidity, they are unveiled immediately (≈100 ms) and fully reversibly by dynamic humid flow, e.g., human breath. They reveal themselves due to the extreme wettability of the patterned (etched) regions, as confirmed by contact angle measurements. The liquid surface tension threshold to induce wetting (revealing the imprinted invisible images) is evaluated by thermodynamic predictions and subsequently verified by exposure to various vapors with different surface tension. The color of the patterned regions is furthermore independently tuned by vapors with different refractive indices. Such a system can play a key role in applications such as anticounterfeiting, identification, and vapor sensing. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Polarization Technique for Mitigating Low Grazing Angle Radar Sea Clutter

DTIC Science & Technology

2017-03-03

alarm mitigation, low grazing angles, polarimetry , radar, sea clutter. I. INTRODUCTION Sea clutter poses unique challenges for maritime radars looking...radar polarimetry offers a practical means of robustly mitigating LGA sea clutter across a range of radar and environmental parameters, we stood up a

Measuring Physicochemical Properties to Inform the Scope of Existing QSAR/QSPR Models (SOT annual meeting)

EPA Science Inventory

Chemical structures and their properties are important for determining their potential toxicological effects, toxicokinetics, and route of exposure. These data are needed to prioritize thousands of environmental chemicals, but are often lacking. In order to fill data gaps, robust...

Testing an Algae-Based Air-Regeneration System

NASA Technical Reports Server (NTRS)

Nienow, James

1998-01-01

The potential of an air-regeneration system based on the growth of unicellular algae on the surface of porous ceramic tubes was evaluated. The system is fairly robust with respect to environmental conditions and is capable of maintaining algal cultures for up to 365 days. Under standard conditions (50-66 micro mol/sq mm s (PPF), 450 micro mol mol of CO2), mature tubes can remove CO2 at a rate of up to 90 micro mol/sq m min. Under these conditions, approximately 200 square meters of area would be required for each member of the crew. However, the rate of uptake increases with both photon flux and CO2 concentration in accordance with Michaelis-Menton dynamics. An extrapolation to conditions of saturating light and carbon dioxide indicates that the area required can be reduced by a factor of at least 2.5.

Development of ecological indicator guilds for land management

USGS Publications Warehouse

Krzysik, A.J.; Balbach, H.E.; Duda, J.J.; Emlen, J.M.; Freeman, D.C.; Graham, J.H.; Kovacic, D.A.; Smith, L.M.; Zak, J.C.

2005-01-01

Agency land-use must be efficiently and cost-effectively monitored to assess conditions and trends in ecosystem processes and natural resources relevant to mission requirements and legal mandates. Ecological Indicators represent important land management tools for tracking ecological changes and preventing irreversible environmental damage in disturbed landscapes. The overall objective of the research was to develop both individual and integrated sets (i.e., statistically derived guilds) of Ecological Indicators to: quantify habitat conditions and trends, track and monitor ecological changes, provide early warning or threshold detection, and provide guidance for land managers. The derivation of Ecological Indicators was based on statistical criteria, ecosystem relevance, reliability and robustness, economy and ease of use for land managers, multi-scale performance, and stress response criteria. The basis for the development of statistically based Ecological Indicators was the identification of ecosystem metrics that analytically tracked a landscape disturbance gradient.

An active acoustic tripwire for simultaneous detection and localization of multiple underwater intruders.

PubMed

Folegot, Thomas; Martinelli, Giovanna; Guerrini, Piero; Stevenson, J Mark

2008-11-01

An algorithm allowing simultaneous detection and localization of multiple submerged targets crossing an acoustic tripwire based on forward scattering is described and then evaluated based upon data collected at sea. This paper quantifies the agreement between the theoretical performance and the results obtained from processing data gathered at sea for crossings at several depths and ranges. Targets crossing the acoustic field produce shadows on each side of the barrier, for specific sensors and for specific acoustic paths. In post-processing, a model is invoked to associate expected paths with the observed shadows. This process allows triangulation of the target's position inside the acoustic field. Precise localization is achieved by taking advantage of the multipath propagation structure of the received signal, together with the diversity of the source and receiver locations. Environmental robustness is demonstrated using simulations and can be explained by the use of an array of sources spatially distributed through the water column.

Piezoelectric sensors based on molecular imprinted polymers for detection of low molecular mass analytes.

PubMed

Uludağ, Yildiz; Piletsky, Sergey A; Turner, Anthony P F; Cooper, Matthew A

2007-11-01

Biomimetic recognition elements employed for the detection of analytes are commonly based on proteinaceous affibodies, immunoglobulins, single-chain and single-domain antibody fragments or aptamers. The alternative supra-molecular approach using a molecularly imprinted polymer now has proven utility in numerous applications ranging from liquid chromatography to bioassays. Despite inherent advantages compared with biochemical/biological recognition (which include robustness, storage endurance and lower costs) there are few contributions that describe quantitative analytical applications of molecularly imprinted polymers for relevant small molecular mass compounds in real-world samples. There is, however, significant literature describing the use of low-power, portable piezoelectric transducers to detect analytes in environmental monitoring and other application areas. Here we review the combination of molecularly imprinted polymers as recognition elements with piezoelectric biosensors for quantitative detection of small molecules. Analytes are classified by type and sample matrix presentation and various molecularly imprinted polymer synthetic fabrication strategies are also reviewed.

Macroscopic Theory for Evolving Biological Systems Akin to Thermodynamics.

PubMed

Kaneko, Kunihiko; Furusawa, Chikara

2018-05-20

We present a macroscopic theory to characterize the plasticity, robustness, and evolvability of biological responses and their fluctuations. First, linear approximation in intracellular reaction dynamics is used to demonstrate proportional changes in the expression of all cellular components in response to a given environmental stress, with the proportion coefficient determined by the change in growth rate as a consequence of the steady growth of cells. We further demonstrate that this relationship is supported through adaptation experiments of bacteria, perhaps too well as this proportionality is held even across cultures of different types of conditions. On the basis of simulations of cell models, we further show that this global proportionality is a consequence of evolution in which expression changes in response to environmental or genetic perturbations are constrained along a unique one-dimensional curve, which is a result of evolutionary robustness. It then follows that the expression changes induced by environmental changes are proportionally reduced across different components of a cell by evolution, which is akin to the Le Chatelier thermodynamics principle. Finally, with the aid of a fluctuation-response relationship, this proportionality is shown to hold between fluctuations caused by genetic changes and those caused by noise. Overall, these results and support from the theoretical and experimental literature suggest a formulation of cellular systems akin to thermodynamics, in which a macroscopic potential is given by the growth rate (or fitness) represented as a function of environmental and evolutionary changes.

Ames Hybrid Combustion Facility

NASA Technical Reports Server (NTRS)

Zilliac, Greg; Karabeyoglu, Mustafa A.; Cantwell, Brian; Hunt, Rusty; DeZilwa, Shane; Shoffstall, Mike; Soderman, Paul T.; Bencze, Daniel P. (Technical Monitor)

2003-01-01

The report summarizes the design, fabrication, safety features, environmental impact, and operation of the Ames Hybrid-Fuel Combustion Facility (HCF). The facility is used in conducting research into the scalability and combustion processes of advanced paraffin-based hybrid fuels for the purpose of assessing their applicability to practical rocket systems. The facility was designed to deliver gaseous oxygen at rates between 0.5 and 16.0 kg/sec to a combustion chamber operating at pressures ranging from 300 to 900. The required run times were of the order of 10 to 20 sec. The facility proved to be robust and reliable and has been used to generate a database of regression-rate measurements of paraffin at oxygen mass flux levels comparable to those of moderate-sized hybrid rocket motors.

Cr2O3 ultrasmall nanoparticles filled carbon nanocapsules deriving from Cr(VI) for enhanced lithium storage

NASA Astrophysics Data System (ADS)

Zhao, Yun; Wang, Jianjiao; Ma, Canliang; Li, Yong

2018-07-01

Based on the considerations in environmental and economic benefits, Cr2O72- as the major chromium pollutant is employed for applications in energy storage. A novel Cr2O3 ultrasmall nanoparticles (NPs) (<5 nm) filled carbon nanocapsule configuration is achieved through a surfactant-free solvothermal route with renewable furfural as the carbon source. The confinement effect that Cr2O3 NPs are restrained in the outer robust carbon shell and the plenty space among Cr2O3 NPs result in substantially enhanced Li-storage performances, such as stable capacity of 568 mAh g-1 at 100 mA g-1 after more than 200 cycles and high capacity retention at large current density.

RAPID COMMUNICATION Time-resolved measurements with a vortex flowmeter in a pulsating turbulent flow using wavelet analysis

NASA Astrophysics Data System (ADS)

Laurantzon, F.; Örlü, R.; Segalini, A.; Alfredsson, P. H.

2010-12-01

Vortex flowmeters are commonly employed in technical applications and are obtainable in a variety of commercially available types. However their robustness and accuracy can easily be impaired by environmental conditions, such as inflow disturbances and/or pulsating conditions. Various post-processing techniques of the vortex signal have been used, but all of these methods are so far targeted on obtaining an improved estimate of the time-averaged bulk velocity. Here, on the other hand, we propose, based on wavelet analysis, a straightforward way to utilize the signal from a vortex shedder to extract the time-resolved and thereby the phase-averaged velocity under pulsatile flow conditions. The method was verified with hot-wire and laser Doppler velocimetry measurements.

Template-Assisted Hydrothermal Growth of Aligned Zinc Oxide Nanowires for Piezoelectric Energy Harvesting Applications

PubMed Central

2016-01-01

A flexible and robust piezoelectric nanogenerator (NG) based on a polymer-ceramic nanocomposite structure has been successfully fabricated via a cost-effective and scalable template-assisted hydrothermal synthesis method. Vertically aligned arrays of dense and uniform zinc oxide (ZnO) nanowires (NWs) with high aspect ratio (diameter ∼250 nm, length ∼12 μm) were grown within nanoporous polycarbonate (PC) templates. The energy conversion efficiency was found to be ∼4.2%, which is comparable to previously reported values for ZnO NWs. The resulting NG is found to have excellent fatigue performance, being relatively immune to detrimental environmental factors and mechanical failure, as the constituent ZnO NWs remain embedded and protected inside the polymer matrix. PMID:27172933

Defining surfaces for skewed, highly variable data

USGS Publications Warehouse

Helsel, D.R.; Ryker, S.J.

2002-01-01

Skewness of environmental data is often caused by more than simply a handful of outliers in an otherwise normal distribution. Statistical procedures for such datasets must be sufficiently robust to deal with distributions that are strongly non-normal, containing both a large proportion of outliers and a skewed main body of data. In the field of water quality, skewness is commonly associated with large variation over short distances. Spatial analysis of such data generally requires either considerable effort at modeling or the use of robust procedures not strongly affected by skewness and local variability. Using a skewed dataset of 675 nitrate measurements in ground water, commonly used methods for defining a surface (least-squares regression and kriging) are compared to a more robust method (loess). Three choices are critical in defining a surface: (i) is the surface to be a central mean or median surface? (ii) is either a well-fitting transformation or a robust and scale-independent measure of center used? (iii) does local spatial autocorrelation assist in or detract from addressing objectives? Published in 2002 by John Wiley & Sons, Ltd.

Synthetic biology and regulatory networks: where metabolic systems biology meets control engineering.

PubMed

He, Fei; Murabito, Ettore; Westerhoff, Hans V

2016-04-01

Metabolic pathways can be engineered to maximize the synthesis of various products of interest. With the advent of computational systems biology, this endeavour is usually carried out through in silico theoretical studies with the aim to guide and complement further in vitro and in vivo experimental efforts. Clearly, what counts is the result in vivo, not only in terms of maximal productivity but also robustness against environmental perturbations. Engineering an organism towards an increased production flux, however, often compromises that robustness. In this contribution, we review and investigate how various analytical approaches used in metabolic engineering and synthetic biology are related to concepts developed by systems and control engineering. While trade-offs between production optimality and cellular robustness have already been studied diagnostically and statically, the dynamics also matter. Integration of the dynamic design aspects of control engineering with the more diagnostic aspects of metabolic, hierarchical control and regulation analysis is leading to the new, conceptual and operational framework required for the design of robust and productive dynamic pathways. © 2016 The Author(s).

Synthesis Methods for Robust Passification and Control

NASA Technical Reports Server (NTRS)

Kelkar, Atul G.; Joshi, Suresh M. (Technical Monitor)

2000-01-01

The research effort under this cooperative agreement has been essentially the continuation of the work from previous grants. The ongoing work has primarily focused on developing passivity-based control techniques for Linear Time-Invariant (LTI) systems. During this period, there has been a significant progress made in the area of passivity-based control of LTI systems and some preliminary results have also been obtained for nonlinear systems, as well. The prior work has addressed optimal control design for inherently passive as well as non- passive linear systems. For exploiting the robustness characteristics of passivity-based controllers the passification methodology was developed for LTI systems that are not inherently passive. Various methods of passification were first proposed in and further developed. The robustness of passification was addressed for multi-input multi-output (MIMO) systems for certain classes of uncertainties using frequency-domain methods. For MIMO systems, a state-space approach using Linear Matrix Inequality (LMI)-based formulation was presented, for passification of non-passive LTI systems. An LMI-based robust passification technique was presented for systems with redundant actuators and sensors. The redundancy in actuators and sensors was used effectively for robust passification using the LMI formulation. The passification was designed to be robust to an interval-type uncertainties in system parameters. The passification techniques were used to design a robust controller for Benchmark Active Control Technology wing under parametric uncertainties. The results on passive nonlinear systems, however, are very limited to date. Our recent work in this area was presented, wherein some stability results were obtained for passive nonlinear systems that are affine in control.

Robust Performance of Marginal Pacific Coral Reef Habitats in Future Climate Scenarios.

PubMed

Freeman, Lauren A

2015-01-01

Coral reef ecosystems are under dual threat from climate change. Increasing sea surface temperatures and thermal stress create environmental limits at low latitudes, and decreasing aragonite saturation state creates environmental limits at high latitudes. This study examines the response of unique coral reef habitats to climate change in the remote Pacific, using the National Center for Atmospheric Research Community Earth System Model version 1 alongside the species distribution algorithm Maxent. Narrow ranges of physico-chemical variables are used to define unique coral habitats and their performance is tested in future climate scenarios. General loss of coral reef habitat is expected in future climate scenarios and has been shown in previous studies. This study found exactly that for most of the predominant physico-chemical environments. However, certain coral reef habitats considered marginal today at high latitude, along the equator and in the eastern tropical Pacific were found to be quite robust in climate change scenarios. Furthermore, an environmental coral reef refuge previously identified in the central south Pacific near French Polynesia was further reinforced. Studying the response of specific habitats showed that the prevailing conditions of this refuge during the 20th century shift to a new set of conditions, more characteristic of higher latitude coral reefs in the 20th century, in future climate scenarios projected to 2100.

Robust discovery of genetic associations incorporating gene-environment interaction and independence.

PubMed

Tchetgen Tchetgen, Eric

2011-03-01

This article considers the detection and evaluation of genetic effects incorporating gene-environment interaction and independence. Whereas ordinary logistic regression cannot exploit the assumption of gene-environment independence, the proposed approach makes explicit use of the independence assumption to improve estimation efficiency. This method, which uses both cases and controls, fits a constrained retrospective regression in which the genetic variant plays the role of the response variable, and the disease indicator and the environmental exposure are the independent variables. The regression model constrains the association of the environmental exposure with the genetic variant among the controls to be null, thus explicitly encoding the gene-environment independence assumption, which yields substantial gain in accuracy in the evaluation of genetic effects. The proposed retrospective regression approach has several advantages. It is easy to implement with standard software, and it readily accounts for multiple environmental exposures of a polytomous or of a continuous nature, while easily incorporating extraneous covariates. Unlike the profile likelihood approach of Chatterjee and Carroll (Biometrika. 2005;92:399-418), the proposed method does not require a model for the association of a polytomous or continuous exposure with the disease outcome, and, therefore, it is agnostic to the functional form of such a model and completely robust to its possible misspecification.

Stochastic noncooperative and cooperative evolutionary game strategies of a population of biological networks under natural selection.

PubMed

Chen, Bor-Sen; Yeh, Chin-Hsun

2017-12-01

We review current static and dynamic evolutionary game strategies of biological networks and discuss the lack of random genetic variations and stochastic environmental disturbances in these models. To include these factors, a population of evolving biological networks is modeled as a nonlinear stochastic biological system with Poisson-driven genetic variations and random environmental fluctuations (stimuli). To gain insight into the evolutionary game theory of stochastic biological networks under natural selection, the phenotypic robustness and network evolvability of noncooperative and cooperative evolutionary game strategies are discussed from a stochastic Nash game perspective. The noncooperative strategy can be transformed into an equivalent multi-objective optimization problem and is shown to display significantly improved network robustness to tolerate genetic variations and buffer environmental disturbances, maintaining phenotypic traits for longer than the cooperative strategy. However, the noncooperative case requires greater effort and more compromises between partly conflicting players. Global linearization is used to simplify the problem of solving nonlinear stochastic evolutionary games. Finally, a simple stochastic evolutionary model of a metabolic pathway is simulated to illustrate the procedure of solving for two evolutionary game strategies and to confirm and compare their respective characteristics in the evolutionary process. Copyright © 2017 Elsevier B.V. All rights reserved.

Integrating Environmental Management of Asthma into Pediatric Health Care: What Worked and What Still Needs Improvement?

PubMed

Roberts, James R; Newman, Nicholas; McCurdy, Leyla E; Chang, Jane S; Salas, Mauro A; Eskridge, Bernard; De Ybarrondo, Lisa; Sandel, Megan; Mazur, Lynnette; Karr, Catherine J

2016-12-01

The National Environmental Education Foundation (NEEF) launched an initiative in 2005 to integrate environmental management of asthma into pediatric health care. This study, a follow-up to a 2013 study, evaluated the program's impact and assessed training results by 5 new faculty champions. We surveyed attendees at training sessions to measure knowledge and the likelihood of asking about and managing environmental triggers of asthma. To conduct the program evaluation, a workshop was held with the faculty champions and NEEF staff in which we identified major program benefits, as well as challenges and suggestions for the future. Trainee baseline knowledge of environmental triggers was low, but they reported robust improvement in environmental triggers knowledge and intention to recommend environmental management. The program has a broad, national scope, reaching more than 12 000 physicians, health care providers, and students, and some faculty champions successfully integrated materials into health record. Program barriers and future endeavors were identified.

Prospective time-resolved LCA of fully electric supercap vehicles in Germany.

PubMed

Zimmermann, Benedikt M; Dura, Hanna; Baumann, Manuel J; Weil, Marcel R

2015-07-01

The ongoing transition of the German electricity supply toward a higher share of renewable and sustainable energy sources, called Energiewende in German, has led to dynamic changes in the environmental impact of electricity over the last few years. Prominent scenario studies predict that comparable dynamics will continue in the coming decades, which will further improve the environmental performance of Germany's electricity supply. Life cycle assessment (LCA) is the methodology commonly used to evaluate environmental performance. Previous LCA studies on electric vehicles have shown that the electricity supply for the vehicles' operation is responsible for the major part of their environmental impact. The core question of this study is how the prospective dynamic development of the German electricity mix will affect the impact of electric vehicles operated in Germany and how LCA can be adapted to analyze this impact in a more robust manner. The previously suggested approach of time-resolved LCA, which is located between static and dynamic LCA, is used in this study and compared with several static approaches. Furthermore, the uncertainty issue associated with scenario studies is addressed in general and in relation to time-resolved LCA. Two scenario studies relevant to policy making have been selected, but a moderate number of modifications have been necessary to adapt the data to the requirements of a life cycle inventory. A potential, fully electric vehicle powered by a supercapacitor energy storage system is used as a generic example. The results show that substantial improvements in the environmental repercussions of the electricity supply and, consequentially, of electric vehicles will be achieved between 2020 and 2031 on the basis of the energy mixes predicted in both studies. This study concludes that although scenarios might not be able to predict the future, they should nonetheless be used as data sources in prospective LCA studies, because in many cases historic data appears to be unsuitable for providing realistic information on the future. The time-resolved LCA approach improves the assessment's robustness substantially, especially when nonlinear developments are foreseen in the future scenarios. This allows for a reduction of bias in LCA-based decision making. However, a deeper integration of time-resolved data in the life cycle inventory and the implementation of a more suitable software framework are desirable. The study describes how life cycle assessment's (LCA) robustness can be improved by respecting prospective fluctuations, like the transition of the German electricity mix, in the modeling of the life cycle inventory. It presents a feasible and rather simple process to add time-resolved data to LCA. The study selects 2 different future scenarios from important German studies and processes their data systematically to make them compatible with the requirements of a life cycle inventory. The use of external scenarios as basis for future-oriented LCA is reflected critically. A case study on electric mobility is presented and used to compare historic, prospective static, and prospective time-resolved electricity mix modeling approaches. The case study emphasizes the benefits of time-resolved LCA in direct comparison with the currently used approaches. © 2015 SETAC.

A new multidimensional stoichiometric classification of compounds: moving beyond the van Krevelen diagram.

NASA Astrophysics Data System (ADS)

Rivas-Ubach, A.; Liu, Y.; Bianchi, T. S.; Tolic, N.; Jansson, C.; Paša-Tolić, L.

2017-12-01

The role of nutrients in organisms, especially primary producers, has been a topic of special interest in ecosystem research for understanding the ecosystem structure and function. The majority of macro-elements in organisms, such as C, H, O, N and P, do not act as single elements but are components of organic compounds (lipids, peptides, carbohydrates, etc), which are more directly related to the physiology of organisms and thus to the ecosystem function. However, accurately deciphering the overall content of the main compound classes (lipids, proteins, carbohydrates,…) in organisms is still a major challenge. van Krevelen (vK) diagrams have been widely used as an estimation of the main compound categories present in environmental samples based on O:C vs H:C molecular ratios, but a stoichiometric classification based exclusively on O:C and H:C ratios is feeble. Different compound classes show large O:C and H:C ratio overlapping and other heteroatoms, such as N and P, should be considered to robustly distinguish the different classes. We propose a new compound classification for biological/environmental samples based on the C:H:O:N:P stoichiometric ratios of thousands of molecular formulas of characterized compounds from 6 different main categories: lipids, peptides, amino-sugars, carbohydrates, nucleotides and phytochemical compounds (oxy-aromatic compounds). This new multidimensional stoichiometric compound constraints classification (MSCC) can be applied to data obtained with high resolution mass spectrometry (HRMS), allowing an accurate overview of the relative abundances of the main compound categories present in organismal samples. The MSCC has been optimized for plants, but it could be also applied to different organisms and serve as a strong starting point to further investigate other environmental complex matrices (soils, aerosols, etc). The proposed MSCC advances environmental research, especially eco-metabolomics, ecophysiology and ecological stoichiometry studies, providing a new tool to understand the ecosystem structure and function at the molecular level.

Qualification testing of fiber-based laser transmitters and on-orbit validation of a commercial laser system

NASA Astrophysics Data System (ADS)

Wright, M. W.; Wilkerson, M. W.; Tang, R. R.

2017-11-01

Qualification testing of fiber based laser transmitters is required for NASA's Deep Space Optical Communications program to mature the technology for space applications. In the absence of fully space qualified systems, commercial systems have been investigated in order to demonstrate the robustness of the technology. To this end, a 2.5 W fiber based laser source was developed as the transmitter for an optical communications experiment flown aboard the ISS as a part of a technology demonstration mission. The low cost system leveraged Mil Standard design principles and Telcordia certified components to the extent possible and was operated in a pressure vessel with active cooling. The laser was capable of high rate modulation but was limited by the mission requirements to 50 Mbps for downlinking stored video from the OPALS payload, externally mounted on the ISS. Environmental testing and space qualification of this unit will be discussed along with plans for a fully space qualified laser transmitter.

Hexagonal-like Nb2O5 Nanoplates-Based Photodetectors and Photocatalyst with High Performances

NASA Astrophysics Data System (ADS)

Liu, Hui; Gao, Nan; Liao, Meiyong; Fang, Xiaosheng

2015-01-01

Ultraviolet (UV) photodetectors are important tools in the fields of optical imaging, environmental monitoring, and air and water sterilization, as well as flame sensing and early rocket plume detection. Herein, hexagonal-like Nb2O5 nanoplates are synthesized using a facile solvothermal method. UV photodetectors based on single Nb2O5 nanoplates are constructed and the optoelectronic properties have been probed. The photodetectors show remarkable sensitivity with a high external quantum efficiency (EQE) of 9617%, and adequate wavelength selectivity with respect to UV-A light. In addition, the photodetectors exhibit robust stability and strong dependence of photocurrent on light intensity. Also, a low-cost drop-casting method is used to fabricate photodetectors based on Nb2O5 nanoplate film, which exhibit singular thermal stability. Moreover, the hexagonal-like Nb2O5 nanoplates show significantly better photocatalytic performances in decomposing Methylene-blue and Rhdamine B dyes than commercial Nb2O5.

TU-AB-BRB-03: Coverage-Based Treatment Planning to Accommodate Organ Deformable Motions and Contouring Uncertainties for Prostate Treatment

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

Xu, H.

The accepted clinical method to accommodate targeting uncertainties inherent in fractionated external beam radiation therapy is to utilize GTV-to-CTV and CTV-to-PTV margins during the planning process to design a PTV-conformal static dose distribution on the planning image set. Ideally, margins are selected to ensure a high (e.g. >95%) target coverage probability (CP) in spite of inherent inter- and intra-fractional positional variations, tissue motions, and initial contouring uncertainties. Robust optimization techniques, also known as probabilistic treatment planning techniques, explicitly incorporate the dosimetric consequences of targeting uncertainties by including CP evaluation into the planning optimization process along with coverage-based planning objectives. Themore » treatment planner no longer needs to use PTV and/or PRV margins; instead robust optimization utilizes probability distributions of the underlying uncertainties in conjunction with CP-evaluation for the underlying CTVs and OARs to design an optimal treated volume. This symposium will describe CP-evaluation methods as well as various robust planning techniques including use of probability-weighted dose distributions, probability-weighted objective functions, and coverage optimized planning. Methods to compute and display the effect of uncertainties on dose distributions will be presented. The use of robust planning to accommodate inter-fractional setup uncertainties, organ deformation, and contouring uncertainties will be examined as will its use to accommodate intra-fractional organ motion. Clinical examples will be used to inter-compare robust and margin-based planning, highlighting advantages of robust-plans in terms of target and normal tissue coverage. Robust-planning limitations as uncertainties approach zero and as the number of treatment fractions becomes small will be presented, as well as the factors limiting clinical implementation of robust planning. Learning Objectives: To understand robust-planning as a clinical alternative to using margin-based planning. To understand conceptual differences between uncertainty and predictable motion. To understand fundamental limitations of the PTV concept that probabilistic planning can overcome. To understand the major contributing factors to target and normal tissue coverage probability. To understand the similarities and differences of various robust planning techniques To understand the benefits and limitations of robust planning techniques.« less

Intelligent robust control for uncertain nonlinear time-varying systems and its application to robotic systems.

PubMed

Chang, Yeong-Chan

2005-12-01

This paper addresses the problem of designing adaptive fuzzy-based (or neural network-based) robust controls for a large class of uncertain nonlinear time-varying systems. This class of systems can be perturbed by plant uncertainties, unmodeled perturbations, and external disturbances. Nonlinear H(infinity) control technique incorporated with adaptive control technique and VSC technique is employed to construct the intelligent robust stabilization controller such that an H(infinity) control is achieved. The problem of the robust tracking control design for uncertain robotic systems is employed to demonstrate the effectiveness of the developed robust stabilization control scheme. Therefore, an intelligent robust tracking controller for uncertain robotic systems in the presence of high-degree uncertainties can easily be implemented. Its solution requires only to solve a linear algebraic matrix inequality and a satisfactorily transient and asymptotical tracking performance is guaranteed. A simulation example is made to confirm the performance of the developed control algorithms.

Robust Satisficing Decision Making for Unmanned Aerial Vehicle Complex Missions under Severe Uncertainty

PubMed Central

Ji, Xiaoting; Niu, Yifeng; Shen, Lincheng

2016-01-01

This paper presents a robust satisficing decision-making method for Unmanned Aerial Vehicles (UAVs) executing complex missions in an uncertain environment. Motivated by the info-gap decision theory, we formulate this problem as a novel robust satisficing optimization problem, of which the objective is to maximize the robustness while satisfying some desired mission requirements. Specifically, a new info-gap based Markov Decision Process (IMDP) is constructed to abstract the uncertain UAV system and specify the complex mission requirements with the Linear Temporal Logic (LTL). A robust satisficing policy is obtained to maximize the robustness to the uncertain IMDP while ensuring a desired probability of satisfying the LTL specifications. To this end, we propose a two-stage robust satisficing solution strategy which consists of the construction of a product IMDP and the generation of a robust satisficing policy. In the first stage, a product IMDP is constructed by combining the IMDP with an automaton representing the LTL specifications. In the second, an algorithm based on robust dynamic programming is proposed to generate a robust satisficing policy, while an associated robustness evaluation algorithm is presented to evaluate the robustness. Finally, through Monte Carlo simulation, the effectiveness of our algorithms is demonstrated on an UAV search mission under severe uncertainty so that the resulting policy can maximize the robustness while reaching the desired performance level. Furthermore, by comparing the proposed method with other robust decision-making methods, it can be concluded that our policy can tolerate higher uncertainty so that the desired performance level can be guaranteed, which indicates that the proposed method is much more effective in real applications. PMID:27835670

Robust Satisficing Decision Making for Unmanned Aerial Vehicle Complex Missions under Severe Uncertainty.

PubMed

Ji, Xiaoting; Niu, Yifeng; Shen, Lincheng

2016-01-01

This paper presents a robust satisficing decision-making method for Unmanned Aerial Vehicles (UAVs) executing complex missions in an uncertain environment. Motivated by the info-gap decision theory, we formulate this problem as a novel robust satisficing optimization problem, of which the objective is to maximize the robustness while satisfying some desired mission requirements. Specifically, a new info-gap based Markov Decision Process (IMDP) is constructed to abstract the uncertain UAV system and specify the complex mission requirements with the Linear Temporal Logic (LTL). A robust satisficing policy is obtained to maximize the robustness to the uncertain IMDP while ensuring a desired probability of satisfying the LTL specifications. To this end, we propose a two-stage robust satisficing solution strategy which consists of the construction of a product IMDP and the generation of a robust satisficing policy. In the first stage, a product IMDP is constructed by combining the IMDP with an automaton representing the LTL specifications. In the second, an algorithm based on robust dynamic programming is proposed to generate a robust satisficing policy, while an associated robustness evaluation algorithm is presented to evaluate the robustness. Finally, through Monte Carlo simulation, the effectiveness of our algorithms is demonstrated on an UAV search mission under severe uncertainty so that the resulting policy can maximize the robustness while reaching the desired performance level. Furthermore, by comparing the proposed method with other robust decision-making methods, it can be concluded that our policy can tolerate higher uncertainty so that the desired performance level can be guaranteed, which indicates that the proposed method is much more effective in real applications.

Signature gene expressions of cell wall integrity pathway concur with tolerance response of industrial yeast Saccharomyces cerevisiae against biomass pretreatment inhibitors

USDA-ARS?s Scientific Manuscript database

Traditional industrial ethanologenic yeast Saccharomyces cerevisiae has a robust performance under various environmental conditions and can be served as a candidate for the next-generation biocatalyst development for advanced biofuels production using lignocellulose mateials. Overcoming toxic compou...

A Balanced Accuracy Fitness Function Leads to Robust Analysis Using Grammatical Evolution Neural Networks in the Case of Class Imbalance

EPA Science Inventory

The identification and characterization of genetic and environmental factors that predict common, complex disease is a major goal of human genetics. The ubiquitous nature of epistatic interaction in the underlying genetic etiology of such disease presents a difficult analytical ...

Grazing in an uncertain environment: Modeling the trade-off between production and robustness

USDA-ARS?s Scientific Manuscript database

Concern with the environmental, economic, and social impacts of the post-WWII model of agricultural intensification has led to renewed interest in grazing as a feeding strategy for temperate livestock farming systems. Putting the culture and utilization of grass at the core of livestock feeding not ...

OPERA: A free and open source QSAR tool for predicting physicochemical properties and environmental fate endpoints

EPA Science Inventory

Collecting the chemical structures and data for necessary QSAR modeling is facilitated by available public databases and open data. However, QSAR model performance is dependent on the quality of data and modeling methodology used. This study developed robust QSAR models for physi...

Partners in research exceed the sum of the parts: partners > parts

USDA-ARS?s Scientific Manuscript database

The overriding goal of analytical chemistry research has always been and will always be the same: develop and validate approaches to achieve the needed quality of results that fit the purpose of the analysis in the fastest, easiest, safest, most economical, robust, and environmentally-friendly way ...

The Future of Toxicity Testing - the NRC Vision and EPA’s ToxCast Program

EPA Science Inventory

The EPA requested the National Research Council (NRC) to develop a vision and strategic plan for toxicity testing in the 21st century. The 2007 report called for transforming toxicology to provide a robust scientific basis for assessing adverse health effects of environmental age...

Cellobiose fermenting yeast produces varied forms of native ß-glucosidase

USDA-ARS?s Scientific Manuscript database

The rapid growing yeast strain NRRL Y-50464 is robust to environmental stress and resistant to 2-furaldehyde (furfural) and 5-[hydroxymethyl]-2-furaldehyde (HMF). It is able to utilize cellobiose as its sole source of carbon and produces ethanol from lignocellulosic biomass by simultaneous saccharif...

Current limitations and a path forward to improve testing for the environmental assessment of endocrine active substances-presentation

EPA Science Inventory

To assess the hazards and risks of possible endocrine active chemicals (EACs), there is a need for robust, validated test methods that detect perturbations of endocrine pathways and provide reliable information for evaluating potential adverse effects on apical endpoints. One iss...

The History and Generality of AQUATOX, a Robust Mechanistic Model

EPA Science Inventory

In 1987, the U.S. Environmental Protection Agency sponsored a workshop in Baltimore on modeling the fate and effects of toxic organics. The specifications for the AQUATOX model came out of this workshop, and the first paper on the modeling concept was published soon after. Since ...

Consumers' health risk-benefit perception of seafood and attitude toward the marine environment: Insights from five European countries.

PubMed

Jacobs, Silke; Sioen, Isabelle; Pieniak, Zuzanna; De Henauw, Stefaan; Maulvault, Ana Luisa; Reuver, Marieke; Fait, Gabriella; Cano-Sancho, German; Verbeke, Wim

2015-11-01

This research classifies European consumers into segments based on their health risk-benefit perception related to seafood consumption. The profiling variables of these segments are seafood consumption frequency, general attitude toward consuming fish, confidence in control organizations, attitude toward the marine environment, environmental concern and socio-demographics. A web-based survey was performed in one western European country (Belgium), one northern European country (Ireland) and three southern European countries (Italy, Portugal and Spain), resulting in a total sample of 2824 participants. A cluster analysis was performed based on risk-benefit perception related to seafood and the profiles of the segments were determined by a robust 2-way ANOVA analysis accounting for country effects. Although this study confirms consumers' positive image of consuming seafood, gradients are found in health risk-benefit perception related to seafood consumption. Seafood consumption frequency is mainly determined by country-related traditions and habits related to seafood rather than by risk-benefit perceptions. Segments with a higher benefit perception, irrespective of their level of risk perception, show a more positive attitude toward consuming seafood and toward the marine environment; moreover, they report a higher concern about the marine environment and have a higher involvement with seafood and with the marine environment. Consequently, information campaigns concentrating on pro-environmental behavior are recommended to raise the involvement with seafood and the marine environment as this is associated with a higher environmental concern. This research underpins that in such information campaigns a nationally differentiated rather than a pan-European or international information strategy should be aimed for because of significant cultural differences between the identified segments. Copyright © 2015. Published by Elsevier Inc.

Use of amplicon sequencing to improve sensitivity in PCR-based detection of microbial pathogen in environmental samples.

PubMed

Saingam, Prakit; Li, Bo; Yan, Tao

2018-06-01

DNA-based molecular detection of microbial pathogens in complex environments is still plagued by sensitivity, specificity and robustness issues. We propose to address these issues by viewing them as inadvertent consequences of requiring specific and adequate amplification (SAA) of target DNA molecules by current PCR methods. Using the invA gene of Salmonella as the model system, we investigated if next generation sequencing (NGS) can be used to directly detect target sequences in false-negative PCR reaction (PCR-NGS) in order to remove the SAA requirement from PCR. False-negative PCR and qPCR reactions were first created using serial dilutions of laboratory-prepared Salmonella genomic DNA and then analyzed directly by NGS. Target invA sequences were detected in all false-negative PCR and qPCR reactions, which lowered the method detection limits near the theoretical minimum of single gene copy detection. The capability of the PCR-NGS approach in correcting false negativity was further tested and confirmed under more environmentally relevant conditions using Salmonella-spiked stream water and sediment samples. Finally, the PCR-NGS approach was applied to ten urban stream water samples and detected invA sequences in eight samples that would be otherwise deemed Salmonella negative. Analysis of the non-target sequences in the false-negative reactions helped to identify primer dime-like short sequences as the main cause of the false negativity. Together, the results demonstrated that the PCR-NGS approach can significantly improve method sensitivity, correct false-negative detections, and enable sequence-based analysis for failure diagnostics in complex environmental samples. Copyright © 2018 Elsevier B.V. All rights reserved.

Detecting breakdown points in metabolic networks.

PubMed

Tagore, Somnath; De, Rajat K

2011-12-14

A complex network of biochemical reactions present in an organism generates various biological moieties necessary for its survival. It is seen that biological systems are robust to genetic and environmental changes at all levels of organization. Functions of various organisms are sustained against mutational changes by using alternative pathways. It is also seen that if any one of the paths for production of the same metabolite is hampered, an alternate path tries to overcome this defect and helps in combating the damage. Certain physical, chemical or genetic change in any of the precursor substrate of a biochemical reaction may damage the production of the ultimate product. We employ a quantitative approach for simulating this phenomena of causing a physical change in the biochemical reactions by performing external perturbations to 12 metabolic pathways under carbohydrate metabolism in Saccharomyces cerevisae as well as 14 metabolic pathways under carbohydrate metabolism in Homo sapiens. Here, we investigate the relationship between structure and degree of compatibility of metabolites against external perturbations, i.e., robustness. Robustness can also be further used to identify the extent to which a metabolic pathway can resist a mutation event. Biological networks with a certain connectivity distribution may be very resilient to a particular attack but not to another. The goal of this work is to determine the exact boundary of network breakdown due to both random and targeted attack, thereby analyzing its robustness. We also find that compared to various non-standard models, metabolic networks are exceptionally robust. Here, we report the use of a 'Resilience-based' score for enumerating the concept of 'network-breakdown'. We also use this approach for analyzing metabolite essentiality providing insight into cellular robustness that can be further used for future drug development. We have investigated the behavior of metabolic pathways under carbohydrate metabolism in S. cerevisae and H. sapiens against random and targeted attack. Both random as well as targeted resilience were calculated by formulating a measure, that we termed as 'Resilience score'. Datasets of metabolites were collected for 12 metabolic pathways belonging to carbohydrate metabolism in S. cerevisae and 14 metabolic pathways belonging to carbohydrate metabolism in H. sapiens from Kyoto Encyclopedia for Genes and Genomes (KEGG). Copyright © 2011 Elsevier Ltd. All rights reserved.

Landscape genomics of Sphaeralcea ambigua in the Mojave Desert: a multivariate, spatially-explicit approach to guide ecological restoration

USGS Publications Warehouse

Shryock, Daniel F.; Havrilla, Caroline A.; DeFalco, Lesley; Esque, Todd C.; Custer, Nathan; Wood, Troy E.

2015-01-01

Local adaptation influences plant species’ responses to climate change and their performance in ecological restoration. Fine-scale physiological or phenological adaptations that direct demographic processes may drive intraspecific variability when baseline environmental conditions change. Landscape genomics characterize adaptive differentiation by identifying environmental drivers of adaptive genetic variability and mapping the associated landscape patterns. We applied such an approach to Sphaeralcea ambigua, an important restoration plant in the arid southwestern United States, by analyzing variation at 153 amplified fragment length polymorphism loci in the context of environmental gradients separating 47 Mojave Desert populations. We identified 37 potentially adaptive loci through a combination of genome scan approaches. We then used a generalized dissimilarity model (GDM) to relate variability in potentially adaptive loci with spatial gradients in temperature, precipitation, and topography. We identified non-linear thresholds in loci frequencies driven by summer maximum temperature and water stress, along with continuous variation corresponding to temperature seasonality. Two GDM-based approaches for mapping predicted patterns of local adaptation are compared. Additionally, we assess uncertainty in spatial interpolations through a novel spatial bootstrapping approach. Our study presents robust, accessible methods for deriving spatially-explicit models of adaptive genetic variability in non-model species that will inform climate change modelling and ecological restoration.

Surface immuno-functionalisation for the capture and detection of Vibrio species in the marine environment: a new management tool for industrial facilities.

PubMed

Laczka, Olivier F; Labbate, Maurizio; Seymour, Justin R; Bourne, David G; Fielder, Stewart S; Doblin, Martina A

2014-01-01

Bacteria from the genus Vibrio are a common and environmentally important group of bacteria within coastal environments and include species pathogenic to aquaculture organisms. Their distribution and abundance are linked to specific environmental parameters, including temperature, salinity and nutrient enrichment. Accurate and efficient detection of Vibrios in environmental samples provides a potential important indicator of overall ecosystem health while also allowing rapid management responses for species pathogenic to humans or species implicated in disease of economically important aquacultured fish and invertebrates. In this study, we developed a surface immuno-functionalisation protocol, based on an avidin-biotin type covalent binding strategy, allowing specific sandwich-type detection of bacteria from the Vibrio genus. The assay was optimized on 12 diverse Vibrio strains, including species that have implications for aquaculture industries, reaching detection limits between 7×10(3) to 3×10(4) cells mL(-1). Current techniques for the detection of total Vibrios rely on laborious or inefficient analyses resulting in delayed management decisions. This work represents a novel approach for a rapid, accurate, sensitive and robust tool for quantifying Vibrios directly in industrial systems and in the environment, thereby facilitating rapid management responses.

Four simple rules that are sufficient to generate the mammalian blastocyst

PubMed Central

Nissen, Silas Boye; Perera, Marta; Gonzalez, Javier Martin; Morgani, Sophie M.; Jensen, Mogens H.; Sneppen, Kim; Brickman, Joshua M.

2017-01-01

Early mammalian development is both highly regulative and self-organizing. It involves the interplay of cell position, predetermined gene regulatory networks, and environmental interactions to generate the physical arrangement of the blastocyst with precise timing. However, this process occurs in the absence of maternal information and in the presence of transcriptional stochasticity. How does the preimplantation embryo ensure robust, reproducible development in this context? It utilizes a versatile toolbox that includes complex intracellular networks coupled to cell—cell communication, segregation by differential adhesion, and apoptosis. Here, we ask whether a minimal set of developmental rules based on this toolbox is sufficient for successful blastocyst development, and to what extent these rules can explain mutant and experimental phenotypes. We implemented experimentally reported mechanisms for polarity, cell—cell signaling, adhesion, and apoptosis as a set of developmental rules in an agent-based in silico model of physically interacting cells. We find that this model quantitatively reproduces specific mutant phenotypes and provides an explanation for the emergence of heterogeneity without requiring any initial transcriptional variation. It also suggests that a fixed time point for the cells’ competence of fibroblast growth factor (FGF)/extracellular signal—regulated kinase (ERK) sets an embryonic clock that enables certain scaling phenomena, a concept that we evaluate quantitatively by manipulating embryos in vitro. Based on these observations, we conclude that the minimal set of rules enables the embryo to experiment with stochastic gene expression and could provide the robustness necessary for the evolutionary diversification of the preimplantation gene regulatory network. PMID:28700688

Watermark: An Application and Methodology and Application for Interactive and intelligent Decision Support for Groundwater Systems

NASA Astrophysics Data System (ADS)

Pierce, S. A.; Wagner, K.; Schwartz, S.; Gentle, J. N., Jr.

2016-12-01

Critical water resources face the effects of historic drought, increased demand, and potential contamination, the need has never been greater to develop resources to effectively communicate conservation and protection across a broad audience and geographical area. The Watermark application and macro-analysis methodology merges topical analysis of context rich corpus from policy texts with multi-attributed solution sets from integrated models of water resource and other subsystems, such as mineral, food, energy, or environmental systems to construct a scalable, robust, and reproducible approach for identifying links between policy and science knowledge bases. The Watermark application is an open-source, interactive workspace to support science-based visualization and decision making. Designed with generalization in mind, Watermark is a flexible platform that allows for data analysis and inclusion of large datasets with an interactive front-end capable of connecting with other applications as well as advanced computing resources. In addition, the Watermark analysis methodology offers functionality that streamlines communication with non-technical users for policy, education, or engagement with groups around scientific topics of societal relevance. The technology stack for Watermark was selected with the goal of creating a robust and dynamic modular codebase that can be adjusted to fit many use cases and scale to support usage loads that range between simple data display to complex scientific simulation-based modelling and analytics. The methodology uses to topical analysis and simulation-optimization to systematically analyze the policy and management realities of resource systems and explicitly connect the social and problem contexts with science-based and engineering knowledge from models. A case example demonstrates use in a complex groundwater resources management study highlighting multi-criteria spatial decision making and uncertainty comparisons.

From Sensor to Observation Web with environmental enablers in the Future Internet.

PubMed

Havlik, Denis; Schade, Sven; Sabeur, Zoheir A; Mazzetti, Paolo; Watson, Kym; Berre, Arne J; Mon, Jose Lorenzo

2011-01-01

This paper outlines the grand challenges in global sustainability research and the objectives of the FP7 Future Internet PPP program within the Digital Agenda for Europe. Large user communities are generating significant amounts of valuable environmental observations at local and regional scales using the devices and services of the Future Internet. These communities' environmental observations represent a wealth of information which is currently hardly used or used only in isolation and therefore in need of integration with other information sources. Indeed, this very integration will lead to a paradigm shift from a mere Sensor Web to an Observation Web with semantically enriched content emanating from sensors, environmental simulations and citizens. The paper also describes the research challenges to realize the Observation Web and the associated environmental enablers for the Future Internet. Such an environmental enabler could for instance be an electronic sensing device, a web-service application, or even a social networking group affording or facilitating the capability of the Future Internet applications to consume, produce, and use environmental observations in cross-domain applications. The term "envirofied" Future Internet is coined to describe this overall target that forms a cornerstone of work in the Environmental Usage Area within the Future Internet PPP program. Relevant trends described in the paper are the usage of ubiquitous sensors (anywhere), the provision and generation of information by citizens, and the convergence of real and virtual realities to convey understanding of environmental observations. The paper addresses the technical challenges in the Environmental Usage Area and the need for designing multi-style service oriented architecture. Key topics are the mapping of requirements to capabilities, providing scalability and robustness with implementing context aware information retrieval. Another essential research topic is handling data fusion and model based computation, and the related propagation of information uncertainty. Approaches to security, standardization and harmonization, all essential for sustainable solutions, are summarized from the perspective of the Environmental Usage Area. The paper concludes with an overview of emerging, high impact applications in the environmental areas concerning land ecosystems (biodiversity), air quality (atmospheric conditions) and water ecosystems (marine asset management).

From Sensor to Observation Web with Environmental Enablers in the Future Internet

PubMed Central

Havlik, Denis; Schade, Sven; Sabeur, Zoheir A.; Mazzetti, Paolo; Watson, Kym; Berre, Arne J.; Mon, Jose Lorenzo

2011-01-01

This paper outlines the grand challenges in global sustainability research and the objectives of the FP7 Future Internet PPP program within the Digital Agenda for Europe. Large user communities are generating significant amounts of valuable environmental observations at local and regional scales using the devices and services of the Future Internet. These communities’ environmental observations represent a wealth of information which is currently hardly used or used only in isolation and therefore in need of integration with other information sources. Indeed, this very integration will lead to a paradigm shift from a mere Sensor Web to an Observation Web with semantically enriched content emanating from sensors, environmental simulations and citizens. The paper also describes the research challenges to realize the Observation Web and the associated environmental enablers for the Future Internet. Such an environmental enabler could for instance be an electronic sensing device, a web-service application, or even a social networking group affording or facilitating the capability of the Future Internet applications to consume, produce, and use environmental observations in cross-domain applications. The term “envirofied” Future Internet is coined to describe this overall target that forms a cornerstone of work in the Environmental Usage Area within the Future Internet PPP program. Relevant trends described in the paper are the usage of ubiquitous sensors (anywhere), the provision and generation of information by citizens, and the convergence of real and virtual realities to convey understanding of environmental observations. The paper addresses the technical challenges in the Environmental Usage Area and the need for designing multi-style service oriented architecture. Key topics are the mapping of requirements to capabilities, providing scalability and robustness with implementing context aware information retrieval. Another essential research topic is handling data fusion and model based computation, and the related propagation of information uncertainty. Approaches to security, standardization and harmonization, all essential for sustainable solutions, are summarized from the perspective of the Environmental Usage Area. The paper concludes with an overview of emerging, high impact applications in the environmental areas concerning land ecosystems (biodiversity), air quality (atmospheric conditions) and water ecosystems (marine asset management). PMID:22163827

Multi-criteria GIS-based siting of an incineration plant for municipal solid waste.

PubMed

Tavares, Gilberto; Zsigraiová, Zdena; Semiao, Viriato

2011-01-01

Siting a municipal solid waste (MSW) incineration plant requires a comprehensive evaluation to identify the best available location(s) that can simultaneously meet the requirements of regulations and minimise economic, environmental, health, and social costs. A spatial multi-criteria evaluation methodology is presented to assess land suitability for a plant siting and applied to Santiago Island of Cape Verde. It combines the analytical hierarchy process (AHP) to estimate the selected evaluation criteria weights with Geographic Information Systems (GIS) for spatial data analysis that avoids the subjectivity of the judgements of decision makers in establishing the influences between some criteria or clusters of criteria. An innovative feature of the method lies in incorporating the environmental impact assessment of the plant operation as a criterion in the decision-making process itself rather than as an a posteriori assessment. Moreover, a two-scale approach is considered. At a global scale an initial screening identifies inter-municipal zones satisfying the decisive requirements (socio-economic, technical and environmental issues, with weights respectively, of 48%, 41% and 11%). A detailed suitability ranking inside the previously identified zones is then performed at a local scale in two phases and includes environmental assessment of the plant operation. Those zones are ranked by combining the non-environmental feasibility of Phase 1 (with a weight of 75%) with the environmental assessment of the plant operation impact of Phase 2 (with a weight of 25%). The reliability and robustness of the presented methodology as a decision supporting tool is assessed through a sensitivity analysis. The results proved the system effectiveness in the ranking process. Copyright © 2011 Elsevier Ltd. All rights reserved.

An epigenome-wide association study meta-analysis of educational attainment.

PubMed

Karlsson Linnér, R; Marioni, R E; Rietveld, C A; Simpkin, A J; Davies, N M; Watanabe, K; Armstrong, N J; Auro, K; Baumbach, C; Bonder, M J; Buchwald, J; Fiorito, G; Ismail, K; Iurato, S; Joensuu, A; Karell, P; Kasela, S; Lahti, J; McRae, A F; Mandaviya, P R; Seppälä, I; Wang, Y; Baglietto, L; Binder, E B; Harris, S E; Hodge, A M; Horvath, S; Hurme, M; Johannesson, M; Latvala, A; Mather, K A; Medland, S E; Metspalu, A; Milani, L; Milne, R L; Pattie, A; Pedersen, N L; Peters, A; Polidoro, S; Räikkönen, K; Severi, G; Starr, J M; Stolk, L; Waldenberger, M; Eriksson, J G; Esko, T; Franke, L; Gieger, C; Giles, G G; Hägg, S; Jousilahti, P; Kaprio, J; Kähönen, M; Lehtimäki, T; Martin, N G; van Meurs, J B C; Ollikainen, M; Perola, M; Posthuma, D; Raitakari, O T; Sachdev, P S; Taskesen, E; Uitterlinden, A G; Vineis, P; Wijmenga, C; Wright, M J; Relton, C; Davey Smith, G; Deary, I J; Koellinger, P D; Benjamin, D J

2017-12-01

The epigenome is associated with biological factors, such as disease status, and environmental factors, such as smoking, alcohol consumption and body mass index. Although there is a widespread perception that environmental influences on the epigenome are pervasive and profound, there has been little evidence to date in humans with respect to environmental factors that are biologically distal. Here we provide evidence on the associations between epigenetic modifications-in our case, CpG methylation-and educational attainment (EA), a biologically distal environmental factor that is arguably among the most important life-shaping experiences for individuals. Specifically, we report the results of an epigenome-wide association study meta-analysis of EA based on data from 27 cohort studies with a total of 10 767 individuals. We find nine CpG probes significantly associated with EA. However, robustness analyses show that all nine probes have previously been found to be associated with smoking. Only two associations remain when we perform a sensitivity analysis in the subset of never-smokers, and these two probes are known to be strongly associated with maternal smoking during pregnancy, and thus their association with EA could be due to correlation between EA and maternal smoking. Moreover, the effect sizes of the associations with EA are far smaller than the known associations with the biologically proximal environmental factors alcohol consumption, body mass index, smoking and maternal smoking during pregnancy. Follow-up analyses that combine the effects of many probes also point to small methylation associations with EA that are highly correlated with the combined effects of smoking. If our findings regarding EA can be generalized to other biologically distal environmental factors, then they cast doubt on the hypothesis that such factors have large effects on the epigenome.

Open Source Dataturbine (OSDT) Android Sensorpod in Environmental Observing Systems

NASA Astrophysics Data System (ADS)

Fountain, T. R.; Shin, P.; Tilak, S.; Trinh, T.; Smith, J.; Kram, S.

2014-12-01

The OSDT Android SensorPod is a custom-designed mobile computing platform for assembling wireless sensor networks for environmental monitoring applications. Funded by an award from the Gordon and Betty Moore Foundation, the OSDT SensorPod represents a significant technological advance in the application of mobile and cloud computing technologies to near-real-time applications in environmental science, natural resources management, and disaster response and recovery. It provides a modular architecture based on open standards and open-source software that allows system developers to align their projects with industry best practices and technology trends, while avoiding commercial vendor lock-in to expensive proprietary software and hardware systems. The integration of mobile and cloud-computing infrastructure represents a disruptive technology in the field of environmental science, since basic assumptions about technology requirements are now open to revision, e.g., the roles of special purpose data loggers and dedicated site infrastructure. The OSDT Android SensorPod was designed with these considerations in mind, and the resulting system exhibits the following characteristics - it is flexible, efficient and robust. The system was developed and tested in the three science applications: 1) a fresh water limnology deployment in Wisconsin, 2) a near coastal marine science deployment at the UCSD Scripps Pier, and 3) a terrestrial ecological deployment in the mountains of Taiwan. As part of a public education and outreach effort, a Facebook page with daily ocean pH measurements from the UCSD Scripps pier was developed. Wireless sensor networks and the virtualization of data and network services is the future of environmental science infrastructure. The OSDT Android SensorPod was designed and developed to harness these new technology developments for environmental monitoring applications.

Changes in travel-related carbon emissions associated with modernization of services for patients with acute myocardial infarction: a case study.

PubMed

Zander, Alexis; Niggebrugge, Aphrodite; Pencheon, David; Lyratzopoulos, Georgios

2011-06-01

Little attention has been paid on the carbon footprint of different healthcare service models. We examined this question for service models for patients with acute ST elevation myocardial infarction (STEMI). We estimated carbon emissions associated with ambulance (patient) transport under a primary percutaneous coronary intervention (pPCI) care model based in tertiary centres, compared with historical emissions under a thrombolysis model based in general hospitals. We used geographical information on 41,449 hospitalizations, and published UK government fuel to carbon emissions conversion factors. The average ambulance journey required for transporting a STEMI patient to its closest care point was 13.0 km under the thrombolysis model and 42.2 km under the pPCI model, producing 3.46 and 11.2 kg of CO(2) emissions, respectively. Thus, introducing pPCI will more than triple ambulance journey associated carbon emissions (by a factor of 3.24). This ratio was robust to sensitivity analysis varying assumptions on conversion factor values; and the number of patients treated. Introducing pPCI to manage STEMI patients results in substantial carbon emissions increase. Environmental profiling of service modernization projects could motivate carbon control strategies, and care pathways design that will reduce patient transport need. Healthcare planners should consider the environmental legacy of quality improvement initiatives.

Engineering tolerance to industrially relevant stress factors in yeast cell factories.

PubMed

Deparis, Quinten; Claes, Arne; Foulquié-Moreno, Maria R; Thevelein, Johan M

2017-06-01

The main focus in development of yeast cell factories has generally been on establishing optimal activity of heterologous pathways and further metabolic engineering of the host strain to maximize product yield and titer. Adequate stress tolerance of the host strain has turned out to be another major challenge for obtaining economically viable performance in industrial production. Although general robustness is a universal requirement for industrial microorganisms, production of novel compounds using artificial metabolic pathways presents additional challenges. Many of the bio-based compounds desirable for production by cell factories are highly toxic to the host cells in the titers required for economic viability. Artificial metabolic pathways also turn out to be much more sensitive to stress factors than endogenous pathways, likely because regulation of the latter has been optimized in evolution in myriads of environmental conditions. We discuss different environmental and metabolic stress factors with high relevance for industrial utilization of yeast cell factories and the experimental approaches used to engineer higher stress tolerance. Improving stress tolerance in a predictable manner in yeast cell factories should facilitate their widespread utilization in the bio-based economy and extend the range of products successfully produced in large scale in a sustainable and economically profitable way. © FEMS 2017.

Engineering tolerance to industrially relevant stress factors in yeast cell factories

PubMed Central

Deparis, Quinten; Claes, Arne; Foulquié-Moreno, Maria R.

2017-01-01

Abstract The main focus in development of yeast cell factories has generally been on establishing optimal activity of heterologous pathways and further metabolic engineering of the host strain to maximize product yield and titer. Adequate stress tolerance of the host strain has turned out to be another major challenge for obtaining economically viable performance in industrial production. Although general robustness is a universal requirement for industrial microorganisms, production of novel compounds using artificial metabolic pathways presents additional challenges. Many of the bio-based compounds desirable for production by cell factories are highly toxic to the host cells in the titers required for economic viability. Artificial metabolic pathways also turn out to be much more sensitive to stress factors than endogenous pathways, likely because regulation of the latter has been optimized in evolution in myriads of environmental conditions. We discuss different environmental and metabolic stress factors with high relevance for industrial utilization of yeast cell factories and the experimental approaches used to engineer higher stress tolerance. Improving stress tolerance in a predictable manner in yeast cell factories should facilitate their widespread utilization in the bio-based economy and extend the range of products successfully produced in large scale in a sustainable and economically profitable way. PMID:28586408

ALLIANCE: An architecture for fault tolerant, cooperative control of heterogeneous mobile robots

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

Parker, L.E.

1995-02-01

This research addresses the problem of achieving fault tolerant cooperation within small- to medium-sized teams of heterogeneous mobile robots. The author describes a novel behavior-based, fully distributed architecture, called ALLIANCE, that utilizes adaptive action selection to achieve fault tolerant cooperative control in robot missions involving loosely coupled, largely independent tasks. The robots in this architecture possess a variety of high-level functions that they can perform during a mission, and must at all times select an appropriate action based on the requirements of the mission, the activities of other robots, the current environmental conditions, and their own internal states. Since suchmore » cooperative teams often work in dynamic and unpredictable environments, the software architecture allows the team members to respond robustly and reliably to unexpected environmental changes and modifications in the robot team that may occur due to mechanical failure, the learning of new skills, or the addition or removal of robots from the team by human intervention. After presenting ALLIANCE, the author describes in detail experimental results of an implementation of this architecture on a team of physical mobile robots performing a cooperative box pushing demonstration. These experiments illustrate the ability of ALLIANCE to achieve adaptive, fault-tolerant cooperative control amidst dynamic changes in the capabilities of the robot team.« less

(Im)Perfect robustness and adaptation of metabolic networks subject to metabolic and gene-expression regulation: marrying control engineering with metabolic control analysis.

PubMed

He, Fei; Fromion, Vincent; Westerhoff, Hans V

2013-11-21

Metabolic control analysis (MCA) and supply-demand theory have led to appreciable understanding of the systems properties of metabolic networks that are subject exclusively to metabolic regulation. Supply-demand theory has not yet considered gene-expression regulation explicitly whilst a variant of MCA, i.e. Hierarchical Control Analysis (HCA), has done so. Existing analyses based on control engineering approaches have not been very explicit about whether metabolic or gene-expression regulation would be involved, but designed different ways in which regulation could be organized, with the potential of causing adaptation to be perfect. This study integrates control engineering and classical MCA augmented with supply-demand theory and HCA. Because gene-expression regulation involves time integration, it is identified as a natural instantiation of the 'integral control' (or near integral control) known in control engineering. This study then focuses on robustness against and adaptation to perturbations of process activities in the network, which could result from environmental perturbations, mutations or slow noise. It is shown however that this type of 'integral control' should rarely be expected to lead to the 'perfect adaptation': although the gene-expression regulation increases the robustness of important metabolite concentrations, it rarely makes them infinitely robust. For perfect adaptation to occur, the protein degradation reactions should be zero order in the concentration of the protein, which may be rare biologically for cells growing steadily. A proposed new framework integrating the methodologies of control engineering and metabolic and hierarchical control analysis, improves the understanding of biological systems that are regulated both metabolically and by gene expression. In particular, the new approach enables one to address the issue whether the intracellular biochemical networks that have been and are being identified by genomics and systems biology, correspond to the 'perfect' regulatory structures designed by control engineering vis-à-vis optimal functions such as robustness. To the extent that they are not, the analyses suggest how they may become so and this in turn should facilitate synthetic biology and metabolic engineering.

(Im)Perfect robustness and adaptation of metabolic networks subject to metabolic and gene-expression regulation: marrying control engineering with metabolic control analysis

PubMed Central

2013-01-01

Background Metabolic control analysis (MCA) and supply–demand theory have led to appreciable understanding of the systems properties of metabolic networks that are subject exclusively to metabolic regulation. Supply–demand theory has not yet considered gene-expression regulation explicitly whilst a variant of MCA, i.e. Hierarchical Control Analysis (HCA), has done so. Existing analyses based on control engineering approaches have not been very explicit about whether metabolic or gene-expression regulation would be involved, but designed different ways in which regulation could be organized, with the potential of causing adaptation to be perfect. Results This study integrates control engineering and classical MCA augmented with supply–demand theory and HCA. Because gene-expression regulation involves time integration, it is identified as a natural instantiation of the ‘integral control’ (or near integral control) known in control engineering. This study then focuses on robustness against and adaptation to perturbations of process activities in the network, which could result from environmental perturbations, mutations or slow noise. It is shown however that this type of ‘integral control’ should rarely be expected to lead to the ‘perfect adaptation’: although the gene-expression regulation increases the robustness of important metabolite concentrations, it rarely makes them infinitely robust. For perfect adaptation to occur, the protein degradation reactions should be zero order in the concentration of the protein, which may be rare biologically for cells growing steadily. Conclusions A proposed new framework integrating the methodologies of control engineering and metabolic and hierarchical control analysis, improves the understanding of biological systems that are regulated both metabolically and by gene expression. In particular, the new approach enables one to address the issue whether the intracellular biochemical networks that have been and are being identified by genomics and systems biology, correspond to the ‘perfect’ regulatory structures designed by control engineering vis-à-vis optimal functions such as robustness. To the extent that they are not, the analyses suggest how they may become so and this in turn should facilitate synthetic biology and metabolic engineering. PMID:24261908

Using offsets to mitigate environmental impacts of major projects: A stakeholder analysis.

PubMed

Martin, Nigel; Evans, Megan; Rice, John; Lodhia, Sumit; Gibbons, Philip

2016-09-01

Global patterns of development suggest that as more projects are initiated, business will need to find acceptable measures to conserve biodiversity. The application of environmental offsets allows firms to combine their economic interests with the environment and society. This article presents the results of a multi-stakeholder analysis related to the design of offsets principles, policies, and regulatory processes, using a large infrastructure projects context. The results indicate that business was primarily interested in using direct offsets and other compensatory measures, known internationally as indirect offsets, to acquit their environmental management obligations. In contrast, the environmental sector argued that highly principled and scientifically robust offsets programs should be implemented and maintained for enduring environmental protection. Stakeholder consensus stressed the importance of offsets registers with commensurate monitoring and enforcement. Our findings provide instructive insights into the countervailing views of offsets policy stakeholders. Copyright © 2016 Elsevier Ltd. All rights reserved.

″The Anthropocene″, Ecosystem Management, and Environmental Virtue.

PubMed

Sandler, Ronald

2016-01-01

*Portions of this article are drawn from: Sandler, R. Environmental Ethics: Theory in Practice, Oxford University Press, New York, in press. In this article I consider contrasting views on the implications of rapid, macroscale anthropogenic change for environmental ethics, particularly ecosystem management, species conservation, and environmental virtue. I begin by reviewing the Anthropocene debate, which has become a primary point of discourse on whether we ought to embrace a more interventionist stance regarding ecosystem management and species conservation. I then discuss the challenges posed by rapid ecological change to predominant ecosystem management and species conservation practices. I argue that these challenges not withstanding, we ought not go all in on interventionist management, even as novel conservation and management techniques can be justified in particular cases. It is possible to adopt a more forward looking normative stance, without licensing robust interventionism. Finally, I discuss the implications of this for some environmental virtues.

Creep Behavior of Hafnia and Ytterbium Silicate Environmental Barrier Coating Systems on SiC/SiC Ceramic Matrix Composites

NASA Technical Reports Server (NTRS)

Zhu, Dongming; Fox, Dennis S.; Ghosn, Louis J.; Harder, Bryan

2011-01-01

Environmental barrier coatings will play a crucial role in future advanced gas turbine engines because of their ability to significantly extend the temperature capability and stability of SiC/SiC ceramic matrix composite (CMC) engine components, thus improving the engine performance. In order to develop high performance, robust coating systems for engine components, appropriate test approaches simulating operating temperature gradient and stress environments for evaluating the critical coating properties must be established. In this paper, thermal gradient mechanical testing approaches for evaluating creep and fatigue behavior of environmental barrier coated SiC/SiC CMC systems will be described. The creep and fatigue behavior of Hafnia and ytterbium silicate environmental barrier coatings on SiC/SiC CMC systems will be reported in simulated environmental exposure conditions. The coating failure mechanisms will also be discussed under the heat flux and stress conditions.

Robust Identification of Local Adaptation from Allele Frequencies

PubMed Central

Günther, Torsten; Coop, Graham

2013-01-01

Comparing allele frequencies among populations that differ in environment has long been a tool for detecting loci involved in local adaptation. However, such analyses are complicated by an imperfect knowledge of population allele frequencies and neutral correlations of allele frequencies among populations due to shared population history and gene flow. Here we develop a set of methods to robustly test for unusual allele frequency patterns and correlations between environmental variables and allele frequencies while accounting for these complications based on a Bayesian model previously implemented in the software Bayenv. Using this model, we calculate a set of “standardized allele frequencies” that allows investigators to apply tests of their choice to multiple populations while accounting for sampling and covariance due to population history. We illustrate this first by showing that these standardized frequencies can be used to detect nonparametric correlations with environmental variables; these correlations are also less prone to spurious results due to outlier populations. We then demonstrate how these standardized allele frequencies can be used to construct a test to detect SNPs that deviate strongly from neutral population structure. This test is conceptually related to FST and is shown to be more powerful, as we account for population history. We also extend the model to next-generation sequencing of population pools—a cost-efficient way to estimate population allele frequencies, but one that introduces an additional level of sampling noise. The utility of these methods is demonstrated in simulations and by reanalyzing human SNP data from the Human Genome Diversity Panel populations and pooled next-generation sequencing data from Atlantic herring. An implementation of our method is available from http://gcbias.org. PMID:23821598

Integration Science and Technology of Advanced Ceramics for Energy and Environmental Applications

NASA Technical Reports Server (NTRS)

Singh, M.

2012-01-01

The discovery of new and innovative materials has been known to culminate in major turning points in human history. The transformative impact and functional manifestation of new materials have been demonstrated in every historical era by their integration into new products, systems, assemblies, and devices. In modern times, the integration of new materials into usable products has a special relevance for the technological development and economic competitiveness of industrial societies. Advanced ceramic technologies dramatically impact the energy and environmental landscape due to potential wide scale applications in all aspects of energy production, storage, distribution, conservation, and efficiency. Examples include gas turbine propulsion systems, fuel cells, thermoelectrics, photovoltaics, distribution and transmission systems based on superconductors, nuclear power generation, and waste disposal. Robust ceramic integration technologies enable hierarchical design and manufacturing of intricate ceramic components starting with geometrically simpler units that are subsequently joined to themselves and/or to metals to create components with progressively higher levels of complexity and functionality. However, for the development of robust and reliable integrated systems with optimum performance under different operating conditions, the detailed understanding of various thermochemical and thermomechanical factors is critical. Different approaches are required for the integration of ceramic-metal and ceramic-ceramic systems across length scales (macro to nano). In this presentation, a few examples of integration of ceramic to metals and ceramic to ceramic systems will be presented. Various challenges and opportunities in design, fabrication, and testing of integrated similar (ceramic-ceramic) and dissimilar (ceramic-metal) material systems will be discussed. Potential opportunities and need for the development of innovative design philosophies, approaches, and integrated system testing under simulated application conditions will also be presented.

The relationship between urban forests and income: A meta-analysis.

PubMed

Gerrish, Ed; Watkins, Shannon Lea

2018-02-01

Urban trees provide substantial public health and public environmental benefits. However, scholarly works suggest that urban trees may be unequally distributed among poor and minority urban communities, meaning that these communities are potentially being deprived of public environmental benefits, a form of environmental injustice. The evidence of this problem is not uniform however, and evidence of inequity varies in size and significance across studies. This variation in results suggests the need for a research synthesis and meta-analysis. We employed a systematic literature search to identify original studies which examined the relationship between urban forest cover and income (n=61) and coded each effect size (n=332). We used meta-analytic techniques to estimate the average (unconditional) relationship between urban forest cover and income and to estimate the impact that methodological choices, measurement, publication characteristics, and study site characteristics had on the magnitude of that relationship. We leveraged variation in study methodology to evaluate the extent to which results were sensitive to methodological choices often debated in the geographic and environmental justice literature but not yet evaluated in environmental amenities research. We found evidence of income-based inequity in urban forest cover (unconditional mean effect size = 0.098; s.e. = .017) that was robust across most measurement and methodological strategies in original studies and results did not differ systematically with study site characteristics. Studies that controlled for spatial autocorrelation, a violation of independent errors, found evidence of substantially less urban forest inequity; future research in this area should test and correct for spatial autocorrelation.

Rank-preserving regression: a more robust rank regression model against outliers.

PubMed

Chen, Tian; Kowalski, Jeanne; Chen, Rui; Wu, Pan; Zhang, Hui; Feng, Changyong; Tu, Xin M

2016-08-30

Mean-based semi-parametric regression models such as the popular generalized estimating equations are widely used to improve robustness of inference over parametric models. Unfortunately, such models are quite sensitive to outlying observations. The Wilcoxon-score-based rank regression (RR) provides more robust estimates over generalized estimating equations against outliers. However, the RR and its extensions do not sufficiently address missing data arising in longitudinal studies. In this paper, we propose a new approach to address outliers under a different framework based on the functional response models. This functional-response-model-based alternative not only addresses limitations of the RR and its extensions for longitudinal data, but, with its rank-preserving property, even provides more robust estimates than these alternatives. The proposed approach is illustrated with both real and simulated data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A Novel Robust H∞ Filter Based on Krein Space Theory in the SINS/CNS Attitude Reference System.

PubMed

Yu, Fei; Lv, Chongyang; Dong, Qianhui

2016-03-18

Owing to their numerous merits, such as compact, autonomous and independence, the strapdown inertial navigation system (SINS) and celestial navigation system (CNS) can be used in marine applications. What is more, due to the complementary navigation information obtained from two different kinds of sensors, the accuracy of the SINS/CNS integrated navigation system can be enhanced availably. Thus, the SINS/CNS system is widely used in the marine navigation field. However, the CNS is easily interfered with by the surroundings, which will lead to the output being discontinuous. Thus, the uncertainty problem caused by the lost measurement will reduce the system accuracy. In this paper, a robust H∞ filter based on the Krein space theory is proposed. The Krein space theory is introduced firstly, and then, the linear state and observation models of the SINS/CNS integrated navigation system are established reasonably. By taking the uncertainty problem into account, in this paper, a new robust H∞ filter is proposed to improve the robustness of the integrated system. At last, this new robust filter based on the Krein space theory is estimated by numerical simulations and actual experiments. Additionally, the simulation and experiment results and analysis show that the attitude errors can be reduced by utilizing the proposed robust filter effectively when the measurements are missing discontinuous. Compared to the traditional Kalman filter (KF) method, the accuracy of the SINS/CNS integrated system is improved, verifying the robustness and the availability of the proposed robust H∞ filter.

Application of stakeholder-based and modelling approaches for supporting robust adaptation decision making under future climatic uncertainty and changing urban-agricultural water demand

NASA Astrophysics Data System (ADS)

Bhave, Ajay; Dessai, Suraje; Conway, Declan; Stainforth, David

2016-04-01

Deep uncertainty in future climate change and socio-economic conditions necessitates the use of assess-risk-of-policy approaches over predict-then-act approaches for adaptation decision making. Robust Decision Making (RDM) approaches embody this principle and help evaluate the ability of adaptation options to satisfy stakeholder preferences under wide-ranging future conditions. This study involves the simultaneous application of two RDM approaches; qualitative and quantitative, in the Cauvery River Basin in Karnataka (population ~23 million), India. The study aims to (a) determine robust water resources adaptation options for the 2030s and 2050s and (b) compare the usefulness of a qualitative stakeholder-driven approach with a quantitative modelling approach. For developing a large set of future scenarios a combination of climate narratives and socio-economic narratives was used. Using structured expert elicitation with a group of climate experts in the Indian Summer Monsoon, climatic narratives were developed. Socio-economic narratives were developed to reflect potential future urban and agricultural water demand. In the qualitative RDM approach, a stakeholder workshop helped elicit key vulnerabilities, water resources adaptation options and performance criteria for evaluating options. During a second workshop, stakeholders discussed and evaluated adaptation options against the performance criteria for a large number of scenarios of climatic and socio-economic change in the basin. In the quantitative RDM approach, a Water Evaluation And Planning (WEAP) model was forced by precipitation and evapotranspiration data, coherent with the climatic narratives, together with water demand data based on socio-economic narratives. We find that compared to business-as-usual conditions options addressing urban water demand satisfy performance criteria across scenarios and provide co-benefits like energy savings and reduction in groundwater depletion, while options reducing agricultural water demand significantly affect downstream water availability. Water demand options demonstrate potential to improve environmental flow conditions and satisfy legal water supply requirements for downstream riparian states. On the other hand, currently planned large scale infrastructural projects demonstrate reduced value in certain scenarios, illustrating the impacts of lock-in effects of large scale infrastructure. From a methodological perspective, we find that while the stakeholder-driven approach revealed robust options in a resource-light manner and helped initiate much needed interaction amongst stakeholders, the modelling approach provides complementary quantitative information. The study reveals robust adaptation options for this important basin and provides a strong methodological basis for carrying out future studies that support adaptation decision making.

Dynamics in microbial communities: Unraveling mechanisms to identify principles

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

Konopka, Allan; Lindemann, Stephen R.; Fredrickson, Jim K.

2015-07-01

Diversity begets higher order properties such as functional stability and robustness in microbial communities, but principles that inform conceptual (and eventually predictive) models of community dynamics are lacking. Recent work has shown that selection as well as dispersal and drift shape communities, but the mechanistic bases for assembly of communities and the forces that maintain their function in the face of environmental perturbation are not well understood. Conceptually, some interactions among community members could generate endogenous dynamics in composition, even in the absence of environmental changes. These endogenous dynamics are further perturbed by exogenous forcing factors to produce a richermore » network of community interactions, and it is this “system” that is the basis for higher order community properties. Elucidation of principles that follow from this conceptual model requires identifying the mechanisms that (a) optimize diversity within a community and (b) impart community stability. The network of interactions between organisms can be an important element by providing a buffer against disturbance beyond the effect of functional redundancy, as alternative pathways with different combinations of microbes can be recruited to fulfill specific functions.« less

A Late Glacial to Holocene record of environmental change from Lake Dojran (Macedonia, Greece)

NASA Astrophysics Data System (ADS)

Francke, A.; Wagner, B.; Leng, M. J.; Rethemeyer, J.

2013-02-01

A Late Glacial to Holocene sediment sequence (Co1260, 717 cm) from Lake Dojran, located at the boarder of the F.Y.R. of Macedonia and Greece, has been investigated to provide information on climate variability in the Balkan region. A robust age-model was established from 13 radiocarbon ages, and indicates that the base of the sequence was deposited at ca. 12 500 cal yr BP, when the lake-level was low. Variations in sedimentological (H2O, TOC, CaCO3, TS, TOC/TN, TOC/TS, grain-size, XRF, δ18Ocarb, δ13Ccarb, δ13Corg) data were linked to hydro-acoustic data and indicate that warmer and more humid climate conditions characterised the remaining period of the Younger Dryas until the beginning of the Holocene. The Holocene exhibits significant environmental variations, including the 8.2 and 4.2 ka cooling events, the Medieval Warm Period and the Little Ice Age. Human induced erosion processes in the catchment of Lake Dojran intensified after 2800 cal yr BP.

Surveying Europe’s Only Cave-Dwelling Chordate Species (Proteus anguinus) Using Environmental DNA

PubMed Central

Márton, Orsolya; Schmidt, Benedikt R.; Gál, Júlia Tünde; Jelić, Dušan

2017-01-01

In surveillance of subterranean fauna, especially in the case of rare or elusive aquatic species, traditional techniques used for epigean species are often not feasible. We developed a non-invasive survey method based on environmental DNA (eDNA) to detect the presence of the red-listed cave-dwelling amphibian, Proteus anguinus, in the caves of the Dinaric Karst. We tested the method in fifteen caves in Croatia, from which the species was previously recorded or expected to occur. We successfully confirmed the presence of P. anguinus from ten caves and detected the species for the first time in five others. Using a hierarchical occupancy model we compared the availability and detection probability of eDNA of two water sampling methods, filtration and precipitation. The statistical analysis showed that both availability and detection probability depended on the method and estimates for both probabilities were higher using filter samples than for precipitation samples. Combining reliable field and laboratory methods with robust statistical modeling will give the best estimates of species occurrence. PMID:28129383

Devil in disguise: Does drinking lead to a disability pension?

PubMed

Böckerman, Petri; Hyytinen, Ari; Maczulskij, Terhi

2016-05-01

To examine whether alcohol consumption in adulthood is related to the incidence of receiving a disability pension later in life. Twin data for Finnish men and women born before 1958 were matched to register-based individual information on disability pensions. Twin differences were used to eliminate both shared environmental and genetic factors. The quantity of alcohol consumption was measured as the weekly average consumption using self-reported data from three surveys (1975, 1981 and 1990). The disability pension data were evaluated from 1990-2004. The models that account for shared environmental and genetic factors reveal that heavy drinkers are significantly more likely to receive a disability pension than moderate drinkers or constant abstainers. Heavy drinking that leads to passing out is also positively related to receiving a disability pension. The results were robust to the use of potential confounders that twins do not share, such as education years, the number of chronic diseases, physical activity at work and leisure, and stressful life events. Drinking profiles in early adulthood are an important predictor of receiving a disability pension later in life. Copyright © 2015 Elsevier Inc. All rights reserved.

Replication of a gene-environment interaction Via Multimodel inference: additive-genetic variance in adolescents' general cognitive ability increases with family-of-origin socioeconomic status.

PubMed

Kirkpatrick, Robert M; McGue, Matt; Iacono, William G

2015-03-01

The present study of general cognitive ability attempts to replicate and extend previous investigations of a biometric moderator, family-of-origin socioeconomic status (SES), in a sample of 2,494 pairs of adolescent twins, non-twin biological siblings, and adoptive siblings assessed with individually administered IQ tests. We hypothesized that SES would covary positively with additive-genetic variance and negatively with shared-environmental variance. Important potential confounds unaddressed in some past studies, such as twin-specific effects, assortative mating, and differential heritability by trait level, were found to be negligible. In our main analysis, we compared models by their sample-size corrected AIC, and base our statistical inference on model-averaged point estimates and standard errors. Additive-genetic variance increased with SES-an effect that was statistically significant and robust to model specification. We found no evidence that SES moderated shared-environmental influence. We attempt to explain the inconsistent replication record of these effects, and provide suggestions for future research.

Replication of a Gene-Environment Interaction via Multimodel Inference: Additive-Genetic Variance in Adolescents’ General Cognitive Ability Increases with Family-of-Origin Socioeconomic Status

PubMed Central

Kirkpatrick, Robert M.; McGue, Matt; Iacono, William G.

2015-01-01

The present study of general cognitive ability attempts to replicate and extend previous investigations of a biometric moderator, family-of-origin socioeconomic status (SES), in a sample of 2,494 pairs of adolescent twins, non-twin biological siblings, and adoptive siblings assessed with individually administered IQ tests. We hypothesized that SES would covary positively with additive-genetic variance and negatively with shared-environmental variance. Important potential confounds unaddressed in some past studies, such as twin-specific effects, assortative mating, and differential heritability by trait level, were found to be negligible. In our main analysis, we compared models by their sample-size corrected AIC, and base our statistical inference on model-averaged point estimates and standard errors. Additive-genetic variance increased with SES—an effect that was statistically significant and robust to model specification. We found no evidence that SES moderated shared-environmental influence. We attempt to explain the inconsistent replication record of these effects, and provide suggestions for future research. PMID:25539975

High-order computational fluid dynamics tools for aircraft design

PubMed Central

Wang, Z. J.

2014-01-01

Most forecasts predict an annual airline traffic growth rate between 4.5 and 5% in the foreseeable future. To sustain that growth, the environmental impact of aircraft cannot be ignored. Future aircraft must have much better fuel economy, dramatically less greenhouse gas emissions and noise, in addition to better performance. Many technical breakthroughs must take place to achieve the aggressive environmental goals set up by governments in North America and Europe. One of these breakthroughs will be physics-based, highly accurate and efficient computational fluid dynamics and aeroacoustics tools capable of predicting complex flows over the entire flight envelope and through an aircraft engine, and computing aircraft noise. Some of these flows are dominated by unsteady vortices of disparate scales, often highly turbulent, and they call for higher-order methods. As these tools will be integral components of a multi-disciplinary optimization environment, they must be efficient to impact design. Ultimately, the accuracy, efficiency, robustness, scalability and geometric flexibility will determine which methods will be adopted in the design process. This article explores these aspects and identifies pacing items. PMID:25024419

Robust planning of dynamic wireless charging infrastructure for battery electric buses

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

Liu, Zhaocai; Song, Ziqi

Battery electric buses with zero tailpipe emissions have great potential in improving environmental sustainability and livability of urban areas. However, the problems of high cost and limited range associated with on-board batteries have substantially limited the popularity of battery electric buses. The technology of dynamic wireless power transfer (DWPT), which provides bus operators with the ability to charge buses while in motion, may be able to effectively alleviate the drawbacks of electric buses. In this paper, we address the problem of simultaneously selecting the optimal location of the DWPT facilities and designing the optimal battery sizes of electric buses formore » a DWPT electric bus system. The problem is first constructed as a deterministic model in which the uncertainty of energy consumption and travel time of electric buses is neglected. The methodology of robust optimization (RO) is then adopted to address the uncertainty of energy consumption and travel time. The affinely adjustable robust counterpart (AARC) of the deterministic model is developed, and its equivalent tractable mathematical programming is derived. Both the deterministic model and the robust model are demonstrated with a real-world bus system. The results of our study demonstrate that the proposed deterministic model can effectively determine the allocation of DWPT facilities and the battery sizes of electric buses for a DWPT electric bus system; and the robust model can further provide optimal designs that are robust against the uncertainty of energy consumption and travel time for electric buses.« less

Robust planning of dynamic wireless charging infrastructure for battery electric buses

DOE PAGES

Liu, Zhaocai; Song, Ziqi

2017-10-01

Battery electric buses with zero tailpipe emissions have great potential in improving environmental sustainability and livability of urban areas. However, the problems of high cost and limited range associated with on-board batteries have substantially limited the popularity of battery electric buses. The technology of dynamic wireless power transfer (DWPT), which provides bus operators with the ability to charge buses while in motion, may be able to effectively alleviate the drawbacks of electric buses. In this paper, we address the problem of simultaneously selecting the optimal location of the DWPT facilities and designing the optimal battery sizes of electric buses formore » a DWPT electric bus system. The problem is first constructed as a deterministic model in which the uncertainty of energy consumption and travel time of electric buses is neglected. The methodology of robust optimization (RO) is then adopted to address the uncertainty of energy consumption and travel time. The affinely adjustable robust counterpart (AARC) of the deterministic model is developed, and its equivalent tractable mathematical programming is derived. Both the deterministic model and the robust model are demonstrated with a real-world bus system. The results of our study demonstrate that the proposed deterministic model can effectively determine the allocation of DWPT facilities and the battery sizes of electric buses for a DWPT electric bus system; and the robust model can further provide optimal designs that are robust against the uncertainty of energy consumption and travel time for electric buses.« less

Application of simple adaptive control to water hydraulic servo cylinder system

NASA Astrophysics Data System (ADS)

Ito, Kazuhisa; Yamada, Tsuyoshi; Ikeo, Shigeru; Takahashi, Koji

2012-09-01

Although conventional model reference adaptive control (MRAC) achieves good tracking performance for cylinder control, the controller structure is much more complicated and has less robustness to disturbance in real applications. This paper discusses the use of simple adaptive control (SAC) for positioning a water hydraulic servo cylinder system. Compared with MRAC, SAC has a simpler and lower order structure, i.e., higher feasibility. The control performance of SAC is examined and evaluated on a water hydraulic servo cylinder system. With the recent increased concerns over global environmental problems, the water hydraulic technique using pure tap water as a pressure medium has become a new drive source comparable to electric, oil hydraulic, and pneumatic drive systems. This technique is also preferred because of its high power density, high safety against fire hazards in production plants, and easy availability. However, the main problems for precise control in a water hydraulic system are steady state errors and overshoot due to its large friction torque and considerable leakage flow. MRAC has been already applied to compensate for these effects, and better control performances have been obtained. However, there have been no reports on the application of SAC for water hydraulics. To make clear the merits of SAC, the tracking control performance and robustness are discussed based on experimental results. SAC is confirmed to give better tracking performance compared with PI control, and a control precision comparable to MRAC (within 10 μm of the reference position) and higher robustness to parameter change, despite the simple controller. The research results ensure a wider application of simple adaptive control in real mechanical systems.

2.4-3.2 GHz robust self-injecting injection-locked phase-locked loop

NASA Astrophysics Data System (ADS)

Yang, Jincheng; Zhang, Zhao; Qi, Nan; Liu, Liyuan; Liu, Jian; Wu, Nanjian

2018-04-01

In this paper, we propose a robust self-injecting injection-locked phase-locked loop (SI-ILPLL). It adopts a phase alignment loop (PAL) based on a subsampling phase frequency detector to align the phase between the injected pulse and the voltage-controlled oscillator (VCO) output. With the proposed phase frequency detector, the PAL performs phase alignment and the pulse generator can self-inject pulses into the VCO for injection locking. The subsampling phase detection and self-injection locking techniques can suppress the phase noise of the SI-ILPLL. The SI-ILPLL shows excellent robustness to environmental interference. The SI-ILPLL is implemented in 65 nm CMOS technology. It occupies an active area of 0.7 mm2. The measured root-mean-square (RMS) jitters at 3.2 GHz output without and with injection locking are 216 and 131 fs, respectively. When the supply voltage varies from 1.17 to 1.23 V and the temperature varies from 0 to 80 °C, the maximum jitter variation of all the output frequencies is less than 50 fs. The measured results demonstrate that even when a large interference appears at the supply voltage and unlocks the SI-ILPLL, the SI-ILPLL can self-recover its injection-locked state rapidly after the disturbance disappears, whereas the conventional ILPLL cannot self-recover its locked state after losing it. The power consumption of the SI-ILPLL is 7.4 mW under a 1.2 V supply voltage. The SI-ILPLL achieves a figure of merit (FOM) of -249 dB.

Are we closer to the vision? A proposed framework for incorporating omics into environmental assessments.

PubMed

Martyniuk, Christopher J

2018-04-01

Environmental science has benefited a great deal from omics-based technologies. High-throughput toxicology has defined adverse outcome pathways (AOPs), prioritized chemicals of concern, and identified novel actions of environmental chemicals. While many of these approaches are conducted under rigorous laboratory conditions, a significant challenge has been the interpretation of omics data in "real-world" exposure scenarios. Clarity in the interpretation of these data limits their use in environmental monitoring programs. In recent years, one overarching objective of many has been to address fundamental questions concerning experimental design and the robustness of data collected under the broad umbrella of environmental genomics. These questions include: (1) the likelihood that molecular profiles return to a predefined baseline level following remediation efforts, (2) how reference site selection in an urban environment influences interpretation of omics data and (3) what is the most appropriate species to monitor in the environment from an omics point of view. In addition, inter-genomics studies have been conducted to assess transcriptome reproducibility in toxicology studies. One lesson learned from inter-genomics studies is that there are core molecular networks that can be identified by multiple laboratories using the same platform. This supports the idea that "omics-networks" defined a priori may be a viable approach moving forward for evaluating environmental impacts over time. Both spatial and temporal variability in ecosystem structure is expected to influence molecular responses to environmental stressors, and it is important to recognize how these variables, as well as individual factor (i.e. sex, age, maturation), may confound interpretation of network responses to chemicals. This mini-review synthesizes the progress made towards adopting these tools into environmental monitoring and identifies future challenges to be addressed, as we move into the next era of high throughput sequencing. A conceptual framework for validating and incorporating molecular networks into environmental monitoring programs is proposed. As AOPs become more defined and their potential in environmental monitoring assessments becomes more recognized, the AOP framework may prove to be the conduit between omics and penultimate ecological responses for environmental risk assessments. Copyright © 2018 Elsevier B.V. All rights reserved.

A Scoping Review of Maternal and Child Health Clinicians Attitudes, Beliefs, Practice, Training and Perceived Self-Competence in Environmental Health.

PubMed

Massaquoi, Lamin Daddy; Edwards, Nancy Christine

2015-12-10

Clinicians regularly assess, diagnose and manage illnesses which are directly or indirectly linked to environmental exposures. Yet, various studies have identified gaps in environmental assessment in routine clinical practice. This review assessed clinicians' environmental health practices, attitudes and beliefs, and competencies and training. Relevant articles were sought using a systematic search strategy using five databases, grey literature and a hand search. Search strategies and protocols were developed using tailored mesh terms and keywords. 43 out of 11,291 articles were eligible for inclusion. Clinicians' attitudes and beliefs towards environmental health and routine clinical practice were generally positive, with most clinicians believing that environmental hazards affect human health. However, with the exception of tobacco smoke exposure, environmental health assessment was infrequently part of routine clinical practice. Clinicians' self-competence in environmental assessment was reported to be inadequate. Major challenges were the time required to complete an assessment, inadequate training and concerns about negative patients' responses. Clinicians have strong positive attitudes and beliefs about the importance of environmental health assessments. However, more concerted and robust strategies will be needed to support clinicians in assuming their assessment and counselling roles related to a wider range of environmental hazards.

Environmental Sustainability and Effects on Urban Micro Region using Agent-Based Modeling of Urbanisation in Select Major Indian Cities

NASA Astrophysics Data System (ADS)

Aithal, B. H.

2015-12-01

Abstract: Urbanisation has gained momentum with globalization in India. Policy decisions to set up commercial, industrial hubs have fuelled large scale migration, added with population upsurge has contributed to the fast growing urban region that needs to be monitored in order to design sustainable urban cities. Unplanned urbanization have resulted in the growth of peri-urban region referred to as urban sprawl, are often devoid of basic amenities and infrastructure leading to large scale environmental problems that are evident. Remote sensing data acquired through space borne sensors at regular interval helps in understanding urban dynamics aided by Geoinformatics which has proved very effective in mapping and monitoring for sustainable urban planning. Cellular automata (CA) is a robust approach for the spatially explicit simulation of land-use land cover dynamics. CA uses rules, states, conditions that are vital factors in modelling urbanisation. This communication effectively introduces simulation assistances of CA with the agent based modelling supported by its fuzzy characteristics and weightages through analytical hierarchal process (AHP). This has been done considering perceived agents such as industries, natural resource etc. Respective agent's role in development of a particular regions into an urban area has been examined with weights and its influence of each of these agents based on its characteristics functions. Validation was performed obtaining a high kappa coefficient indicating the quality and the allocation performance of the model & validity of the model to predict future projections. The prediction using the proposed model was performed for 2030. Further environmental sustainability of each of these cities are explored such as water features, environment, greenhouse gas emissions, effects on human human health etc., Modeling suggests trend of various land use classes transformation with the spurt in urban expansions based on specific regions and policies providing a visual spatial information to both urban planners and city managers. Further environmental sustainability assessment indicates dwindling natural resources and increase in thermal discomfort to the living population thereby indicating need for balanced and planned development.

Structural damage detection based on stochastic subspace identification and statistical pattern recognition: II. Experimental validation under varying temperature

NASA Astrophysics Data System (ADS)

Lin, Y. Q.; Ren, W. X.; Fang, S. E.

2011-11-01

Although most vibration-based damage detection methods can acquire satisfactory verification on analytical or numerical structures, most of them may encounter problems when applied to real-world structures under varying environments. The damage detection methods that directly extract damage features from the periodically sampled dynamic time history response measurements are desirable but relevant research and field application verification are still lacking. In this second part of a two-part paper, the robustness and performance of the statistics-based damage index using the forward innovation model by stochastic subspace identification of a vibrating structure proposed in the first part have been investigated against two prestressed reinforced concrete (RC) beams tested in the laboratory and a full-scale RC arch bridge tested in the field under varying environments. Experimental verification is focused on temperature effects. It is demonstrated that the proposed statistics-based damage index is insensitive to temperature variations but sensitive to the structural deterioration or state alteration. This makes it possible to detect the structural damage for the real-scale structures experiencing ambient excitations and varying environmental conditions.

Joining and Integration of Silicon Carbide-Based Materials for High Temperature Applications

NASA Technical Reports Server (NTRS)

Halbig, Michael C.; Singh, Mrityunjay

2016-01-01

Advanced joining and integration technologies of silicon carbide-based ceramics and ceramic matrix composites are enabling for their implementation into wide scale aerospace and ground-based applications. The robust joining and integration technologies allow for large and complex shapes to be fabricated and integrated with the larger system. Potential aerospace applications include lean-direct fuel injectors, thermal actuators, turbine vanes, blades, shrouds, combustor liners and other hot section components. Ground based applications include components for energy and environmental systems. Performance requirements and processing challenges are identified for the successful implementation different joining technologies. An overview will be provided of several joining approaches which have been developed for high temperature applications. In addition, various characterization approaches were pursued to provide an understanding of the processing-microstructure-property relationships. Microstructural analysis of the joint interfaces was conducted using optical, scanning electron, and transmission electron microscopy to identify phases and evaluate the bond quality. Mechanical testing results will be presented along with the need for new standardized test methods. The critical need for tailoring interlayer compositions for optimum joint properties will also be highlighted.

Knowledge base and sensor bus messaging service architecture for critical tsunami warning and decision-support

NASA Astrophysics Data System (ADS)

Sabeur, Z. A.; Wächter, J.; Middleton, S. E.; Zlatev, Z.; Häner, R.; Hammitzsch, M.; Loewe, P.

2012-04-01

The intelligent management of large volumes of environmental monitoring data for early tsunami warning requires the deployment of robust and scalable service oriented infrastructure that is supported by an agile knowledge-base for critical decision-support In the TRIDEC project (TRIDEC 2010-2013), a sensor observation service bus of the TRIDEC system is being developed for the advancement of complex tsunami event processing and management. Further, a dedicated TRIDEC system knowledge-base is being implemented to enable on-demand access to semantically rich OGC SWE compliant hydrodynamic observations and operationally oriented meta-information to multiple subscribers. TRIDEC decision support requires a scalable and agile real-time processing architecture which enables fast response to evolving subscribers requirements as the tsunami crisis develops. This is also achieved with the support of intelligent processing services which specialise in multi-level fusion methods with relevance feedback and deep learning. The TRIDEC knowledge base development work coupled with that of the generic sensor bus platform shall be presented to demonstrate advanced decision-support with situation awareness in context of tsunami early warning and crisis management.

Reducing DUI among US college students: results of an environmental prevention trial.

PubMed

Clapp, John D; Johnson, Mark; Voas, Robert B; Lange, James E; Shillington, Audrey; Russell, Cristel

2005-03-01

Driving under the influence (DUI) of alcohol is among the most common and serious alcohol-related problems experienced by US college students. Community-based prevention trials using environmental approaches to DUI prevention have been effective in reducing DUI. Such interventions remain untested in college settings. This study is the first to test the efficacy of an environmental prevention campaign to reduce DUI among college students. We used a quasi-experimental non-equivalent comparison group design to test the efficacy of the DUI prevention intervention. Students at the experimental university were exposed to a DUI prevention intervention that included a social marketing campaign, a media advocacy campaign and increased law enforcement (DUI checkpoints and roving DUI patrols). Students from two large public universities located along the US/Mexico border participated in the seven-semester study. In total, 4832 college students took part. Using telephone interviews of randomly selected students, we took pre- and postintervention measures of self-reported DUI. Self-reported DUI (past year) decreased significantly from pre-test to post-test (odds ratio = 0.55) at the intervention school, whereas rates at the comparison campus remained stable. The campus-intervention interaction was statistically significant (P < 0.05), suggesting that the campaign led to the observed change in DUI. Environmental DUI campaigns similar to those validated in community prevention trials can be effective in college settings. Further research, however, is needed to determine the robustness of the changes associated with such campaigns.

Development of 3D Oxide Fuel Mechanics Models

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

Spencer, B. W.; Casagranda, A.; Pitts, S. A.

This report documents recent work to improve the accuracy and robustness of the mechanical constitutive models used in the BISON fuel performance code. These developments include migration of the fuel mechanics models to be based on the MOOSE Tensor Mechanics module, improving the robustness of the smeared cracking model, implementing a capability to limit the time step size based on material model response, and improving the robustness of the return mapping iterations used in creep and plasticity models.

Global motion compensated visual attention-based video watermarking

NASA Astrophysics Data System (ADS)

Oakes, Matthew; Bhowmik, Deepayan; Abhayaratne, Charith

2016-11-01

Imperceptibility and robustness are two key but complementary requirements of any watermarking algorithm. Low-strength watermarking yields high imperceptibility but exhibits poor robustness. High-strength watermarking schemes achieve good robustness but often suffer from embedding distortions resulting in poor visual quality in host media. This paper proposes a unique video watermarking algorithm that offers a fine balance between imperceptibility and robustness using motion compensated wavelet-based visual attention model (VAM). The proposed VAM includes spatial cues for visual saliency as well as temporal cues. The spatial modeling uses the spatial wavelet coefficients while the temporal modeling accounts for both local and global motion to arrive at the spatiotemporal VAM for video. The model is then used to develop a video watermarking algorithm, where a two-level watermarking weighting parameter map is generated from the VAM saliency maps using the saliency model and data are embedded into the host image according to the visual attentiveness of each region. By avoiding higher strength watermarking in the visually attentive region, the resulting watermarked video achieves high perceived visual quality while preserving high robustness. The proposed VAM outperforms the state-of-the-art video visual attention methods in joint saliency detection and low computational complexity performance. For the same embedding distortion, the proposed visual attention-based watermarking achieves up to 39% (nonblind) and 22% (blind) improvement in robustness against H.264/AVC compression, compared to existing watermarking methodology that does not use the VAM. The proposed visual attention-based video watermarking results in visual quality similar to that of low-strength watermarking and a robustness similar to those of high-strength watermarking.

Robust regression for large-scale neuroimaging studies.

PubMed

Fritsch, Virgile; Da Mota, Benoit; Loth, Eva; Varoquaux, Gaël; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun L W; Brühl, Rüdiger; Butzek, Brigitte; Conrod, Patricia; Flor, Herta; Garavan, Hugh; Lemaitre, Hervé; Mann, Karl; Nees, Frauke; Paus, Tomas; Schad, Daniel J; Schümann, Gunter; Frouin, Vincent; Poline, Jean-Baptiste; Thirion, Bertrand

2015-05-01

Multi-subject datasets used in neuroimaging group studies have a complex structure, as they exhibit non-stationary statistical properties across regions and display various artifacts. While studies with small sample sizes can rarely be shown to deviate from standard hypotheses (such as the normality of the residuals) due to the poor sensitivity of normality tests with low degrees of freedom, large-scale studies (e.g. >100 subjects) exhibit more obvious deviations from these hypotheses and call for more refined models for statistical inference. Here, we demonstrate the benefits of robust regression as a tool for analyzing large neuroimaging cohorts. First, we use an analytic test based on robust parameter estimates; based on simulations, this procedure is shown to provide an accurate statistical control without resorting to permutations. Second, we show that robust regression yields more detections than standard algorithms using as an example an imaging genetics study with 392 subjects. Third, we show that robust regression can avoid false positives in a large-scale analysis of brain-behavior relationships with over 1500 subjects. Finally we embed robust regression in the Randomized Parcellation Based Inference (RPBI) method and demonstrate that this combination further improves the sensitivity of tests carried out across the whole brain. Altogether, our results show that robust procedures provide important advantages in large-scale neuroimaging group studies. Copyright © 2015 Elsevier Inc. All rights reserved.

SU-E-T-625: Robustness Evaluation and Robust Optimization of IMPT Plans Based on Per-Voxel Standard Deviation of Dose Distributions.

PubMed

Liu, W; Mohan, R

2012-06-01

Proton dose distributions, IMPT in particular, are highly sensitive to setup and range uncertainties. We report a novel method, based on per-voxel standard deviation (SD) of dose distributions, to evaluate the robustness of proton plans and to robustly optimize IMPT plans to render them less sensitive to uncertainties. For each optimization iteration, nine dose distributions are computed - the nominal one, and one each for ± setup uncertainties along x, y and z axes and for ± range uncertainty. SD of dose in each voxel is used to create SD-volume histogram (SVH) for each structure. SVH may be considered a quantitative representation of the robustness of the dose distribution. For optimization, the desired robustness may be specified in terms of an SD-volume (SV) constraint on the CTV and incorporated as a term in the objective function. Results of optimization with and without this constraint were compared in terms of plan optimality and robustness using the so called'worst case' dose distributions; which are obtained by assigning the lowest among the nine doses to each voxel in the clinical target volume (CTV) and the highest to normal tissue voxels outside the CTV. The SVH curve and the area under it for each structure were used as quantitative measures of robustness. Penalty parameter of SV constraint may be varied to control the tradeoff between robustness and plan optimality. We applied these methods to one case each of H&N and lung. In both cases, we found that imposing SV constraint improved plan robustness but at the cost of normal tissue sparing. SVH-based optimization and evaluation is an effective tool for robustness evaluation and robust optimization of IMPT plans. Studies need to be conducted to test the methods for larger cohorts of patients and for other sites. This research is supported by National Cancer Institute (NCI) grant P01CA021239, the University Cancer Foundation via the Institutional Research Grant program at the University of Texas MD Anderson Cancer Center, and MD Anderson’s cancer center support grant CA016672. © 2012 American Association of Physicists in Medicine.

Optimal run-and-tumble-based transportation of a Janus particle with active steering

NASA Astrophysics Data System (ADS)

Mano, Tomoyuki; Delfau, Jean-Baptiste; Iwasawa, Junichiro; Sano, Masaki

2017-03-01

Although making artificial micrometric swimmers has been made possible by using various propulsion mechanisms, guiding their motion in the presence of thermal fluctuations still remains a great challenge. Such a task is essential in biological systems, which present a number of intriguing solutions that are robust against noisy environmental conditions as well as variability in individual genetic makeup. Using synthetic Janus particles driven by an electric field, we present a feedback-based particle-guiding method quite analogous to the “run-and-tumbling” behavior of Escherichia coli but with a deterministic steering in the tumbling phase: the particle is set to the run state when its orientation vector aligns with the target, whereas the transition to the “steering” state is triggered when it exceeds a tolerance angle αα. The active and deterministic reorientation of the particle is achieved by a characteristic rotational motion that can be switched on and off by modulating the ac frequency of the electric field, which is reported in this work. Relying on numerical simulations and analytical results, we show that this feedback algorithm can be optimized by tuning the tolerance angle αα. The optimal resetting angle depends on signal to noise ratio in the steering state, and it is shown in the experiment. The proposed method is simple and robust for targeting, despite variability in self-propelling speeds and angular velocities of individual particles.

Real-Time Continuous Response Spectra Exceedance Calculation Displayed in a Web-Browser Enables Rapid and Robust Damage Evaluation by First Responders

NASA Astrophysics Data System (ADS)

Franke, M.; Skolnik, D. A.; Harvey, D.; Lindquist, K.

2014-12-01

A novel and robust approach is presented that provides near real-time earthquake alarms for critical structures at distributed locations and large facilities using real-time estimation of response spectra obtained from near free-field motions. Influential studies dating back to the 1980s identified spectral response acceleration as a key ground motion characteristic that correlates well with observed damage in structures. Thus, monitoring and reporting on exceedance of spectra-based thresholds are useful tools for assessing the potential for damage to facilities or multi-structure campuses based on input ground motions only. With as little as one strong-motion station per site, this scalable approach can provide rapid alarms on the damage status of remote towns, critical infrastructure (e.g., hospitals, schools) and points of interests (e.g., bridges) for a very large number of locations enabling better rapid decision making during critical and difficult immediate post-earthquake response actions. Details on the novel approach are presented along with an example implementation for a large energy company. Real-time calculation of PSA exceedance and alarm dissemination are enabled with Bighorn, an extension module based on the Antelope software package that combines real-time spectral monitoring and alarm capabilities with a robust built-in web display server. Antelope is an environmental data collection software package from Boulder Real Time Technologies (BRTT) typically used for very large seismic networks and real-time seismic data analyses. The primary processing engine produces continuous time-dependent response spectra for incoming acceleration streams. It utilizes expanded floating-point data representations within object ring-buffer packets and waveform files in a relational database. This leads to a very fast method for computing response spectra for a large number of channels. A Python script evaluates these response spectra for exceedance of one or more specified spectral limits, reporting any such exceedances via alarm packets that are put in the object ring-buffer for use by any alarm processes that need them. The web-display subsystem allows alert dissemination, interactive exploration, and alarm cancellation via the WWW.

Barriers to Sustainability in Mature-Age Adult Learners: Working toward Identity Change

ERIC Educational Resources Information Center

Martin, Akilah R.; Chen, Joseph C.

2016-01-01

While research on K-12 environmental education (EE) has been quite robust, there has been less focus on effective approaches for mature-age adult learners. This qualitative study examined perceptions of barriers to sustainability in American, mature-age adult learners. Results revealed two interacting, superordinate themes: personal relevance and…