Combining wet and dry research: experience with model development for cardiac mechano-electric structure-function studies

PubMed Central

Quinn, T. Alexander; Kohl, Peter

2013-01-01

Since the development of the first mathematical cardiac cell model 50 years ago, computational modelling has become an increasingly powerful tool for the analysis of data and for the integration of information related to complex cardiac behaviour. Current models build on decades of iteration between experiment and theory, representing a collective understanding of cardiac function. All models, whether computational, experimental, or conceptual, are simplified representations of reality and, like tools in a toolbox, suitable for specific applications. Their range of applicability can be explored (and expanded) by iterative combination of ‘wet’ and ‘dry’ investigation, where experimental or clinical data are used to first build and then validate computational models (allowing integration of previous findings, quantitative assessment of conceptual models, and projection across relevant spatial and temporal scales), while computational simulations are utilized for plausibility assessment, hypotheses-generation, and prediction (thereby defining further experimental research targets). When implemented effectively, this combined wet/dry research approach can support the development of a more complete and cohesive understanding of integrated biological function. This review illustrates the utility of such an approach, based on recent examples of multi-scale studies of cardiac structure and mechano-electric function. PMID:23334215

Robust Semi-Active Ride Control under Stochastic Excitation

DTIC Science & Technology

2014-01-01

broad classes of time-series models which are of practical importance; the Auto-Regressive (AR) models, the Integrated (I) models, and the Moving...Average (MA) models [12]. Combinations of these models result in autoregressive moving average (ARMA) and autoregressive integrated moving average...Down Up 4) Down Down These four cases can be written in compact form as: (20) Where is the Heaviside

Run Environment and Data Management for Earth System Models

NASA Astrophysics Data System (ADS)

Widmann, H.; Lautenschlager, M.; Fast, I.; Legutke, S.

2009-04-01

The Integrating Model and Data Infrastructure (IMDI) developed and maintained by the Model and Data Group (M&D) comprises the Standard Compile Environment (SCE) and the Standard Run Environment (SRE). The IMDI software has a modular design, which allows to combine and couple a suite of model components and as well to execute the tasks independently and on various platforms. Furthermore the modular structure enables the extension to new model combinations and new platforms. The SRE presented here enables the configuration and performance of earth system model experiments from model integration up to storage and visualization of data. We focus on recently implemented tasks such as synchronous data base filling, graphical monitoring and automatic generation of meta data in XML forms during run time. As well we address the capability to run experiments in heterogeneous IT environments with different computing systems for model integration, data processing and storage. These features are demonstrated for model configurations and on platforms used in current or upcoming projects, e.g. MILLENNIUM or IPCC AR5.

An Instructional Merger: HyperCard and the Integrative Teaching Model.

ERIC Educational Resources Information Center

Massie, Carolyn M.; Volk, Larry G.

Teaching methods have been developed and tested that encourage students to process information and refine their thinking skills. The information processing model is known as the Integrative Teaching Model. By combining the computer technology in the HyperCard application for data display and retrieval, instructional delivery of this teaching model…

Discovering Anti-platelet Drug Combinations with an Integrated Model of Activator-Inhibitor Relationships, Activator-Activator Synergies and Inhibitor-Inhibitor Synergies

PubMed Central

Lombardi, Federica; Golla, Kalyan; Fitzpatrick, Darren J.; Casey, Fergal P.; Moran, Niamh; Shields, Denis C.

2015-01-01

Identifying effective therapeutic drug combinations that modulate complex signaling pathways in platelets is central to the advancement of effective anti-thrombotic therapies. However, there is no systems model of the platelet that predicts responses to different inhibitor combinations. We developed an approach which goes beyond current inhibitor-inhibitor combination screening to efficiently consider other signaling aspects that may give insights into the behaviour of the platelet as a system. We investigated combinations of platelet inhibitors and activators. We evaluated three distinct strands of information, namely: activator-inhibitor combination screens (testing a panel of inhibitors against a panel of activators); inhibitor-inhibitor synergy screens; and activator-activator synergy screens. We demonstrated how these analyses may be efficiently performed, both experimentally and computationally, to identify particular combinations of most interest. Robust tests of activator-activator synergy and of inhibitor-inhibitor synergy required combinations to show significant excesses over the double doses of each component. Modeling identified multiple effects of an inhibitor of the P2Y12 ADP receptor, and complementarity between inhibitor-inhibitor synergy effects and activator-inhibitor combination effects. This approach accelerates the mapping of combination effects of compounds to develop combinations that may be therapeutically beneficial. We integrated the three information sources into a unified model that predicted the benefits of a triple drug combination targeting ADP, thromboxane and thrombin signaling. PMID:25875950

The combination of circle topology and leaky integrator neurons remarkably improves the performance of echo state network on time series prediction.

PubMed

Xue, Fangzheng; Li, Qian; Li, Xiumin

2017-01-01

Recently, echo state network (ESN) has attracted a great deal of attention due to its high accuracy and efficient learning performance. Compared with the traditional random structure and classical sigmoid units, simple circle topology and leaky integrator neurons have more advantages on reservoir computing of ESN. In this paper, we propose a new model of ESN with both circle reservoir structure and leaky integrator units. By comparing the prediction capability on Mackey-Glass chaotic time series of four ESN models: classical ESN, circle ESN, traditional leaky integrator ESN, circle leaky integrator ESN, we find that our circle leaky integrator ESN shows significantly better performance than other ESNs with roughly 2 orders of magnitude reduction of the predictive error. Moreover, this model has stronger ability to approximate nonlinear dynamics and resist noise than conventional ESN and ESN with only simple circle structure or leaky integrator neurons. Our results show that the combination of circle topology and leaky integrator neurons can remarkably increase dynamical diversity and meanwhile decrease the correlation of reservoir states, which contribute to the significant improvement of computational performance of Echo state network on time series prediction.

Dynamic combination of sensory and reward information under time pressure

PubMed Central

Farashahi, Shiva; Kao, Chang-Hao

2018-01-01

When making choices, collecting more information is beneficial but comes at the cost of sacrificing time that could be allocated to making other potentially rewarding decisions. To investigate how the brain balances these costs and benefits, we conducted a series of novel experiments in humans and simulated various computational models. Under six levels of time pressure, subjects made decisions either by integrating sensory information over time or by dynamically combining sensory and reward information over time. We found that during sensory integration, time pressure reduced performance as the deadline approached, and choice was more strongly influenced by the most recent sensory evidence. By fitting performance and reaction time with various models we found that our experimental results are more compatible with leaky integration of sensory information with an urgency signal or a decision process based on stochastic transitions between discrete states modulated by an urgency signal. When combining sensory and reward information, subjects spent less time on integration than optimally prescribed when reward decreased slowly over time, and the most recent evidence did not have the maximal influence on choice. The suboptimal pattern of reaction time was partially mitigated in an equivalent control experiment in which sensory integration over time was not required, indicating that the suboptimal response time was influenced by the perception of imperfect sensory integration. Meanwhile, during combination of sensory and reward information, performance did not drop as the deadline approached, and response time was not different between correct and incorrect trials. These results indicate a decision process different from what is involved in the integration of sensory information over time. Together, our results not only reveal limitations in sensory integration over time but also illustrate how these limitations influence dynamic combination of sensory and reward information. PMID:29584717

Organizing integrated care in a university hospital: application of a conceptual framework.

PubMed

Axelsson, Runo; Axelsson, Susanna Bihari; Gustafsson, Jeppe; Seemann, Janne

2014-04-01

As a result of New Public Management, a number of industrial models of quality management have been implemented in health care, mainly in hospitals. At the same time, the concept of integrated care has been developed within other parts of the health sector. The aim of the article is to discuss the relevance of integrated care for hospitals. The discussion is based on application of a conceptual framework outlining a number of organizational models of integrated care. These models are illustrated in a case study of a Danish university hospital implementing a new organization for improving the patient flows of the hospital. The study of the reorganization is based mainly on qualitative data from individual and focus group interviews. The new organization of the university hospital can be regarded as a matrix structure combining a vertical integration of clinical departments with a horizontal integration of patient flows. This structure has elements of both interprofessional and interorganizational integration. A strong focus on teamwork, meetings and information exchange is combined with elements of case management and co-location. It seems that integrated care can be a relevant concept for a hospital. Although the organizational models may challenge established professional boundaries and financial control systems, this concept can be a more promising way to improve the quality of care than the industrial models that have been imported into health care. This application of the concept may also contribute to widen the field of integrated care.

Integrating satellite imagery with simulation modeling to improve burn severity mapping

Treesearch

Eva C. Karau; Pamela G. Sikkink; Robert E. Keane; Gregory K. Dillon

2014-01-01

Both satellite imagery and spatial fire effects models are valuable tools for generating burn severity maps that are useful to fire scientists and resource managers. The purpose of this study was to test a new mapping approach that integrates imagery and modeling to create more accurate burn severity maps. We developed and assessed a statistical model that combines the...

An integrated CFD/experimental analysis of aerodynamic forces and moments

NASA Technical Reports Server (NTRS)

Melton, John E.; Robertson, David D.; Moyer, Seth A.

1989-01-01

Aerodynamic analysis using computational fluid dynamics (CFD) is most fruitful when it is combined with a thorough program of wind tunnel testing. The understanding of aerodynamic phenomena is enhanced by the synergistic use of both analysis methods. A technique is described for an integrated approach to determining the forces and moments acting on a wind tunnel model by using a combination of experimentally measured pressures and CFD predictions. The CFD code used was FLO57 (an Euler solver) and the wind tunnel model was a heavily instrumented delta wing with 62.5 deg of leading-edge sweep. A thorough comparison of the CFD results and the experimental data is presented for surface pressure distributions and longitudinal forces and moments. The experimental pressures were also integrated over the surface of the model and the resulting forces and moments are compared to the CFD and wind tunnel results. The accurate determination of various drag increments via the combined use of the CFD and experimental pressures is presented in detail.

The Integration of Evaluation Paradigms Through Metaphor.

ERIC Educational Resources Information Center

Felker, Roberta M.

The point of view is presented that evaluation projects can be enriched by not using either an exclusively quantitative model or an exclusively qualitative model but by combining both models in one project. The concept of metaphor is used to clarify the usefulness of the combination. Iconic or holistic metaphors describe an object or event as…

Integrative modelling for One Health: pattern, process and participation

PubMed Central

Redding, D. W.; Wood, J. L. N.

2017-01-01

This paper argues for an integrative modelling approach for understanding zoonoses disease dynamics, combining process, pattern and participatory models. Each type of modelling provides important insights, but all are limited. Combining these in a ‘3P’ approach offers the opportunity for a productive conversation between modelling efforts, contributing to a ‘One Health’ agenda. The aim is not to come up with a composite model, but seek synergies between perspectives, encouraging cross-disciplinary interactions. We illustrate our argument with cases from Africa, and in particular from our work on Ebola virus and Lassa fever virus. Combining process-based compartmental models with macroecological data offers a spatial perspective on potential disease impacts. However, without insights from the ground, the ‘black box’ of transmission dynamics, so crucial to model assumptions, may not be fully understood. We show how participatory modelling and ethnographic research of Ebola and Lassa fever can reveal social roles, unsafe practices, mobility and movement and temporal changes in livelihoods. Together with longer-term dynamics of change in societies and ecologies, all can be important in explaining disease transmission, and provide important complementary insights to other modelling efforts. An integrative modelling approach therefore can offer help to improve disease control efforts and public health responses. This article is part of the themed issue ‘One Health for a changing world: zoonoses, ecosystems and human well-being’. PMID:28584172

Combined Log Inventory and Process Simulation Models for the Planning and Control of Sawmill Operations

Treesearch

Guillermo A. Mendoza; Roger J. Meimban; Philip A. Araman; William G. Luppold

1991-01-01

A log inventory model and a real-time hardwood process simulation model were developed and combined into an integrated production planning and control system for hardwood sawmills. The log inventory model was designed to monitor and periodically update the status of the logs in the log yard. The process simulation model was designed to estimate various sawmill...

Estimating demographic parameters using a combination of known-fate and open N-mixture models

USGS Publications Warehouse

Schmidt, Joshua H.; Johnson, Devin S.; Lindberg, Mark S.; Adams, Layne G.

2015-01-01

Accurate estimates of demographic parameters are required to infer appropriate ecological relationships and inform management actions. Known-fate data from marked individuals are commonly used to estimate survival rates, whereas N-mixture models use count data from unmarked individuals to estimate multiple demographic parameters. However, a joint approach combining the strengths of both analytical tools has not been developed. Here we develop an integrated model combining known-fate and open N-mixture models, allowing the estimation of detection probability, recruitment, and the joint estimation of survival. We demonstrate our approach through both simulations and an applied example using four years of known-fate and pack count data for wolves (Canis lupus). Simulation results indicated that the integrated model reliably recovered parameters with no evidence of bias, and survival estimates were more precise under the joint model. Results from the applied example indicated that the marked sample of wolves was biased toward individuals with higher apparent survival rates than the unmarked pack mates, suggesting that joint estimates may be more representative of the overall population. Our integrated model is a practical approach for reducing bias while increasing precision and the amount of information gained from mark–resight data sets. We provide implementations in both the BUGS language and an R package.

Quantitative analysis of microbial biomass yield in aerobic bioreactor.

PubMed

Watanabe, Osamu; Isoda, Satoru

2013-12-01

We have studied the integrated model of reaction rate equations with thermal energy balance in aerobic bioreactor for food waste decomposition and showed that the integrated model has the capability both of monitoring microbial activity in real time and of analyzing biodegradation kinetics and thermal-hydrodynamic properties. On the other hand, concerning microbial metabolism, it was known that balancing catabolic reactions with anabolic reactions in terms of energy and electron flow provides stoichiometric metabolic reactions and enables the estimation of microbial biomass yield (stoichiometric reaction model). We have studied a method for estimating real-time microbial biomass yield in the bioreactor during food waste decomposition by combining the integrated model with the stoichiometric reaction model. As a result, it was found that the time course of microbial biomass yield in the bioreactor during decomposition can be evaluated using the operational data of the bioreactor (weight of input food waste and bed temperature) by the combined model. The combined model can be applied to manage a food waste decomposition not only for controlling system operation to keep microbial activity stable, but also for producing value-added products such as compost on optimum condition. Copyright © 2013 The Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.

Estimating demographic parameters using a combination of known-fate and open N-mixture models.

PubMed

Schmidt, Joshua H; Johnson, Devin S; Lindberg, Mark S; Adams, Layne G

2015-10-01

Accurate estimates of demographic parameters are required to infer appropriate ecological relationships and inform management actions. Known-fate data from marked individuals are commonly used to estimate survival rates, whereas N-mixture models use count data from unmarked individuals to estimate multiple demographic parameters. However, a joint approach combining the strengths of both analytical tools has not been developed. Here we develop an integrated model combining known-fate and open N-mixture models, allowing the estimation of detection probability, recruitment, and the joint estimation of survival. We demonstrate our approach through both simulations and an applied example using four years of known-fate and pack count data for wolves (Canis lupus). Simulation results indicated that the integrated model reliably recovered parameters with no evidence of bias, and survival estimates were more precise under the joint model. Results from the applied example indicated that the marked sample of wolves was biased toward individuals with higher apparent survival rates than the unmarked pack mates, suggesting that joint estimates may be more representative of the overall population. Our integrated model is a practical approach for reducing bias while increasing precision and the amount of information gained from mark-resight data sets. We provide implementations in both the BUGS language and an R package.

Framework programmable platform for the advanced software development workstation. Integration mechanism design document

NASA Technical Reports Server (NTRS)

Mayer, Richard J.; Blinn, Thomas M.; Mayer, Paula S. D.; Reddy, Uday; Ackley, Keith; Futrell, Mike

1991-01-01

The Framework Programmable Software Development Platform (FPP) is a project aimed at combining effective tool and data integration mechanisms with a model of the software development process in an intelligent integrated software development environment. Guided by this model, this system development framework will take advantage of an integrated operating environment to automate effectively the management of the software development process so that costly mistakes during the development phase can be eliminated.

Integral Nursing: An Emerging Framework for Engaging the Evolution of the Profession.

ERIC Educational Resources Information Center

Fiandt, Kathryn; Forman, John; Megel, Mary Erickson; Pakieser, Ruth A.; Burge, Stephanie

2003-01-01

Proposes the Integral Nursing framework, which combines Wilber's All-Quadrant/All-Level model, a heuristic device to organize human experience, and the Spiral Dynamics model of human development organized around value memes or cultural units of information. Includes commentary by Beth L. Rodgers. (Contains 17 references.) (JOW)

Computational toxicology using the OpenTox application programming interface and Bioclipse

PubMed Central

2011-01-01

Background Toxicity is a complex phenomenon involving the potential adverse effect on a range of biological functions. Predicting toxicity involves using a combination of experimental data (endpoints) and computational methods to generate a set of predictive models. Such models rely strongly on being able to integrate information from many sources. The required integration of biological and chemical information sources requires, however, a common language to express our knowledge ontologically, and interoperating services to build reliable predictive toxicology applications. Findings This article describes progress in extending the integrative bio- and cheminformatics platform Bioclipse to interoperate with OpenTox, a semantic web framework which supports open data exchange and toxicology model building. The Bioclipse workbench environment enables functionality from OpenTox web services and easy access to OpenTox resources for evaluating toxicity properties of query molecules. Relevant cases and interfaces based on ten neurotoxins are described to demonstrate the capabilities provided to the user. The integration takes advantage of semantic web technologies, thereby providing an open and simplifying communication standard. Additionally, the use of ontologies ensures proper interoperation and reliable integration of toxicity information from both experimental and computational sources. Conclusions A novel computational toxicity assessment platform was generated from integration of two open science platforms related to toxicology: Bioclipse, that combines a rich scriptable and graphical workbench environment for integration of diverse sets of information sources, and OpenTox, a platform for interoperable toxicology data and computational services. The combination provides improved reliability and operability for handling large data sets by the use of the Open Standards from the OpenTox Application Programming Interface. This enables simultaneous access to a variety of distributed predictive toxicology databases, and algorithm and model resources, taking advantage of the Bioclipse workbench handling the technical layers. PMID:22075173

Combining Feature Selection and Integration—A Neural Model for MT Motion Selectivity

PubMed Central

Beck, Cornelia; Neumann, Heiko

2011-01-01

Background The computation of pattern motion in visual area MT based on motion input from area V1 has been investigated in many experiments and models attempting to replicate the main mechanisms. Two different core conceptual approaches were developed to explain the findings. In integrationist models the key mechanism to achieve pattern selectivity is the nonlinear integration of V1 motion activity. In contrast, selectionist models focus on the motion computation at positions with 2D features. Methodology/Principal Findings Recent experiments revealed that neither of the two concepts alone is sufficient to explain all experimental data and that most of the existing models cannot account for the complex behaviour found. MT pattern selectivity changes over time for stimuli like type II plaids from vector average to the direction computed with an intersection of constraint rule or by feature tracking. Also, the spatial arrangement of the stimulus within the receptive field of a MT cell plays a crucial role. We propose a recurrent neural model showing how feature integration and selection can be combined into one common architecture to explain these findings. The key features of the model are the computation of 1D and 2D motion in model area V1 subpopulations that are integrated in model MT cells using feedforward and feedback processing. Our results are also in line with findings concerning the solution of the aperture problem. Conclusions/Significance We propose a new neural model for MT pattern computation and motion disambiguation that is based on a combination of feature selection and integration. The model can explain a range of recent neurophysiological findings including temporally dynamic behaviour. PMID:21814543

Modelling audiovisual integration of affect from videos and music.

PubMed

Gao, Chuanji; Wedell, Douglas H; Kim, Jongwan; Weber, Christine E; Shinkareva, Svetlana V

2018-05-01

Two experiments examined how affective values from visual and auditory modalities are integrated. Experiment 1 paired music and videos drawn from three levels of valence while holding arousal constant. Experiment 2 included a parallel combination of three levels of arousal while holding valence constant. In each experiment, participants rated their affective states after unimodal and multimodal presentations. Experiment 1 revealed a congruency effect in which stimulus combinations of the same extreme valence resulted in more extreme state ratings than component stimuli presented in isolation. An interaction between music and video valence reflected the greater influence of negative affect. Video valence was found to have a significantly greater effect on combined ratings than music valence. The pattern of data was explained by a five parameter differential weight averaging model that attributed greater weight to the visual modality and increased weight with decreasing values of valence. Experiment 2 revealed a congruency effect only for high arousal combinations and no interaction effects. This pattern was explained by a three parameter constant weight averaging model with greater weight for the auditory modality and a very low arousal value for the initial state. These results demonstrate key differences in audiovisual integration between valence and arousal.

Organizing integrated care in a university hospital: application of a conceptual framework

PubMed Central

Axelsson, Runo; Axelsson, Susanna Bihari; Gustafsson, Jeppe; Seemann, Janne

2014-01-01

Background and aim As a result of New Public Management, a number of industrial models of quality management have been implemented in health care, mainly in hospitals. At the same time, the concept of integrated care has been developed within other parts of the health sector. The aim of the article is to discuss the relevance of integrated care for hospitals. Theory and methods The discussion is based on application of a conceptual framework outlining a number of organizational models of integrated care. These models are illustrated in a case study of a Danish university hospital implementing a new organization for improving the patient flows of the hospital. The study of the reorganization is based mainly on qualitative data from individual and focus group interviews. Results The new organization of the university hospital can be regarded as a matrix structure combining a vertical integration of clinical departments with a horizontal integration of patient flows. This structure has elements of both interprofessional and interorganizational integration. A strong focus on teamwork, meetings and information exchange is combined with elements of case management and co-location. Conclusions It seems that integrated care can be a relevant concept for a hospital. Although the organizational models may challenge established professional boundaries and financial control systems, this concept can be a more promising way to improve the quality of care than the industrial models that have been imported into health care. This application of the concept may also contribute to widen the field of integrated care. PMID:24966806

Time-varying volatility in Malaysian stock exchange: An empirical study using multiple-volatility-shift fractionally integrated model

NASA Astrophysics Data System (ADS)

Cheong, Chin Wen

2008-02-01

This article investigated the influences of structural breaks on the fractionally integrated time-varying volatility model in the Malaysian stock markets which included the Kuala Lumpur composite index and four major sectoral indices. A fractionally integrated time-varying volatility model combined with sudden changes is developed to study the possibility of structural change in the empirical data sets. Our empirical results showed substantial reduction in fractional differencing parameters after the inclusion of structural change during the Asian financial and currency crises. Moreover, the fractionally integrated model with sudden change in volatility performed better in the estimation and specification evaluations.

Integrated Modeling of Optical Systems (IMOS): An Assessment and Future Directions

NASA Technical Reports Server (NTRS)

Moore, Gregory; Broduer, Steve (Technical Monitor)

2001-01-01

Integrated Modeling of Optical Systems (IMOS) is a finite element-based code combining structural, thermal, and optical ray-tracing capabilities in a single environment for analysis of space-based optical systems. We'll present some recent examples of IMOS usage and discuss future development directions. Due to increasing model sizes and a greater emphasis on multidisciplinary analysis and design, much of the anticipated future work will be in the areas of improved architecture, numerics, and overall performance and analysis integration.

Evaluating agricultural nonpoint-source pollution using integrated geographic information systems and hydrologic/water quality model

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

Tim, U.S.; Jolly, R.

1994-01-01

Considerable progress has been made in developing physically based, distributed parameter, hydrologic/water quality (HIWQ) models for planning and control of nonpoint-source pollution. The widespread use of these models is often constrained by the excessive and time-consuming input data demands and the lack of computing efficiencies necessary for iterative simulation of alternative management strategies. Recent developments in geographic information systems (GIS) provide techniques for handling large amounts of spatial data for modeling nonpoint-source pollution problems. Because a GIS can be used to combine information from several sources to form an array of model input data and to examine any combinations ofmore » spatial input/output data, it represents a highly effective tool for HiWQ modeling. This paper describes the integration of a distributed-parameter model (AGNPS) with a GIS (ARC/INFO) to examine nonpoint sources of pollution in an agricultural watershed. The ARC/INFO GIS provided the tools to generate and spatially organize the disparate data to support modeling, while the AGNPS model was used to predict several water quality variables including soil erosion and sedimentation within a watershed. The integrated system was used to evaluate the effectiveness of several alternative management strategies in reducing sediment pollution in a 417-ha watershed located in southern Iowa. The implementation of vegetative filter strips and contour buffer (grass) strips resulted in a 41 and 47% reduction in sediment yield at the watershed outlet, respectively. In addition, when the integrated system was used, the combination of the above management strategies resulted in a 71% reduction in sediment yield. In general, the study demonstrated the utility of integrating a simulation model with GIS for nonpoini-source pollution control and planning. Such techniques can help characterize the diffuse sources of pollution at the landscape level. 52 refs., 6 figs., 1 tab.« less

INTEGRATING MODELS WITH STAKEHOLDER PREFERENCE OF WATER QUALITY INDICATORS: A CASE STUDY OF LAKE LANIER, GEORGIA, USA

EPA Science Inventory

One important aspect of Integrated Environmental Assessment is combining a scientific expertise and stakeholder concerns. Here, we propose a method to integrate stakeholder preferences, in particular preferences of stakeholders with differing environmental perspectives with a se...

Flood extent and water level estimation from SAR using data-model integration

NASA Astrophysics Data System (ADS)

Ajadi, O. A.; Meyer, F. J.

2017-12-01

Synthetic Aperture Radar (SAR) images have long been recognized as a valuable data source for flood mapping. Compared to other sources, SAR's weather and illumination independence and large area coverage at high spatial resolution supports reliable, frequent, and detailed observations of developing flood events. Accordingly, SAR has the potential to greatly aid in the near real-time monitoring of natural hazards, such as flood detection, if combined with automated image processing. This research works towards increasing the reliability and temporal sampling of SAR-derived flood hazard information by integrating information from multiple SAR sensors and SAR modalities (images and Interferometric SAR (InSAR) coherence) and by combining SAR-derived change detection information with hydrologic and hydraulic flood forecast models. First, the combination of multi-temporal SAR intensity images and coherence information for generating flood extent maps is introduced. The application of least-squares estimation integrates flood information from multiple SAR sensors, thus increasing the temporal sampling. SAR-based flood extent information will be combined with a Digital Elevation Model (DEM) to reduce false alarms and to estimate water depth and flood volume. The SAR-based flood extent map is assimilated into the Hydrologic Engineering Center River Analysis System (Hec-RAS) model to aid in hydraulic model calibration. The developed technology is improving the accuracy of flood information by exploiting information from data and models. It also provides enhanced flood information to decision-makers supporting the response to flood extent and improving emergency relief efforts.

Integrating observational and modelling systems for the management of the Great Barrier Reef

NASA Astrophysics Data System (ADS)

Baird, M. E.; Jones, E. M.; Margvelashvili, N.; Mongin, M.; Rizwi, F.; Robson, B.; Schroeder, T.; Skerratt, J.; Steven, A. D.; Wild-Allen, K.

2016-02-01

Observational and modelling systems provide two sources of knowledge that must be combined to provide a more complete view than either observations or models alone can provide. Here we describe the eReefs coupled hydrodynamic, sediment and biogeochemical model that has been developed for the Great Barrier Reef; and the multiple observations that are used to constrain the model. Two contrasting examples of model - observational integration are highlighted. First we explore the carbon chemistry of the waters above the reef, for which observations are accurate, but expensive and therefore sparse, while model behaviour is highly skilful. For carbon chemistry, observations are used to constrain model parameterisation and quantify model error, with the model output itself providing the most useable knowledge for management purposes. In contrast, ocean colour provides inaccurate, but cheap and spatially and temporally extensive observations. Thus observations are best combined with the model in a data assimilating framework, where a custom-designed optical model has been developed for the purposes of incorporating ocean colour observations. The future management of Great Barrier Reef water quality will be based on an integration of observing and modelling systems, providing the most robust information available.

Shared or Integrated: Which Type of Integration is More Effective Improves Students’ Creativity?

NASA Astrophysics Data System (ADS)

Mariyam, M.; Kaniawati, I.; Sriyati, S.

2017-09-01

Integrated science learning has various types of integration. This study aims to apply shared and integrated type of integration with project based learning (PjBL) model to improve students’ creativity on waste recycling theme. The research method used is a quasi experiment with the matching-only pre test-post test design. The samples of this study are 108 students consisting of 36 students (experiment class 1st), 35 students (experiment class 2nd) and 37 students (control class 3rd) at one of Junior High School in Tanggamus, Lampung. The results show that there is difference of creativity improvement in the class applied by PjBL model with shared type of integration, integrated type of integration and without any integration in waste recycling theme. Class applied by PjBL model with shared type of integration has the higher creativity improvement than the PjBL model with integrated type of integration and without any integration. Integrated science learning using shared type only combines 2 lessons, hence an intact concept is resulted. So, PjBL model with shared type of integration more effective improves students’ creativity than integrated type.

Integrative Modeling of Electrical Properties of Pacemaker Cardiac Cells

NASA Astrophysics Data System (ADS)

Grigoriev, M.; Babich, L.

2016-06-01

This work represents modeling of electrical properties of pacemaker (sinus) cardiac cells. Special attention is paid to electrical potential arising from transmembrane current of Na+, K+ and Ca2+ ions. This potential is calculated using the NaCaX model. In this respect, molar concentration of ions in the intercellular space which is calculated on the basis of the GENTEX model is essential. Combined use of two different models allows referring this approach to integrative modeling.

Full waveform inversion of combined towed streamer and limited OBS seismic data: a theoretical study

NASA Astrophysics Data System (ADS)

Yang, Huachen; Zhang, Jianzhong

2018-06-01

In marine seismic oil exploration, full waveform inversion (FWI) of towed-streamer data is used to reconstruct velocity models. However, the FWI of towed-streamer data easily converges to a local minimum solution due to the lack of low-frequency content. In this paper, we propose a new FWI technique using towed-streamer data, its integrated data sets and limited OBS data. Both integrated towed-streamer seismic data and OBS data have low-frequency components. Therefore, at early iterations in the new FWI technique, the OBS data combined with the integrated towed-streamer data sets reconstruct an appropriate background model. And the towed-streamer seismic data play a major role in later iterations to improve the resolution of the model. The new FWI technique is tested on numerical examples. The results show that when starting models are not accurate enough, the models inverted using the new FWI technique are superior to those inverted using conventional FWI.

Stages and Processes of Self-Change of Smoking: Toward an Integrative Model of Change.

ERIC Educational Resources Information Center

Prochaska, James O.; DiClemente, Carlo C.

1983-01-01

Applied an integrative model of change to the study of subjects (N=872) changing their smoking habits on their own. The subjects represented five stages of change: (1) precontemplation; (2) contemplation; (3) action; (4) maintenance; and (5) relapse. Relapsers' responses were a combination of contemplation and action. (JAC)

Online Collaborative Mentoring for Technology Integration in Pre-Service Teacher Education

ERIC Educational Resources Information Center

Dorner, Helga; Kumar, Swapna

2016-01-01

The Mentored Innovation Model is an online collaborative mentoring model developed in Hungary to help teachers integrate technology in their classrooms in meaningful ways. It combines an online modular approach of formal pedagogical ICT training with an informal online community experience of sharing, developing and critiquing of shared learning…

Conceptualising Integration in CLIL and Multilingual Education

ERIC Educational Resources Information Center

Nikula, Tarja, Ed.; Dafouz, Emma, Ed.; Moore, Pat, Ed.; Smit, Ute, Ed.

2016-01-01

Content and Language Integrated Learning (CLIL) is a form of education that combines language and content learning objectives, a shared concern with other models of bilingual education. While CLIL research has often addressed learning outcomes, this volume focuses on how integration can be conceptualised and investigated. Using different…

Integrated energy balance analysis for Space Station Freedom

NASA Technical Reports Server (NTRS)

Tandler, John

1991-01-01

An integrated simulation model is described which characterizes the dynamic interaction of the energy transport subsystems of Space Station Freedom for given orbital conditions and for a given set of power and thermal loads. Subsystems included in the model are the Electric Power System (EPS), the Internal Thermal Control System (ITCS), the External Thermal Control System (ETCS), and the cabin Temperature and Humidity Control System (THC) (which includes the avionics air cooling, cabin air cooling, and intermodule ventilation systems). Models of the subsystems were developed in a number of system-specific modeling tools and validated. The subsystem models are then combined into integrated models to address a number of integrated performance issues involving the ability of the integrated energy transport system of Space Station Freedom to provide power, controlled cabin temperature and humidity, and equipment thermal control to support operations.

A Causal Inference Model Explains Perception of the McGurk Effect and Other Incongruent Audiovisual Speech.

PubMed

Magnotti, John F; Beauchamp, Michael S

2017-02-01

Audiovisual speech integration combines information from auditory speech (talker's voice) and visual speech (talker's mouth movements) to improve perceptual accuracy. However, if the auditory and visual speech emanate from different talkers, integration decreases accuracy. Therefore, a key step in audiovisual speech perception is deciding whether auditory and visual speech have the same source, a process known as causal inference. A well-known illusion, the McGurk Effect, consists of incongruent audiovisual syllables, such as auditory "ba" + visual "ga" (AbaVga), that are integrated to produce a fused percept ("da"). This illusion raises two fundamental questions: first, given the incongruence between the auditory and visual syllables in the McGurk stimulus, why are they integrated; and second, why does the McGurk effect not occur for other, very similar syllables (e.g., AgaVba). We describe a simplified model of causal inference in multisensory speech perception (CIMS) that predicts the perception of arbitrary combinations of auditory and visual speech. We applied this model to behavioral data collected from 60 subjects perceiving both McGurk and non-McGurk incongruent speech stimuli. The CIMS model successfully predicted both the audiovisual integration observed for McGurk stimuli and the lack of integration observed for non-McGurk stimuli. An identical model without causal inference failed to accurately predict perception for either form of incongruent speech. The CIMS model uses causal inference to provide a computational framework for studying how the brain performs one of its most important tasks, integrating auditory and visual speech cues to allow us to communicate with others.

Challenges in horizontal model integration.

PubMed

Kolczyk, Katrin; Conradi, Carsten

2016-03-11

Systems Biology has motivated dynamic models of important intracellular processes at the pathway level, for example, in signal transduction and cell cycle control. To answer important biomedical questions, however, one has to go beyond the study of isolated pathways towards the joint study of interacting signaling pathways or the joint study of signal transduction and cell cycle control. Thereby the reuse of established models is preferable, as it will generally reduce the modeling effort and increase the acceptance of the combined model in the field. Obtaining a combined model can be challenging, especially if the submodels are large and/or come from different working groups (as is generally the case, when models stored in established repositories are used). To support this task, we describe a semi-automatic workflow based on established software tools. In particular, two frequent challenges are described: identification of the overlap and subsequent (re)parameterization of the integrated model. The reparameterization step is crucial, if the goal is to obtain a model that can reproduce the data explained by the individual models. For demonstration purposes we apply our workflow to integrate two signaling pathways (EGF and NGF) from the BioModels Database.

The INTEGRAL long monitoring of persistent ultra compact X-ray bursters

NASA Astrophysics Data System (ADS)

Fiocchi, M.; Bazzano, A.; Ubertini, P.; Bird, A. J.; Natalucci, L.; Sguera, V.

2008-12-01

Context: The combination of compact objects, short period variability and peculiar chemical composition of the ultra compact X-ray binaries make up a very interesting laboratory to study accretion processes and thermonuclear burning on the neutron star surface. Improved large optical telescopes and more sensitive X-ray satellites have increased the number of known ultra compact X-ray binaries allowing their study with unprecedented detail. Aims: We analyze the average properties common to all ultra compact bursters observed by INTEGRAL from 0.2 keV to 150 keV. Methods: We have performed a systematic analysis of the INTEGRAL public data and Key-Program proprietary observations of a sample of the ultra compact X-ray binaries. In order to study their average properties in a very broad energy band, we combined INTEGRAL with BeppoSAX and SWIFT data whenever possible. For sources not showing any significant flux variations along the INTEGRAL monitoring, we build the average spectrum by combining all available data; in the case of variable fluxes, we use simultaneous INTEGRAL and SWIFT observations when available. Otherwise we compared IBIS and PDS data to check the variability and combine BeppoSAX with INTEGRAL /IBIS data. Results: All spectra are well represented by a two component model consisting of a disk-blackbody and Comptonised emission. The majority of these compact sources spend most of the time in a canonical low/hard state, with a dominating Comptonised component and accretion rate dot {M} lower than 10-9 {M⊙}/yr, not depending on the model used to fit the data. INTEGRAL is an ESA project with instruments and Science Data Center funded by ESA member states (especially the PI countries: Denmark, France, Germany, Italy, Switzerland, Spain), Czech Republic and Poland, and with the participation of Russia and the USA.

Integrated cost-effectiveness analysis of agri-environmental measures for water quality.

PubMed

Balana, Bedru B; Jackson-Blake, Leah; Martin-Ortega, Julia; Dunn, Sarah

2015-09-15

This paper presents an application of integrated methodological approach for identifying cost-effective combinations of agri-environmental measures to achieve water quality targets. The methodological approach involves linking hydro-chemical modelling with economic costs of mitigation measures. The utility of the approach was explored for the River Dee catchment in North East Scotland, examining the cost-effectiveness of mitigation measures for nitrogen (N) and phosphorus (P) pollutants. In-stream nitrate concentration was modelled using the STREAM-N and phosphorus using INCA-P model. Both models were first run for baseline conditions and then their effectiveness for changes in land management was simulated. Costs were based on farm income foregone, capital and operational expenditures. The costs and effects data were integrated using 'Risk Solver Platform' optimization in excel to produce the most cost-effective combination of measures by which target nutrient reductions could be attained at a minimum economic cost. The analysis identified different combination of measures as most cost-effective for the two pollutants. An important aspect of this paper is integration of model-based effectiveness estimates with economic cost of measures for cost-effectiveness analysis of land and water management options. The methodological approach developed is not limited to the two pollutants and the selected agri-environmental measures considered in the paper; the approach can be adapted to the cost-effectiveness analysis of any catchment-scale environmental management options. Copyright © 2015 Elsevier Ltd. All rights reserved.

Acoustic Parametric Array for Identifying Standoff Targets

NASA Astrophysics Data System (ADS)

Hinders, M. K.; Rudd, K. E.

2010-02-01

An integrated simulation method for investigating nonlinear sound beams and 3D acoustic scattering from any combination of complicated objects is presented. A standard finite-difference simulation method is used to model pulsed nonlinear sound propagation from a source to a scattering target via the KZK equation. Then, a parallel 3D acoustic simulation method based on the finite integration technique is used to model the acoustic wave interaction with the target. Any combination of objects and material layers can be placed into the 3D simulation space to study the resulting interaction. Several example simulations are presented to demonstrate the simulation method and 3D visualization techniques. The combined simulation method is validated by comparing experimental and simulation data and a demonstration of how this combined simulation method assisted in the development of a nonlinear acoustic concealed weapons detector is also presented.

Integrated species distribution models: combining presence-background data and site-occupancy data with imperfect detection

USGS Publications Warehouse

Koshkina, Vira; Wang, Yang; Gordon, Ascelin; Dorazio, Robert; White, Matthew; Stone, Lewi

2017-01-01

Two main sources of data for species distribution models (SDMs) are site-occupancy (SO) data from planned surveys, and presence-background (PB) data from opportunistic surveys and other sources. SO surveys give high quality data about presences and absences of the species in a particular area. However, due to their high cost, they often cover a smaller area relative to PB data, and are usually not representative of the geographic range of a species. In contrast, PB data is plentiful, covers a larger area, but is less reliable due to the lack of information on species absences, and is usually characterised by biased sampling. Here we present a new approach for species distribution modelling that integrates these two data types.We have used an inhomogeneous Poisson point process as the basis for constructing an integrated SDM that fits both PB and SO data simultaneously. It is the first implementation of an Integrated SO–PB Model which uses repeated survey occupancy data and also incorporates detection probability.The Integrated Model's performance was evaluated, using simulated data and compared to approaches using PB or SO data alone. It was found to be superior, improving the predictions of species spatial distributions, even when SO data is sparse and collected in a limited area. The Integrated Model was also found effective when environmental covariates were significantly correlated. Our method was demonstrated with real SO and PB data for the Yellow-bellied glider (Petaurus australis) in south-eastern Australia, with the predictive performance of the Integrated Model again found to be superior.PB models are known to produce biased estimates of species occupancy or abundance. The small sample size of SO datasets often results in poor out-of-sample predictions. Integrated models combine data from these two sources, providing superior predictions of species abundance compared to using either data source alone. Unlike conventional SDMs which have restrictive scale-dependence in their predictions, our Integrated Model is based on a point process model and has no such scale-dependency. It may be used for predictions of abundance at any spatial-scale while still maintaining the underlying relationship between abundance and area.

Data integration for inference about spatial processes: A model-based approach to test and account for data inconsistency

PubMed Central

Pedrini, Paolo; Bragalanti, Natalia; Groff, Claudio

2017-01-01

Recently-developed methods that integrate multiple data sources arising from the same ecological processes have typically utilized structured data from well-defined sampling protocols (e.g., capture-recapture and telemetry). Despite this new methodological focus, the value of opportunistic data for improving inference about spatial ecological processes is unclear and, perhaps more importantly, no procedures are available to formally test whether parameter estimates are consistent across data sources and whether they are suitable for integration. Using data collected on the reintroduced brown bear population in the Italian Alps, a population of conservation importance, we combined data from three sources: traditional spatial capture-recapture data, telemetry data, and opportunistic data. We developed a fully integrated spatial capture-recapture (SCR) model that included a model-based test for data consistency to first compare model estimates using different combinations of data, and then, by acknowledging data-type differences, evaluate parameter consistency. We demonstrate that opportunistic data lend itself naturally to integration within the SCR framework and highlight the value of opportunistic data for improving inference about space use and population size. This is particularly relevant in studies of rare or elusive species, where the number of spatial encounters is usually small and where additional observations are of high value. In addition, our results highlight the importance of testing and accounting for inconsistencies in spatial information from structured and unstructured data so as to avoid the risk of spurious or averaged estimates of space use and consequently, of population size. Our work supports the use of a single modeling framework to combine spatially-referenced data while also accounting for parameter consistency. PMID:28973034

An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network

PubMed Central

Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

2015-01-01

Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish–Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection. PMID:26447696

An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network.

PubMed

Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

2015-01-01

Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish-Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection.

Developing CCUS system models to handle the complexity of multiple sources and sinks: An update on Tasks 5.3 and 5.4

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

Middleton, Richard Stephen

2017-05-22

This presentation is part of US-China Clean Coal project and describes the impact of power plant cycling, techno economic modeling of combined IGCC and CCS, integrated capacity generation decision making for power utilities, and a new decision support tool for integrated assessment of CCUS.

Aeroelastic modeling for the FIT team F/A-18 simulation

NASA Technical Reports Server (NTRS)

Zeiler, Thomas A.; Wieseman, Carol D.

1989-01-01

Some details of the aeroelastic modeling of the F/A-18 aircraft done for the Functional Integration Technology (FIT) team's research in integrated dynamics modeling and how these are combined with the FIT team's integrated dynamics model are described. Also described are mean axis corrections to elastic modes, the addition of nonlinear inertial coupling terms into the equations of motion, and the calculation of internal loads time histories using the integrated dynamics model in a batch simulation program. A video tape made of a loads time history animation was included as a part of the oral presentation. Also discussed is work done in one of the areas of unsteady aerodynamic modeling identified as needing improvement, specifically, in correction factor methodologies for improving the accuracy of stability derivatives calculated with a doublet lattice code.

Workshop on Current Issues in Predictive Approaches to Intelligence and Security Analytics: Fostering the Creation of Decision Advantage through Model Integration and Evaluation

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

Sanfilippo, Antonio P.

2010-05-23

The increasing asymmetric nature of threats to the security, health and sustainable growth of our society requires that anticipatory reasoning become an everyday activity. Currently, the use of anticipatory reasoning is hindered by the lack of systematic methods for combining knowledge- and evidence-based models, integrating modeling algorithms, and assessing model validity, accuracy and utility. The workshop addresses these gaps with the intent of fostering the creation of a community of interest on model integration and evaluation that may serve as an aggregation point for existing efforts and a launch pad for new approaches.

Bayesian maximum entropy integration of ozone observations and model predictions: an application for attainment demonstration in North Carolina.

PubMed

de Nazelle, Audrey; Arunachalam, Saravanan; Serre, Marc L

2010-08-01

States in the USA are required to demonstrate future compliance of criteria air pollutant standards by using both air quality monitors and model outputs. In the case of ozone, the demonstration tests aim at relying heavily on measured values, due to their perceived objectivity and enforceable quality. Weight given to numerical models is diminished by integrating them in the calculations only in a relative sense. For unmonitored locations, the EPA has suggested the use of a spatial interpolation technique to assign current values. We demonstrate that this approach may lead to erroneous assignments of nonattainment and may make it difficult for States to establish future compliance. We propose a method that combines different sources of information to map air pollution, using the Bayesian Maximum Entropy (BME) Framework. The approach gives precedence to measured values and integrates modeled data as a function of model performance. We demonstrate this approach in North Carolina, using the State's ozone monitoring network in combination with outputs from the Multiscale Air Quality Simulation Platform (MAQSIP) modeling system. We show that the BME data integration approach, compared to a spatial interpolation of measured data, improves the accuracy and the precision of ozone estimations across the state.

Toward an Integration of Cognitive and Genetic Models of Risk for Depression

PubMed Central

Gibb, Brandon E.; Beevers, Christopher G.; McGeary, John E.

2012-01-01

There is growing interest in integrating cognitive and genetic models of depression risk. We review two ways in which these models can be meaningfully integrated. First, information-processing biases may represent intermediate phenotypes for specific genetic influences. These genetic influences may represent main effects on specific cognitive processes or may moderate the impact of environmental influences on information-processing biases. Second, cognitive and genetic influences may combine to increase reactivity to environmental stressors, increasing risk for depression in a gene × cognition × environment model of risk. There is now growing support for both of these ways of integrating cognitive and genetic models of depression risk. Specifically, there is support for genetic influences on information-processing biases, particularly the link between 5-HTTLPR and attentional biases, from both genetic association and gene × environment (G × E) studies. There is also initial support for gene × cognition × environment models of risk in which specific genetic influences contribute to increased reactivity to environmental influences. We review this research and discuss important areas of future research, particularly the need for larger samples that allow for a broader examination of genetic and epigenetic influences as well as the combined influence of variability across a number of genes. PMID:22920216

Sequential Modelling of Building Rooftops by Integrating Airborne LIDAR Data and Optical Imagery: Preliminary Results

NASA Astrophysics Data System (ADS)

Sohn, G.; Jung, J.; Jwa, Y.; Armenakis, C.

2013-05-01

This paper presents a sequential rooftop modelling method to refine initial rooftop models derived from airborne LiDAR data by integrating it with linear cues retrieved from single imagery. A cue integration between two datasets is facilitated by creating new topological features connecting between the initial model and image lines, with which new model hypotheses (variances to the initial model) are produced. We adopt Minimum Description Length (MDL) principle for competing the model candidates and selecting the optimal model by considering the balanced trade-off between the model closeness and the model complexity. Our preliminary results, combined with the Vaihingen data provided by ISPRS WGIII/4 demonstrate the image-driven modelling cues can compensate the limitations posed by LiDAR data in rooftop modelling.

Combined Feature Based and Shape Based Visual Tracker for Robot Navigation

NASA Technical Reports Server (NTRS)

Deans, J.; Kunz, C.; Sargent, R.; Park, E.; Pedersen, L.

2005-01-01

We have developed a combined feature based and shape based visual tracking system designed to enable a planetary rover to visually track and servo to specific points chosen by a user with centimeter precision. The feature based tracker uses invariant feature detection and matching across a stereo pair, as well as matching pairs before and after robot movement in order to compute an incremental 6-DOF motion at each tracker update. This tracking method is subject to drift over time, which can be compensated by the shape based method. The shape based tracking method consists of 3D model registration, which recovers 6-DOF motion given sufficient shape and proper initialization. By integrating complementary algorithms, the combined tracker leverages the efficiency and robustness of feature based methods with the precision and accuracy of model registration. In this paper, we present the algorithms and their integration into a combined visual tracking system.

Earth Observations, Models and Geo-Design in Support of SDG Implementation and Monitoring

NASA Astrophysics Data System (ADS)

Plag, H. P.; Jules-Plag, S.

2016-12-01

Implementation and Monitoring of the United Nations' Sustainable Development Goals (SDGs) requires support from Earth observation and scientific communities. Applying a goal-based approach to determine the data needs to the Targets and Indicators associated with the SDGs demonstrates that integration of environmental with socio-economic and statistical data is required. Large data gaps exist for the built environment. A Geo-Design platform can provide the infrastructure and conceptual model for the data integration. The development of policies and actions to foster the implementation of SDGs in many cases requires research and the development of tools to answer "what if" questions. Here, agent-based models and model webs combined with a Geo-Design platform are promising avenues. This advanced combined infrastructure can also play a crucial role in the necessary capacity building. We will use the example of SDG 5 (Gender equality) to illustrate these approaches. SDG 11 (Sustainable Cities and Communities) is used to underline the cross-goal linkages and the joint benefits of Earth observations, data integration, and modeling tools for multiple SDGs.

BEopt-CA (Ex) -- A Tool for Optimal Integration of EE/DR/ES+PV in Existing California Homes. Cooperative Research and Development Final Report, CRADA Number CRD-11-429

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

Christensen, Craig

Opportunities for combining energy efficiency, demand response, and energy storage with PV are often missed, because the required knowledge and expertise for these different technologies exist in separate organizations or individuals. Furthermore, there is a lack of quantitative tools to optimize energy efficiency, demand response and energy storage with PV, especially for existing buildings. Our goal is to develop a modeling tool, BEopt-CA (Ex), with capabilities to facilitate identification and implementation of a balanced integration of energy efficiency (EE), demand response (DR), and energy storage (ES) with photovoltaics (PV) within the residential retrofit market. To achieve this goal, we willmore » adapt and extend an existing tool -- BEopt -- that is designed to identify optimal combinations of efficiency and PV in new home designs. In addition, we will develop multifamily residential modeling capabilities for use in California, to facilitate integration of distributed solar power into the grid in order to maximize its value to California ratepayers. The project is follow-on research that leverages previous California Solar Initiative RD&D investment in the BEopt software. BEopt facilitates finding the least cost combination of energy efficiency and renewables to support integrated DSM (iDSM) and Zero Net Energy (ZNE) in California residential buildings. However, BEopt is currently focused on modeling single-family houses and does not include satisfactory capabilities for modeling multifamily homes. The project brings BEopt's existing modeling and optimization capabilities to multifamily buildings, including duplexes, triplexes, townhouses, flats, and low-rise apartment buildings.« less

Integrating sensorimotor systems in a robot model of cricket behavior

NASA Astrophysics Data System (ADS)

Webb, Barbara H.; Harrison, Reid R.

2000-10-01

The mechanisms by which animals manage sensorimotor integration and coordination of different behaviors can be investigated in robot models. In previous work the first author has build a robot that localizes sound based on close modeling of the auditory and neural system in the cricket. It is known that the cricket combines its response to sound with other sensorimotor activities such as an optomotor reflex and reactions to mechanical stimulation for the antennae and cerci. Behavioral evidence suggests some ways these behaviors may be integrated. We have tested the addition of an optomotor response, using an analog VLSI circuit developed by the second author, to the sound localizing behavior and have shown that it can, as in the cricket, improve the directness of the robot's path to sound. In particular it substantially improves behavior when the robot is subject to a motor disturbance. Our aim is to better understand how the insect brain functions in controlling complex combinations of behavior, with the hope that this will also suggest novel mechanisms for sensory integration on robots.

MMM: A toolbox for integrative structure modeling.

PubMed

Jeschke, Gunnar

2018-01-01

Structural characterization of proteins and their complexes may require integration of restraints from various experimental techniques. MMM (Multiscale Modeling of Macromolecules) is a Matlab-based open-source modeling toolbox for this purpose with a particular emphasis on distance distribution restraints obtained from electron paramagnetic resonance experiments on spin-labelled proteins and nucleic acids and their combination with atomistic structures of domains or whole protomers, small-angle scattering data, secondary structure information, homology information, and elastic network models. MMM does not only integrate various types of restraints, but also various existing modeling tools by providing a common graphical user interface to them. The types of restraints that can support such modeling and the available model types are illustrated by recent application examples. © 2017 The Protein Society.

Supervisor's Interactive Model of Organizational Relationships

ERIC Educational Resources Information Center

O'Reilly, Frances L.; Matt, John; McCaw, William P.

2014-01-01

The Supervisor's Interactive Model of Organizational Relationships (SIMOR) integrates two models addressed in the leadership literature and then highlights the importance of relationships. The Supervisor's Interactive Model of Organizational Relationships combines the modified Hersey and Blanchard model of situational leadership, the…

SAINT: A combined simulation language for modeling man-machine systems

NASA Technical Reports Server (NTRS)

Seifert, D. J.

1979-01-01

SAINT (Systems Analysis of Integrated Networks of Tasks) is a network modeling and simulation technique for design and analysis of complex man machine systems. SAINT provides the conceptual framework for representing systems that consist of discrete task elements, continuous state variables, and interactions between them. It also provides a mechanism for combining human performance models and dynamic system behaviors in a single modeling structure. The SAINT technique is described and applications of the SAINT are discussed.

The study of integration about measurable image and 4D production

NASA Astrophysics Data System (ADS)

Zhang, Chunsen; Hu, Pingbo; Niu, Weiyun

2008-12-01

In this paper, we create the geospatial data of three-dimensional (3D) modeling by the combination of digital photogrammetry and digital close-range photogrammetry. For large-scale geographical background, we make the establishment of DEM and DOM combination of three-dimensional landscape model based on the digital photogrammetry which uses aerial image data to make "4D" (DOM: Digital Orthophoto Map, DEM: Digital Elevation Model, DLG: Digital Line Graphic and DRG: Digital Raster Graphic) production. For the range of building and other artificial features which the users are interested in, we realize that the real features of the three-dimensional reconstruction adopting the method of the digital close-range photogrammetry can come true on the basis of following steps : non-metric cameras for data collection, the camera calibration, feature extraction, image matching, and other steps. At last, we combine three-dimensional background and local measurements real images of these large geographic data and realize the integration of measurable real image and the 4D production.The article discussed the way of the whole flow and technology, achieved the three-dimensional reconstruction and the integration of the large-scale threedimensional landscape and the metric building.

The Integration of Health and Counseling Services on College Campuses: Is There a Risk in Maintaining Student Patients' Privacy?

ERIC Educational Resources Information Center

Davenport, Robin G.

2017-01-01

The formation of integrated centers on college campuses that combine health services and counseling provide clear advantages for students. There is currently no "best practices" model that informs integrated centers' operational procedures. The "continuity of care" requirement of medical providers can conflict with the strict…

Towards integrated solutions for water, energy, and land using an integrated nexus modeling framework

NASA Astrophysics Data System (ADS)

Wada, Y.

2017-12-01

Humanity has already reached or even exceeded the Earth's carrying capacity. Growing needs for food, energy and water will only exacerbate existing challenges over the next decades. Consequently, the acceptance of "business as usual" is eroding and we are being challenged to adopt new, more integrated, and more inclusive development pathways that avoid dangerous interference with the local environment and global planetary boundaries. This challenge is embodied in the United Nation's Sustainable Development Goals (SDGs), which endeavor to set a global agenda for moving towards more sustainable development strategies. To improve and sustain human welfare, it is critical that access to modern, reliable, and affordable water, energy, and food is expanded and maintained. The Integrated Solutions for Water, Energy, and Land (IS-WEL) project has been launched by IIASA, together with the Global Environment Facility (GEF) and the United Nations Industrial Development Organization (UNIDO). This project focuses on the water-energy-land nexus in the context of other major global challenges such as urbanization, environmental degradation, and equitable and sustainable futures. It develops a consistent framework for looking at the water-energy-land nexus and identify strategies for achieving the needed transformational outcomes through an advanced assessment framework. A multi-scalar approach are being developed that aims to combine global and regional integrated assessment tools with local stakeholder knowledge in order to identify robust solutions to energy, water, food, and ecosystem security in selected regions of the world. These are regions facing multiple energy, water and land use challenges and rapid demographic and economic changes, and are hardest hit by increasing climate variability and change. This project combines the global integrated assessment model (MESSAGE) with the global land (GLOBIOM) and water (Community Water Model) model respectively, and the integrated modeling framework are then combined with detailed regional decision support tools for water-energy-land nexus analysis in case study regions. A number of stakeholder meetings are used to engage local communities in the definition of important nexus drivers, scenario development and definition of performance metrics.

Integrated Turbine-Based Combined Cycle Dynamic Simulation Model

NASA Technical Reports Server (NTRS)

Haid, Daniel A.; Gamble, Eric J.

2011-01-01

A Turbine-Based Combined Cycle (TBCC) dynamic simulation model has been developed to demonstrate all modes of operation, including mode transition, for a turbine-based combined cycle propulsion system. The High Mach Transient Engine Cycle Code (HiTECC) is a highly integrated tool comprised of modules for modeling each of the TBCC systems whose interactions and controllability affect the TBCC propulsion system thrust and operability during its modes of operation. By structuring the simulation modeling tools around the major TBCC functional modes of operation (Dry Turbojet, Afterburning Turbojet, Transition, and Dual Mode Scramjet) the TBCC mode transition and all necessary intermediate events over its entire mission may be developed, modeled, and validated. The reported work details the use of the completed model to simulate a TBCC propulsion system as it accelerates from Mach 2.5, through mode transition, to Mach 7. The completion of this model and its subsequent use to simulate TBCC mode transition significantly extends the state-of-the-art for all TBCC modes of operation by providing a numerical simulation of the systems, interactions, and transient responses affecting the ability of the propulsion system to transition from turbine-based to ramjet/scramjet-based propulsion while maintaining constant thrust.

Combining the boundary shift integral and tensor-based morphometry for brain atrophy estimation

NASA Astrophysics Data System (ADS)

Michalkiewicz, Mateusz; Pai, Akshay; Leung, Kelvin K.; Sommer, Stefan; Darkner, Sune; Sørensen, Lauge; Sporring, Jon; Nielsen, Mads

2016-03-01

Brain atrophy from structural magnetic resonance images (MRIs) is widely used as an imaging surrogate marker for Alzheimers disease. Their utility has been limited due to the large degree of variance and subsequently high sample size estimates. The only consistent and reasonably powerful atrophy estimation methods has been the boundary shift integral (BSI). In this paper, we first propose a tensor-based morphometry (TBM) method to measure voxel-wise atrophy that we combine with BSI. The combined model decreases the sample size estimates significantly when compared to BSI and TBM alone.

Evaluation of stormwater micropollutant source control and end-of-pipe control strategies using an uncertainty-calibrated integrated dynamic simulation model.

PubMed

Vezzaro, L; Sharma, A K; Ledin, A; Mikkelsen, P S

2015-03-15

The estimation of micropollutant (MP) fluxes in stormwater systems is a fundamental prerequisite when preparing strategies to reduce stormwater MP discharges to natural waters. Dynamic integrated models can be important tools in this step, as they can be used to integrate the limited data provided by monitoring campaigns and to evaluate the performance of different strategies based on model simulation results. This study presents an example where six different control strategies, including both source-control and end-of-pipe treatment, were compared. The comparison focused on fluxes of heavy metals (copper, zinc) and organic compounds (fluoranthene). MP fluxes were estimated by using an integrated dynamic model, in combination with stormwater quality measurements. MP sources were identified by using GIS land usage data, runoff quality was simulated by using a conceptual accumulation/washoff model, and a stormwater retention pond was simulated by using a dynamic treatment model based on MP inherent properties. Uncertainty in the results was estimated with a pseudo-Bayesian method. Despite the great uncertainty in the MP fluxes estimated by the runoff quality model, it was possible to compare the six scenarios in terms of discharged MP fluxes, compliance with water quality criteria, and sediment accumulation. Source-control strategies obtained better results in terms of reduction of MP emissions, but all the simulated strategies failed in fulfilling the criteria based on emission limit values. The results presented in this study shows how the efficiency of MP pollution control strategies can be quantified by combining advanced modeling tools (integrated stormwater quality model, uncertainty calibration). Copyright © 2014 Elsevier Ltd. All rights reserved.

Low temperature ablation models made by pressure/vacuum application

NASA Technical Reports Server (NTRS)

Fischer, M. C.; Heier, W. C.

1970-01-01

Method developed employs high pressure combined with strong vacuum force to compact ablation models into desired conical shape. Technique eliminates vapor hazard and results in high material density providing excellent structural integrity.

From Physical Process to Economic Cost - Integrated Approaches of Landslide Risk Assessment

NASA Astrophysics Data System (ADS)

Klose, M.; Damm, B.

2014-12-01

The nature of landslides is complex in many respects, with landslide hazard and impact being dependent on a variety of factors. This obviously requires an integrated assessment for fundamental understanding of landslide risk. Integrated risk assessment, according to the approach presented in this contribution, implies combining prediction of future landslide occurrence with analysis of landslide impact in the past. A critical step for assessing landslide risk in integrated perspective is to analyze what types of landslide damage affected people and property in which way and how people contributed and responded to these damage types. In integrated risk assessment, the focus is on systematic identification and monetization of landslide damage, and analytical tools that allow deriving economic costs from physical landslide processes are at the heart of this approach. The broad spectrum of landslide types and process mechanisms as well as nonlinearity between landslide magnitude, damage intensity, and direct costs are some main factors explaining recent challenges in risk assessment. The two prevailing approaches for assessing the impact of landslides in economic terms are cost survey (ex-post) and risk analysis (ex-ante). Both approaches are able to complement each other, but yet a combination of them has not been realized so far. It is common practice today to derive landslide risk without considering landslide process-based cause-effect relationships, since integrated concepts or new modeling tools expanding conventional methods are still widely missing. The approach introduced in this contribution is based on a systematic framework that combines cost survey and GIS-based tools for hazard or cost modeling with methods to assess interactions between land use practices and landslides in historical perspective. Fundamental understanding of landslide risk also requires knowledge about the economic and fiscal relevance of landslide losses, wherefore analysis of their impact on public budgets is a further component of this approach. In integrated risk assessment, combination of methods plays an important role, with the objective of collecting and integrating complex data sets on landslide risk.

Lignocellulosic biorefinery as a model for sustainable development of biofuels and value added products.

PubMed

De Bhowmick, Goldy; Sarmah, Ajit K; Sen, Ramkrishna

2018-01-01

A constant shift of society's dependence from petroleum-based energy resources towards renewable biomass-based has been the key to tackle the greenhouse gas emissions. Effective use of biomass feedstock, particularly lignocellulosic, has gained worldwide attention lately. Lignocellulosic biomass as a potent bioresource, however, cannot be a sustainable alternative if the production cost is too high and/ or the availability is limited. Recycling the lignocellulosic biomass from various sources into value added products such as bio-oil, biochar or other biobased chemicals in a bio-refinery model is a sensible idea. Combination of integrated conversion techniques along with process integration is suggested as a sustainable approach. Introducing 'series concept' accompanying intermittent dark/photo fermentation with co-cultivation of microalgae is conceptualised. While the cost of downstream processing for a single type of feedstock would be high, combining different feedstocks and integrating them in a bio-refinery model would lessen the production cost and reduce CO 2 emission. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparison of two weighted integration models for the cueing task: linear and likelihood

NASA Technical Reports Server (NTRS)

Shimozaki, Steven S.; Eckstein, Miguel P.; Abbey, Craig K.

2003-01-01

In a task in which the observer must detect a signal at two locations, presenting a precue that predicts the location of a signal leads to improved performance with a valid cue (signal location matches the cue), compared to an invalid cue (signal location does not match the cue). The cue validity effect has often been explained with a limited capacity attentional mechanism improving the perceptual quality at the cued location. Alternatively, the cueing effect can also be explained by unlimited capacity models that assume a weighted combination of noisy responses across the two locations. We compare two weighted integration models, a linear model and a sum of weighted likelihoods model based on a Bayesian observer. While qualitatively these models are similar, quantitatively they predict different cue validity effects as the signal-to-noise ratios (SNR) increase. To test these models, 3 observers performed in a cued discrimination task of Gaussian targets with an 80% valid precue across a broad range of SNR's. Analysis of a limited capacity attentional switching model was also included and rejected. The sum of weighted likelihoods model best described the psychophysical results, suggesting that human observers approximate a weighted combination of likelihoods, and not a weighted linear combination.

Time on your hands: Perceived duration of sensory events is biased toward concurrent actions.

PubMed

Yon, Daniel; Edey, Rosanna; Ivry, Richard B; Press, Clare

2017-02-01

Perceptual systems must rapidly generate accurate representations of the world from sensory inputs that are corrupted by internal and external noise. We can typically obtain more veridical representations by integrating information from multiple channels, but this integration can lead to biases when inputs are, in fact, not from the same source. Although a considerable amount is known about how different sources of information are combined to influence what we perceive, it is not known whether temporal features are combined. It is vital to address this question given the divergent predictions made by different models of cue combination and time perception concerning the plausibility of cross-modal temporal integration, and the implications that such integration would have for research programs in action control and social cognition. Here we present four experiments investigating the influence of movement duration on the perceived duration of an auditory tone. Participants either explicitly (Experiments 1-2) or implicitly (Experiments 3-4) produced hand movements of shorter or longer durations, while judging the duration of a concurrently presented tone (500-950 ms in duration). Across all experiments, judgments of tone duration were attracted toward the duration of executed movements (i.e., tones were perceived to be longer when executing a movement of longer duration). Our results demonstrate that temporal information associated with movement biases perceived auditory duration, placing important constraints on theories modeling cue integration for state estimation, as well as models of time perception, action control and social cognition. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

IMHOTEP—a composite score integrating popular tools for predicting the functional consequences of non-synonymous sequence variants

PubMed Central

Knecht, Carolin; Mort, Matthew; Junge, Olaf; Cooper, David N.; Krawczak, Michael

2017-01-01

Abstract The in silico prediction of the functional consequences of mutations is an important goal of human pathogenetics. However, bioinformatic tools that classify mutations according to their functionality employ different algorithms so that predictions may vary markedly between tools. We therefore integrated nine popular prediction tools (PolyPhen-2, SNPs&GO, MutPred, SIFT, MutationTaster2, Mutation Assessor and FATHMM as well as conservation-based Grantham Score and PhyloP) into a single predictor. The optimal combination of these tools was selected by means of a wide range of statistical modeling techniques, drawing upon 10 029 disease-causing single nucleotide variants (SNVs) from Human Gene Mutation Database and 10 002 putatively ‘benign’ non-synonymous SNVs from UCSC. Predictive performance was found to be markedly improved by model-based integration, whilst maximum predictive capability was obtained with either random forest, decision tree or logistic regression analysis. A combination of PolyPhen-2, SNPs&GO, MutPred, MutationTaster2 and FATHMM was found to perform as well as all tools combined. Comparison of our approach with other integrative approaches such as Condel, CoVEC, CAROL, CADD, MetaSVM and MetaLR using an independent validation dataset, revealed the superiority of our newly proposed integrative approach. An online implementation of this approach, IMHOTEP (‘Integrating Molecular Heuristics and Other Tools for Effect Prediction’), is provided at http://www.uni-kiel.de/medinfo/cgi-bin/predictor/. PMID:28180317

Improving the Accuracy of Mapping Urban Vegetation Carbon Density by Combining Shadow Remove, Spectral Unmixing Analysis and Spatial Modeling

NASA Astrophysics Data System (ADS)

Qie, G.; Wang, G.; Wang, M.

2016-12-01

Mixed pixels and shadows due to buildings in urban areas impede accurate estimation and mapping of city vegetation carbon density. In most of previous studies, these factors are often ignored, which thus result in underestimation of city vegetation carbon density. In this study we presented an integrated methodology to improve the accuracy of mapping city vegetation carbon density. Firstly, we applied a linear shadow remove analysis (LSRA) on remotely sensed Landsat 8 images to reduce the shadow effects on carbon estimation. Secondly, we integrated a linear spectral unmixing analysis (LSUA) with a linear stepwise regression (LSR), a logistic model-based stepwise regression (LMSR) and k-Nearest Neighbors (kNN), and utilized and compared the integrated models on shadow-removed images to map vegetation carbon density. This methodology was examined in Shenzhen City of Southeast China. A data set from a total of 175 sample plots measured in 2013 and 2014 was used to train the models. The independent variables statistically significantly contributing to improving the fit of the models to the data and reducing the sum of squared errors were selected from a total of 608 variables derived from different image band combinations and transformations. The vegetation fraction from LSUA was then added into the models as an important independent variable. The estimates obtained were evaluated using a cross-validation method. Our results showed that higher accuracies were obtained from the integrated models compared with the ones using traditional methods which ignore the effects of mixed pixels and shadows. This study indicates that the integrated method has great potential on improving the accuracy of urban vegetation carbon density estimation. Key words: Urban vegetation carbon, shadow, spectral unmixing, spatial modeling, Landsat 8 images

Framework Programmable Platform for the advanced software development workstation: Framework processor design document

NASA Technical Reports Server (NTRS)

Mayer, Richard J.; Blinn, Thomas M.; Mayer, Paula S. D.; Ackley, Keith A.; Crump, Wes; Sanders, Les

1991-01-01

The design of the Framework Processor (FP) component of the Framework Programmable Software Development Platform (FFP) is described. The FFP is a project aimed at combining effective tool and data integration mechanisms with a model of the software development process in an intelligent integrated software development environment. Guided by the model, this Framework Processor will take advantage of an integrated operating environment to provide automated support for the management and control of the software development process so that costly mistakes during the development phase can be eliminated.

On accommodating spatial interactions in a Generalized Heterogeneous Data Model (GHDM) of mixed types of dependent variables.

DOT National Transportation Integrated Search

2015-12-01

We develop an econometric framework for incorporating spatial dependence in integrated model systems of latent variables and multidimensional mixed data outcomes. The framework combines Bhats Generalized Heterogeneous Data Model (GHDM) with a spat...

Situational Favorability and Perceived Environmental Uncertainty: An Integrative Approach

ERIC Educational Resources Information Center

Nebeker, Delbert M.

1975-01-01

Presents the conceptual and empirical basis for a possible combining of Fiedler's contingency model of leadership effectiveness and Lawrence and Lorsch's contingency organization theory. Using perceived environmental uncertainty as the integrating concept, a measure of decision uncertainty was found to be significantly related to Fiedler's…

Towards integrated modelling: full image simulations for WEAVE

NASA Astrophysics Data System (ADS)

Dalton, Gavin; Ham, Sun Jeong; Trager, Scott; Abrams, Don Carlos; Bonifacio, Piercarlo; Aguerri, J. A. L.; Middleton, Kevin; Benn, Chris; Rogers, Kevin; Stuik, Remko; Carrasco, Esperanza; Vallenari, Antonella; Jin, Shoko; Lewis, Jim

2016-08-01

We present an integrated end-end simulation of the spectral images that will be obtained by the weave spectrograph, which aims to include full modelling of all effects from the top of the atmosphere to the detector. These data are based in input spectra from a combination of library spectra and synthetic models, and will be used to provide inputs for an endend test of the full weave data pipeline and archive systems, prior to 1st light of the instrument.

Process and data fragmentation-oriented enterprise network integration with collaboration modelling and collaboration agents

NASA Astrophysics Data System (ADS)

Li, Qing; Wang, Ze-yuan; Cao, Zhi-chao; Du, Rui-yang; Luo, Hao

2015-08-01

With the process of globalisation and the development of management models and information technology, enterprise cooperation and collaboration has developed from intra-enterprise integration, outsourcing and inter-enterprise integration, and supply chain management, to virtual enterprises and enterprise networks. Some midfielder enterprises begin to serve for different supply chains. Therefore, they combine related supply chains into a complex enterprise network. The main challenges for enterprise network's integration and collaboration are business process and data fragmentation beyond organisational boundaries. This paper reviews the requirements of enterprise network's integration and collaboration, as well as the development of new information technologies. Based on service-oriented architecture (SOA), collaboration modelling and collaboration agents are introduced to solve problems of collaborative management for service convergence under the condition of process and data fragmentation. A model-driven methodology is developed to design and deploy the integrating framework. An industrial experiment is designed and implemented to illustrate the usage of developed technologies in this paper.

Technosocial Modeling of IED Threat Scenarios and Attacks

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

Whitney, Paul D.; Brothers, Alan J.; Coles, Garill A.

2009-03-23

This paper describes an approach for integrating sociological and technical models to develop more complete threat assessment. Current approaches to analyzing and addressing threats tend to focus on the technical factors. This paper addresses development of predictive models that encompass behavioral as well as these technical factors. Using improvised explosive device (IED) attacks as motivation, this model supports identification of intervention activities 'left of boom' as well as prioritizing attack modalities. We show how Bayes nets integrate social factors associated with IED attacks into general threat model containing technical and organizational steps from planning through obtaining the IED to initiationmore » of the attack. The social models are computationally-based representations of relevant social science literature that describes human decision making and physical factors. When combined with technical models, the resulting model provides improved knowledge integration into threat assessment for monitoring. This paper discusses the construction of IED threat scenarios, integration of diverse factors into an analytical framework for threat assessment, indicator identification for future threats, and future research directions.« less

Reactive Power Pricing Model Considering the Randomness of Wind Power Output

NASA Astrophysics Data System (ADS)

Dai, Zhong; Wu, Zhou

2018-01-01

With the increase of wind power capacity integrated into grid, the influence of the randomness of wind power output on the reactive power distribution of grid is gradually highlighted. Meanwhile, the power market reform puts forward higher requirements for reasonable pricing of reactive power service. Based on it, the article combined the optimal power flow model considering wind power randomness with integrated cost allocation method to price reactive power. Meanwhile, considering the advantages and disadvantages of the present cost allocation method and marginal cost pricing, an integrated cost allocation method based on optimal power flow tracing is proposed. The model realized the optimal power flow distribution of reactive power with the minimal integrated cost and wind power integration, under the premise of guaranteeing the balance of reactive power pricing. Finally, through the analysis of multi-scenario calculation examples and the stochastic simulation of wind power outputs, the article compared the results of the model pricing and the marginal cost pricing, which proved that the model is accurate and effective.

Integrating a geographic information system, a scientific visualization system and an orographic precipitation model

USGS Publications Warehouse

Hay, L.; Knapp, L.

1996-01-01

Investigating natural, potential, and man-induced impacts on hydrological systems commonly requires complex modelling with overlapping data requirements, and massive amounts of one- to four-dimensional data at multiple scales and formats. Given the complexity of most hydrological studies, the requisite software infrastructure must incorporate many components including simulation modelling, spatial analysis and flexible, intuitive displays. There is a general requirement for a set of capabilities to support scientific analysis which, at this time, can only come from an integration of several software components. Integration of geographic information systems (GISs) and scientific visualization systems (SVSs) is a powerful technique for developing and analysing complex models. This paper describes the integration of an orographic precipitation model, a GIS and a SVS. The combination of these individual components provides a robust infrastructure which allows the scientist to work with the full dimensionality of the data and to examine the data in a more intuitive manner.

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

Kornreich, Drew E; Vaidya, Rajendra U; Ammerman, Curtt N

Integrated Computational Materials Engineering (ICME) is a novel overarching approach to bridge length and time scales in computational materials science and engineering. This approach integrates all elements of multi-scale modeling (including various empirical and science-based models) with materials informatics to provide users the opportunity to tailor material selections based on stringent application needs. Typically, materials engineering has focused on structural requirements (stress, strain, modulus, fracture toughness etc.) while multi-scale modeling has been science focused (mechanical threshold strength model, grain-size models, solid-solution strengthening models etc.). Materials informatics (mechanical property inventories) on the other hand, is extensively data focused. All of thesemore » elements are combined within the framework of ICME to create architecture for the development, selection and design new composite materials for challenging environments. We propose development of the foundations for applying ICME to composite materials development for nuclear and high-radiation environments (including nuclear-fusion energy reactors, nuclear-fission reactors, and accelerators). We expect to combine all elements of current material models (including thermo-mechanical and finite-element models) into the ICME framework. This will be accomplished through the use of a various mathematical modeling constructs. These constructs will allow the integration of constituent models, which in tum would allow us to use the adaptive strengths of using a combinatorial scheme (fabrication and computational) for creating new composite materials. A sample problem where these concepts are used is provided in this summary.« less

Interventions and approaches to integrating HIV and mental health services: a systematic review

PubMed Central

Chuah, Fiona Leh Hoon; Haldane, Victoria Elizabeth; Cervero-Liceras, Francisco; Ong, Suan Ee; Sigfrid, Louise A; Murphy, Georgina; Watt, Nicola; Balabanova, Dina; Hogarth, Sue; Maimaris, Will; Otero, Laura; Buse, Kent; McKee, Martin; Piot, Peter; Perel, Pablo; Legido-Quigley, Helena

2017-01-01

Abstract Background The frequency in which HIV and AIDS and mental health problems co-exist, and the complex bi-directional relationship between them, highlights the need for effective care models combining services for HIV and mental health. Here, we present a systematic review that synthesizes the literature on interventions and approaches integrating these services. Methods This review was part of a larger systematic review on integration of services for HIV and non-communicable diseases. Eligible studies included those that described or evaluated an intervention or approach aimed at integrating HIV and mental health care. We searched multiple databases from inception until October 2015, independently screened articles identified for inclusion, conducted data extraction, and assessed evaluative papers for risk of bias. Results Forty-five articles were eligible for this review. We identified three models of integration at the meso and micro levels: single-facility integration, multi-facility integration, and integrated care coordinated by a non-physician case manager. Single-site integration enhances multidisciplinary coordination and reduces access barriers for patients. However, the practicality and cost-effectiveness of providing a full continuum of specialized care on-site for patients with complex needs is arguable. Integration based on a collaborative network of specialized agencies may serve those with multiple co-morbidities but fragmented and poorly coordinated care can pose barriers. Integrated care coordinated by a single case manager can enable continuity of care for patients but requires appropriate training and support for case managers. Involving patients as key actors in facilitating integration within their own treatment plan is a promising approach. Conclusion This review identified much diversity in integration models combining HIV and mental health services, which are shown to have potential in yielding positive patient and service delivery outcomes when implemented within appropriate contexts. Our review revealed a lack of research in low- and middle- income countries, and was limited to most studies being descriptive. Overall, studies that seek to evaluate and compare integration models in terms of long-term outcomes and cost-effectiveness are needed, particularly at the health system level and in regions with high HIV and AIDS burden. PMID:29106512

General practice, primary care, and health service psychology: concepts, competencies, and the Combined-Integrated model.

PubMed

Schulte, Timothy J; Isley, Elayne; Link, Nancy; Shealy, Craig N; Winfrey, LaPearl Logan

2004-10-01

The profession of psychology is being impacted profoundly by broader changes within the national system of health care, as mental and behavioral health services are being recognized as essential components of a comprehensive, preventive, and cost-efficient primary care system. To fully define and embrace this role, the discipline of professional psychology must develop a shared disciplinary identity of health service psychology and a generalized competency-based model for doctoral education and training. This very framework has been adopted by Combined-Integrated (C-I) doctoral programs in professional psychology, which train across the practice areas (clinical, counseling, and school psychology) to provide a general and integrative foundation for their students. Because C-I programs produce general practitioners who are competent to function within a variety of health service settings, this innovative training approach has great potential to educate and train psychologists for a changing health care marketplace. Copyright 2004 Wiley Periodicals, Inc.

Hybrid perturbation methods based on statistical time series models

NASA Astrophysics Data System (ADS)

San-Juan, Juan Félix; San-Martín, Montserrat; Pérez, Iván; López, Rosario

2016-04-01

In this work we present a new methodology for orbit propagation, the hybrid perturbation theory, based on the combination of an integration method and a prediction technique. The former, which can be a numerical, analytical or semianalytical theory, generates an initial approximation that contains some inaccuracies derived from the fact that, in order to simplify the expressions and subsequent computations, not all the involved forces are taken into account and only low-order terms are considered, not to mention the fact that mathematical models of perturbations not always reproduce physical phenomena with absolute precision. The prediction technique, which can be based on either statistical time series models or computational intelligence methods, is aimed at modelling and reproducing missing dynamics in the previously integrated approximation. This combination results in the precision improvement of conventional numerical, analytical and semianalytical theories for determining the position and velocity of any artificial satellite or space debris object. In order to validate this methodology, we present a family of three hybrid orbit propagators formed by the combination of three different orders of approximation of an analytical theory and a statistical time series model, and analyse their capability to process the effect produced by the flattening of the Earth. The three considered analytical components are the integration of the Kepler problem, a first-order and a second-order analytical theories, whereas the prediction technique is the same in the three cases, namely an additive Holt-Winters method.

NREL and Panasonic | Energy Systems Integration Facility | NREL

Science.gov Websites

with distribution system modeling for the first time. The tool combines NREL's building energy system distribution system models, and Panasonic will perform cost-benefit analyses. Along with the creation of the

Browsing Space Weather Data and Models with the Integrated Space Weather Analysis (iSWA) System

NASA Technical Reports Server (NTRS)

Maddox, Marlo M.; Mullinix, Richard E.; Berrios, David H.; Hesse, Michael; Rastaetter, Lutz; Pulkkinen, Antti; Hourcle, Joseph A.; Thompson, Barbara J.

2011-01-01

The Integrated Space Weather Analysis (iSWA) System is a comprehensive web-based platform for space weather information that combines data from solar, heliospheric and geospace observatories with forecasts based on the most advanced space weather models. The iSWA system collects, generates, and presents a wide array of space weather resources in an intuitive, user-configurable, and adaptable format - thus enabling users to respond to current and future space weather impacts as well as enabling post-impact analysis. iSWA currently provides over 200 data and modeling products, and features a variety of tools that allow the user to browse, combine, and examine data and models from various sources. This presentation will consist of a summary of the iSWA products and an overview of the customizable user interfaces, and will feature several tutorial demonstrations highlighting the interactive tools and advanced capabilities.

Visual influence on path integration in darkness indicates a multimodal representation of large-scale space

PubMed Central

Tcheang, Lili; Bülthoff, Heinrich H.; Burgess, Neil

2011-01-01

Our ability to return to the start of a route recently performed in darkness is thought to reflect path integration of motion-related information. Here we provide evidence that motion-related interoceptive representations (proprioceptive, vestibular, and motor efference copy) combine with visual representations to form a single multimodal representation guiding navigation. We used immersive virtual reality to decouple visual input from motion-related interoception by manipulating the rotation or translation gain of the visual projection. First, participants walked an outbound path with both visual and interoceptive input, and returned to the start in darkness, demonstrating the influences of both visual and interoceptive information in a virtual reality environment. Next, participants adapted to visual rotation gains in the virtual environment, and then performed the path integration task entirely in darkness. Our findings were accurately predicted by a quantitative model in which visual and interoceptive inputs combine into a single multimodal representation guiding navigation, and are incompatible with a model of separate visual and interoceptive influences on action (in which path integration in darkness must rely solely on interoceptive representations). Overall, our findings suggest that a combined multimodal representation guides large-scale navigation, consistent with a role for visual imagery or a cognitive map. PMID:21199934

Integration of auditory and vibrotactile stimuli: Effects of frequency

PubMed Central

Wilson, E. Courtenay; Reed, Charlotte M.; Braida, Louis D.

2010-01-01

Perceptual integration of vibrotactile and auditory sinusoidal tone pulses was studied in detection experiments as a function of stimulation frequency. Vibrotactile stimuli were delivered through a single channel vibrator to the left middle fingertip. Auditory stimuli were presented diotically through headphones in a background of 50 dB sound pressure level broadband noise. Detection performance for combined auditory-tactile presentations was measured using stimulus levels that yielded 63% to 77% correct unimodal performance. In Experiment 1, the vibrotactile stimulus was 250 Hz and the auditory stimulus varied between 125 and 2000 Hz. In Experiment 2, the auditory stimulus was 250 Hz and the tactile stimulus varied between 50 and 400 Hz. In Experiment 3, the auditory and tactile stimuli were always equal in frequency and ranged from 50 to 400 Hz. The highest rates of detection for the combined-modality stimulus were obtained when stimulating frequencies in the two modalities were equal or closely spaced (and within the Pacinian range). Combined-modality detection for closely spaced frequencies was generally consistent with an algebraic sum model of perceptual integration; wider-frequency spacings were generally better fit by a Pythagorean sum model. Thus, perceptual integration of auditory and tactile stimuli at near-threshold levels appears to depend both on absolute frequency and relative frequency of stimulation within each modality. PMID:21117754

Modeling and control of a brushless DC axial flow ventricular assist device.

PubMed

Giridharan, Guruprasad A; Skliar, Mikhail; Olsen, Donald B; Pantalos, George M

2002-01-01

This article presents an integrated model of the human circulatory system that incorporates circulatory support by a brushless DC axial flow ventricular assist device (VAD), and a feedback VAD controller designed to maintain physiologically sufficient perfusion. The developed integrated model combines a network type model of the circulatory system with a nonlinear dynamic model of the brushless DC pump We show that maintaining a reference differential pressure between the left ventricle and aorta leads to adequate perfusion for different pathologic cases, ranging from normal heart to left heart asystole, and widely varying physical activity scenarios from rest to exercise.

Spheroidal Integral Equations for Geodetic Inversion of Geopotential Gradients

NASA Astrophysics Data System (ADS)

Novák, Pavel; Šprlák, Michal

2018-03-01

The static Earth's gravitational field has traditionally been described in geodesy and geophysics by the gravitational potential (geopotential for short), a scalar function of 3-D position. Although not directly observable, geopotential functionals such as its first- and second-order gradients are routinely measured by ground, airborne and/or satellite sensors. In geodesy, these observables are often used for recovery of the static geopotential at some simple reference surface approximating the actual Earth's surface. A generalized mathematical model is represented by a surface integral equation which originates in solving Dirichlet's boundary-value problem of the potential theory defined for the harmonic geopotential, spheroidal boundary and globally distributed gradient data. The mathematical model can be used for combining various geopotential gradients without necessity of their re-sampling or prior continuation in space. The model extends the apparatus of integral equations which results from solving boundary-value problems of the potential theory to all geopotential gradients observed by current ground, airborne and satellite sensors. Differences between spherical and spheroidal formulations of integral kernel functions of Green's kind are investigated. Estimated differences reach relative values at the level of 3% which demonstrates the significance of spheroidal approximation for flattened bodies such as the Earth. The observation model can be used for combined inversion of currently available geopotential gradients while exploring their spectral and stochastic characteristics. The model would be even more relevant to gravitational field modelling of other bodies in space with more pronounced spheroidal geometry than that of the Earth.

Integrating GPS, GYRO, vehicle speed sensor, and digital map to provide accurate and real-time position in an intelligent navigation system

NASA Astrophysics Data System (ADS)

Li, Qingquan; Fang, Zhixiang; Li, Hanwu; Xiao, Hui

2005-10-01

The global positioning system (GPS) has become the most extensively used positioning and navigation tool in the world. Applications of GPS abound in surveying, mapping, transportation, agriculture, military planning, GIS, and the geosciences. However, the positional and elevation accuracy of any given GPS location is prone to error, due to a number of factors. The applications of Global Positioning System (GPS) positioning is more and more popular, especially the intelligent navigation system which relies on GPS and Dead Reckoning technology is developing quickly for future huge market in China. In this paper a practical combined positioning model of GPS/DR/MM is put forward, which integrates GPS, Gyro, Vehicle Speed Sensor (VSS) and digital navigation maps to provide accurate and real-time position for intelligent navigation system. This model is designed for automotive navigation system making use of Kalman filter to improve position and map matching veracity by means of filtering raw GPS and DR signals, and then map-matching technology is used to provide map coordinates for map displaying. In practical examples, for illustrating the validity of the model, several experiments and their results of integrated GPS/DR positioning in intelligent navigation system will be shown for the conclusion that Kalman Filter based GPS/DR integrating position approach is necessary, feasible and efficient for intelligent navigation application. Certainly, this combined positioning model, similar to other model, can not resolve all situation issues. Finally, some suggestions are given for further improving integrated GPS/DR/MM application.

An investigation of multidisciplinary complex health care interventions - steps towards an integrative treatment model in the rehabilitation of People with Multiple Sclerosis

PubMed Central

2012-01-01

Background The Danish Multiple Sclerosis Society initiated a large-scale bridge building and integrative treatment project to take place from 2004–2010 at a specialized Multiple Sclerosis (MS) hospital. In this project, a team of five conventional health care practitioners and five alternative practitioners was set up to work together in developing and offering individualized treatments to 200 people with MS. The purpose of this paper is to present results from the six year treatment collaboration process regarding the development of an integrative treatment model. Discussion The collaborative work towards an integrative treatment model for people with MS, involved six steps: 1) Working with an initial model 2) Unfolding the different treatment philosophies 3) Discussing the elements of the Intervention-Mechanism-Context-Outcome-scheme (the IMCO-scheme) 4) Phrasing the common assumptions for an integrative MS program theory 5) Developing the integrative MS program theory 6) Building the integrative MS treatment model. The model includes important elements of the different treatment philosophies represented in the team and thereby describes a common understanding of the complexity of the courses of treatment. Summary An integrative team of practitioners has developed an integrative model for combined treatments of People with Multiple Sclerosis. The model unites different treatment philosophies and focuses on process-oriented factors and the strengthening of the patients’ resources and competences on a physical, an emotional and a cognitive level. PMID:22524586

The brain, self and society: a social-neuroscience model of predictive processing.

PubMed

Kelly, Michael P; Kriznik, Natasha M; Kinmonth, Ann Louise; Fletcher, Paul C

2018-05-10

This paper presents a hypothesis about how social interactions shape and influence predictive processing in the brain. The paper integrates concepts from neuroscience and sociology where a gulf presently exists between the ways that each describe the same phenomenon - how the social world is engaged with by thinking humans. We combine the concepts of predictive processing models (also called predictive coding models in the neuroscience literature) with ideal types, typifications and social practice - concepts from the sociological literature. This generates a unified hypothetical framework integrating the social world and hypothesised brain processes. The hypothesis combines aspects of neuroscience and psychology with social theory to show how social behaviors may be "mapped" onto brain processes. It outlines a conceptual framework that connects the two disciplines and that may enable creative dialogue and potential future research.

Theory, modeling, and integrated studies in the Arase (ERG) project

NASA Astrophysics Data System (ADS)

Seki, Kanako; Miyoshi, Yoshizumi; Ebihara, Yusuke; Katoh, Yuto; Amano, Takanobu; Saito, Shinji; Shoji, Masafumi; Nakamizo, Aoi; Keika, Kunihiro; Hori, Tomoaki; Nakano, Shin'ya; Watanabe, Shigeto; Kamiya, Kei; Takahashi, Naoko; Omura, Yoshiharu; Nose, Masahito; Fok, Mei-Ching; Tanaka, Takashi; Ieda, Akimasa; Yoshikawa, Akimasa

2018-02-01

Understanding of underlying mechanisms of drastic variations of the near-Earth space (geospace) is one of the current focuses of the magnetospheric physics. The science target of the geospace research project Exploration of energization and Radiation in Geospace (ERG) is to understand the geospace variations with a focus on the relativistic electron acceleration and loss processes. In order to achieve the goal, the ERG project consists of the three parts: the Arase (ERG) satellite, ground-based observations, and theory/modeling/integrated studies. The role of theory/modeling/integrated studies part is to promote relevant theoretical and simulation studies as well as integrated data analysis to combine different kinds of observations and modeling. Here we provide technical reports on simulation and empirical models related to the ERG project together with their roles in the integrated studies of dynamic geospace variations. The simulation and empirical models covered include the radial diffusion model of the radiation belt electrons, GEMSIS-RB and RBW models, CIMI model with global MHD simulation REPPU, GEMSIS-RC model, plasmasphere thermosphere model, self-consistent wave-particle interaction simulations (electron hybrid code and ion hybrid code), the ionospheric electric potential (GEMSIS-POT) model, and SuperDARN electric field models with data assimilation. ERG (Arase) science center tools to support integrated studies with various kinds of data are also briefly introduced.[Figure not available: see fulltext.

Sensitivity of an Integrated Mesoscale Atmosphere and Agriculture Land Modeling System (WRF/CMAQ-EPIC) to MODIS Vegetation and Lightning Assimilation

EPA Science Inventory

The combined meteorology and air quality modeling system composed of the Weather Research and Forecast (WRF) model and Community Multiscale Air Quality (CMAQ) model is an important decision support tool that is used in research and regulatory decisions related to emissions, meteo...

Developing the next generation of forest ecosystem models

Treesearch

Christopher R. Schwalm; Alan R. Ek

2002-01-01

Forest ecology and management are model-rich areas for research. Models are often cast as either empirical or mechanistic. With evolving climate change, hybrid models gain new relevance because of their ability to integrate existing mechanistic knowledge with empiricism based on causal thinking. The utility of hybrid platforms results in the combination of...

Manufacturing of highly integrated mechatronic modules by using the technology of embedding stereolithography

NASA Astrophysics Data System (ADS)

Rechtenwald, Thomas; Frick, Thomas; Schmidt, Michael

The embedding stereolithography is an additive, hybrid process, which allows the construction of highly integrated 3D assemblies for the use in automotive applications. The flexible process of stereolithography is combined with the embedding of functional components and supplemented by the additive manufacturing of electrical or optical conductive structures. This combination of sub-processes implies a high potential regarding the obtainable integration density of mechatronical modules. This work considers basic restrictions, which limit the mechanical stability of the manufactured modules by calculating the superposition of residual and external stress using a thermo-mechanical finite element model and develops a procedure to qualify stereolithography matrix materials for the process of the embedding stereolithography.

Multidisciplinary insight into clonal expansion of HTLV-1-infected cells in adult T-cell leukemia via modeling by deterministic finite automata coupled with high-throughput sequencing.

PubMed

Farmanbar, Amir; Firouzi, Sanaz; Park, Sung-Joon; Nakai, Kenta; Uchimaru, Kaoru; Watanabe, Toshiki

2017-01-31

Clonal expansion of leukemic cells leads to onset of adult T-cell leukemia (ATL), an aggressive lymphoid malignancy with a very poor prognosis. Infection with human T-cell leukemia virus type-1 (HTLV-1) is the direct cause of ATL onset, and integration of HTLV-1 into the human genome is essential for clonal expansion of leukemic cells. Therefore, monitoring clonal expansion of HTLV-1-infected cells via isolation of integration sites assists in analyzing infected individuals from early infection to the final stage of ATL development. However, because of the complex nature of clonal expansion, the underlying mechanisms have yet to be clarified. Combining computational/mathematical modeling with experimental and clinical data of integration site-based clonality analysis derived from next generation sequencing technologies provides an appropriate strategy to achieve a better understanding of ATL development. As a comprehensively interdisciplinary project, this study combined three main aspects: wet laboratory experiments, in silico analysis and empirical modeling. We analyzed clinical samples from HTLV-1-infected individuals with a broad range of proviral loads using a high-throughput methodology that enables isolation of HTLV-1 integration sites and accurate measurement of the size of infected clones. We categorized clones into four size groups, "very small", "small", "big", and "very big", based on the patterns of clonal growth and observed clone sizes. We propose an empirical formal model based on deterministic finite state automata (DFA) analysis of real clinical samples to illustrate patterns of clonal expansion. Through the developed model, we have translated biological data of clonal expansion into the formal language of mathematics and represented the observed clonality data with DFA. Our data suggest that combining experimental data (absolute size of clones) with DFA can describe the clonality status of patients. This kind of modeling provides a basic understanding as well as a unique perspective for clarifying the mechanisms of clonal expansion in ATL.

Effects of spatially distributed sectoral water management on the redistribution of water resources in an integrated water model

NASA Astrophysics Data System (ADS)

Voisin, Nathalie; Hejazi, Mohamad I.; Leung, L. Ruby; Liu, Lu; Huang, Maoyi; Li, Hong-Yi; Tesfa, Teklu

2017-05-01

Realistic representations of sectoral water withdrawals and consumptive demands and their allocation to surface and groundwater sources are important for improving modeling of the integrated water cycle. To inform future model development, we enhance the representation of water management in a regional Earth system (ES) model with a spatially distributed allocation of sectoral water demands simulated by a regional integrated assessment (IA) model to surface and groundwater systems. The integrated modeling framework (IA-ES) is evaluated by analyzing the simulated regulated flow and sectoral supply deficit in major hydrologic regions of the conterminous U.S, which differ from ES studies looking at water storage variations. Decreases in historical supply deficit are used as metrics to evaluate IA-ES model improvement in representating the complex sectoral human activities for assessing future adaptation and mitigation strategies. We also assess the spatial changes in both regulated flow and unmet demands, for irrigation and nonirrigation sectors, resulting from the individual and combined additions of groundwater and return flow modules. Results show that groundwater use has a pronounced regional and sectoral effect by reducing water supply deficit. The effects of sectoral return flow exhibit a clear east-west contrast in the hydrologic patterns, so the return flow component combined with the IA sectoral demands is a major driver for spatial redistribution of water resources and water deficits in the US. Our analysis highlights the need for spatially distributed sectoral representation of water management to capture the regional differences in interbasin redistribution of water resources and deficits.

Response-Time Tests of Logical-Rule Models of Categorization

ERIC Educational Resources Information Center

Little, Daniel R.; Nosofsky, Robert M.; Denton, Stephen E.

2011-01-01

A recent resurgence in logical-rule theories of categorization has motivated the development of a class of models that predict not only choice probabilities but also categorization response times (RTs; Fific, Little, & Nosofsky, 2010). The new models combine mental-architecture and random-walk approaches within an integrated framework and…

INTEGRATION OF AN ECONOMY UNDER IMPERFECT COMPETITION WITH A TWELVE-CELL ECOLOGICAL MODEL

EPA Science Inventory

This report documents the scientific research work done to date on developing a generalized mathematical model depicting a combined economic-ecological-social system with the goal of making it available to the scientific community. The model is preliminary and has not been tested...

A Process Model for Assessing Adolescent Risk for Suicide.

ERIC Educational Resources Information Center

Stoelb, Matt; Chiriboga, Jennifer

1998-01-01

This comprehensive assessment process model includes primary, secondary, and situational risk factors and their combined implications and significance in determining an adolescent's level or risk for suicide. Empirical data and clinical intuition are integrated to form a working client model that guides the professional in continuously reassessing…

PHOTOTOXIC POLYCYCLIC AROMATIC HYDROCARBONS IN SEDIMENTS: A MODEL-BASED APPROACH FOR ASSESSING RISK

EPA Science Inventory

Over the past five years we have developed a number of models which will be combined in an integrated framework with chemical-monitoring information to assess the potential for widespread risk of phototoxic PAHs in sediments.

An integrated approach for high spatial resolution mapping of water and carbon fluxes using multi-sensor data

USDA-ARS?s Scientific Manuscript database

In the last few years, modeling of surface processes, such as water and carbon balances, vegetation growth and energy budgets, has focused on integrated approaches that combine aspects of hydrology, biology and meteorology into unified analyses. In this context, remotely sensed data often have a cor...

Integrated presentation of ecological risk from multiple stressors

NASA Astrophysics Data System (ADS)

Goussen, Benoit; Price, Oliver R.; Rendal, Cecilie; Ashauer, Roman

2016-10-01

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic.

Integrated presentation of ecological risk from multiple stressors.

PubMed

Goussen, Benoit; Price, Oliver R; Rendal, Cecilie; Ashauer, Roman

2016-10-26

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic.

Integrated approach to estimate the ocean's time variable dynamic topography including its covariance matrix

NASA Astrophysics Data System (ADS)

Müller, Silvia; Brockmann, Jan Martin; Schuh, Wolf-Dieter

2015-04-01

The ocean's dynamic topography as the difference between the sea surface and the geoid reflects many characteristics of the general ocean circulation. Consequently, it provides valuable information for evaluating or tuning ocean circulation models. The sea surface is directly observed by satellite radar altimetry while the geoid cannot be observed directly. The satellite-based gravity field determination requires different measurement principles (satellite-to-satellite tracking (e.g. GRACE), satellite-gravity-gradiometry (GOCE)). In addition, hydrographic measurements (salinity, temperature and pressure; near-surface velocities) provide information on the dynamic topography. The observation types have different representations and spatial as well as temporal resolutions. Therefore, the determination of the dynamic topography is not straightforward. Furthermore, the integration of the dynamic topography into ocean circulation models requires not only the dynamic topography itself but also its inverse covariance matrix on the ocean model grid. We developed a rigorous combination method in which the dynamic topography is parameterized in space as well as in time. The altimetric sea surface heights are expressed as a sum of geoid heights represented in terms of spherical harmonics and the dynamic topography parameterized by a finite element method which can be directly related to the particular ocean model grid. Besides the difficult task of combining altimetry data with a gravity field model, a major aspect is the consistent combination of satellite data and in-situ observations. The particular characteristics and the signal content of the different observations must be adequately considered requiring the introduction of auxiliary parameters. Within our model the individual observation groups are combined in terms of normal equations considering their full covariance information; i.e. a rigorous variance/covariance propagation from the original measurements to the final product is accomplished. In conclusion, the developed integrated approach allows for estimating the dynamic topography and its inverse covariance matrix on arbitrary grids in space and time. The inverse covariance matrix contains the appropriate weights for model-data misfits in least-squares ocean model inversions. The focus of this study is on the North Atlantic Ocean. We will present the conceptual design and dynamic topography estimates based on time variable data from seven satellite altimeter missions (Jason-1, Jason-2, Topex/Poseidon, Envisat, ERS-2, GFO, Cryosat2) in combination with the latest GOCE gravity field model and in-situ data from the Argo floats and near-surface drifting buoys.

Modeling and Simulation of Bus Dispatching Policy for Timed Transfers on Signalized Networks

NASA Astrophysics Data System (ADS)

Cho, Hsun-Jung; Lin, Guey-Shii

2007-12-01

The major work of this study is to formulate the system cost functions and to integrate the bus dispatching policy with signal control. The integrated model mainly includes the flow dispersion model for links, signal control model for nodes, and dispatching control model for transfer terminals. All such models are inter-related for transfer operations in one-center transit network. The integrated model that combines dispatching policies with flexible signal control modes can be applied to assess the effectiveness of transfer operations. It is found that, if bus arrival information is reliable, an early dispatching decision made at the mean bus arrival times is preferable. The costs for coordinated operations with slack times are relatively low at the optimal common headway when applying adaptive route control. Based on such findings, a threshold function of bus headway for justifying an adaptive signal route control under various time values of auto drivers is developed.

Assessing time-integrated dissolved concentrations and predicting toxicity of metals during diel cycling in streams

USGS Publications Warehouse

Balistrieri, Laurie S.; Nimick, David A.; Mebane, Christopher A.

2012-01-01

Evaluating water quality and the health of aquatic organisms is challenging in systems with systematic diel (24 hour) or less predictable runoff-induced changes in water composition. To advance our understanding of how to evaluate environmental health in these dynamic systems, field studies of diel cycling were conducted in two streams (Silver Bow Creek and High Ore Creek) affected by historical mining activities in southwestern Montana. A combination of sampling and modeling tools were used to assess the toxicity of metals in these systems. Diffusive Gradients in Thin Films (DGT) samplers were deployed at multiple time intervals during diel sampling to confirm that DGT integrates time-varying concentrations of dissolved metals. Thermodynamic speciation calculations using site specific water compositions, including time-integrated dissolved metal concentrations determined from DGT, and a competitive, multiple-metal biotic ligand model incorporated into the Windemere Humic Aqueous Model Version 6.0 (WHAM VI) were used to determine the chemical speciation of dissolved metals and biotic ligands. The model results were combined with previously collected toxicity data on cutthroat trout to derive a relationship that predicts the relative survivability of these fish at a given site. This integrative approach may prove useful for assessing water quality and toxicity of metals to aquatic organisms in dynamic systems and evaluating whether potential changes in environmental health of aquatic systems are due to anthropogenic activities or natural variability.

Advances in understanding river-groundwater interactions

NASA Astrophysics Data System (ADS)

Brunner, Philip; Therrien, René; Renard, Philippe; Simmons, Craig T.; Franssen, Harrie-Jan Hendricks

2017-09-01

River-groundwater interactions are at the core of a wide range of major contemporary challenges, including the provision of high-quality drinking water in sufficient quantities, the loss of biodiversity in river ecosystems, or the management of environmental flow regimes. This paper reviews state of the art approaches in characterizing and modeling river and groundwater interactions. Our review covers a wide range of approaches, including remote sensing to characterize the streambed, emerging methods to measure exchange fluxes between rivers and groundwater, and developments in several disciplines relevant to the river-groundwater interface. We discuss approaches for automated calibration, and real-time modeling, which improve the simulation and understanding of river-groundwater interactions. Although the integration of these various approaches and disciplines is advancing, major research gaps remain to be filled to allow more complete and quantitative integration across disciplines. New possibilities for generating realistic distributions of streambed properties, in combination with more data and novel data types, have great potential to improve our understanding and predictive capabilities for river-groundwater systems, especially in combination with the integrated simulation of the river and groundwater flow as well as calibration methods. Understanding the implications of different data types and resolution, the development of highly instrumented field sites, ongoing model development, and the ultimate integration of models and data are important future research areas. These developments are required to expand our current understanding to do justice to the complexity of natural systems.

Parameter redundancy in discrete state-space and integrated models.

PubMed

Cole, Diana J; McCrea, Rachel S

2016-09-01

Discrete state-space models are used in ecology to describe the dynamics of wild animal populations, with parameters, such as the probability of survival, being of ecological interest. For a particular parametrization of a model it is not always clear which parameters can be estimated. This inability to estimate all parameters is known as parameter redundancy or a model is described as nonidentifiable. In this paper we develop methods that can be used to detect parameter redundancy in discrete state-space models. An exhaustive summary is a combination of parameters that fully specify a model. To use general methods for detecting parameter redundancy a suitable exhaustive summary is required. This paper proposes two methods for the derivation of an exhaustive summary for discrete state-space models using discrete analogues of methods for continuous state-space models. We also demonstrate that combining multiple data sets, through the use of an integrated population model, may result in a model in which all parameters are estimable, even though models fitted to the separate data sets may be parameter redundant. © 2016 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Integration Research on Gas Turbine and Tunnel Kiln Combined System

NASA Astrophysics Data System (ADS)

Shi, Hefei; Ma, Liangdong; Liu, Mingsheng

2018-04-01

Through the integrated modeling of gas turbine and tunnel kiln combined system, a thermodynamic calculation method of combined system is put forward, and the combined system operation parameters are obtained. By this method, the optimization of the combined system is analyzed and the optimal configuration of the gas turbine is calculated. At the same time, the thermal efficiency of the combined system is analyzed, and the heat distribution and thermal efficiency of the system before and after the improvement are explained. Taking the 1500 kg/h ceramic production as an example, pointed out that if the tunnel kiln has a gas turbine with a power of 342 kw. The amount of electricity of the combined system that produced per unit volume of the fuel which consumes more than it used to will be 7.19 kwh, the system thermal efficiency will reach 57.49%, which higher than the individual gas turbine’s cycle thermal efficiency 20% at least.

"Could I return to my life?" Integrated Narrative Nursing Model in Education (INNE).

PubMed

Artioli, Giovanna; Foà, Chiara; Cosentino, Chiara; Sulla, Francesco; Sollami, Alfonso; Taffurelli, Chiara

2018-03-28

The Integrated Narrative Nursing Model (INNM) is an approach that integrates the qualitative methodology typical of the human sciences, with the quantitative methodology more often associated with the natural sciences. This complex model, which combines a focus on narrative with quantitative measures, has recently been effectively applied to the assessment of chronic patients. In this study, the model is applied to the planning phase of education (Integrated Narrative Nursing Education, INNE), and proves to be a valid instrument for the promotion of the current educational paradigm that is centered on the engagement of both the patient and the caregiver in their own path of care. The aim of this study is therefore to describe the nurse's strategy in the planning of an educational intervention by using the INNE model. The case of a 70-year-old woman with pulmonary neoplasm is described at her first admission to Hospice. Each step conducted by the reference nurse, who uses INNE to record the nurse-patient narrative and collect subsequent questionnaires in order to create a shared educational plan, is also described. The information collected was submitted, starting from a grounded methodology to the following four levels of analysis: I. Needs Assessment, II. Narrative Diagnosis, III. Quantitative Outcome, IV. Integrated Outcome. Step IV, which is derived from the integration of all levels of analysis, allows a nurse to define, even graphically, the conceptual map of a patient's needs, resources and perspectives, in a completely tailored manner. The INNE model offers a valid methodological support for the professional who intends to educate the patient through an inter-subjective and engaged pathway, between the professional, their patient and the socio-relational context. It is a matter of adopting a complex vision that combines processes and methods that require a steady scientific basis and advanced methodological expertise with active listening and empathy - skills which require emotional intelligence.

Integrated Decision Strategies for Skin Sensitization Hazard

PubMed Central

Strickland, Judy; Zang, Qingda; Kleinstreuer, Nicole; Paris, Michael; Lehmann, David M.; Choksi, Neepa; Matheson, Joanna; Jacobs, Abigail; Lowit, Anna; Allen, David; Casey, Warren

2016-01-01

One of the top priorities of ICCVAM is the identification and evaluation of non-animal alternatives for skin sensitization testing. Although skin sensitization is a complex process, the key biological events of the process have been well characterized in an adverse outcome pathway (AOP) proposed by OECD. Accordingly, ICCVAM is working to develop integrated decision strategies based on the AOP using in vitro, in chemico, and in silico information. Data were compiled for 120 substances tested in the murine local lymph node assay (LLNA), direct peptide reactivity assay (DPRA), human cell line activation test (h-CLAT), and KeratinoSens assay. Data for six physicochemical properties that may affect skin penetration were also collected, and skin sensitization read-across predictions were performed using OECD QSAR Toolbox. All data were combined into a variety of potential integrated decision strategies to predict LLNA outcomes using a training set of 94 substances and an external test set of 26 substances. Fifty-four models were built using multiple combinations of machine learning approaches and predictor variables. The seven models with the highest accuracy (89–96% for the test set and 96–99% for the training set) for predicting LLNA outcomes used a support vector machine (SVM) approach with different combinations of predictor variables. The performance statistics of the SVM models were higher than any of the non-animal tests alone and higher than simple test battery approaches using these methods. These data suggest that computational approaches are promising tools to effectively integrate data sources to identify potential skin sensitizers without animal testing. PMID:26851134

Separation of atmospheric, oceanic and hydrological polar motion excitation mechanisms based on a combination of geometric and gravimetric space observations

NASA Astrophysics Data System (ADS)

Göttl, F.; Schmidt, M.; Seitz, F.; Bloßfeld, M.

2015-04-01

The goal of our study is to determine accurate time series of geophysical Earth rotation excitations to learn more about global dynamic processes in the Earth system. For this purpose, we developed an adjustment model which allows to combine precise observations from space geodetic observation systems, such as Satellite Laser Ranging (SLR), Global Navigation Satellite Systems, Very Long Baseline Interferometry, Doppler Orbit determination and Radiopositioning Integrated on Satellite, satellite altimetry and satellite gravimetry in order to separate geophysical excitation mechanisms of Earth rotation. Three polar motion time series are applied to derive the polar motion excitation functions (integral effect). Furthermore we use five time variable gravity field solutions from Gravity Recovery and Climate Experiment to determine not only the integral mass effect but also the oceanic and hydrological mass effects by applying suitable filter techniques and a land-ocean mask. For comparison the integral mass effect is also derived from degree 2 potential coefficients that are estimated from SLR observations. The oceanic mass effect is also determined from sea level anomalies observed by satellite altimetry by reducing the steric sea level anomalies derived from temperature and salinity fields of the oceans. Due to the combination of all geodetic estimated excitations the weaknesses of the individual processing strategies can be reduced and the technique-specific strengths can be accounted for. The formal errors of the adjusted geodetic solutions are smaller than the RMS differences of the geophysical model solutions. The improved excitation time series can be used to improve the geophysical modeling.

Developing mesoscopic models for the before and after study of the inter-county connector : [research summary].

DOT National Transportation Integrated Search

2013-03-01

It has become apparent in recent years that significant benefits will be obtained if : the Maryland State Highway Administration (SHA) can combine its data products : and modeling tools for integrated transportation operations and planning. Examples ...

Closed-form solutions in stress-driven two-phase integral elasticity for bending of functionally graded nano-beams

NASA Astrophysics Data System (ADS)

Barretta, Raffaele; Fabbrocino, Francesco; Luciano, Raimondo; Sciarra, Francesco Marotti de

2018-03-01

Strain-driven and stress-driven integral elasticity models are formulated for the analysis of the structural behaviour of fuctionally graded nano-beams. An innovative stress-driven two-phases constitutive mixture defined by a convex combination of local and nonlocal phases is presented. The analysis reveals that the Eringen strain-driven fully nonlocal model cannot be used in Structural Mechanics since it is ill-posed and the local-nonlocal mixtures based on the Eringen integral model partially resolve the ill-posedeness of the model. In fact, a singular behaviour of continuous nano-structures appears if the local fraction tends to vanish so that the ill-posedness of the Eringen integral model is not eliminated. On the contrary, local-nonlocal mixtures based on the stress-driven theory are mathematically and mechanically appropriate for nanosystems. Exact solutions of inflected functionally graded nanobeams of technical interest are established by adopting the new local-nonlocal mixture stress-driven integral relation. Effectiveness of the new nonlocal approach is tested by comparing the contributed results with the ones corresponding to the mixture Eringen theory.

Hub and pylon fairing integration for helicopter drag reduction

NASA Technical Reports Server (NTRS)

Martin, D. M.; Mort, R. W.; Squires, P. K.; Young, L. A.

1991-01-01

The results of testing hub and pylon fairings mounted on a one-fifth scale helicopter with the goal of reducing parasite drag are presented. Lift, drag, and pitching moment, as well as side force and yawing moment, were measured. The primary objective of the test was to validate the drag reduction capability of integrated hub and pylon configurations in the aerodynamic environment produced by a rotating hub in forward flight. In addition to the baseline helicopter without fairings, three hub fairings and three pylon fairings were tested in various combinations. The three hub fairings tested reflect two different conceptual design approaches to implementing an integrated fairing configuration on an actual aircraft. The design philosophy is discussed in detail and comparisons are made between the wind tunnel models and potential full-scale prototypes. The data show that model drag can be reduced by as much as 20.8 percent by combining a small hub fairing with circular arc upper and flat lower surfaces and a nontapered 34-percent thick pylon fairing. Aerodynamic effects caused by the fairings, which may have a significant impact on static longitudinal and directional stability, were observed. The results support previous research which showed that the greatest reduction in model drag is achieved if the hub and pylon fairings are integrated with minimum gap between the two.

A progress report on estuary modeling by the finite-element method

USGS Publications Warehouse

Gray, William G.

1978-01-01

Various schemes are investigated for finite-element modeling of two-dimensional surface-water flows. The first schemes investigated combine finite-element spatial discretization with split-step time stepping schemes that have been found useful in finite-difference computations. Because of the large number of numerical integrations performed in space and the large sparse matrices solved, these finite-element schemes were found to be economically uncompetitive with finite-difference schemes. A very promising leapfrog scheme is proposed which, when combined with a novel very fast spatial integration procedure, eliminates the need to solve any matrices at all. Additional problems attacked included proper propagation of waves and proper specification of the normal flow-boundary condition. This report indicates work in progress and does not come to a definitive conclusion as to the best approach for finite-element modeling of surface-water problems. The results presented represent findings obtained between September 1973 and July 1976. (Woodard-USGS)

Method and system to estimate variables in an integrated gasification combined cycle (IGCC) plant

DOEpatents

Kumar, Aditya; Shi, Ruijie; Dokucu, Mustafa

2013-09-17

System and method to estimate variables in an integrated gasification combined cycle (IGCC) plant are provided. The system includes a sensor suite to measure respective plant input and output variables. An extended Kalman filter (EKF) receives sensed plant input variables and includes a dynamic model to generate a plurality of plant state estimates and a covariance matrix for the state estimates. A preemptive-constraining processor is configured to preemptively constrain the state estimates and covariance matrix to be free of constraint violations. A measurement-correction processor may be configured to correct constrained state estimates and a constrained covariance matrix based on processing of sensed plant output variables. The measurement-correction processor is coupled to update the dynamic model with corrected state estimates and a corrected covariance matrix. The updated dynamic model may be configured to estimate values for at least one plant variable not originally sensed by the sensor suite.

Integrating count and detection–nondetection data to model population dynamics

USGS Publications Warehouse

Zipkin, Elise F.; Rossman, Sam; Yackulic, Charles B.; Wiens, David; Thorson, James T.; Davis, Raymond J.; Grant, Evan H. Campbell

2017-01-01

There is increasing need for methods that integrate multiple data types into a single analytical framework as the spatial and temporal scale of ecological research expands. Current work on this topic primarily focuses on combining capture–recapture data from marked individuals with other data types into integrated population models. Yet, studies of species distributions and trends often rely on data from unmarked individuals across broad scales where local abundance and environmental variables may vary. We present a modeling framework for integrating detection–nondetection and count data into a single analysis to estimate population dynamics, abundance, and individual detection probabilities during sampling. Our dynamic population model assumes that site-specific abundance can change over time according to survival of individuals and gains through reproduction and immigration. The observation process for each data type is modeled by assuming that every individual present at a site has an equal probability of being detected during sampling processes. We examine our modeling approach through a series of simulations illustrating the relative value of count vs. detection–nondetection data under a variety of parameter values and survey configurations. We also provide an empirical example of the model by combining long-term detection–nondetection data (1995–2014) with newly collected count data (2015–2016) from a growing population of Barred Owl (Strix varia) in the Pacific Northwest to examine the factors influencing population abundance over time. Our model provides a foundation for incorporating unmarked data within a single framework, even in cases where sampling processes yield different detection probabilities. This approach will be useful for survey design and to researchers interested in incorporating historical or citizen science data into analyses focused on understanding how demographic rates drive population abundance.

Integrating count and detection-nondetection data to model population dynamics.

PubMed

Zipkin, Elise F; Rossman, Sam; Yackulic, Charles B; Wiens, J David; Thorson, James T; Davis, Raymond J; Grant, Evan H Campbell

2017-06-01

There is increasing need for methods that integrate multiple data types into a single analytical framework as the spatial and temporal scale of ecological research expands. Current work on this topic primarily focuses on combining capture-recapture data from marked individuals with other data types into integrated population models. Yet, studies of species distributions and trends often rely on data from unmarked individuals across broad scales where local abundance and environmental variables may vary. We present a modeling framework for integrating detection-nondetection and count data into a single analysis to estimate population dynamics, abundance, and individual detection probabilities during sampling. Our dynamic population model assumes that site-specific abundance can change over time according to survival of individuals and gains through reproduction and immigration. The observation process for each data type is modeled by assuming that every individual present at a site has an equal probability of being detected during sampling processes. We examine our modeling approach through a series of simulations illustrating the relative value of count vs. detection-nondetection data under a variety of parameter values and survey configurations. We also provide an empirical example of the model by combining long-term detection-nondetection data (1995-2014) with newly collected count data (2015-2016) from a growing population of Barred Owl (Strix varia) in the Pacific Northwest to examine the factors influencing population abundance over time. Our model provides a foundation for incorporating unmarked data within a single framework, even in cases where sampling processes yield different detection probabilities. This approach will be useful for survey design and to researchers interested in incorporating historical or citizen science data into analyses focused on understanding how demographic rates drive population abundance. © 2017 by the Ecological Society of America.

Addressable-Matrix Integrated-Circuit Test Structure

NASA Technical Reports Server (NTRS)

Sayah, Hoshyar R.; Buehler, Martin G.

1991-01-01

Method of quality control based on use of row- and column-addressable test structure speeds collection of data on widths of resistor lines and coverage of steps in integrated circuits. By use of straightforward mathematical model, line widths and step coverages deduced from measurements of electrical resistances in each of various combinations of lines, steps, and bridges addressable in test structure. Intended for use in evaluating processes and equipment used in manufacture of application-specific integrated circuits.

The Reciprocal Internal/External Frame of Reference Model: An Integration of Models of Relations between Academic Achievement and Self-Concept

ERIC Educational Resources Information Center

Moller, Jens; Retelsdorf, Jan; Koller, Olaf; Marsh, Herb W.

2011-01-01

The reciprocal internal/external frame of reference model (RI/EM) combines the internal/external frame of reference model and the reciprocal effects model. The RI/EM predicts positive effects of mathematics and verbal achievement and academic self-concepts (ASC) on subsequent mathematics and verbal achievements and ASCs within domains and negative…

An Integrated Approach to Modeling Solar Electric Propulsion Vehicles During Long Duration, Near-Earth Orbit Transfers

NASA Technical Reports Server (NTRS)

Smith, David A.; Hojnicki, Jeffrey S.; Sjauw, Waldy K.

2014-01-01

Recent NASA interest in utilizing solar electronic propulsion (SEP) technology to transfer payloads, e.g. from low-Earth orbit (LEO) to higher energy geostationary-Earth orbit (GEO) or to Earth escape, has necessitated the development of high fidelity SEP vehicle models and simulations. These models and simulations need to be capable of capturing vehicle dynamics and sub-system interactions experienced during the transfer trajectories which are typically accomplished with continuous-burn (potentially interrupted by solar eclipse), long duration "spiral out" maneuvers taking several months or more to complete. This paper presents details of an integrated simulation approach achieved by combining a high fidelity vehicle simulation code with a detailed solar array model. The combined simulation tool gives researchers the functionality to study the integrated effects of various vehicle sub-systems (e.g. vehicle guidance, navigation and control (GN&C), electric propulsion system (EP)) with time varying power production. Results from a simulation model of a vehicle with a 50 kW class SEP system using the integrated tool are presented and compared to the results from another simulation model employing a 50 kW end-of-life (EOL) fixed power level assumption. These models simulate a vehicle under three degree of freedom dynamics (i.e. translational dynamics only) and include the effects of a targeting guidance algorithm (providing a "near optimal" transfer) during a LEO to near Earth escape (C (sub 3) = -2.0 km (sup 2) / sec (sup -2) spiral trajectory. The presented results include the impact of the fully integrated, time-varying solar array model (e.g. cumulative array degradation from traversing the Van Allen belts, impact of solar eclipses on the vehicle and the related temperature responses in the solar arrays due to operating in the Earth's thermal environment, high fidelity array power module, etc.); these are used to assess the impact on vehicle performance (i.e. propellant consumption) and transit times.

Selected Tether Applications Cost Model

NASA Technical Reports Server (NTRS)

Keeley, Michael G.

1988-01-01

Diverse cost-estimating techniques and data combined into single program. Selected Tether Applications Cost Model (STACOM 1.0) is interactive accounting software tool providing means for combining several independent cost-estimating programs into fully-integrated mathematical model capable of assessing costs, analyzing benefits, providing file-handling utilities, and putting out information in text and graphical forms to screen, printer, or plotter. Program based on Lotus 1-2-3, version 2.0. Developed to provide clear, concise traceability and visibility into methodology and rationale for estimating costs and benefits of operations of Space Station tether deployer system.

Integrated Modeling, Mapping, and Simulation (IMMS) Framework for Exercise and Response Planning

NASA Technical Reports Server (NTRS)

Mapar, Jalal; Hoette, Trisha; Mahrous, Karim; Pancerella, Carmen M.; Plantenga, Todd; Yang, Christine; Yang, Lynn; Hopmeier, Michael

2011-01-01

EmergenCy management personnel at federal, stale, and local levels can benefit from the increased situational awareness and operational efficiency afforded by simulation and modeling for emergency preparedness, including planning, training and exercises. To support this goal, the Department of Homeland Security's Science & Technology Directorate is funding the Integrated Modeling, Mapping, and Simulation (IMMS) program to create an integrating framework that brings together diverse models for use by the emergency response community. SUMMIT, one piece of the IMMS program, is the initial software framework that connects users such as emergency planners and exercise developers with modeling resources, bridging the gap in expertise and technical skills between these two communities. SUMMIT was recently deployed to support exercise planning for National Level Exercise 2010. Threat, casualty. infrastructure, and medical surge models were combined within SUMMIT to estimate health care resource requirements for the exercise ground truth.

Information Extraction for System-Software Safety Analysis: Calendar Year 2007 Year-End Report

NASA Technical Reports Server (NTRS)

Malin, Jane T.

2008-01-01

This annual report describes work to integrate a set of tools to support early model-based analysis of failures and hazards due to system-software interactions. The tools perform and assist analysts in the following tasks: 1) extract model parts from text for architecture and safety/hazard models; 2) combine the parts with library information to develop the models for visualization and analysis; 3) perform graph analysis on the models to identify possible paths from hazard sources to vulnerable entities and functions, in nominal and anomalous system-software configurations; 4) perform discrete-time-based simulation on the models to investigate scenarios where these paths may play a role in failures and mishaps; and 5) identify resulting candidate scenarios for software integration testing. This paper describes new challenges in a NASA abort system case, and enhancements made to develop the integrated tool set.

Interventions and approaches to integrating HIV and mental health services: a systematic review.

PubMed

Chuah, Fiona Leh Hoon; Haldane, Victoria Elizabeth; Cervero-Liceras, Francisco; Ong, Suan Ee; Sigfrid, Louise A; Murphy, Georgina; Watt, Nicola; Balabanova, Dina; Hogarth, Sue; Maimaris, Will; Otero, Laura; Buse, Kent; McKee, Martin; Piot, Peter; Perel, Pablo; Legido-Quigley, Helena

2017-11-01

The frequency in which HIV and AIDS and mental health problems co-exist, and the complex bi-directional relationship between them, highlights the need for effective care models combining services for HIV and mental health. Here, we present a systematic review that synthesizes the literature on interventions and approaches integrating these services. This review was part of a larger systematic review on integration of services for HIV and non-communicable diseases. Eligible studies included those that described or evaluated an intervention or approach aimed at integrating HIV and mental health care. We searched multiple databases from inception until October 2015, independently screened articles identified for inclusion, conducted data extraction, and assessed evaluative papers for risk of bias. Forty-five articles were eligible for this review. We identified three models of integration at the meso and micro levels: single-facility integration, multi-facility integration, and integrated care coordinated by a non-physician case manager. Single-site integration enhances multidisciplinary coordination and reduces access barriers for patients. However, the practicality and cost-effectiveness of providing a full continuum of specialized care on-site for patients with complex needs is arguable. Integration based on a collaborative network of specialized agencies may serve those with multiple co-morbidities but fragmented and poorly coordinated care can pose barriers. Integrated care coordinated by a single case manager can enable continuity of care for patients but requires appropriate training and support for case managers. Involving patients as key actors in facilitating integration within their own treatment plan is a promising approach. This review identified much diversity in integration models combining HIV and mental health services, which are shown to have potential in yielding positive patient and service delivery outcomes when implemented within appropriate contexts. Our review revealed a lack of research in low- and middle- income countries, and was limited to most studies being descriptive. Overall, studies that seek to evaluate and compare integration models in terms of long-term outcomes and cost-effectiveness are needed, particularly at the health system level and in regions with high HIV and AIDS burden. © The Author 2017. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine.

Spreadsheet Modeling of (Q,R) Inventory Policies

ERIC Educational Resources Information Center

Cobb, Barry R.

2013-01-01

This teaching brief describes a method for finding an approximately optimal combination of order quantity and reorder point in a continuous review inventory model using a discrete expected shortage calculation. The technique is an alternative to a model where expected shortage is calculated by integration, and can allow students who have not had a…

Integrating Narrative and Action Processes in Group Counseling Practice: A Multimodal Approach for Helping Clients

ERIC Educational Resources Information Center

Westwood, Marvin J.; Ewasiw, Joan F.

2011-01-01

The aim of this article is to introduce an integrated approach for helping clients. The approach combines and builds on two group-based interventions: guided autobiography and therapeutic enactment. Descriptions of the two interventions individually and a transtheoretical model for change are provided. How change occurs through the proposed…

A Novel Integrated Ecological Model for the study of Sustainability

EPA Science Inventory

In recent years, there has been a growing interest among various sections of the society in the study of sustainability. Recently, a generalized mathematical model depicting a combined economic-ecological-social system has been proposed to help in the formal study of sustainabili...

A multi-model assessment of the co-benefits of climate mitigation for global air quality

NASA Astrophysics Data System (ADS)

Rao, Shilpa; Klimont, Zbigniew; Leitao, Joana; Riahi, Keywan; van Dingenen, Rita; Aleluia Reis, Lara; Calvin, Katherine; Dentener, Frank; Drouet, Laurent; Fujimori, Shinichiro; Harmsen, Mathijs; Luderer, Gunnar; Heyes, Chris; Strefler, Jessica; Tavoni, Massimo; van Vuuren, Detlef P.

2016-12-01

We present a model comparison study that combines multiple integrated assessment models with a reduced-form global air quality model to assess the potential co-benefits of global climate mitigation policies in relation to the World Health Organization (WHO) goals on air quality and health. We include in our assessment, a range of alternative assumptions on the implementation of current and planned pollution control policies. The resulting air pollution emission ranges significantly extend those in the Representative Concentration Pathways. Climate mitigation policies complement current efforts on air pollution control through technology and fuel transformations in the energy system. A combination of stringent policies on air pollution control and climate change mitigation results in 40% of the global population exposed to PM levels below the WHO air quality guideline; with the largest improvements estimated for India, China, and Middle East. Our results stress the importance of integrated multisector policy approaches to achieve the Sustainable Development Goals.

A measurement theory of illusory conjunctions.

PubMed

Prinzmetal, William; Ivry, Richard B; Beck, Diane; Shimizu, Naomi

2002-04-01

Illusory conjunctions refer to the incorrect perceptual combination of correctly perceived features, such as color and shape. Research on the phenomenon has been hampered by the lack of a measurement theory that accounts for guessing features, as well as the incorrect combination of correctly perceived features. Recently, several investigators have suggested using multinomial models as a tool for measuring feature integration. The authors examined the adequacy of these models in 2 experiments by testing whether model parameters reflect changes in stimulus factors. In a third experiment, confidence ratings were used as a tool for testing the model. Multinomial models accurately reflected both variations in stimulus factors and observers' trial-by-trial confidence ratings.

Integrated pest management and allocation of control efforts for vector-borne diseases

USGS Publications Warehouse

Ginsberg, H.S.

2001-01-01

Applications of various control methods were evaluated to determine how to integrate methods so as to minimize the number of human cases of vector-borne diseases. These diseases can be controlled by lowering the number of vector-human contacts (e.g., by pesticide applications or use of repellents), or by lowering the proportion of vectors infected with pathogens (e.g., by lowering or vaccinating reservoir host populations). Control methods should be combined in such a way as to most efficiently lower the probability of human encounter with an infected vector. Simulations using a simple probabilistic model of pathogen transmission suggest that the most efficient way to integrate different control methods is to combine methods that have the same effect (e.g., combine treatments that lower the vector population; or combine treatments that lower pathogen prevalence in vectors). Combining techniques that have different effects (e.g., a technique that lowers vector populations with a technique that lowers pathogen prevalence in vectors) will be less efficient than combining two techniques that both lower vector populations or combining two techniques that both lower pathogen prevalence, costs being the same. Costs of alternative control methods generally differ, so the efficiency of various combinations at lowering human contact with infected vectors should be estimated at available funding levels. Data should be collected from initial trials to improve the effects of subsequent interventions on the number of human cases.

Framework Programmable Platform for the Advanced Software Development Workstation (FPP/ASDW). Demonstration framework document. Volume 1: Concepts and activity descriptions

NASA Technical Reports Server (NTRS)

Mayer, Richard J.; Blinn, Thomas M.; Dewitte, Paul S.; Crump, John W.; Ackley, Keith A.

1992-01-01

The Framework Programmable Software Development Platform (FPP) is a project aimed at effectively combining tool and data integration mechanisms with a model of the software development process to provide an intelligent integrated software development environment. Guided by the model, this system development framework will take advantage of an integrated operating environment to automate effectively the management of the software development process so that costly mistakes during the development phase can be eliminated. The Advanced Software Development Workstation (ASDW) program is conducting research into development of advanced technologies for Computer Aided Software Engineering (CASE).

[Disease-syndrome combination in integrated traditional Chinese and Western medicine in andrology: Confusions and countermeasures in studies].

PubMed

Zhang, Min-Jian

2017-07-01

Researches on the mechanisms underlying the therapeutic effects of the disease-syndrome combination approach in integrated traditional Chinese and Western medicine are becoming a hot spot in andrology, but many recent studies of this kind have failed to explain the connotation of integrated traditional Chinese and Western medicine in andrology. Related existing problems include repeated researches into the same indexes of action mechanisms of different therapeutic principles of traditional Chinese medicine (TCM), Chinese herbal compound and special prescriptions, studies focusing on individual diseases but ignoring symptoms, immature syndrome models for studies of mechanisms, and too much attention to uncertain or immature target mechanisms. The stress should be placed on the action mechanisms of Chinese herbal compound and special prescriptions on male diseases and, what is more important, on the clarification of the essential principles of differentiation and treatment of TCM syndromes. In the recent years, proteomics, genomics, transcriptomics and metabolomics have shed some light upon researches into the mechanisms underlying the therapeutic effects of the disease-syndrome combination approach in integrated traditional Chinese and Western medicine in andrology. An insight into the TCM syndrome, a macroscopic inductive analysis, and a comprehension of such microcosmic aspects as the gene, protein, metabolism and metagenome may contribute to some breakthroughs and new ideas in the studies of disease-syndrome combination in integrated traditional Chinese and Western medicine in andrology.

Bayesian-based integration of multisensory naturalistic perithreshold stimuli.

PubMed

Regenbogen, Christina; Johansson, Emilia; Andersson, Patrik; Olsson, Mats J; Lundström, Johan N

2016-07-29

Most studies exploring multisensory integration have used clearly perceivable stimuli. According to the principle of inverse effectiveness, the added neural and behavioral benefit of integrating clear stimuli is reduced in comparison to stimuli with degraded and less salient unisensory information. Traditionally, speed and accuracy measures have been analyzed separately with few studies merging these to gain an understanding of speed-accuracy trade-offs in multisensory integration. In two separate experiments, we assessed multisensory integration of naturalistic audio-visual objects consisting of individually-tailored perithreshold dynamic visual and auditory stimuli, presented within a multiple-choice task, using a Bayesian Hierarchical Drift Diffusion Model that combines response time and accuracy. For both experiments, unisensory stimuli were degraded to reach a 75% identification accuracy level for all individuals and stimuli to promote multisensory binding. In Experiment 1, we subsequently presented uni- and their respective bimodal stimuli followed by a 5-alternative-forced-choice task. In Experiment 2, we controlled for low-level integration and attentional differences. Both experiments demonstrated significant superadditive multisensory integration of bimodal perithreshold dynamic information. We present evidence that the use of degraded sensory stimuli may provide a link between previous findings of inverse effectiveness on a single neuron level and overt behavior. We further suggest that a combined measure of accuracy and reaction time may be a more valid and holistic approach of studying multisensory integration and propose the application of drift diffusion models for studying behavioral correlates as well as brain-behavior relationships of multisensory integration. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Management Tool for Assessing Aquaculture Environmental Impacts in Chilean Patagonian Fjords: Integrating Hydrodynamic and Pellets Dispersion Models

NASA Astrophysics Data System (ADS)

Tironi, Antonio; Marin, Víctor H.; Campuzano, Francisco J.

2010-05-01

This article introduces a management tool for salmon farming, with a scope in the local sustainability of salmon aquaculture of the Aysen Fjord, Chilean Patagonia. Based on Integrated Coastal Zone Management (ICZM) principles, the tool combines a large 3-level nested hydrodynamic model, a particle tracking module and a GIS application into an assessment tool for particulate waste dispersal of salmon farming activities. The model offers an open source alternative to particulate waste modeling and evaluation, contributing with valuable information for local decision makers in the process of locating new facilities and monitoring stations.

Solving the hypersingular boundary integral equation for the Burton and Miller formulation.

PubMed

Langrenne, Christophe; Garcia, Alexandre; Bonnet, Marc

2015-11-01

This paper presents an easy numerical implementation of the Burton and Miller (BM) formulation, where the hypersingular Helmholtz integral is regularized by identities from the associated Laplace equation and thus needing only the evaluation of weakly singular integrals. The Helmholtz equation and its normal derivative are combined directly with combinations at edge or corner collocation nodes not used when the surface is not smooth. The hypersingular operators arising in this process are regularized and then evaluated by an indirect procedure based on discretized versions of the Calderón identities linking the integral operators for associated Laplace problems. The method is valid for acoustic radiation and scattering problems involving arbitrarily shaped three-dimensional bodies. Unlike other approaches using direct evaluation of hypersingular integrals, collocation points still coincide with mesh nodes, as is usual when using conforming elements. Using higher-order shape functions (with the boundary element method model size kept fixed) reduces the overall numerical integration effort while increasing the solution accuracy. To reduce the condition number of the resulting BM formulation at low frequencies, a regularized version α = ik/(k(2 )+ λ) of the classical BM coupling factor α = i/k is proposed. Comparisons with the combined Helmholtz integral equation Formulation method of Schenck are made for four example configurations, two of them featuring non-smooth surfaces.

Integrating Heterogeneous Healthcare Datasets and Visual Analytics for Disease Bio-surveillance and Dynamics

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

Ramanathan, Arvind; Pullum, Laura L; Steed, Chad A

2013-01-01

n this paper, we present an overview of the big data chal- lenges in disease bio-surveillance and then discuss the use of visual analytics for integrating data and turning it into knowl- edge. We will explore two integration scenarios: (1) combining text and multimedia sources to improve situational awareness and (2) enhancing disease spread model data with real-time bio-surveillance data. Together, the proposed integration methodologies can improve awareness about when, where and how emerging diseases can affect wide geographic regions.

Integrating Learning Styles and Personality Traits into an Affective Model to Support Learner's Learning

NASA Astrophysics Data System (ADS)

Leontidis, Makis; Halatsis, Constantin

The aim of this paper is to present a model in order to integrate the learning style and the personality traits of a learner into an enhanced Affective Style which is stored in the learner’s model. This model which can deal with the cognitive abilities as well as the affective preferences of the learner is called Learner Affective Model (LAM). The LAM is used to retain learner’s knowledge and activities during his interaction with a Web-based learning environment and also to provide him with the appropriate pedagogical guidance. The proposed model makes use of an ontological approach in combination with the Bayesian Network model and contributes to the efficient management of the LAM in an Affective Module.

Carbon-free hydrogen production from low rank coal

NASA Astrophysics Data System (ADS)

Aziz, Muhammad; Oda, Takuya; Kashiwagi, Takao

2018-02-01

Novel carbon-free integrated system of hydrogen production and storage from low rank coal is proposed and evaluated. To measure the optimum energy efficiency, two different systems employing different chemical looping technologies are modeled. The first integrated system consists of coal drying, gasification, syngas chemical looping, and hydrogenation. On the other hand, the second system combines coal drying, coal direct chemical looping, and hydrogenation. In addition, in order to cover the consumed electricity and recover the energy, combined cycle is adopted as addition module for power generation. The objective of the study is to find the best system having the highest performance in terms of total energy efficiency, including hydrogen production efficiency and power generation efficiency. To achieve a thorough energy/heat circulation throughout each module and the whole integrated system, enhanced process integration technology is employed. It basically incorporates two core basic technologies: exergy recovery and process integration. Several operating parameters including target moisture content in drying module, operating pressure in chemical looping module, are observed in terms of their influence to energy efficiency. From process modeling and calculation, two integrated systems can realize high total energy efficiency, higher than 60%. However, the system employing coal direct chemical looping represents higher energy efficiency, including hydrogen production and power generation, which is about 83%. In addition, optimum target moisture content in drying and operating pressure in chemical looping also have been defined.

Exact subthreshold integration with continuous spike times in discrete-time neural network simulations.

PubMed

Morrison, Abigail; Straube, Sirko; Plesser, Hans Ekkehard; Diesmann, Markus

2007-01-01

Very large networks of spiking neurons can be simulated efficiently in parallel under the constraint that spike times are bound to an equidistant time grid. Within this scheme, the subthreshold dynamics of a wide class of integrate-and-fire-type neuron models can be integrated exactly from one grid point to the next. However, the loss in accuracy caused by restricting spike times to the grid can have undesirable consequences, which has led to interest in interpolating spike times between the grid points to retrieve an adequate representation of network dynamics. We demonstrate that the exact integration scheme can be combined naturally with off-grid spike events found by interpolation. We show that by exploiting the existence of a minimal synaptic propagation delay, the need for a central event queue is removed, so that the precision of event-driven simulation on the level of single neurons is combined with the efficiency of time-driven global scheduling. Further, for neuron models with linear subthreshold dynamics, even local event queuing can be avoided, resulting in much greater efficiency on the single-neuron level. These ideas are exemplified by two implementations of a widely used neuron model. We present a measure for the efficiency of network simulations in terms of their integration error and show that for a wide range of input spike rates, the novel techniques we present are both more accurate and faster than standard techniques.

Middle and long-term prediction of UT1-UTC based on combination of Gray Model and Autoregressive Integrated Moving Average

NASA Astrophysics Data System (ADS)

Jia, Song; Xu, Tian-he; Sun, Zhang-zhen; Li, Jia-jing

2017-02-01

UT1-UTC is an important part of the Earth Orientation Parameters (EOP). The high-precision predictions of UT1-UTC play a key role in practical applications of deep space exploration, spacecraft tracking and satellite navigation and positioning. In this paper, a new prediction method with combination of Gray Model (GM(1, 1)) and Autoregressive Integrated Moving Average (ARIMA) is developed. The main idea is as following. Firstly, the UT1-UTC data are preprocessed by removing the leap second and Earth's zonal harmonic tidal to get UT1R-TAI data. Periodic terms are estimated and removed by the least square to get UT2R-TAI. Then the linear terms of UT2R-TAI data are modeled by the GM(1, 1), and the residual terms are modeled by the ARIMA. Finally, the UT2R-TAI prediction can be performed based on the combined model of GM(1, 1) and ARIMA, and the UT1-UTC predictions are obtained by adding the corresponding periodic terms, leap second correction and the Earth's zonal harmonic tidal correction. The results show that the proposed model can be used to predict UT1-UTC effectively with higher middle and long-term (from 32 to 360 days) accuracy than those of LS + AR, LS + MAR and WLS + MAR.

Thinking about Faculty

ERIC Educational Resources Information Center

Light, Donald, Jr.

1974-01-01

Research and teaching do not integrate easily. There have been alternate models for higher education which did not rely on this combination. Restructuring the academic professions to conform with the reality of academic life can be accomplished by accepting an alternate model such as that of the good undergraduate teacher. (JH)

Integration of pavement cracking prediction model with asset management and vehicle-infrastructure interaction models.

DOT National Transportation Integrated Search

2015-01-01

Not long after the construction of a pavement or a new pavement surface, various : forms of deterioration begin to accumulate due to the harsh effects of traffic loading : combined with weathering action. In a recent NEXTRANS project, a pavement crac...

An approach to developing an integrated pyroprocessing simulator

NASA Astrophysics Data System (ADS)

Lee, Hyo Jik; Ko, Won Il; Choi, Sung Yeol; Kim, Sung Ki; Kim, In Tae; Lee, Han Soo

2014-02-01

Pyroprocessing has been studied for a decade as one of the promising fuel recycling options in Korea. We have built a pyroprocessing integrated inactive demonstration facility (PRIDE) to assess the feasibility of integrated pyroprocessing technology and scale-up issues of the processing equipment. Even though such facility cannot be replaced with a real integrated facility using spent nuclear fuel (SF), many insights can be obtained in terms of the world's largest integrated pyroprocessing operation. In order to complement or overcome such limited test-based research, a pyroprocessing Modelling and simulation study began in 2011. The Korea Atomic Energy Research Institute (KAERI) suggested a Modelling architecture for the development of a multi-purpose pyroprocessing simulator consisting of three-tiered models: unit process, operation, and plant-level-model. The unit process model can be addressed using governing equations or empirical equations as a continuous system (CS). In contrast, the operation model describes the operational behaviors as a discrete event system (DES). The plant-level model is an integrated model of the unit process and an operation model with various analysis modules. An interface with different systems, the incorporation of different codes, a process-centered database design, and a dynamic material flow are discussed as necessary components for building a framework of the plant-level model. As a sample model that contains methods decoding the above engineering issues was thoroughly reviewed, the architecture for building the plant-level-model was verified. By analyzing a process and operation-combined model, we showed that the suggested approach is effective for comprehensively understanding an integrated dynamic material flow. This paper addressed the current status of the pyroprocessing Modelling and simulation activity at KAERI, and also predicted its path forward.

An approach to developing an integrated pyroprocessing simulator

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

Lee, Hyo Jik; Ko, Won Il; Choi, Sung Yeol

Pyroprocessing has been studied for a decade as one of the promising fuel recycling options in Korea. We have built a pyroprocessing integrated inactive demonstration facility (PRIDE) to assess the feasibility of integrated pyroprocessing technology and scale-up issues of the processing equipment. Even though such facility cannot be replaced with a real integrated facility using spent nuclear fuel (SF), many insights can be obtained in terms of the world's largest integrated pyroprocessing operation. In order to complement or overcome such limited test-based research, a pyroprocessing Modelling and simulation study began in 2011. The Korea Atomic Energy Research Institute (KAERI) suggestedmore » a Modelling architecture for the development of a multi-purpose pyroprocessing simulator consisting of three-tiered models: unit process, operation, and plant-level-model. The unit process model can be addressed using governing equations or empirical equations as a continuous system (CS). In contrast, the operation model describes the operational behaviors as a discrete event system (DES). The plant-level model is an integrated model of the unit process and an operation model with various analysis modules. An interface with different systems, the incorporation of different codes, a process-centered database design, and a dynamic material flow are discussed as necessary components for building a framework of the plant-level model. As a sample model that contains methods decoding the above engineering issues was thoroughly reviewed, the architecture for building the plant-level-model was verified. By analyzing a process and operation-combined model, we showed that the suggested approach is effective for comprehensively understanding an integrated dynamic material flow. This paper addressed the current status of the pyroprocessing Modelling and simulation activity at KAERI, and also predicted its path forward.« less

Modeling the Energy Use of a Connected and Automated Transportation System (Poster)

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

Gonder, J.; Brown, A.

Early research points to large potential impacts of connected and automated vehicles (CAVs) on transportation energy use - dramatic savings, increased use, or anything in between. Due to a lack of suitable data and integrated modeling tools to explore these complex future systems, analyses to date have relied on simple combinations of isolated effects. This poster proposes a framework for modeling the potential energy implications from increasing penetration of CAV technologies and for assessing technology and policy options to steer them toward favorable energy outcomes. Current CAV modeling challenges include estimating behavior change, understanding potential vehicle-to-vehicle interactions, and assessing trafficmore » flow and vehicle use under different automation scenarios. To bridge these gaps and develop a picture of potential future automated systems, NREL is integrating existing modeling capabilities with additional tools and data inputs to create a more fully integrated CAV assessment toolkit.« less

An Outline of a Proposed Five- plus Three-Year Combined Undergraduate-Master's Degree for Clinical Medicine Majors at Nanjing Medical University

ERIC Educational Resources Information Center

Gao, Xing-Ya; Yu, Rong-Bin; Shen, Hong-Bing; Chen, Qi

2014-01-01

To build an effective model to train excellent doctors, Nanjing Medical University has proposed a five- plus three-year combined undergraduate-master's clinical medicine degree program. The program integrates undergraduate education, the education of research students, and standardized doctor residency training into a single system, allowing…

Piloted Evaluation of an Integrated Methodology for Propulsion and Airframe Control Design

NASA Technical Reports Server (NTRS)

Bright, Michelle M.; Simon, Donald L.; Garg, Sanjay; Mattern, Duane L.; Ranaudo, Richard J.; Odonoghue, Dennis P.

1994-01-01

An integrated methodology for propulsion and airframe control has been developed and evaluated for a Short Take-Off Vertical Landing (STOVL) aircraft using a fixed base flight simulator at NASA Lewis Research Center. For this evaluation the flight simulator is configured for transition flight using a STOVL aircraft model, a full nonlinear turbofan engine model, simulated cockpit and displays, and pilot effectors. The paper provides a brief description of the simulation models, the flight simulation environment, the displays and symbology, the integrated control design, and the piloted tasks used for control design evaluation. In the simulation, the pilots successfully completed typical transition phase tasks such as combined constant deceleration with flight path tracking, and constant acceleration wave-off maneuvers. The pilot comments of the integrated system performance and the display symbology are discussed and analyzed to identify potential areas of improvement.

Bayesian Cue Integration as a Developmental Outcome of Reward Mediated Learning

PubMed Central

Weisswange, Thomas H.; Rothkopf, Constantin A.; Rodemann, Tobias; Triesch, Jochen

2011-01-01

Average human behavior in cue combination tasks is well predicted by Bayesian inference models. As this capability is acquired over developmental timescales, the question arises, how it is learned. Here we investigated whether reward dependent learning, that is well established at the computational, behavioral, and neuronal levels, could contribute to this development. It is shown that a model free reinforcement learning algorithm can indeed learn to do cue integration, i.e. weight uncertain cues according to their respective reliabilities and even do so if reliabilities are changing. We also consider the case of causal inference where multimodal signals can originate from one or multiple separate objects and should not always be integrated. In this case, the learner is shown to develop a behavior that is closest to Bayesian model averaging. We conclude that reward mediated learning could be a driving force for the development of cue integration and causal inference. PMID:21750717

Integrating Identity Management With Federated Healthcare Data Models

NASA Astrophysics Data System (ADS)

Hu, Jun; Peyton, Liam

In order to manage performance and provide integrated services, health care data needs to be linked and aggregated across data sources from different organizations. The Internet and secure B2B networks offer the possibility of providing near real-time integration. However, there are three major stumbling blocks. One is to standardize and agree upon a common data model across organizations. The second is to match identities between different locations in order to link and aggregate records. The third is to protect identity and ensure compliance with privacy laws. In this paper, we analyze three main approaches to the problem and use a healthcare scenario to illustrate how each one addresses different aspects of the problem while failing to address others. We then present a systematic framework in which the different approaches can be flexibly combined for a more comprehensive approach to integrate identity management with federated healthcare data models.

Experiences Integrating Transmission and Distribution Simulations for DERs with the Integrated Grid Modeling System (IGMS)

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

Palmintier, Bryan; Hale, Elaine; Hodge, Bri-Mathias

2016-08-11

This paper discusses the development of, approaches for, experiences with, and some results from a large-scale, high-performance-computer-based (HPC-based) co-simulation of electric power transmission and distribution systems using the Integrated Grid Modeling System (IGMS). IGMS was developed at the National Renewable Energy Laboratory (NREL) as a novel Independent System Operator (ISO)-to-appliance scale electric power system modeling platform that combines off-the-shelf tools to simultaneously model 100s to 1000s of distribution systems in co-simulation with detailed ISO markets, transmission power flows, and AGC-level reserve deployment. Lessons learned from the co-simulation architecture development are shared, along with a case study that explores the reactivemore » power impacts of PV inverter voltage support on the bulk power system.« less

An Optimized Integrator Windup Protection Technique Applied to a Turbofan Engine Control

NASA Technical Reports Server (NTRS)

Watts, Stephen R.; Garg, Sanjay

1995-01-01

This paper introduces a new technique for providing memoryless integrator windup protection which utilizes readily available optimization software tools. This integrator windup protection synthesis provides a concise methodology for creating integrator windup protection for each actuation system loop independently while assuring both controller and closed loop system stability. The individual actuation system loops' integrator windup protection can then be combined to provide integrator windup protection for the entire system. This technique is applied to an H(exp infinity) based multivariable control designed for a linear model of an advanced afterburning turbofan engine. The resulting transient characteristics are examined for the integrated system while encountering single and multiple actuation limits.

Integrated communications and optical navigation system

NASA Astrophysics Data System (ADS)

Mueller, J.; Pajer, G.; Paluszek, M.

2013-12-01

The Integrated Communications and Optical Navigation System (ICONS) is a flexible navigation system for spacecraft that does not require global positioning system (GPS) measurements. The navigation solution is computed using an Unscented Kalman Filter (UKF) that can accept any combination of range, range-rate, planet chord width, landmark, and angle measurements using any celestial object. Both absolute and relative orbit determination is supported. The UKF employs a full nonlinear dynamical model of the orbit including gravity models and disturbance models. The ICONS package also includes attitude determination algorithms using the UKF algorithm with the Inertial Measurement Unit (IMU). The IMU is used as the dynamical base for the attitude determination algorithms. This makes the sensor a more capable plug-in replacement for a star tracker, thus reducing the integration and test cost of adding this sensor to a spacecraft. Recent additions include an integrated optical communications system which adds communications, and integrated range and range rate measurement and timing. The paper includes test results from trajectories based on the NASA New Horizons spacecraft.

Optimisation potential for a SBR plant based upon integrated modelling for dry and wet weather conditions.

PubMed

Rönner-Holm, S G E; Kaufmann Alves, I; Steinmetz, H; Holm, N C

2009-01-01

Integrated dynamic simulation analysis of a full-scale municipal sequential batch reactor (SBR) wastewater treatment plant (WWTP) was performed using the KOSMO pollution load simulation model for the combined sewer system (CSS) and the ASM3 + EAWAG-BioP model for the WWTP. Various optimising strategies for dry and storm weather conditions were developed to raise the purification and hydraulic performance and to reduce operation costs based on simulation studies with the calibrated WWTP model. The implementation of some strategies on the plant led to lower effluent values and an average annual saving of 49,000 euro including sewage tax, which is 22% of the total running costs. Dynamic simulation analysis of CSS for an increased WWTP influent over a period of one year showed high potentials for reducing combined sewer overflow (CSO) volume by 18-27% and CSO loads for COD by 22%, NH(4)-N and P(total) by 33%. In addition, the SBR WWTP could easily handle much higher influents without exceeding the monitoring values. During the integrated simulation of representative storm events, the total emission load for COD dropped to 90%, the sewer system emitted 47% less, whereas the pollution load in the WWTP effluent increased to only 14% with 2% higher running costs.

Young LMC clusters: the role of red supergiants and multiple stellar populations in their integrated light and CMDs

NASA Astrophysics Data System (ADS)

Asa'd, Randa S.; Vazdekis, Alexandre; Cerviño, Miguel; Noël, Noelia E. D.; Beasley, Michael A.; Kassab, Mahmoud

2017-11-01

The optical integrated spectra of three Large Magellanic Cloud young stellar clusters (NGC 1984, NGC 1994 and NGC 2011) exhibit concave continua and prominent molecular bands which deviate significantly from the predictions of single stellar population (SSP) models. In order to understand the appearance of these spectra, we create a set of young stellar population (MILES) models, which we make available to the community. We use archival International Ultraviolet Explorer integrated UV spectra to independently constrain the cluster masses and extinction, and rule out strong stochastic effects in the optical spectra. In addition, we also analyse deep colour-magnitude diagrams of the clusters to provide independent age determinations based on isochrone fitting. We explore hypotheses, including age spreads in the clusters, a top-heavy initial mass function, different SSP models and the role of red supergiant stars (RSG). We find that the strong molecular features in the optical spectra can be only reproduced by modelling an increased fraction of about ˜20 per cent by luminosity of RSG above what is predicted by canonical stellar evolution models. Given the uncertainties in stellar evolution at Myr ages, we cannot presently rule out the presence of Myr age spreads in these clusters. Our work combines different wavelengths as well as different approaches (resolved data as well as integrated spectra for the same sample) in order to reveal the complete picture. We show that each approach provides important information but in combination we can better understand the cluster stellar populations.

Combining inferred regulatory and reconstructed metabolic networks enhances phenotype prediction in yeast.

PubMed

Wang, Zhuo; Danziger, Samuel A; Heavner, Benjamin D; Ma, Shuyi; Smith, Jennifer J; Li, Song; Herricks, Thurston; Simeonidis, Evangelos; Baliga, Nitin S; Aitchison, John D; Price, Nathan D

2017-05-01

Gene regulatory and metabolic network models have been used successfully in many organisms, but inherent differences between them make networks difficult to integrate. Probabilistic Regulation Of Metabolism (PROM) provides a partial solution, but it does not incorporate network inference and underperforms in eukaryotes. We present an Integrated Deduced And Metabolism (IDREAM) method that combines statistically inferred Environment and Gene Regulatory Influence Network (EGRIN) models with the PROM framework to create enhanced metabolic-regulatory network models. We used IDREAM to predict phenotypes and genetic interactions between transcription factors and genes encoding metabolic activities in the eukaryote, Saccharomyces cerevisiae. IDREAM models contain many fewer interactions than PROM and yet produce significantly more accurate growth predictions. IDREAM consistently outperformed PROM using any of three popular yeast metabolic models and across three experimental growth conditions. Importantly, IDREAM's enhanced accuracy makes it possible to identify subtle synthetic growth defects. With experimental validation, these novel genetic interactions involving the pyruvate dehydrogenase complex suggested a new role for fatty acid-responsive factor Oaf1 in regulating acetyl-CoA production in glucose grown cells.

Integrating E-Learning into the Direct-Instruction Model to Enhance the Effectiveness of Critical-Thinking Instruction

ERIC Educational Resources Information Center

Yeh, Yu-Chu

2009-01-01

The "Direct-instruction Model" favors the use of teacher explanations and modeling combined with student practice and feedback to teach thinking skills. Using this paradigm, this study incorporates e-learning during an 18-week experimental instruction period that includes 48 preservice teachers. The instructional design in this study emphasizes…

A Comparative Study of Cooperative Education and Work-Integrated Learning in Germany, South Africa, and Namibia

ERIC Educational Resources Information Center

Reinhard, Karin; Pogrzeba, Anna; Townsend, Rosemary; Pop, Carver Albertus

2016-01-01

The Baden-Wuerttemberg Cooperative State University was the first higher education institution in Germany to combine on-the-job training and academic studies. The study model integrates theory and practice, both being components of cooperative education. The success of this university is based on its cooperation with over 10,000 companies.…

Optimized acoustic biochip integrated with microfluidics for biomarkers detection in molecular diagnostics.

PubMed

Papadakis, G; Friedt, J M; Eck, M; Rabus, D; Jobst, G; Gizeli, E

2017-09-01

The development of integrated platforms incorporating an acoustic device as the detection element requires addressing simultaneously several challenges of technological and scientific nature. The present work was focused on the design of a microfluidic module, which, combined with a dual or array type Love wave acoustic chip could be applied to biomedical applications and molecular diagnostics. Based on a systematic study we optimized the mechanics of the flow cell attachment and the sealing material so that fluidic interfacing/encapsulation would impose minimal losses to the acoustic wave. We have also investigated combinations of operating frequencies with waveguide materials and thicknesses for maximum sensitivity during the detection of protein and DNA biomarkers. Within our investigations neutravidin was used as a model protein biomarker and unpurified PCR amplified Salmonella DNA as the model genetic target. Our results clearly indicate the need for experimental verification of the optimum engineering and analytical parameters, in order to develop commercially viable systems for integrated analysis. The good reproducibility of the signal together with the ability of the array biochip to detect multiple samples hold promise for the future use of the integrated system in a Lab-on-a-Chip platform for application to molecular diagnostics.

Integrated presentation of ecological risk from multiple stressors

PubMed Central

Goussen, Benoit; Price, Oliver R.; Rendal, Cecilie; Ashauer, Roman

2016-01-01

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic. PMID:27782171

Miscibility and Thermodynamics of Mixing of Different Models of Formamide and Water in Computer Simulation.

PubMed

Kiss, Bálint; Fábián, Balázs; Idrissi, Abdenacer; Szőri, Milán; Jedlovszky, Pál

2017-07-27

The thermodynamic changes that occur upon mixing five models of formamide and three models of water, including the miscibility of these model combinations itself, is studied by performing Monte Carlo computer simulations using an appropriately chosen thermodynamic cycle and the method of thermodynamic integration. The results show that the mixing of these two components is close to the ideal mixing, as both the energy and entropy of mixing turn out to be rather close to the ideal term in the entire composition range. Concerning the energy of mixing, the OPLS/AA_mod model of formamide behaves in a qualitatively different way than the other models considered. Thus, this model results in negative, while the other ones in positive energy of mixing values in combination with all three water models considered. Experimental data supports this latter behavior. Although the Helmholtz free energy of mixing always turns out to be negative in the entire composition range, the majority of the model combinations tested either show limited miscibility, or, at least, approach the miscibility limit very closely in certain compositions. Concerning both the miscibility and the energy of mixing of these model combinations, we recommend the use of the combination of the CHARMM formamide and TIP4P water models in simulations of water-formamide mixtures.

Integrated surface/subsurface permafrost thermal hydrology: Model formulation and proof-of-concept simulations

DOE PAGES

Painter, Scott L.; Coon, Ethan T.; Atchley, Adam L.; ...

2016-08-11

The need to understand potential climate impacts and feedbacks in Arctic regions has prompted recent interest in modeling of permafrost dynamics in a warming climate. A new fine-scale integrated surface/subsurface thermal hydrology modeling capability is described and demonstrated in proof-of-concept simulations. The new modeling capability combines a surface energy balance model with recently developed three-dimensional subsurface thermal hydrology models and new models for nonisothermal surface water flows and snow distribution in the microtopography. Surface water flows are modeled using the diffusion wave equation extended to include energy transport and phase change of ponded water. Variation of snow depth in themore » microtopography, physically the result of wind scour, is also modeled heuristically with a diffusion wave equation. The multiple surface and subsurface processes are implemented by leveraging highly parallel community software. Fully integrated thermal hydrology simulations on the tilted open book catchment, an important test case for integrated surface/subsurface flow modeling, are presented. Fine-scale 100-year projections of the integrated permafrost thermal hydrological system on an ice wedge polygon at Barrow Alaska in a warming climate are also presented. Finally, these simulations demonstrate the feasibility of microtopography-resolving, process-rich simulations as a tool to help understand possible future evolution of the carbon-rich Arctic tundra in a warming climate.« less

Combining observations in the reflective solar and thermal domains for improved mapping of carbon, water and energy fluxes

USDA-ARS?s Scientific Manuscript database

The REGularized canopy reFLECtance (REGFLEC) modeling tool integrates leaf optics, canopy reflectance, and atmospheric radiative transfer model components, facilitating accurate retrieval of leaf area index (LAI) and leaf chlorophyll content (Cab) directly from at-sensor radiances in green, red and ...

Genetic Programming for Automatic Hydrological Modelling

NASA Astrophysics Data System (ADS)

Chadalawada, Jayashree; Babovic, Vladan

2017-04-01

One of the recent challenges for the hydrologic research community is the need for the development of coupled systems that involves the integration of hydrologic, atmospheric and socio-economic relationships. This poses a requirement for novel modelling frameworks that can accurately represent complex systems, given, the limited understanding of underlying processes, increasing volume of data and high levels of uncertainity. Each of the existing hydrological models vary in terms of conceptualization and process representation and is the best suited to capture the environmental dynamics of a particular hydrological system. Data driven approaches can be used in the integration of alternative process hypotheses in order to achieve a unified theory at catchment scale. The key steps in the implementation of integrated modelling framework that is influenced by prior understanding and data, include, choice of the technique for the induction of knowledge from data, identification of alternative structural hypotheses, definition of rules, constraints for meaningful, intelligent combination of model component hypotheses and definition of evaluation metrics. This study aims at defining a Genetic Programming based modelling framework that test different conceptual model constructs based on wide range of objective functions and evolves accurate and parsimonious models that capture dominant hydrological processes at catchment scale. In this paper, GP initializes the evolutionary process using the modelling decisions inspired from the Superflex framework [Fenicia et al., 2011] and automatically combines them into model structures that are scrutinized against observed data using statistical, hydrological and flow duration curve based performance metrics. The collaboration between data driven and physical, conceptual modelling paradigms improves the ability to model and manage hydrologic systems. Fenicia, F., D. Kavetski, and H. H. Savenije (2011), Elements of a flexible approach for conceptual hydrological modeling: 1. Motivation and theoretical development, Water Resources Research, 47(11).

Architectural approaches for HL7-based health information systems implementation.

PubMed

López, D M; Blobel, B

2010-01-01

Information systems integration is hard, especially when semantic and business process interoperability requirements need to be met. To succeed, a unified methodology, approaching different aspects of systems architecture such as business, information, computational, engineering and technology viewpoints, has to be considered. The paper contributes with an analysis and demonstration on how the HL7 standard set can support health information systems integration. Based on the Health Information Systems Development Framework (HIS-DF), common architectural models for HIS integration are analyzed. The framework is a standard-based, consistent, comprehensive, customizable, scalable methodology that supports the design of semantically interoperable health information systems and components. Three main architectural models for system integration are analyzed: the point to point interface, the messages server and the mediator models. Point to point interface and messages server models are completely supported by traditional HL7 version 2 and version 3 messaging. The HL7 v3 standard specification, combined with service-oriented, model-driven approaches provided by HIS-DF, makes the mediator model possible. The different integration scenarios are illustrated by describing a proof-of-concept implementation of an integrated public health surveillance system based on Enterprise Java Beans technology. Selecting the appropriate integration architecture is a fundamental issue of any software development project. HIS-DF provides a unique methodological approach guiding the development of healthcare integration projects. The mediator model - offered by the HIS-DF and supported in HL7 v3 artifacts - is the more promising one promoting the development of open, reusable, flexible, semantically interoperable, platform-independent, service-oriented and standard-based health information systems.

Model-Based Systems

NASA Technical Reports Server (NTRS)

Frisch, Harold P.

2007-01-01

Engineers, who design systems using text specification documents, focus their work upon the completed system to meet Performance, time and budget goals. Consistency and integrity is difficult to maintain within text documents for a single complex system and more difficult to maintain as several systems are combined into higher-level systems, are maintained over decades, and evolve technically and in performance through updates. This system design approach frequently results in major changes during the system integration and test phase, and in time and budget overruns. Engineers who build system specification documents within a model-based systems environment go a step further and aggregate all of the data. They interrelate all of the data to insure consistency and integrity. After the model is constructed, the various system specification documents are prepared, all from the same database. The consistency and integrity of the model is assured, therefore the consistency and integrity of the various specification documents is insured. This article attempts to define model-based systems relative to such an environment. The intent is to expose the complexity of the enabling problem by outlining what is needed, why it is needed and how needs are being addressed by international standards writing teams.

A framework for understanding outcomes of integrated care programs for the hospitalised elderly

PubMed Central

Hartgerink, Jacqueline M.; Cramm, Jane M.; van Wijngaarden, Jeroen D.H.; Bakker, Ton J.E.M.; Mackenbach, Johan P.; Nieboer, Anna P.

2013-01-01

Introduction Integrated care has emerged as a new strategy to enhance the quality of care for hospitalised elderly. Current models do not provide insight into the mechanisms underlying integrated care delivery. Therefore, we developed a framework to identify the underlying mechanisms of integrated care delivery. We should understand how they operate and interact, so that integrated care programmes can enhance the quality of care and eventually patient outcomes. Theory and methods Interprofessional collaboration among professionals is considered to be critical in integrated care delivery due to many interdependent work requirements. A review of integrated care components brings to light a distinction between the cognitive and behavioural components of interprofessional collaboration. Results Effective integrated care programmes combine the interacting components of care delivery. These components affect professionals’ cognitions and behaviour, which in turn affect quality of care. Insight is gained into how these components alter the way care is delivered through mechanisms such as combining individual knowledge and actively seeking new information. Conclusion We expect that insight into the cognitive and behavioural mechanisms will contribute to the understanding of integrated care programmes. The framework can be used to identify the underlying mechanisms of integrated care responsible for producing favourable outcomes, allowing comparisons across programmes. PMID:24363635

Causal Evidence for a Mechanism of Semantic Integration in the Angular Gyrus as Revealed by High-Definition Transcranial Direct Current Stimulation

PubMed Central

Peelle, Jonathan E.; Bonner, Michael F.; Grossman, Murray

2016-01-01

A defining aspect of human cognition is the ability to integrate conceptual information into complex semantic combinations. For example, we can comprehend “plaid” and “jacket” as individual concepts, but we can also effortlessly combine these concepts to form the semantic representation of “plaid jacket.” Many neuroanatomic models of semantic memory propose that heteromodal cortical hubs integrate distributed semantic features into coherent representations. However, little work has specifically examined these proposed integrative mechanisms and the causal role of these regions in semantic integration. Here, we test the hypothesis that the angular gyrus (AG) is critical for integrating semantic information by applying high-definition transcranial direct current stimulation (tDCS) to an fMRI-guided region-of-interest in the left AG. We found that anodal stimulation to the left AG modulated semantic integration but had no effect on a letter-string control task. Specifically, anodal stimulation to the left AG resulted in faster comprehension of semantically meaningful combinations like “tiny radish” relative to non-meaningful combinations, such as “fast blueberry,” when compared to the effects observed during sham stimulation and stimulation to a right-hemisphere control brain region. Moreover, the size of the effect from brain stimulation correlated with the degree of semantic coherence between the word pairs. These findings demonstrate that the left AG plays a causal role in the integration of lexical-semantic information, and that high-definition tDCS to an associative cortical hub can selectively modulate integrative processes in semantic memory. SIGNIFICANCE STATEMENT A major goal of neuroscience is to understand the neural basis of behaviors that are fundamental to human intelligence. One essential behavior is the ability to integrate conceptual knowledge from semantic memory, allowing us to construct an almost unlimited number of complex concepts from a limited set of basic constituents (e.g., “leaf” and “wet” can be combined into the more complex representation “wet leaf”). Here, we present a novel approach to studying integrative processes in semantic memory by applying focal brain stimulation to a heteromodal cortical hub implicated in semantic processing. Our findings demonstrate a causal role of the left angular gyrus in lexical-semantic integration and provide motivation for novel therapeutic applications in patients with lexical-semantic deficits. PMID:27030767

Causal Evidence for a Mechanism of Semantic Integration in the Angular Gyrus as Revealed by High-Definition Transcranial Direct Current Stimulation.

PubMed

Price, Amy Rose; Peelle, Jonathan E; Bonner, Michael F; Grossman, Murray; Hamilton, Roy H

2016-03-30

A defining aspect of human cognition is the ability to integrate conceptual information into complex semantic combinations. For example, we can comprehend "plaid" and "jacket" as individual concepts, but we can also effortlessly combine these concepts to form the semantic representation of "plaid jacket." Many neuroanatomic models of semantic memory propose that heteromodal cortical hubs integrate distributed semantic features into coherent representations. However, little work has specifically examined these proposed integrative mechanisms and the causal role of these regions in semantic integration. Here, we test the hypothesis that the angular gyrus (AG) is critical for integrating semantic information by applying high-definition transcranial direct current stimulation (tDCS) to an fMRI-guided region-of-interest in the left AG. We found that anodal stimulation to the left AG modulated semantic integration but had no effect on a letter-string control task. Specifically, anodal stimulation to the left AG resulted in faster comprehension of semantically meaningful combinations like "tiny radish" relative to non-meaningful combinations, such as "fast blueberry," when compared to the effects observed during sham stimulation and stimulation to a right-hemisphere control brain region. Moreover, the size of the effect from brain stimulation correlated with the degree of semantic coherence between the word pairs. These findings demonstrate that the left AG plays a causal role in the integration of lexical-semantic information, and that high-definition tDCS to an associative cortical hub can selectively modulate integrative processes in semantic memory. A major goal of neuroscience is to understand the neural basis of behaviors that are fundamental to human intelligence. One essential behavior is the ability to integrate conceptual knowledge from semantic memory, allowing us to construct an almost unlimited number of complex concepts from a limited set of basic constituents (e.g., "leaf" and "wet" can be combined into the more complex representation "wet leaf"). Here, we present a novel approach to studying integrative processes in semantic memory by applying focal brain stimulation to a heteromodal cortical hub implicated in semantic processing. Our findings demonstrate a causal role of the left angular gyrus in lexical-semantic integration and provide motivation for novel therapeutic applications in patients with lexical-semantic deficits. Copyright © 2016 the authors 0270-6474/16/363829-10$15.00/0.

COMBINE*: An integrated opto-mechanical tool for laser performance modeling

NASA Astrophysics Data System (ADS)

Rehak, M.; Di Nicola, J. M.

2015-02-01

Accurate modeling of thermal, mechanical and optical processes is important for achieving reliable, high-performance high energy lasers such as those at the National Ignition Facility [1] (NIF). The need for this capability is even more critical for high average power, high repetition rate applications. Modeling the effects of stresses and temperature fields on optical properties allows for optimal design of optical components and more generally of the architecture of the laser system itself. Stresses change the indices of refractions and induce inhomogeneities and anisotropy. We present a modern, integrated analysis tool that efficiently produces reliable results that are used in our laser propagation tools such as VBL [5]. COMBINE is built on and supplants the existing legacy tools developed for the previous generations of lasers at LLNL but also uses commercially available mechanical finite element codes ANSYS or COMSOL (including computational fluid dynamics). The COMBINE code computes birefringence and wave front distortions due to mechanical stresses on lenses and slabs of arbitrary geometry. The stresses calculated typically originate from mounting support, vacuum load, gravity, heat absorption and/or attending cooling. Of particular importance are the depolarization and detuning effects of nonlinear crystals due to thermal loading. Results are given in the form of Jones matrices, depolarization maps and wave front distributions. An incremental evaluation of Jones matrices and ray propagation in a 3D mesh with a stress and temperature field is performed. Wavefront and depolarization maps are available at the optical aperture and at slices within the optical element. The suite is validated, user friendly, supported, documented and amenable to collaborative development. * COMBINE stands for Code for Opto-Mechanical Birefringence Integrated Numerical Evaluations.

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

Mohanty, Subhasish; Majumdar, Saurindranath

Irradiation creep plays a major role in the structural integrity of the graphite components in high temperature gas cooled reactors. Finite element procedures combined with a suitable irradiation creep model can be used to simulate the time-integrated structural integrity of complex shapes, such as the reactor core graphite reflector and fuel bricks. In the present work a comparative study was undertaken to understand the effect of linear and nonlinear irradiation creep on results of finite element based stress analysis. Numerical results were generated through finite element simulations of a typical graphite reflector.

Evaluation of parallel reduction strategies for fusion of sensory information from a robot team

NASA Astrophysics Data System (ADS)

Lyons, Damian M.; Leroy, Joseph

2015-05-01

The advantage of using a team of robots to search or to map an area is that by navigating the robots to different parts of the area, searching or mapping can be completed more quickly. A crucial aspect of the problem is the combination, or fusion, of data from team members to generate an integrated model of the search/mapping area. In prior work we looked at the issue of removing mutual robots views from an integrated point cloud model built from laser and stereo sensors, leading to a cleaner and more accurate model. This paper addresses a further challenge: Even with mutual views removed, the stereo data from a team of robots can quickly swamp a WiFi connection. This paper proposes and evaluates a communication and fusion approach based on the parallel reduction operation, where data is combined in a series of steps of increasing subsets of the team. Eight different strategies for selecting the subsets are evaluated for bandwidth requirements using three robot missions, each carried out with teams of four Pioneer 3-AT robots. Our results indicate that selecting groups to combine based on similar pose but distant location yields the best results.

Dynamic modeling and simulation of an integral bipropellant propulsion double-valve combined test system

NASA Astrophysics Data System (ADS)

Chen, Yang; Wang, Huasheng; Xia, Jixia; Cai, Guobiao; Zhang, Zhenpeng

2017-04-01

For the pressure reducing regulator and check valve double-valve combined test system in an integral bipropellant propulsion system, a system model is established with modular models of various typical components. The simulation research is conducted on the whole working process of an experiment of 9 MPa working condition from startup to rated working condition and finally to shutdown. Comparison of simulation results with test data shows: five working conditions including standby, startup, rated pressurization, shutdown and halt and nine stages of the combined test system are comprehensively disclosed; valve-spool opening and closing details of the regulator and two check valves are accurately revealed; the simulation also clarifies two phenomena which test data are unable to clarify, one is the critical opening state in which the check valve spools slightly open and close alternately in their own fully closed positions, the other is the obvious effects of flow-field temperature drop and temperature rise in pipeline network with helium gas flowing. Moreover, simulation results with consideration of component wall heat transfer are closer to the test data than those under the adiabatic-wall condition, and more able to reveal the dynamic characteristics of the system in various working stages.

[Traceability of Wine Varieties Using Near Infrared Spectroscopy Combined with Cyclic Voltammetry].

PubMed

Li, Meng-hua; Li, Jing-ming; Li, Jun-hui; Zhang, Lu-da; Zhao, Long-lian

2015-06-01

To achieve the traceability of wine varieties, a method was proposed to fuse Near-infrared (NIR) spectra and cyclic voltammograms (CV) which contain different information using D-S evidence theory. NIR spectra and CV curves of three different varieties of wines (cabernet sauvignon, merlot, cabernet gernischt) which come from seven different geographical origins were collected separately. The discriminant models were built using PLS-DA method. Based on this, D-S evidence theory was then applied to achieve the integration of the two kinds of discrimination results. After integrated by D-S evidence theory, the accuracy rate of cross-validation is 95.69% and validation set is 94.12% for wine variety identification. When only considering the wine that come from Yantai, the accuracy rate of cross-validation is 99.46% and validation set is 100%. All the traceability models after fusion achieved better results on classification than individual method. These results suggest that the proposed method combining electrochemical information with spectral information using the D-S evidence combination formula is benefit to the improvement of model discrimination effect, and is a promising tool for discriminating different kinds of wines.

Lessons learned while integrating habitat, dispersal, disturbance, and life-history traits into species habitat models under climate change

Treesearch

Louis R. Iverson; Anantha M. Prasad; Stephen N. Matthews; Matthew P. Peters

2011-01-01

We present an approach to modeling potential climate-driven changes in habitat for tree and bird species in the eastern United States. First, we took an empirical-statistical modeling approach, using randomForest, with species abundance data from national inventories combined with soil, climate, and landscape variables, to build abundance-based habitat models for 134...

Development of the AFRL Aircrew Perfomance and Protection Data Bank

DTIC Science & Technology

2007-12-01

Growth model and statistical model of hypobaric chamber simulations. It offers a quick and readily accessible online DCS risk assessment tool for...are used for the DCS prediction instead of the original model. ADRAC is based on more than 20 years of hypobaric chamber studies using human...prediction based on the combined Bubble Growth model and statistical model of hypobaric chamber simulations was integrated into the Data Bank. It

Kinematic Structural Modelling in Bayesian Networks

NASA Astrophysics Data System (ADS)

Schaaf, Alexander; de la Varga, Miguel; Florian Wellmann, J.

2017-04-01

We commonly capture our knowledge about the spatial distribution of distinct geological lithologies in the form of 3-D geological models. Several methods exist to create these models, each with its own strengths and limitations. We present here an approach to combine the functionalities of two modeling approaches - implicit interpolation and kinematic modelling methods - into one framework, while explicitly considering parameter uncertainties and thus model uncertainty. In recent work, we proposed an approach to implement implicit modelling algorithms into Bayesian networks. This was done to address the issues of input data uncertainty and integration of geological information from varying sources in the form of geological likelihood functions. However, one general shortcoming of implicit methods is that they usually do not take any physical constraints into consideration, which can result in unrealistic model outcomes and artifacts. On the other hand, kinematic structural modelling intends to reconstruct the history of a geological system based on physically driven kinematic events. This type of modelling incorporates simplified, physical laws into the model, at the cost of a substantial increment of usable uncertain parameters. In the work presented here, we show an integration of these two different modelling methodologies, taking advantage of the strengths of both of them. First, we treat the two types of models separately, capturing the information contained in the kinematic models and their specific parameters in the form of likelihood functions, in order to use them in the implicit modelling scheme. We then go further and combine the two modelling approaches into one single Bayesian network. This enables the direct flow of information between the parameters of the kinematic modelling step and the implicit modelling step and links the exclusive input data and likelihoods of the two different modelling algorithms into one probabilistic inference framework. In addition, we use the capabilities of Noddy to analyze the topology of structural models to demonstrate how topological information, such as the connectivity of two layers across an unconformity, can be used as a likelihood function. In an application to a synthetic case study, we show that our approach leads to a successful combination of the two different modelling concepts. Specifically, we show that we derive ensemble realizations of implicit models that now incorporate the knowledge of the kinematic aspects, representing an important step forward in the integration of knowledge and a corresponding estimation of uncertainties in structural geological models.

Combined Treatment Effects of Radiation and Immunotherapy: Studies in an Autochthonous Prostate Cancer Model

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

Wada, Satoshi; Harris, Timothy J.; Tryggestad, Erik

2013-11-15

Purpose: To optimize the combination of ionizing radiation and cellular immunotherapy using a preclinical autochthonous model of prostate cancer. Methods and Materials: Transgenic mice expressing a model antigen under a prostate-specific promoter were treated using a platform that integrates cone-beam CT imaging with 3-dimensional conformal therapy. Using this technology we investigated the immunologic and therapeutic effects of combining ionizing radiation with granulocyte/macrophage colony-stimulating factor-secreting cellular immunotherapy for prostate cancer in mice bearing autochthonous prostate tumors. Results: The combination of ionizing radiation and immunotherapy resulted in a significant decrease in pathologic tumor grade and gross tumor bulk that was not evidentmore » with either single-modality therapy. Furthermore, combinatorial therapy resulted in improved overall survival in a preventive metastasis model and in the setting of established micrometastases. Mechanistically, combined therapy resulted in an increase of the ratio of effector-to-regulatory T cells for both CD4 and CD8 tumor-infiltrating lymphocytes. Conclusions: Our preclinical model establishes a potential role for the use of combined radiation-immunotherapy in locally advanced prostate cancer, which warrants further exploration in a clinical setting.« less

Potential of pedestrian protection systems--a parameter study using finite element models of pedestrian dummy and generic passenger vehicles.

PubMed

Fredriksson, Rikard; Shin, Jaeho; Untaroiu, Costin D

2011-08-01

To study the potential of active, passive, and integrated (combined active and passive) safety systems in reducing pedestrian upper body loading in typical impact configurations. Finite element simulations using models of generic sedan car fronts and the Polar II pedestrian dummy were performed for 3 impact configurations at 2 impact speeds. Chest contact force, head injury criterion (HIC(15)), head angular acceleration, and the cumulative strain damage measure (CSDM(0.25)) were employed as injury parameters. Further, 3 countermeasures were modeled: an active autonomous braking system, a passive deployable countermeasure, and an integrated system combining the active and passive systems. The auto-brake system was modeled by reducing impact speed by 10 km/h (equivalent to ideal full braking over 0.3 s) and introducing a pitch of 1 degree and in-crash deceleration of 1 g. The deployable system consisted of a deployable hood, lifting 100 mm in the rear, and a lower windshield air bag. All 3 countermeasures showed benefit in a majority of impact configurations in terms of injury prevention. The auto-brake system reduced chest force in a majority of the configurations and decreased HIC(15), head angular acceleration, and CSDM in all configurations. Averaging all impact configurations, the auto-brake system showed reductions of injury predictors from 20 percent (chest force) to 82 percent (HIC). The passive deployable countermeasure reduced chest force and HIC(15) in a majority of configurations and head angular acceleration and CSDM in all configurations, although the CSDM decrease in 2 configurations was minimal. On average a reduction from 20 percent (CSDM) to 58 percent (HIC) was recorded in the passive deployable countermeasures. Finally, the integrated system evaluated in this study reduced all injury assessment parameters in all configurations compared to the reference situations. The average reductions achieved by the integrated system ranged from 56 percent (CSDM) to 85 percent (HIC). Both the active (autonomous braking) and passive deployable system studied had a potential to decrease pedestrian upper body loading. An integrated pedestrian safety system combining the active and passive systems increased the potential of the individual systems in reducing pedestrian head and chest loading.

A self-resetting spiking phase-change neuron

NASA Astrophysics Data System (ADS)

Cobley, R. A.; Hayat, H.; Wright, C. D.

2018-05-01

Neuromorphic, or brain-inspired, computing applications of phase-change devices have to date concentrated primarily on the implementation of phase-change synapses. However, the so-called accumulation mode of operation inherent in phase-change materials and devices can also be used to mimic the integrative properties of a biological neuron. Here we demonstrate, using physical modelling of nanoscale devices and SPICE modelling of associated circuits, that a single phase-change memory cell integrated into a comparator type circuit can deliver a basic hardware mimic of an integrate-and-fire spiking neuron with self-resetting capabilities. Such phase-change neurons, in combination with phase-change synapses, can potentially open a new route for the realisation of all-phase-change neuromorphic computing.

An integrated approach to system design, reliability, and diagnosis

NASA Technical Reports Server (NTRS)

Patterson-Hine, F. A.; Iverson, David L.

1990-01-01

The requirement for ultradependability of computer systems in future avionics and space applications necessitates a top-down, integrated systems ingeneering approach for design, implementation, testing, and operation. The functional analyses of hardware and software systems must be combined by models that are flexible enough to represent their interactions and behavior. The information contained in these models must be accessible throughout all phases of the system life cycle in order to maintain consistency and accuracy in design and operational decisions. One approach being taken by researchers at Ames Research Center is the creation of an object-oriented environment that integrates information about system components required in the reliability evaluation with behavioral information useful for diagnostic algorithms.

A self-resetting spiking phase-change neuron.

PubMed

Cobley, R A; Hayat, H; Wright, C D

2018-05-11

Neuromorphic, or brain-inspired, computing applications of phase-change devices have to date concentrated primarily on the implementation of phase-change synapses. However, the so-called accumulation mode of operation inherent in phase-change materials and devices can also be used to mimic the integrative properties of a biological neuron. Here we demonstrate, using physical modelling of nanoscale devices and SPICE modelling of associated circuits, that a single phase-change memory cell integrated into a comparator type circuit can deliver a basic hardware mimic of an integrate-and-fire spiking neuron with self-resetting capabilities. Such phase-change neurons, in combination with phase-change synapses, can potentially open a new route for the realisation of all-phase-change neuromorphic computing.

Risk assessment of climate systems for national security.

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

Backus, George A.; Boslough, Mark Bruce Elrick; Brown, Theresa Jean

2012-10-01

Climate change, through drought, flooding, storms, heat waves, and melting Arctic ice, affects the production and flow of resource within and among geographical regions. The interactions among governments, populations, and sectors of the economy require integrated assessment based on risk, through uncertainty quantification (UQ). This project evaluated the capabilities with Sandia National Laboratories to perform such integrated analyses, as they relate to (inter)national security. The combining of the UQ results from climate models with hydrological and economic/infrastructure impact modeling appears to offer the best capability for national security risk assessments.

Cell signaling heterogeneity is modulated by both cell-intrinsic and -extrinsic mechanisms: An integrated approach to understanding targeted therapy.

PubMed

Kim, Eunjung; Kim, Jae-Young; Smith, Matthew A; Haura, Eric B; Anderson, Alexander R A

2018-03-01

During the last decade, our understanding of cancer cell signaling networks has significantly improved, leading to the development of various targeted therapies that have elicited profound but, unfortunately, short-lived responses. This is, in part, due to the fact that these targeted therapies ignore context and average out heterogeneity. Here, we present a mathematical framework that addresses the impact of signaling heterogeneity on targeted therapy outcomes. We employ a simplified oncogenic rat sarcoma (RAS)-driven mitogen-activated protein kinase (MAPK) and phosphoinositide 3-kinase-protein kinase B (PI3K-AKT) signaling pathway in lung cancer as an experimental model system and develop a network model of the pathway. We measure how inhibition of the pathway modulates protein phosphorylation as well as cell viability under different microenvironmental conditions. Training the model on this data using Monte Carlo simulation results in a suite of in silico cells whose relative protein activities and cell viability match experimental observation. The calibrated model predicts distributional responses to kinase inhibitors and suggests drug resistance mechanisms that can be exploited in drug combination strategies. The suggested combination strategies are validated using in vitro experimental data. The validated in silico cells are further interrogated through an unsupervised clustering analysis and then integrated into a mathematical model of tumor growth in a homogeneous and resource-limited microenvironment. We assess posttreatment heterogeneity and predict vast differences across treatments with similar efficacy, further emphasizing that heterogeneity should modulate treatment strategies. The signaling model is also integrated into a hybrid cellular automata (HCA) model of tumor growth in a spatially heterogeneous microenvironment. As a proof of concept, we simulate tumor responses to targeted therapies in a spatially segregated tissue structure containing tumor and stroma (derived from patient tissue) and predict complex cell signaling responses that suggest a novel combination treatment strategy.

Person-Centered Counseling and Solution-Focused Brief Therapy: An Integrative Model for School Counselors

ERIC Educational Resources Information Center

Dameron, Merry Leigh

2016-01-01

Increasing demands upon the time of the professional school counselor combined with the call by the American School Counselor Association to provide direct services to students may lead many in the profession to wonder from what theoretical standpoint(s) they can best meet these lofty goals. I propose a two phase approach combining person-centered…

Integration of Geodata in Documenting Castle Ruins

NASA Astrophysics Data System (ADS)

Delis, P.; Wojtkowska, M.; Nerc, P.; Ewiak, I.; Lada, A.

2016-06-01

Textured three dimensional models are currently the one of the standard methods of representing the results of photogrammetric works. A realistic 3D model combines the geometrical relations between the structure's elements with realistic textures of each of its elements. Data used to create 3D models of structures can be derived from many different sources. The most commonly used tool for documentation purposes, is a digital camera and nowadays terrestrial laser scanning (TLS). Integration of data acquired from different sources allows modelling and visualization of 3D models historical structures. Additional aspect of data integration is possibility of complementing of missing points for example in point clouds. The paper shows the possibility of integrating data from terrestrial laser scanning with digital imagery and an analysis of the accuracy of the presented methods. The paper describes results obtained from raw data consisting of a point cloud measured using terrestrial laser scanning acquired from a Leica ScanStation2 and digital imagery taken using a Kodak DCS Pro 14N camera. The studied structure is the ruins of the Ilza castle in Poland.

Deep Impact Sequence Planning Using Multi-Mission Adaptable Planning Tools With Integrated Spacecraft Models

NASA Technical Reports Server (NTRS)

Wissler, Steven S.; Maldague, Pierre; Rocca, Jennifer; Seybold, Calina

2006-01-01

The Deep Impact mission was ambitious and challenging. JPL's well proven, easily adaptable multi-mission sequence planning tools combined with integrated spacecraft subsystem models enabled a small operations team to develop, validate, and execute extremely complex sequence-based activities within very short development times. This paper focuses on the core planning tool used in the mission, APGEN. It shows how the multi-mission design and adaptability of APGEN made it possible to model spacecraft subsystems as well as ground assets throughout the lifecycle of the Deep Impact project, starting with models of initial, high-level mission objectives, and culminating in detailed predictions of spacecraft behavior during mission-critical activities.

An integrated occupational hygiene consultation model for the catering industry.

PubMed

Lin, Yi-Kuei; Lee, Lien-Hsiung

2010-07-01

Vegetable oil used in food processing, during high-temperature exposure, will generate particulate matter (PM) and polycyclic aromatic hydrocarbons (PAHs), which are carcinogenic chemical compounds, with the potential to cause lung disease for restaurant kitchen staff. This study's design includes a three-stage consultation process with eight major consultation items, in order to build an integrated consultation model for occupational hygiene. This model combines inspection and consultation, targeting Chinese restaurants in the catering industry. Characteristics of the integrated consultation model include cooperation between different government departments and collaboration with nongovernmental, professional consulting organizations. An additional benefit of the model is the building of a good partnership relationship with the Catering Trade Association. The consultation model helps Chinese restaurants attain improvements in their work environments with minimal investment. Postconsultation, results show a 63.35% and 61.98% (P < 0.001) decrease in the mean time-weighted concentration of exposure to PM and PAHs, respectively. The overall regulation compliance rate of Chinese restaurants significantly increased from 34.3% to 89.6%. These results show that the integrated consultation model for occupational hygiene not only helps small and medium enterprises reduce exposure concentrations in the workplace but also has specific potential for successful implementation in Taiwan.

Testing a Longitudinal Integrated Self-Efficacy and Self-Determination Theory Model for Physical Activity Post-Cardiac Rehabilitation

PubMed Central

Sweet, Shane N.; Fortier, Michelle S.; Strachan, Shaelyn M.; Blanchard, Chris M.; Boulay, Pierre

2014-01-01

Self-determination theory and self-efficacy theory are prominent theories in the physical activity literature, and studies have begun integrating their concepts. Sweet, Fortier, Strachan and Blanchard (2012) have integrated these two theories in a cross-sectional study. Therefore, this study sought to test a longitudinal integrated model to predict physical activity at the end of a 4-month cardiac rehabilitation program based on theory, research and Sweet et al.’s cross-sectional model. Participants from two cardiac rehabilitation programs (N=109) answered validated self-report questionnaires at baseline, two and four months. Data were analyzed using Amos to assess the path analysis and model fit. Prior to integration, perceived competence and self-efficacy were combined, and labeled as confidence. After controlling for 2-month physical activity and cardiac rehabilitation site, no motivational variables significantly predicted residual change in 4-month physical activity. Although confidence at two months did not predict residual change in 4-month physical activity, it had a strong positive relationship with 2-month physical activity (β=0.30, P<0.001). The overall model retained good fit indices. In conclusion, results diverged from theoretical predictions of physical activity, but self-determination and self-efficacy theory were still partially supported. Because the model had good fit, this study demonstrated that theoretical integration is feasible. PMID:26973926

A semantic web framework to integrate cancer omics data with biological knowledge.

PubMed

Holford, Matthew E; McCusker, James P; Cheung, Kei-Hoi; Krauthammer, Michael

2012-01-25

The RDF triple provides a simple linguistic means of describing limitless types of information. Triples can be flexibly combined into a unified data source we call a semantic model. Semantic models open new possibilities for the integration of variegated biological data. We use Semantic Web technology to explicate high throughput clinical data in the context of fundamental biological knowledge. We have extended Corvus, a data warehouse which provides a uniform interface to various forms of Omics data, by providing a SPARQL endpoint. With the querying and reasoning tools made possible by the Semantic Web, we were able to explore quantitative semantic models retrieved from Corvus in the light of systematic biological knowledge. For this paper, we merged semantic models containing genomic, transcriptomic and epigenomic data from melanoma samples with two semantic models of functional data - one containing Gene Ontology (GO) data, the other, regulatory networks constructed from transcription factor binding information. These two semantic models were created in an ad hoc manner but support a common interface for integration with the quantitative semantic models. Such combined semantic models allow us to pose significant translational medicine questions. Here, we study the interplay between a cell's molecular state and its response to anti-cancer therapy by exploring the resistance of cancer cells to Decitabine, a demethylating agent. We were able to generate a testable hypothesis to explain how Decitabine fights cancer - namely, that it targets apoptosis-related gene promoters predominantly in Decitabine-sensitive cell lines, thus conveying its cytotoxic effect by activating the apoptosis pathway. Our research provides a framework whereby similar hypotheses can be developed easily.

Combining Quality Work-Integrated Learning and Career Development Learning through the Use of the SOAR Model to Enhance Employability

ERIC Educational Resources Information Center

Reddan, Gregory; Rauchle, Maja

2017-01-01

This paper presents students' perceptions of the benefits to employability of a suite of courses that incorporate both work-integrated learning (WIL) and career development learning (CDL). Field Project A and Field Project B are elective courses in the Bachelor of Exercise Science at Griffith University. These courses engage students in active and…

Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios

PubMed Central

Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming

2015-01-01

This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN. PMID:26593919

Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios.

PubMed

Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming

2015-11-17

This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN.

Integrated Data Analysis for Fusion: A Bayesian Tutorial for Fusion Diagnosticians

NASA Astrophysics Data System (ADS)

Dinklage, Andreas; Dreier, Heiko; Fischer, Rainer; Gori, Silvio; Preuss, Roland; Toussaint, Udo von

2008-03-01

Integrated Data Analysis (IDA) offers a unified way of combining information relevant to fusion experiments. Thereby, IDA meets with typical issues arising in fusion data analysis. In IDA, all information is consistently formulated as probability density functions quantifying uncertainties in the analysis within the Bayesian probability theory. For a single diagnostic, IDA allows the identification of faulty measurements and improvements in the setup. For a set of diagnostics, IDA gives joint error distributions allowing the comparison and integration of different diagnostics results. Validation of physics models can be performed by model comparison techniques. Typical data analysis applications benefit from IDA capabilities of nonlinear error propagation, the inclusion of systematic effects and the comparison of different physics models. Applications range from outlier detection, background discrimination, model assessment and design of diagnostics. In order to cope with next step fusion device requirements, appropriate techniques are explored for fast analysis applications.

Interactions of elevation, aspect, and slope in models of forest species composition and productivity

Treesearch

Albert R. Stage; Christian Salas

2007-01-01

We present a linear model for the interacting effects of elevation, aspect, and slope for use in predicting forest productivity or species composition. The model formulation we propose integrates interactions of these three factors in a mathematical expression representing their combined effect in terms of a cosine function of aspect with a phase shift and amplitude...

MollDE: a homology modeling framework you can click with.

PubMed

Canutescu, Adrian A; Dunbrack, Roland L

2005-06-15

Molecular Integrated Development Environment (MolIDE) is an integrated application designed to provide homology modeling tools and protocols under a uniform, user-friendly graphical interface. Its main purpose is to combine the most frequent modeling steps in a semi-automatic, interactive way, guiding the user from the target protein sequence to the final three-dimensional protein structure. The typical basic homology modeling process is composed of building sequence profiles of the target sequence family, secondary structure prediction, sequence alignment with PDB structures, assisted alignment editing, side-chain prediction and loop building. All of these steps are available through a graphical user interface. MolIDE's user-friendly and streamlined interactive modeling protocol allows the user to focus on the important modeling questions, hiding from the user the raw data generation and conversion steps. MolIDE was designed from the ground up as an open-source, cross-platform, extensible framework. This allows developers to integrate additional third-party programs to MolIDE. http://dunbrack.fccc.edu/molide/molide.php rl_dunbrack@fccc.edu.

Diagnosis by integrating model-based reasoning with knowledge-based reasoning

NASA Technical Reports Server (NTRS)

Bylander, Tom

1988-01-01

Our research investigates how observations can be categorized by integrating a qualitative physical model with experiential knowledge. Our domain is diagnosis of pathologic gait in humans, in which the observations are the gait motions, muscle activity during gait, and physical exam data, and the diagnostic hypotheses are the potential muscle weaknesses, muscle mistimings, and joint restrictions. Patients with underlying neurological disorders typically have several malfunctions. Among the problems that need to be faced are: the ambiguity of the observations, the ambiguity of the qualitative physical model, correspondence of the observations and hypotheses to the qualitative physical model, the inherent uncertainty of experiential knowledge, and the combinatorics involved in forming composite hypotheses. Our system divides the work so that the knowledge-based reasoning suggests which hypotheses appear more likely than others, the qualitative physical model is used to determine which hypotheses explain which observations, and another process combines these functionalities to construct a composite hypothesis based on explanatory power and plausibility. We speculate that the reasoning architecture of our system is generally applicable to complex domains in which a less-than-perfect physical model and less-than-perfect experiential knowledge need to be combined to perform diagnosis.

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

PubMed

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

2018-06-01

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

Integrating language models into classifiers for BCI communication: a review

NASA Astrophysics Data System (ADS)

Speier, W.; Arnold, C.; Pouratian, N.

2016-06-01

Objective. The present review systematically examines the integration of language models to improve classifier performance in brain-computer interface (BCI) communication systems. Approach. The domain of natural language has been studied extensively in linguistics and has been used in the natural language processing field in applications including information extraction, machine translation, and speech recognition. While these methods have been used for years in traditional augmentative and assistive communication devices, information about the output domain has largely been ignored in BCI communication systems. Over the last few years, BCI communication systems have started to leverage this information through the inclusion of language models. Main results. Although this movement began only recently, studies have already shown the potential of language integration in BCI communication and it has become a growing field in BCI research. BCI communication systems using language models in their classifiers have progressed down several parallel paths, including: word completion; signal classification; integration of process models; dynamic stopping; unsupervised learning; error correction; and evaluation. Significance. Each of these methods have shown significant progress, but have largely been addressed separately. Combining these methods could use the full potential of language model, yielding further performance improvements. This integration should be a priority as the field works to create a BCI system that meets the needs of the amyotrophic lateral sclerosis population.

Integrating language models into classifiers for BCI communication: a review.

PubMed

Speier, W; Arnold, C; Pouratian, N

2016-06-01

The present review systematically examines the integration of language models to improve classifier performance in brain-computer interface (BCI) communication systems. The domain of natural language has been studied extensively in linguistics and has been used in the natural language processing field in applications including information extraction, machine translation, and speech recognition. While these methods have been used for years in traditional augmentative and assistive communication devices, information about the output domain has largely been ignored in BCI communication systems. Over the last few years, BCI communication systems have started to leverage this information through the inclusion of language models. Although this movement began only recently, studies have already shown the potential of language integration in BCI communication and it has become a growing field in BCI research. BCI communication systems using language models in their classifiers have progressed down several parallel paths, including: word completion; signal classification; integration of process models; dynamic stopping; unsupervised learning; error correction; and evaluation. Each of these methods have shown significant progress, but have largely been addressed separately. Combining these methods could use the full potential of language model, yielding further performance improvements. This integration should be a priority as the field works to create a BCI system that meets the needs of the amyotrophic lateral sclerosis population.

Understanding Water-Energy-Ecology Nexus from an Integrated Earth-Human System Perspective

NASA Astrophysics Data System (ADS)

Li, H. Y.; Zhang, X.; Wan, W.; Zhuang, Y.; Hejazi, M. I.; Leung, L. R.

2017-12-01

Both Earth and human systems exert notable controls on streamflow and stream temperature that influence energy production and ecosystem health. An integrated water model representing river processes and reservoir regulations has been developed and coupled to a land surface model and an integrated assessment model of energy, land, water, and socioeconomics to investigate the energy-water-ecology nexus in the context of climate change and water management. Simulations driven by two climate change projections following the RCP 4.5 and RCP 8.5 radiative forcing scenarios, with and without water management, are analyzed to evaluate the individual and combined effects of climate change and water management on streamflow and stream temperature in the U.S. The simulations revealed important impacts of climate change and water management on hydrological droughts. The simulations also revealed the dynamics of competition between changes in water demand and water availability in the RCP 4.5 and RCP 8.5 scenarios that influence streamflow and stream temperature, with important consequences to thermoelectricity production and future survival of juvenile Salmon. The integrated water model is being implemented to the Accelerated Climate Modeling for Energy (ACME), a coupled Earth System Model, to enable future investigations of the energy-water-ecology nexus in the integrated Earth-Human system.

Improving wave forecasting by integrating ensemble modelling and machine learning

NASA Astrophysics Data System (ADS)

O'Donncha, F.; Zhang, Y.; James, S. C.

2017-12-01

Modern smart-grid networks use technologies to instantly relay information on supply and demand to support effective decision making. Integration of renewable-energy resources with these systems demands accurate forecasting of energy production (and demand) capacities. For wave-energy converters, this requires wave-condition forecasting to enable estimates of energy production. Current operational wave forecasting systems exhibit substantial errors with wave-height RMSEs of 40 to 60 cm being typical, which limits the reliability of energy-generation predictions thereby impeding integration with the distribution grid. In this study, we integrate physics-based models with statistical learning aggregation techniques that combine forecasts from multiple, independent models into a single "best-estimate" prediction of the true state. The Simulating Waves Nearshore physics-based model is used to compute wind- and currents-augmented waves in the Monterey Bay area. Ensembles are developed based on multiple simulations perturbing input data (wave characteristics supplied at the model boundaries and winds) to the model. A learning-aggregation technique uses past observations and past model forecasts to calculate a weight for each model. The aggregated forecasts are compared to observation data to quantify the performance of the model ensemble and aggregation techniques. The appropriately weighted ensemble model outperforms an individual ensemble member with regard to forecasting wave conditions.

Performance Analysis on Carrier Phase-Based Tightly-Coupled GPS/BDS/INS Integration in GNSS Degraded and Denied Environments

PubMed Central

Han, Houzeng; Wang, Jian; Wang, Jinling; Tan, Xinglong

2015-01-01

The integration of Global Navigation Satellite Systems (GNSS) carrier phases with Inertial Navigation System (INS) measurements is essential to provide accurate and continuous position, velocity and attitude information, however it is necessary to fix ambiguities rapidly and reliably to obtain high accuracy navigation solutions. In this paper, we present the notion of combining the Global Positioning System (GPS), the BeiDou Navigation Satellite System (BDS) and low-cost micro-electro-mechanical sensors (MEMS) inertial systems for reliable navigation. An adaptive multipath factor-based tightly-coupled (TC) GPS/BDS/INS integration algorithm is presented and the overall performance of the integrated system is illustrated. A twenty seven states TC GPS/BDS/INS model is adopted with an extended Kalman filter (EKF), which is carried out by directly fusing ambiguity fixed double-difference (DD) carrier phase measurements with the INS predicted pseudoranges to estimate the error states. The INS-aided integer ambiguity resolution (AR) strategy is developed by using a dynamic model, a two-step estimation procedure is applied with adaptively estimated covariance matrix to further improve the AR performance. A field vehicular test was carried out to demonstrate the positioning performance of the combined system. The results show the TC GPS/BDS/INS system significantly improves the single-epoch AR reliability as compared to that of GPS/BDS-only or single satellite navigation system integrated strategy, especially for high cut-off elevations. The AR performance is also significantly improved for the combined system with adaptive covariance matrix in the presence of low elevation multipath related to the GNSS-only case. A total of fifteen simulated outage tests also show that the time to relock of the GPS/BDS signals is shortened, which improves the system availability. The results also indicate that TC integration system achieves a few centimeters accuracy in positioning based on the comparison analysis and covariance analysis, even in harsh environments (e.g., in urban canyons), thus we can see the advantage of positioning at high cut-off elevations that the combined GPS/BDS brings. PMID:25875191

Performance analysis on carrier phase-based tightly-coupled GPS/BDS/INS integration in GNSS degraded and denied environments.

PubMed

Han, Houzeng; Wang, Jian; Wang, Jinling; Tan, Xinglong

2015-04-14

The integration of Global Navigation Satellite Systems (GNSS) carrier phases with Inertial Navigation System (INS) measurements is essential to provide accurate and continuous position, velocity and attitude information, however it is necessary to fix ambiguities rapidly and reliably to obtain high accuracy navigation solutions. In this paper, we present the notion of combining the Global Positioning System (GPS), the BeiDou Navigation Satellite System (BDS) and low-cost micro-electro-mechanical sensors (MEMS) inertial systems for reliable navigation. An adaptive multipath factor-based tightly-coupled (TC) GPS/BDS/INS integration algorithm is presented and the overall performance of the integrated system is illustrated. A twenty seven states TC GPS/BDS/INS model is adopted with an extended Kalman filter (EKF), which is carried out by directly fusing ambiguity fixed double-difference (DD) carrier phase measurements with the INS predicted pseudoranges to estimate the error states. The INS-aided integer ambiguity resolution (AR) strategy is developed by using a dynamic model, a two-step estimation procedure is applied with adaptively estimated covariance matrix to further improve the AR performance. A field vehicular test was carried out to demonstrate the positioning performance of the combined system. The results show the TC GPS/BDS/INS system significantly improves the single-epoch AR reliability as compared to that of GPS/BDS-only or single satellite navigation system integrated strategy, especially for high cut-off elevations. The AR performance is also significantly improved for the combined system with adaptive covariance matrix in the presence of low elevation multipath related to the GNSS-only case. A total of fifteen simulated outage tests also show that the time to relock of the GPS/BDS signals is shortened, which improves the system availability. The results also indicate that TC integration system achieves a few centimeters accuracy in positioning based on the comparison analysis and covariance analysis, even in harsh environments (e.g., in urban canyons), thus we can see the advantage of positioning at high cut-off elevations that the combined GPS/BDS brings.

Modeling integrated fixed-film activated sludge and moving-bed biofilm reactor systems II: evaluation.

PubMed

Boltz, Joshua P; Johnson, Bruce R; Daigger, Glen T; Sandino, Julian; Elenter, Deborah

2009-06-01

A steady-state model presented by Boltz, Johnson, Daigger, and Sandino (2009) describing integrated fixed-film activated sludge (IFAS) and moving-bed biofilm reactor (MBBR) systems has been demonstrated to simulate, with reasonable accuracy, four wastewater treatment configurations with published operational data. Conditions simulated include combined carbon oxidation and nitrification (both IFAS and MBBR), tertiary nitrification MBBR, and post denitrification IFAS with methanol addition as the external carbon source. Simulation results illustrate that the IFAS/MBBR model is sufficiently accurate for describing ammonia-nitrogen reduction, nitrate/nitrite-nitrogen reduction and production, biofilm and suspended biomass distribution, and sludge production.

Theoretical modeling of multiprotein complexes by iSPOT: Integration of small-angle X-ray scattering, hydroxyl radical footprinting, and computational docking.

PubMed

Huang, Wei; Ravikumar, Krishnakumar M; Parisien, Marc; Yang, Sichun

2016-12-01

Structural determination of protein-protein complexes such as multidomain nuclear receptors has been challenging for high-resolution structural techniques. Here, we present a combined use of multiple biophysical methods, termed iSPOT, an integration of shape information from small-angle X-ray scattering (SAXS), protection factors probed by hydroxyl radical footprinting, and a large series of computationally docked conformations from rigid-body or molecular dynamics (MD) simulations. Specifically tested on two model systems, the power of iSPOT is demonstrated to accurately predict the structures of a large protein-protein complex (TGFβ-FKBP12) and a multidomain nuclear receptor homodimer (HNF-4α), based on the structures of individual components of the complexes. Although neither SAXS nor footprinting alone can yield an unambiguous picture for each complex, the combination of both, seamlessly integrated in iSPOT, narrows down the best-fit structures that are about 3.2Å and 4.2Å in RMSD from their corresponding crystal structures, respectively. Furthermore, this proof-of-principle study based on the data synthetically derived from available crystal structures shows that the iSPOT-using either rigid-body or MD-based flexible docking-is capable of overcoming the shortcomings of standalone computational methods, especially for HNF-4α. By taking advantage of the integration of SAXS-based shape information and footprinting-based protection/accessibility as well as computational docking, this iSPOT platform is set to be a powerful approach towards accurate integrated modeling of many challenging multiprotein complexes. Copyright © 2016 Elsevier Inc. All rights reserved.

Combining observations in the reflective solar and thermal domains for improved carbon and energy flux estimation

USDA-ARS?s Scientific Manuscript database

This study investigates the utility of integrating remotely sensed estimates of leaf chlorophyll (Cab) into a therma-based Two-Source Energy Balance (TSEB) model that estimates land-surface CO2 and energy fluxes using an analytical, light-use-efficiency (LUE) based model of canopy resistance. The LU...

A mixed integer program to model spatial wildfire behavior and suppression placement decisions

Treesearch

Erin J. Belval; Yu Wei; Michael Bevers

2015-01-01

Wildfire suppression combines multiple objectives and dynamic fire behavior to form a complex problem for decision makers. This paper presents a mixed integer program designed to explore integrating spatial fire behavior and suppression placement decisions into a mathematical programming framework. Fire behavior and suppression placement decisions are modeled using...

A Framework for Studying Minority Youths' Transitions to Fatherhood: The Case of Puerto Rican Adolescents

ERIC Educational Resources Information Center

Erkut, Sumru; Szalacha, Laura A.; Coll, Cynthia Garcia

2005-01-01

A theoretical framework is proposed for studying minority young men's involvement with their babies that combines the integrative model of minority youth development and a life course developmental perspective with Lamb's revised four-factor model of father involvement. This framework posits a relationship between demographic and family background…

Linking Science Analysis with Observation Planning: A Full Circle Data Lifecycle

NASA Technical Reports Server (NTRS)

Grosvenor, Sandy; Jones, Jeremy; Koratkar, Anuradha; Li, Connie; Mackey, Jennifer; Neher, Ken; Wolf, Karl; Obenschain, Arthur F. (Technical Monitor)

2001-01-01

A clear goal of the Virtual Observatory (VO) is to enable new science through analysis of integrated astronomical archives. An additional and powerful possibility of the VO is to link and integrate these new analyses with planning of new observations. By providing tools that can be used for observation planning in the VO, the VO will allow the data lifecycle to come full circle: from theory to observations to data and back around to new theories and new observations. The Scientist's Expert Assistant (SEA) Simulation Facility (SSF) is working to combine the ability to access existing archives with the ability to model and visualize new observations. Integrating the two will allow astronomers to better use the integrated archives of the VO to plan and predict the success of potential new observations more efficiently, The full circle lifecycle enabled by SEA can allow astronomers to make substantial leaps in the quality of data and science returns on new observations. Our paper examines the exciting potential of integrating archival analysis with new observation planning, such as performing data calibration analysis on archival images and using that analysis to predict the success of new observations, or performing dynamic signal-to-noise analysis combining historical results with modeling of new instruments or targets. We will also describe how the development of the SSF is progressing and what have been its successes and challenges.

Linking Science Analysis with Observation Planning: A Full Circle Data Lifecycle

NASA Technical Reports Server (NTRS)

Jones, Jeremy; Grosvenor, Sandy; Wolf, Karl; Li, Connie; Koratkar, Anuradha; Powers, Edward I. (Technical Monitor)

2001-01-01

A clear goal of the Virtual Observatory (VO) is to enable new science through analysis of integrated astronomical archives. An additional and powerful possibility of the VO is to link and integrate these new analyses with planning of new observations. By providing tools that can be used for observation planning in the VO, the VO will allow the data lifecycle to come full circle: from theory to observations to data and back around to new theories and new observations. The Scientist's Expert Assistant (SEA) Simulation Facility (SSF) is working to combine the ability to access existing archives with the ability to model and visualize new observations. Integrating the two will allow astronomers to better use the integrated archives of the VO to plan and predict the success of potential new observations. The full circle lifecycle enabled by SEA can allow astronomers to make substantial leaps in the quality of data and science returns on new observations. Our paper will examine the exciting potential of integrating archival analysis with new observation planning, such as performing data calibration analysis on archival images and using that analysis to predict the success of new observations, or performing dynamic signal-to-noise analysis combining historical results with modeling of new instruments or targets. We will also describe how the development of the SSF is progressing and what has been its successes and challenges.

An integrated radar model solution for mission level performance and cost trades

NASA Astrophysics Data System (ADS)

Hodge, John; Duncan, Kerron; Zimmerman, Madeline; Drupp, Rob; Manno, Mike; Barrett, Donald; Smith, Amelia

2017-05-01

A fully integrated Mission-Level Radar model is in development as part of a multi-year effort under the Northrop Grumman Mission Systems (NGMS) sector's Model Based Engineering (MBE) initiative to digitally interconnect and unify previously separate performance and cost models. In 2016, an NGMS internal research and development (IR and D) funded multidisciplinary team integrated radio frequency (RF), power, control, size, weight, thermal, and cost models together using a commercial-off-the-shelf software, ModelCenter, for an Active Electronically Scanned Array (AESA) radar system. Each represented model was digitally connected with standard interfaces and unified to allow end-to-end mission system optimization and trade studies. The radar model was then linked to the Air Force's own mission modeling framework (AFSIM). The team first had to identify the necessary models, and with the aid of subject matter experts (SMEs) understand and document the inputs, outputs, and behaviors of the component models. This agile development process and collaboration enabled rapid integration of disparate models and the validation of their combined system performance. This MBE framework will allow NGMS to design systems more efficiently and affordably, optimize architectures, and provide increased value to the customer. The model integrates detailed component models that validate cost and performance at the physics level with high-level models that provide visualization of a platform mission. This connectivity of component to mission models allows hardware and software design solutions to be better optimized to meet mission needs, creating cost-optimal solutions for the customer, while reducing design cycle time through risk mitigation and early validation of design decisions.

An integrated mathematical model for chemical oxygen demand (COD) removal in moving bed biofilm reactors (MBBR) including predation and hydrolysis.

PubMed

Revilla, Marta; Galán, Berta; Viguri, Javier R

2016-07-01

An integrated mathematical model is proposed for modelling a moving bed biofilm reactor (MBBR) for removal of chemical oxygen demand (COD) under aerobic conditions. The composite model combines the following: (i) a one-dimensional biofilm model, (ii) a bulk liquid model, and (iii) biological processes in the bulk liquid and biofilm considering the interactions among autotrophic, heterotrophic and predator microorganisms. Depending on the values for the soluble biodegradable COD loading rate (SCLR), the model takes into account a) the hydrolysis of slowly biodegradable compounds in the bulk liquid, and b) the growth of predator microorganisms in the bulk liquid and in the biofilm. The integration of the model and the SCLR allows a general description of the behaviour of COD removal by the MBBR under various conditions. The model is applied for two in-series MBBR wastewater plant from an integrated cellulose and viscose production and accurately describes the experimental concentrations of COD, total suspended solids (TSS), nitrogen and phosphorous obtained during 14 months working at different SCLRs and nutrient dosages. The representation of the microorganism group distribution in the biofilm and in the bulk liquid allow for verification of the presence of predator microorganisms in the second reactor under some operational conditions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Integrated monitoring and information systems for managing aquatic invasive species in a changing climate.

PubMed

Lee, Henry; Reusser, Deborah A; Olden, Julian D; Smith, Scott S; Graham, Jim; Burkett, Virginia; Dukes, Jeffrey S; Piorkowski, Robert J; McPhedran, John

2008-06-01

Changes in temperature, precipitation, and other climatic drivers and sea-level rise will affect populations of existing native and non-native aquatic species and the vulnerability of aquatic environments to new invasions. Monitoring surveys provide the foundation for assessing the combined effects of climate change and invasions by providing baseline biotic and environmental conditions, although the utility of a survey depends on whether the results are quantitative or qualitative, and other design considerations. The results from a variety of monitoring programs in the United States are available in integrated biological information systems, although many include only non-native species, not native species. Besides including natives, we suggest these systems could be improved through the development of standardized methods that capture habitat and physiological requirements and link regional and national biological databases into distributed Web portals that allow drawing information from multiple sources. Combining the outputs from these biological information systems with environmental data would allow the development of ecological-niche models that predict the potential distribution or abundance of native and non-native species on the basis of current environmental conditions. Environmental projections from climate models can be used in these niche models to project changes in species distributions or abundances under altered climatic conditions and to identify potential high-risk invaders. There are, however, a number of challenges, such as uncertainties associated with projections from climate and niche models and difficulty in integrating data with different temporal and spatial granularity. Even with these uncertainties, integration of biological and environmental information systems, niche models, and climate projections would improve management of aquatic ecosystems under the dual threats of biotic invasions and climate change.

Integrated monitoring and information systems for managing aquatic invasive species in a changing climate

USGS Publications Warehouse

Lee, Henry; Reusser, Deborah A.; Olden, Julian D.; Smith, Scott S.; Graham, Jim; Burkett, Virginia; Dukes, Jeffrey S.; Piorkowski, Robert J.; Mcphedran, John

2008-01-01

Changes in temperature, precipitation, and other climatic drivers and sea-level rise will affect populations of existing native and non-native aquatic species and the vulnerability of aquatic environments to new invasions. Monitoring surveys provide the foundation for assessing the combined effects of climate change and invasions by providing baseline biotic and environmental conditions, although the utility of a survey depends on whether the results are quantitative or qualitative, and other design considerations. The results from a variety of monitoring programs in the United States are available in integrated biological information systems, although many include only non-native species, not native species. Besides including natives, we suggest these systems could be improved through the development of standardized methods that capture habitat and physiological requirements and link regional and national biological databases into distributed Web portals that allow drawing information from multiple sources. Combining the outputs from these biological information systems with environmental data would allow the development of ecological-niche models that predict the potential distribution or abundance of native and non-native species on the basis of current environmental conditions. Environmental projections from climate models can be used in these niche models to project changes in species distributions or abundances under altered climatic conditions and to identify potential high-risk invaders. There are, however, a number of challenges, such as uncertainties associated with projections from climate and niche models and difficulty in integrating data with different temporal and spatial granularity. Even with these uncertainties, integration of biological and environmental information systems, niche models, and climate projections would improve management of aquatic ecosystems under the dual threats of biotic invasions and climate change

Smith predictor based-sliding mode controller for integrating processes with elevated deadtime.

PubMed

Camacho, Oscar; De la Cruz, Francisco

2004-04-01

An approach to control integrating processes with elevated deadtime using a Smith predictor sliding mode controller is presented. A PID sliding surface and an integrating first-order plus deadtime model have been used to synthesize the controller. Since the performance of existing controllers with a Smith predictor decrease in the presence of modeling errors, this paper presents a simple approach to combining the Smith predictor with the sliding mode concept, which is a proven, simple, and robust procedure. The proposed scheme has a set of tuning equations as a function of the characteristic parameters of the model. For implementation of our proposed approach, computer based industrial controllers that execute PID algorithms can be used. The performance and robustness of the proposed controller are compared with the Matausek-Micić scheme for linear systems using simulations.

Modeling complex tone perception: grouping harmonics with combination-sensitive neurons.

PubMed

Medvedev, Andrei V; Chiao, Faye; Kanwal, Jagmeet S

2002-06-01

Perception of complex communication sounds is a major function of the auditory system. To create a coherent precept of these sounds the auditory system may instantaneously group or bind multiple harmonics within complex sounds. This perception strategy simplifies further processing of complex sounds and facilitates their meaningful integration with other sensory inputs. Based on experimental data and a realistic model, we propose that associative learning of combinations of harmonic frequencies and nonlinear facilitation of responses to those combinations, also referred to as "combination-sensitivity," are important for spectral grouping. For our model, we simulated combination sensitivity using Hebbian and associative types of synaptic plasticity in auditory neurons. We also provided a parallel tonotopic input that converges and diverges within the network. Neurons in higher-order layers of the network exhibited an emergent property of multifrequency tuning that is consistent with experimental findings. Furthermore, this network had the capacity to "recognize" the pitch or fundamental frequency of a harmonic tone complex even when the fundamental frequency itself was missing.

The water-energy nexus at water supply and its implications on the integrated water and energy management.

PubMed

Khalkhali, Masoumeh; Westphal, Kirk; Mo, Weiwei

2018-09-15

Water and energy are highly interdependent in the modern world, and hence, it is important to understand their constantly changing and nonlinear interconnections to inform the integrated management of water and energy. In this study, a hydrologic model, a water systems model, and an energy model were developed and integrated into a system dynamics modeling framework. This framework was then applied to a water supply system in the northeast US to capture its water-energy interactions under a set of future population, climate, and system operation scenarios. A hydrologic model was first used to simulate the system's hydrologic inflows and outflows under temperature and precipitation changes on a weekly-basis. A water systems model that combines the hydrologic model and management rules (e.g., water release and transfer) was then developed to dynamically simulate the system's water storage and water head. Outputs from the water systems model were used in the energy model to estimate hydropower generation. It was found that critical water-energy synergies and tradeoffs exist, and there is a possibility for integrated water and energy management to achieve better outcomes. This analysis also shows the importance of a holistic understanding of the systems as a whole, which would allow utility managers to make proactive long-term management decisions. The modeling framework is generalizable to other water supply systems with hydropower generation capacities to inform the integrated management of water and energy resources. Copyright © 2018 Elsevier B.V. All rights reserved.

Python scripting in the nengo simulator.

PubMed

Stewart, Terrence C; Tripp, Bryan; Eliasmith, Chris

2009-01-01

Nengo (http://nengo.ca) is an open-source neural simulator that has been greatly enhanced by the recent addition of a Python script interface. Nengo provides a wide range of features that are useful for physiological simulations, including unique features that facilitate development of population-coding models using the neural engineering framework (NEF). This framework uses information theory, signal processing, and control theory to formalize the development of large-scale neural circuit models. Notably, it can also be used to determine the synaptic weights that underlie observed network dynamics and transformations of represented variables. Nengo provides rich NEF support, and includes customizable models of spike generation, muscle dynamics, synaptic plasticity, and synaptic integration, as well as an intuitive graphical user interface. All aspects of Nengo models are accessible via the Python interface, allowing for programmatic creation of models, inspection and modification of neural parameters, and automation of model evaluation. Since Nengo combines Python and Java, it can also be integrated with any existing Java or 100% Python code libraries. Current work includes connecting neural models in Nengo with existing symbolic cognitive models, creating hybrid systems that combine detailed neural models of specific brain regions with higher-level models of remaining brain areas. Such hybrid models can provide (1) more realistic boundary conditions for the neural components, and (2) more realistic sub-components for the larger cognitive models.

Python Scripting in the Nengo Simulator

PubMed Central

Stewart, Terrence C.; Tripp, Bryan; Eliasmith, Chris

2008-01-01

Nengo (http://nengo.ca) is an open-source neural simulator that has been greatly enhanced by the recent addition of a Python script interface. Nengo provides a wide range of features that are useful for physiological simulations, including unique features that facilitate development of population-coding models using the neural engineering framework (NEF). This framework uses information theory, signal processing, and control theory to formalize the development of large-scale neural circuit models. Notably, it can also be used to determine the synaptic weights that underlie observed network dynamics and transformations of represented variables. Nengo provides rich NEF support, and includes customizable models of spike generation, muscle dynamics, synaptic plasticity, and synaptic integration, as well as an intuitive graphical user interface. All aspects of Nengo models are accessible via the Python interface, allowing for programmatic creation of models, inspection and modification of neural parameters, and automation of model evaluation. Since Nengo combines Python and Java, it can also be integrated with any existing Java or 100% Python code libraries. Current work includes connecting neural models in Nengo with existing symbolic cognitive models, creating hybrid systems that combine detailed neural models of specific brain regions with higher-level models of remaining brain areas. Such hybrid models can provide (1) more realistic boundary conditions for the neural components, and (2) more realistic sub-components for the larger cognitive models. PMID:19352442

Coupling of a distributed stakeholder-built system dynamics socio-economic model with SAHYSMOD for sustainable soil salinity management - Part 1: Model development

NASA Astrophysics Data System (ADS)

Inam, Azhar; Adamowski, Jan; Prasher, Shiv; Halbe, Johannes; Malard, Julien; Albano, Raffaele

2017-08-01

Effective policies, leading to sustainable management solutions for land and water resources, require a full understanding of interactions between socio-economic and physical processes. However, the complex nature of these interactions, combined with limited stakeholder engagement, hinders the incorporation of socio-economic components into physical models. The present study addresses this challenge by integrating the physical Spatial Agro Hydro Salinity Model (SAHYSMOD) with a participatory group-built system dynamics model (GBSDM) that includes socio-economic factors. A stepwise process to quantify the GBSDM is presented, along with governing equations and model assumptions. Sub-modules of the GBSDM, describing agricultural, economic, water and farm management factors, are linked together with feedbacks and finally coupled with the physically based SAHYSMOD model through commonly used tools (i.e., MS Excel and a Python script). The overall integrated model (GBSDM-SAHYSMOD) can be used to help facilitate the role of stakeholders with limited expertise and resources in model and policy development and implementation. Following the development of the integrated model, a testing methodology was used to validate the structure and behavior of the integrated model. Model robustness under different operating conditions was also assessed. The model structure was able to produce anticipated real behaviours under the tested scenarios, from which it can be concluded that the formulated structures generate the right behaviour for the right reasons.

Framework Programmable Platform for the Advanced Software Development Workstation: Preliminary system design document

NASA Technical Reports Server (NTRS)

Mayer, Richard J.; Blinn, Thomas M.; Mayer, Paula S. D.; Ackley, Keith A.; Crump, John W., IV; Henderson, Richard; Futrell, Michael T.

1991-01-01

The Framework Programmable Software Development Platform (FPP) is a project aimed at combining effective tool and data integration mechanisms with a model of the software development process in an intelligent integrated software environment. Guided by the model, this system development framework will take advantage of an integrated operating environment to automate effectively the management of the software development process so that costly mistakes during the development phase can be eliminated. The focus here is on the design of components that make up the FPP. These components serve as supporting systems for the Integration Mechanism and the Framework Processor and provide the 'glue' that ties the FPP together. Also discussed are the components that allow the platform to operate in a distributed, heterogeneous environment and to manage the development and evolution of software system artifacts.

IMGMD: A platform for the integration and standardisation of In silico Microbial Genome-scale Metabolic Models.

PubMed

Ye, Chao; Xu, Nan; Dong, Chuan; Ye, Yuannong; Zou, Xuan; Chen, Xiulai; Guo, Fengbiao; Liu, Liming

2017-04-07

Genome-scale metabolic models (GSMMs) constitute a platform that combines genome sequences and detailed biochemical information to quantify microbial physiology at the system level. To improve the unity, integrity, correctness, and format of data in published GSMMs, a consensus IMGMD database was built in the LAMP (Linux + Apache + MySQL + PHP) system by integrating and standardizing 328 GSMMs constructed for 139 microorganisms. The IMGMD database can help microbial researchers download manually curated GSMMs, rapidly reconstruct standard GSMMs, design pathways, and identify metabolic targets for strategies on strain improvement. Moreover, the IMGMD database facilitates the integration of wet-lab and in silico data to gain an additional insight into microbial physiology. The IMGMD database is freely available, without any registration requirements, at http://imgmd.jiangnan.edu.cn/database.

An integrated microalgal growth model and its application to optimize the biomass production of Scenedesmus sp. LX1 in open pond under the nutrient level of domestic secondary effluent.

PubMed

Wu, Yin-Hu; Li, Xin; Yu, Yin; Hu, Hong-Ying; Zhang, Tian-Yuan; Li, Feng-Min

2013-09-01

Microalgal growth is the key to the coupled system of wastewater treatment and microalgal biomass production. In this study, Monod model, Droop model and Steele model were incorporated to obtain an integrated growth model describing the combined effects of nitrogen, phosphorus and light intensity on the growth rate of Scenedesmus sp. LX1. The model parameters were obtained via fitting experimental data to these classical models. Furthermore, the biomass production of Scenedesmus sp. LX1 in open pond under nutrient level of secondary effluent was analyzed based on the integrated model, predicting a maximal microalgal biomass production rate about 20 g m(-2) d(-1). In order to optimize the biomass production of open pond the microalgal biomass concentration, light intensity on the surface of open pond, total depth of culture medium and hydraulic retention time should be 500 g m(-3), 16,000 lx, 0.2 m and 5.2 d in the conditions of this study, respectively. Copyright © 2013 Elsevier Ltd. All rights reserved.

Modeling integrated cellular machinery using hybrid Petri-Boolean networks.

PubMed

Berestovsky, Natalie; Zhou, Wanding; Nagrath, Deepak; Nakhleh, Luay

2013-01-01

The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM) that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them using such more detailed mathematical models.

Modeling Integrated Cellular Machinery Using Hybrid Petri-Boolean Networks

PubMed Central

Berestovsky, Natalie; Zhou, Wanding; Nagrath, Deepak; Nakhleh, Luay

2013-01-01

The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM) that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them using such more detailed mathematical models. PMID:24244124

Cross-scale integration of knowledge for predicting species ranges: a metamodeling framework

PubMed Central

Talluto, Matthew V.; Boulangeat, Isabelle; Ameztegui, Aitor; Aubin, Isabelle; Berteaux, Dominique; Butler, Alyssa; Doyon, Frédérik; Drever, C. Ronnie; Fortin, Marie-Josée; Franceschini, Tony; Liénard, Jean; McKenney, Dan; Solarik, Kevin A.; Strigul, Nikolay; Thuiller, Wilfried; Gravel, Dominique

2016-01-01

Aim Current interest in forecasting changes to species ranges have resulted in a multitude of approaches to species distribution models (SDMs). However, most approaches include only a small subset of the available information, and many ignore smaller-scale processes such as growth, fecundity, and dispersal. Furthermore, different approaches often produce divergent predictions with no simple method to reconcile them. Here, we present a flexible framework for integrating models at multiple scales using hierarchical Bayesian methods. Location Eastern North America (as an example). Methods Our framework builds a metamodel that is constrained by the results of multiple sub-models and provides probabilistic estimates of species presence. We applied our approach to a simulated dataset to demonstrate the integration of a correlative SDM with a theoretical model. In a second example, we built an integrated model combining the results of a physiological model with presence-absence data for sugar maple (Acer saccharum), an abundant tree native to eastern North America. Results For both examples, the integrated models successfully included information from all data sources and substantially improved the characterization of uncertainty. For the second example, the integrated model outperformed the source models with respect to uncertainty when modelling the present range of the species. When projecting into the future, the model provided a consensus view of two models that differed substantially in their predictions. Uncertainty was reduced where the models agreed and was greater where they diverged, providing a more realistic view of the state of knowledge than either source model. Main conclusions We conclude by discussing the potential applications of our method and its accessibility to applied ecologists. In ideal cases, our framework can be easily implemented using off-the-shelf software. The framework has wide potential for use in species distribution modelling and can drive better integration of multi-source and multi-scale data into ecological decision-making. PMID:27499698

Cross-scale integration of knowledge for predicting species ranges: a metamodeling framework.

PubMed

Talluto, Matthew V; Boulangeat, Isabelle; Ameztegui, Aitor; Aubin, Isabelle; Berteaux, Dominique; Butler, Alyssa; Doyon, Frédérik; Drever, C Ronnie; Fortin, Marie-Josée; Franceschini, Tony; Liénard, Jean; McKenney, Dan; Solarik, Kevin A; Strigul, Nikolay; Thuiller, Wilfried; Gravel, Dominique

2016-02-01

Current interest in forecasting changes to species ranges have resulted in a multitude of approaches to species distribution models (SDMs). However, most approaches include only a small subset of the available information, and many ignore smaller-scale processes such as growth, fecundity, and dispersal. Furthermore, different approaches often produce divergent predictions with no simple method to reconcile them. Here, we present a flexible framework for integrating models at multiple scales using hierarchical Bayesian methods. Eastern North America (as an example). Our framework builds a metamodel that is constrained by the results of multiple sub-models and provides probabilistic estimates of species presence. We applied our approach to a simulated dataset to demonstrate the integration of a correlative SDM with a theoretical model. In a second example, we built an integrated model combining the results of a physiological model with presence-absence data for sugar maple ( Acer saccharum ), an abundant tree native to eastern North America. For both examples, the integrated models successfully included information from all data sources and substantially improved the characterization of uncertainty. For the second example, the integrated model outperformed the source models with respect to uncertainty when modelling the present range of the species. When projecting into the future, the model provided a consensus view of two models that differed substantially in their predictions. Uncertainty was reduced where the models agreed and was greater where they diverged, providing a more realistic view of the state of knowledge than either source model. We conclude by discussing the potential applications of our method and its accessibility to applied ecologists. In ideal cases, our framework can be easily implemented using off-the-shelf software. The framework has wide potential for use in species distribution modelling and can drive better integration of multi-source and multi-scale data into ecological decision-making.

A Multimodal Approach to Elimination of Stuttering.

ERIC Educational Resources Information Center

Beaty, David T.

1980-01-01

The case of a 15-year-old stutterer is presented to illustrate A. Lazarus's multimodal behavior therapy model, proposed to integrate various procedures. A combination of role playing, metronome use, biofeedback training, and assertion training was used. (CL)

Model predictive control system and method for integrated gasification combined cycle power generation

DOEpatents

Kumar, Aditya; Shi, Ruijie; Kumar, Rajeeva; Dokucu, Mustafa

2013-04-09

Control system and method for controlling an integrated gasification combined cycle (IGCC) plant are provided. The system may include a controller coupled to a dynamic model of the plant to process a prediction of plant performance and determine a control strategy for the IGCC plant over a time horizon subject to plant constraints. The control strategy may include control functionality to meet a tracking objective and control functionality to meet an optimization objective. The control strategy may be configured to prioritize the tracking objective over the optimization objective based on a coordinate transformation, such as an orthogonal or quasi-orthogonal projection. A plurality of plant control knobs may be set in accordance with the control strategy to generate a sequence of coordinated multivariable control inputs to meet the tracking objective and the optimization objective subject to the prioritization resulting from the coordinate transformation.

Innovation in Evaluating the Impact of Integrated Service-Delivery: The Integra Indexes of HIV and Reproductive Health Integration.

PubMed

Mayhew, Susannah H; Ploubidis, George B; Sloggett, Andy; Church, Kathryn; Obure, Carol D; Birdthistle, Isolde; Sweeney, Sedona; Warren, Charlotte E; Watts, Charlotte; Vassall, Anna

2016-01-01

The body of knowledge on evaluating complex interventions for integrated healthcare lacks both common definitions of 'integrated service delivery' and standard measures of impact. Using multiple data sources in combination with statistical modelling the aim of this study is to develop a measure of HIV-reproductive health (HIV-RH) service integration that can be used to assess the degree of service integration, and the degree to which integration may have health benefits to clients, or reduce service costs. Data were drawn from the Integra Initiative's client flow (8,263 clients in Swaziland and 25,539 in Kenya) and costing tools implemented between 2008-2012 in 40 clinics providing RH services in Kenya and Swaziland. We used latent variable measurement models to derive dimensions of HIV-RH integration using these data, which quantified the extent and type of integration between HIV and RH services in Kenya and Swaziland. The modelling produced two clear and uncorrelated dimensions of integration at facility level leading to the development of two sub-indexes: a Structural Integration Index (integrated physical and human resource infrastructure) and a Functional Integration Index (integrated delivery of services to clients). The findings highlight the importance of multi-dimensional assessments of integration, suggesting that structural integration is not sufficient to achieve the integrated delivery of care to clients--i.e. "functional integration". These Indexes are an important methodological contribution for evaluating complex multi-service interventions. They help address the need to broaden traditional evaluations of integrated HIV-RH care through the incorporation of a functional integration measure, to avoid misleading conclusions on its 'impact' on health outcomes. This is particularly important for decision-makers seeking to promote integration in resource constrained environments.

Outside-In Systems Pharmacology Combines Innovative Computational Methods With High-Throughput Whole Vertebrate Studies.

PubMed

Schulthess, Pascal; van Wijk, Rob C; Krekels, Elke H J; Yates, James W T; Spaink, Herman P; van der Graaf, Piet H

2018-04-25

To advance the systems approach in pharmacology, experimental models and computational methods need to be integrated from early drug discovery onward. Here, we propose outside-in model development, a model identification technique to understand and predict the dynamics of a system without requiring prior biological and/or pharmacological knowledge. The advanced data required could be obtained by whole vertebrate, high-throughput, low-resource dose-exposure-effect experimentation with the zebrafish larva. Combinations of these innovative techniques could improve early drug discovery. © 2018 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Response Surface Modeling of Combined-Cycle Propulsion Components using Computational Fluid Dynamics

NASA Technical Reports Server (NTRS)

Steffen, C. J., Jr.

2002-01-01

Three examples of response surface modeling with CFD are presented for combined cycle propulsion components. The examples include a mixed-compression-inlet during hypersonic flight, a hydrogen-fueled scramjet combustor during hypersonic flight, and a ducted-rocket nozzle during all-rocket flight. Three different experimental strategies were examined, including full factorial, fractionated central-composite, and D-optimal with embedded Plackett-Burman designs. The response variables have been confined to integral data extracted from multidimensional CFD results. Careful attention to uncertainty assessment and modeling bias has been addressed. The importance of automating experimental setup and effectively communicating statistical results are emphasized.

Exploring the Feasibility of Service Integration in a Low-Income Setting: A Mixed Methods Investigation into Different Models of Reproductive Health and HIV Care in Swaziland

PubMed Central

Church, Kathryn; Wringe, Alison; Lewin, Simon; Ploubidis, George B.; Fakudze, Phelele; Mayhew, Susannah H.

2015-01-01

Integrating reproductive health (RH) with HIV care is a policy priority in high HIV prevalence settings, despite doubts surrounding its feasibility and varying evidence of effects on health outcomes. The process and outcomes of integrated RH-HIV care were investigated in Swaziland, through a comparative case study of four service models, ranging from fully integrated to fully stand-alone HIV services, selected purposively within one town. A client exit survey (n=602) measured integrated care received and unmet family planning (FP) needs. Descriptive statistics were used to assess the degree of integration per clinic and client demand for services. Logistic regression modelling was used to test the hypothesis that clients at more integrated sites had lower unmet FP needs than clients in a stand-alone site. Qualitative methods included in-depth interviews with clients and providers to explore contextual factors influencing the feasibility of integrated RH-HIV care delivery; data were analysed thematically, combining deductive and inductive approaches. Results demonstrated that clinic models were not as integrated in practice as had been claimed. Fragmentation of HIV care was common. Services accessed per provider were no higher at the more integrated clinics compared to stand-alone models (p>0.05), despite reported demand. While women at more integrated sites received more FP and pregnancy counselling than stand-alone models, they received condoms (a method of choice) less often, and there was no statistical evidence of difference in unmet FP needs by model of care. Multiple contextual factors influenced integration practices, including provider de-skilling within sub-specialist roles; norms of task-oriented routinised HIV care; perceptions of heavy client loads; imbalanced client-provider interactions hindering articulation of RH needs; and provider motivation challenges. Thus, despite institutional support, factors related to the social context of care inhibited provision of fully integrated RH-HIV services in these clinics. Programmes should move beyond simplistic training and equipment provision if integrated care interventions are to be sustained. PMID:25978632

[How timely are the methods taught in psychotherapy training and practice?].

PubMed

Beutel, Manfred E; Michal, Matthias; Wiltink, Jörg; Subic-Wrana, Claudia

2015-01-01

Even though many psychotherapists consider themselves to be eclectic or integrative, training and reimbursement in the modern healthcare system are clearly oriented toward the model of distinct psychotherapy approaches. Prompted by the proposition to favor general, disorder-oriented psychotherapy, we investigate how timely distinctive methods are that are taught in training and practice. We reviewed the pertinent literature regarding general and specific factors, the effectiveness of integrative and eclectic treatments, orientation toward specific disorders, manualization and psychotherapeutic training. There is a lack of systematic studies on the efficacy of combining therapy methods from different approaches. The first empirical findings reveal that a superiority of combined versus single treatmentmethods has yet to be demonstrated. The development of transnosological manuals shows the limits of disorder-specific treatment.General factors such as therapeutic alliance or education about the model of disease and treatment rationale require specific definitions. Taking reference to a specific treatment approach provides important consistency of theory, training therapy and supervision, though this does not preclude an openness toward other therapy concepts. Current manualized examples show that methods and techniques can indeed be integrated from other approaches. Integrating different methods can also be seen as a developmental task for practitioners and researchers which may be mastered increasingly better with more experience.

A hybrid approach to survival model building using integration of clinical and molecular information in censored data.

PubMed

Choi, Ickwon; Kattan, Michael W; Wells, Brian J; Yu, Changhong

2012-01-01

In medical society, the prognostic models, which use clinicopathologic features and predict prognosis after a certain treatment, have been externally validated and used in practice. In recent years, most research has focused on high dimensional genomic data and small sample sizes. Since clinically similar but molecularly heterogeneous tumors may produce different clinical outcomes, the combination of clinical and genomic information, which may be complementary, is crucial to improve the quality of prognostic predictions. However, there is a lack of an integrating scheme for clinic-genomic models due to the P ≥ N problem, in particular, for a parsimonious model. We propose a methodology to build a reduced yet accurate integrative model using a hybrid approach based on the Cox regression model, which uses several dimension reduction techniques, L₂ penalized maximum likelihood estimation (PMLE), and resampling methods to tackle the problem. The predictive accuracy of the modeling approach is assessed by several metrics via an independent and thorough scheme to compare competing methods. In breast cancer data studies on a metastasis and death event, we show that the proposed methodology can improve prediction accuracy and build a final model with a hybrid signature that is parsimonious when integrating both types of variables.

Study on UKF based federal integrated navigation for high dynamic aviation

NASA Astrophysics Data System (ADS)

Zhao, Gang; Shao, Wei; Chen, Kai; Yan, Jie

2011-08-01

High dynamic aircraft is a very attractive new generation vehicles, in which provides near space aviation with large flight envelope both speed and altitude, for example the hypersonic vehicles. The complex flight environments for high dynamic vehicles require high accuracy and stability navigation scheme. Since the conventional Strapdown Inertial Navigation System (SINS) and Global Position System (GPS) federal integrated scheme based on EKF (Extended Kalman Filter) is invalidation in GPS single blackout situation because of high speed flight, a new high precision and stability integrated navigation approach is presented in this paper, in which the SINS, GPS and Celestial Navigation System (CNS) is combined as a federal information fusion configuration based on nonlinear Unscented Kalman Filter (UKF) algorithm. Firstly, the new integrated system state error is modeled. According to this error model, the SINS system is used as the navigation solution mathematic platform. The SINS combine with GPS constitute one error estimation filter subsystem based on UKF to obtain local optimal estimation, and the SINS combine with CNS constitute another error estimation subsystem. A non-reset federated configuration filter based on partial information is proposed to fuse two local optimal estimations to get global optimal error estimation, and the global optimal estimation is used to correct the SINS navigation solution. The χ 2 fault detection method is used to detect the subsystem fault, and the fault subsystem is isolation through fault interval to protect system away from the divergence. The integrated system takes advantages of SINS, GPS and CNS to an immense improvement for high accuracy and reliably high dynamic navigation application. Simulation result shows that federated fusion of using GPS and CNS to revise SINS solution is reasonable and availably with good estimation performance, which are satisfied with the demands of high dynamic flight navigation. The UKF is superior than EKF based integrated scheme, in which has smaller estimation error and quickly convergence rate.

Neighborhood and Family Intersections: Prospective Implications for Mexican American Adolescents’ Mental Health

PubMed Central

White, Rebecca M. B.; Roosa, Mark W.; Zeiders, Katharine H.

2012-01-01

We present an integrated model for understanding Mexican American youth mental health within family, neighborhood, and cultural contexts. We combined two common perspectives on neighborhood effects to hypothesize that (a) parents’ perceptions of neighborhood risk would negatively impact their children’s mental health by disrupting key parenting and family processes, and (b) objective neighborhood risk would alter the effect parent and family processes had on youth mental health. We further incorporated a cultural perspective to hypothesize that an ethnic minority group’s culture-specific values may support parents to successfully confront neighborhood risk. We provided a conservative test of the integrated model by simultaneously examining three parenting and family process variables: maternal warmth, maternal harsh parenting, and family cohesion. The hypothesized model was estimated prospectively in a diverse, community-based sample of Mexican American adolescents and their mothers (N = 749) living in the Southwestern, U.S. Support for specific elements of the hypothesized model varied depending on the parenting or family process variable examined. For family cohesion results were consistent with the combined neighborhood perspectives. The effects of maternal warmth on youth mental health were altered by objective neighborhood risk. For harsh parenting results were somewhat consistent with the cultural perspective. The value of the integrated model for research on the impacts of family, neighborhood, and cultural contexts on youth mental health are discussed, as are implications for preventive interventions for Mexican American families and youth. PMID:22866932

Neighborhood and family intersections: prospective implications for Mexican American adolescents' mental health.

PubMed

White, Rebecca M B; Roosa, Mark W; Zeiders, Katharine H

2012-10-01

We present an integrated model for understanding Mexican American youth mental health within family, neighborhood, and cultural contexts. We combined two common perspectives on neighborhood effects to hypothesize that (a) parents' perceptions of neighborhood risk would negatively impact their children's mental health by disrupting key parenting and family processes, and (b) objective neighborhood risk would alter the effect parent and family processes had on youth mental health. We further incorporated a cultural perspective to hypothesize that an ethnic minority group's culture-specific values may support parents to successfully confront neighborhood risk. We provided a conservative test of the integrated model by simultaneously examining three parenting and family process variables: maternal warmth, maternal harsh parenting, and family cohesion. The hypothesized model was estimated prospectively in a diverse, community-based sample of Mexican American adolescents and their mothers (N = 749) living in the southwestern United States. Support for specific elements of the hypothesized model varied depending on the parenting or family process variable examined. For family cohesion results were consistent with the combined neighborhood perspectives. The effects of maternal warmth on youth mental health were altered by objective neighborhood risk. For harsh parenting, results were somewhat consistent with the cultural perspective. The value of the integrated model for research on the impacts of family, neighborhood, and cultural contexts on youth mental health are discussed, as are implications for preventive interventions for Mexican American families and youth. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

A Hyaluronan-Based Injectable Hydrogel Improves the Survival and Integration of Stem Cell Progeny following Transplantation.

PubMed

Ballios, Brian G; Cooke, Michael J; Donaldson, Laura; Coles, Brenda L K; Morshead, Cindi M; van der Kooy, Derek; Shoichet, Molly S

2015-06-09

The utility of stem cells and their progeny in adult transplantation models has been limited by poor survival and integration. We designed an injectable and bioresorbable hydrogel blend of hyaluronan and methylcellulose (HAMC) and tested it with two cell types in two animal models, thereby gaining an understanding of its general applicability for enhanced cell distribution, survival, integration, and functional repair relative to conventional cell delivery in saline. HAMC improves cell survival and integration of retinal stem cell (RSC)-derived rods in the retina. The pro-survival mechanism of HAMC is ascribed to the interaction of the CD44 receptor with HA. Transient disruption of the retinal outer limiting membrane, combined with HAMC delivery, results in significantly improved rod survival and visual function. HAMC also improves the distribution, viability, and functional repair of neural stem and progenitor cells (NSCs). The HAMC delivery system improves cell transplantation efficacy in two CNS models, suggesting broad applicability. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Innovation in Evaluating the Impact of Integrated Service-Delivery: The Integra Indexes of HIV and Reproductive Health Integration

PubMed Central

Mayhew, Susannah H.; Ploubidis, George B.; Sloggett, Andy; Church, Kathryn; Obure, Carol D.; Birdthistle, Isolde; Sweeney, Sedona; Warren, Charlotte E.; Watts, Charlotte; Vassall, Anna

2016-01-01

Background The body of knowledge on evaluating complex interventions for integrated healthcare lacks both common definitions of ‘integrated service delivery’ and standard measures of impact. Using multiple data sources in combination with statistical modelling the aim of this study is to develop a measure of HIV-reproductive health (HIV-RH) service integration that can be used to assess the degree of service integration, and the degree to which integration may have health benefits to clients, or reduce service costs. Methods and Findings Data were drawn from the Integra Initiative’s client flow (8,263 clients in Swaziland and 25,539 in Kenya) and costing tools implemented between 2008–2012 in 40 clinics providing RH services in Kenya and Swaziland. We used latent variable measurement models to derive dimensions of HIV-RH integration using these data, which quantified the extent and type of integration between HIV and RH services in Kenya and Swaziland. The modelling produced two clear and uncorrelated dimensions of integration at facility level leading to the development of two sub-indexes: a Structural Integration Index (integrated physical and human resource infrastructure) and a Functional Integration Index (integrated delivery of services to clients). The findings highlight the importance of multi-dimensional assessments of integration, suggesting that structural integration is not sufficient to achieve the integrated delivery of care to clients—i.e. “functional integration”. Conclusions These Indexes are an important methodological contribution for evaluating complex multi-service interventions. They help address the need to broaden traditional evaluations of integrated HIV-RH care through the incorporation of a functional integration measure, to avoid misleading conclusions on its ‘impact’ on health outcomes. This is particularly important for decision-makers seeking to promote integration in resource constrained environments. PMID:26800517

The interface between population and development models, plans and policies.

PubMed

Cohen, S I

1989-01-01

Scant attention has been given to integrating policy issues in population economics and development economics into more general frameworks. Reviewing the state of the art, this paper examines problems in incorporating population economics variables in development planning. Specifically, conceptual issues in defining population economics variables, modelling relationships between them, and operationalizing frameworks for decision making are explored with hopes of yielding tentative solutions. Several controversial policy issues affecting the development process are also examined in the closing section. 2 of these issues would be the social efficiency of interventions with fertility, and of resource allocations to human development. The effective combination between agriculture and industry in promoting and equitably distributing income growth among earning population groups is a 3rd issue of consideration. Finally, the paper looks at the optimal combination between transfer payments and provisions in kind in guaranteeing minimum consumption needs for poverty groups. Overall, the paper finds significant obstacles to refining the integration of population economics and development policy. Namely, integrating time and place dimensions in classifying people by activity, operationalizing population economics variable models to meet the practical situations of planning and programs, and assessing conflicts and complementarities between alternative policies pose problems. 2 scholarly comments follow the main body of the paper.

Agent-based modeling of deforestation in southern Yucatán, Mexico, and reforestation in the Midwest United States

PubMed Central

Manson, Steven M.; Evans, Tom

2007-01-01

We combine mixed-methods research with integrated agent-based modeling to understand land change and economic decision making in the United States and Mexico. This work demonstrates how sustainability science benefits from combining integrated agent-based modeling (which blends methods from the social, ecological, and information sciences) and mixed-methods research (which interleaves multiple approaches ranging from qualitative field research to quantitative laboratory experiments and interpretation of remotely sensed imagery). We test assumptions of utility-maximizing behavior in household-level landscape management in south-central Indiana, linking parcel data, land cover derived from aerial photography, and findings from laboratory experiments. We examine the role of uncertainty and limited information, preferences, differential demographic attributes, and past experience and future time horizons. We also use evolutionary programming to represent bounded rationality in agriculturalist households in the southern Yucatán of Mexico. This approach captures realistic rule of thumb strategies while identifying social and environmental factors in a manner similar to econometric models. These case studies highlight the role of computational models of decision making in land-change contexts and advance our understanding of decision making in general. PMID:18093928

A small sample test of the factor structure of postural movement and bilateral motor integration using structural equation modeling.

PubMed

Lin, Chin-Kai; Wu, Huey-Min; Lin, Chung-Hui; Wu, Yuh-Yih; Wu, Pei-Fang; Kuo, Bor-Chen; Yeung, Kwok-Tak

2012-10-01

The goal of this study was to examine the relationship between the validity of postural movement and bilateral motor integration in terms of sensory integration theory. Participants in this study were 61 Chinese children ages 48 to 70 months. Structural equation modeling was applied to assess the relation between measures tapping postural movement and bilateral motor integration: for postural movement, the measures involve the Monkey Task, Side-Sit Co-contraction, Prone on Elbows, Wheelbarrow Walk, Airplane, and Scooter Board Co-contraction from the DeGangi-Berk Test of Sensory Integration, and Standing Balance with Eyes Closed/Opened in Southern California Sensory Integration Tests. For bilateral motor integration, the measures chosen were the Rolling Pin Activity, Jump and Turn, Diadokokinesis, Drumming, and Upper Extremity Control from the DeGangi-Berk Test of Sensory Integration, and Cross the Midline in Southern California Sensory Integration Tests (SCSIT). Postural movement was highly correlated with the bilateral motor integration. The factor structure fit the theoretical conceptualization, classifying postural movement and bilateral motor integration together in the same category. Therapists could combine two separate objectives (postural movement and bilateral motor integration) of intervention in an activity to improve the adaptive skills based on the vestibular-proprioceptive integration.

Dynamic coupling of three hydrodynamic models

NASA Astrophysics Data System (ADS)

Hartnack, J. N.; Philip, G. T.; Rungoe, M.; Smith, G.; Johann, G.; Larsen, O.; Gregersen, J.; Butts, M. B.

2008-12-01

The need for integrated modelling is evidently present within the field of flood management and flood forecasting. Engineers, modellers and managers are faced with flood problems which transcend the classical hydrodynamic fields of urban, river and coastal flooding. Historically the modeller has been faced with having to select one hydrodynamic model to cover all the aspects of the potentially complex dynamics occurring in a flooding situation. Such a single hydrodynamic model does not cover all dynamics of flood modelling equally well. Thus the ideal choice may in fact be a combination of models. Models combining two numerical/hydrodynamic models are becoming more standard, typically these models combine a 1D river model with a 2D overland flow model or alternatively a 1D sewer/collection system model with a 2D overland solver. In complex coastal/urban areas the flood dynamics may include rivers/streams, collection/storm water systems along with the overland flow. The dynamics within all three areas is of the same time scale and there is feedback in the system across the couplings. These two aspects dictate a fully dynamic three way coupling as opposed to running the models sequentially. It will be shown that the main challenges of the three way coupling are time step issues related to the difference in numerical schemes used in the three model components and numerical instabilities caused by the linking of the model components. MIKE FLOOD combines the models MIKE 11, MIKE 21 and MOUSE into one modelling framework which makes it possible to couple any combination of river, urban and overland flow fully dynamically. The MIKE FLOOD framework will be presented with an overview of the coupling possibilities. The flood modelling concept will be illustrated through real life cases in Australia and in Germany. The real life cases reflect dynamics and interactions across all three model components which are not possible to reproduce using a two-way coupling alone. The models comprise 2D inundation modelling, river networks with multiple structures (pumps, weirs, culverts), urban drainage networks as well as dam break modelling. The models were used to quantify the results of storm events or failures (dam break, pumping failures etc) coinciding with high discharge in river system and heavy rainfall. The detailed representation of the flow path through the city allowed a direct assessment of flood risk Thus it is found that the three-way coupled model is a practical and useful tool for integrated flood management.

Adaptive exponential integrate-and-fire model as an effective description of neuronal activity.

PubMed

Brette, Romain; Gerstner, Wulfram

2005-11-01

We introduce a two-dimensional integrate-and-fire model that combines an exponential spike mechanism with an adaptation equation, based on recent theoretical findings. We describe a systematic method to estimate its parameters with simple electrophysiological protocols (current-clamp injection of pulses and ramps) and apply it to a detailed conductance-based model of a regular spiking neuron. Our simple model predicts correctly the timing of 96% of the spikes (+/-2 ms) of the detailed model in response to injection of noisy synaptic conductances. The model is especially reliable in high-conductance states, typical of cortical activity in vivo, in which intrinsic conductances were found to have a reduced role in shaping spike trains. These results are promising because this simple model has enough expressive power to reproduce qualitatively several electrophysiological classes described in vitro.

Simulation of a steady-state integrated human thermal system.

NASA Technical Reports Server (NTRS)

Hsu, F. T.; Fan, L. T.; Hwang, C. L.

1972-01-01

The mathematical model of an integrated human thermal system is formulated. The system consists of an external thermal regulation device on the human body. The purpose of the device (a network of cooling tubes held in contact with the surface of the skin) is to maintain the human body in a state of thermoneutrality. The device is controlled by varying the inlet coolant temperature and coolant mass flow rate. The differential equations of the model are approximated by a set of algebraic equations which result from the application of the explicit forward finite difference method to the differential equations. The integrated human thermal system is simulated for a variety of combinations of the inlet coolant temperature, coolant mass flow rate, and metabolic rates.

Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact Scenarios

NASA Technical Reports Server (NTRS)

Annett, Martin S.; Horta, Lucas G.; Jackson, Karen E.; Polanco, Michael A.; Littell, Justin D.

2012-01-01

Two full-scale crash tests of an MD-500 helicopter were conducted in 2009 and 2010 at NASA Langley's Landing and Impact Research Facility in support of NASA s Subsonic Rotary Wing Crashworthiness Project. The first crash test was conducted to evaluate the performance of an externally mounted composite deployable energy absorber (DEA) under combined impact conditions. In the second crash test, the energy absorber was removed to establish baseline loads that are regarded as severe but survivable. The presence of this energy absorbing device reduced the peak impact acceleration levels by a factor of three. Accelerations and kinematic data collected from the crash tests were compared to a system-integrated finite element model of the test article developed in parallel with the test program. In preparation for the full-scale crash test, a series of sub-scale and MD-500 mass simulator tests were conducted to evaluate the impact performances of various components and subsystems, including new crush tubes and the DEA blocks. Parameters defined for the system-integrated finite element model were determined from these tests. Results from 19 accelerometers placed throughout the airframe were compared to finite element model responses. The model developed for the purposes of predicting acceleration responses from the first crash test was inadequate when evaluating more severe conditions seen in the second crash test. A newly developed model calibration approach that includes uncertainty estimation, parameter sensitivity, impact shape orthogonality, and numerical optimization was used to calibrate model results for the full-scale crash test without the DEA. This combination of heuristic and quantitative methods identified modeling deficiencies, evaluated parameter importance, and proposed required model changes. The multidimensional calibration techniques presented here are particularly effective in identifying model adequacy. Acceleration results for the calibrated model were compared to test results and the original model results. There was a noticeable improvement in the pilot and copilot region, a slight improvement in the occupant model response, and an over-stiffening effect in the passenger region. One lesson learned was that this approach should be adopted early on, in combination with the building-block approaches that are customarily used, for model development and pretest predictions. Complete crash simulations with validated finite element models can be used to satisfy crash certification requirements, potentially reducing overall development costs.

A rotorcraft flight/propulsion control integration study

NASA Technical Reports Server (NTRS)

Ruttledge, D. G. C.

1986-01-01

An eclectic approach was taken to a study of the integration of digital flight and propulsion controls for helicopters. The basis of the evaluation was the current Gen Hel simulation of the UH-60A Black Hawk helicopter with a model of the GE T700 engine. A list of flight maneuver segments to be used in evaluating the effectiveness of such an integrated control system was composed, based on past experience and an extensive survey of the U.S. Army Air-to-Air Combat Test data. A number of possible features of an integrated system were examined and screened. Those that survived the screening were combined into a design that replaced the T700 fuel control and part of the control system in the UH-60A Gen Hel simulation. This design included portions of an existing pragmatic adaptive fuel control designed by the Chandler-Evans Company and an linear quadratic regulator (LQR) based N(p) governor designed by the GE company, combined with changes in the basic Sikorsky Aircraft designed control system. The integrated system exhibited improved total performance in many areas of the flight envelope.

ADMET Evaluation in Drug Discovery. 16. Predicting hERG Blockers by Combining Multiple Pharmacophores and Machine Learning Approaches.

PubMed

Wang, Shuangquan; Sun, Huiyong; Liu, Hui; Li, Dan; Li, Youyong; Hou, Tingjun

2016-08-01

Blockade of human ether-à-go-go related gene (hERG) channel by compounds may lead to drug-induced QT prolongation, arrhythmia, and Torsades de Pointes (TdP), and therefore reliable prediction of hERG liability in the early stages of drug design is quite important to reduce the risk of cardiotoxicity-related attritions in the later development stages. In this study, pharmacophore modeling and machine learning approaches were combined to construct classification models to distinguish hERG active from inactive compounds based on a diverse data set. First, an optimal ensemble of pharmacophore hypotheses that had good capability to differentiate hERG active from inactive compounds was identified by the recursive partitioning (RP) approach. Then, the naive Bayesian classification (NBC) and support vector machine (SVM) approaches were employed to construct classification models by integrating multiple important pharmacophore hypotheses. The integrated classification models showed improved predictive capability over any single pharmacophore hypothesis, suggesting that the broad binding polyspecificity of hERG can only be well characterized by multiple pharmacophores. The best SVM model achieved the prediction accuracies of 84.7% for the training set and 82.1% for the external test set. Notably, the accuracies for the hERG blockers and nonblockers in the test set reached 83.6% and 78.2%, respectively. Analysis of significant pharmacophores helps to understand the multimechanisms of action of hERG blockers. We believe that the combination of pharmacophore modeling and SVM is a powerful strategy to develop reliable theoretical models for the prediction of potential hERG liability.

A Community Framework for Integrative, Coupled Modeling of Human-Earth Systems

NASA Astrophysics Data System (ADS)

Barton, C. M.; Nelson, G. C.; Tucker, G. E.; Lee, A.; Porter, C.; Ullah, I.; Hutton, E.; Hoogenboom, G.; Rogers, K. G.; Pritchard, C.

2017-12-01

We live today in a humanized world, where critical zone dynamics are driven by coupled human and biophysical processes. First generation modeling platforms have been invaluable in providing insight into dynamics of biophysical systems and social systems. But to understand today's humanized planet scientifically and to manage it sustainably, we need integrative modeling of this coupled human-Earth system. To address both scientific and policy questions, we also need modeling that can represent variable combinations of human-Earth system processes at multiple scales. Simply adding more code needed to do this to large, legacy first generation models is impractical, expensive, and will make them even more difficult to evaluate or understand. We need an approach to modeling that mirrors and benefits from the architecture of the complexly coupled systems we hope to model. Building on a series of international workshops over the past two years, we present a community framework to enable and support an ecosystem of diverse models as components that can be interconnected as needed to facilitate understanding of a range of complex human-earth systems interactions. Models are containerized in Docker to make them platform independent. A Basic Modeling Interface and Standard Names ontology (developed by the Community Surface Dynamics Modeling System) is applied to make them interoperable. They are then transformed into RESTful micro-services to allow them to be connected and run in a browser environment. This enables a flexible, multi-scale modeling environment to help address diverse issues with combinations of smaller, focused, component models that are easier to understand and evaluate. We plan to develop, deploy, and maintain this framework for integrated, coupled modeling in an open-source collaborative development environment that can democratize access to advanced technology and benefit from diverse global participation in model development. We also present an initial proof-of-concept of this framework, coupling a widely used agricultural crop model (DSSAT) with a widely used hydrology model (TopoFlow).

Features of spatial and functional segregation and integration of the primate connectome revealed by trade-off between wiring cost and efficiency

PubMed Central

Chen, Yuhan; Wang, Shengjun

2017-01-01

The primate connectome, possessing a characteristic global topology and specific regional connectivity profiles, is well organized to support both segregated and integrated brain function. However, the organization mechanisms shaping the characteristic connectivity and its relationship to functional requirements remain unclear. The primate brain connectome is shaped by metabolic economy as well as functional values. Here, we explored the influence of two competing factors and additional advanced functional requirements on the primate connectome employing an optimal trade-off model between neural wiring cost and the representative functional requirement of processing efficiency. Moreover, we compared this model with a generative model combining spatial distance and topological similarity, with the objective of statistically reproducing multiple topological features of the network. The primate connectome indeed displays a cost-efficiency trade-off and that up to 67% of the connections were recovered by optimal combination of the two basic factors of wiring economy and processing efficiency, clearly higher than the proportion of connections (56%) explained by the generative model. While not explicitly aimed for, the trade-off model captured several key topological features of the real connectome as the generative model, yet better explained the connectivity of most regions. The majority of the remaining 33% of connections unexplained by the best trade-off model were long-distance links, which are concentrated on few cortical areas, termed long-distance connectors (LDCs). The LDCs are mainly non-hubs, but form a densely connected group overlapping on spatially segregated functional modalities. LDCs are crucial for both functional segregation and integration across different scales. These organization features revealed by the optimization analysis provide evidence that the demands of advanced functional segregation and integration among spatially distributed regions may play a significant role in shaping the cortical connectome, in addition to the basic cost-efficiency trade-off. These findings also shed light on inherent vulnerabilities of brain networks in diseases. PMID:28961235

Features of spatial and functional segregation and integration of the primate connectome revealed by trade-off between wiring cost and efficiency.

PubMed

Chen, Yuhan; Wang, Shengjun; Hilgetag, Claus C; Zhou, Changsong

2017-09-01

The primate connectome, possessing a characteristic global topology and specific regional connectivity profiles, is well organized to support both segregated and integrated brain function. However, the organization mechanisms shaping the characteristic connectivity and its relationship to functional requirements remain unclear. The primate brain connectome is shaped by metabolic economy as well as functional values. Here, we explored the influence of two competing factors and additional advanced functional requirements on the primate connectome employing an optimal trade-off model between neural wiring cost and the representative functional requirement of processing efficiency. Moreover, we compared this model with a generative model combining spatial distance and topological similarity, with the objective of statistically reproducing multiple topological features of the network. The primate connectome indeed displays a cost-efficiency trade-off and that up to 67% of the connections were recovered by optimal combination of the two basic factors of wiring economy and processing efficiency, clearly higher than the proportion of connections (56%) explained by the generative model. While not explicitly aimed for, the trade-off model captured several key topological features of the real connectome as the generative model, yet better explained the connectivity of most regions. The majority of the remaining 33% of connections unexplained by the best trade-off model were long-distance links, which are concentrated on few cortical areas, termed long-distance connectors (LDCs). The LDCs are mainly non-hubs, but form a densely connected group overlapping on spatially segregated functional modalities. LDCs are crucial for both functional segregation and integration across different scales. These organization features revealed by the optimization analysis provide evidence that the demands of advanced functional segregation and integration among spatially distributed regions may play a significant role in shaping the cortical connectome, in addition to the basic cost-efficiency trade-off. These findings also shed light on inherent vulnerabilities of brain networks in diseases.

Identification of the mechanism of action of a glucokinase activator from oral glucose tolerance test data in type 2 diabetic patients based on an integrated glucose-insulin model.

PubMed

Jauslin, Petra M; Karlsson, Mats O; Frey, Nicolas

2012-12-01

A mechanistic drug-disease model was developed on the basis of a previously published integrated glucose-insulin model by Jauslin et al. A glucokinase activator was used as a test compound to evaluate the model's ability to identify a drug's mechanism of action and estimate its effects on glucose and insulin profiles following oral glucose tolerance tests. A kinetic-pharmacodynamic approach was chosen to describe the drug's pharmacodynamic effects in a dose-response-time model. Four possible mechanisms of action of antidiabetic drugs were evaluated, and the corresponding affected model parameters were identified: insulin secretion, glucose production, insulin effect on glucose elimination, and insulin-independent glucose elimination. Inclusion of drug effects in the model at these sites of action was first tested one-by-one and then in combination. The results demonstrate the ability of this model to identify the dual mechanism of action of a glucokinase activator and describe and predict its effects: Estimating a stimulating drug effect on insulin secretion and an inhibiting effect on glucose output resulted in a significantly better model fit than any other combination of effect sites. The model may be used for dose finding in early clinical drug development and for gaining more insight into a drug candidate's mechanism of action.

RACE/A: An Architectural Account of the Interactions between Learning, Task Control, and Retrieval Dynamics

ERIC Educational Resources Information Center

van Maanen, Leendert; van Rijn, Hedderik; Taatgen, Niels

2012-01-01

This article discusses how sequential sampling models can be integrated in a cognitive architecture. The new theory Retrieval by Accumulating Evidence in an Architecture (RACE/A) combines the level of detail typically provided by sequential sampling models with the level of task complexity typically provided by cognitive architectures. We will use…

Professional Development for Secondary School Mathematics Teachers: A Peer Mentoring Model

ERIC Educational Resources Information Center

Kensington-Miller, Barbara

2012-01-01

Professional development is important for all teachers, and in low socio-economic schools where the challenges of teaching are greater this need is crucial. A model involving a combination of one-on-one peer mentoring integrated with group peer mentoring was piloted with experienced mathematics teachers of senior students in low socio-economic…

The Impact of Three Factors on the Recovery of Item Parameters for the Three-Parameter Logistic Model

ERIC Educational Resources Information Center

Kim, Kyung Yong; Lee, Won-Chan

2017-01-01

This article provides a detailed description of three factors (specification of the ability distribution, numerical integration, and frame of reference for the item parameter estimates) that might affect the item parameter estimation of the three-parameter logistic model, and compares five item calibration methods, which are combinations of the…

Selected National Cancer Institute Breast Cancer Research Topics | NIH MedlinePlus the Magazine

MedlinePlus

... effective treatments for these women. The Integrative Cancer Biology Program combines experimental and clinical research with mathematical modeling to gain new insights into cancer biology, prevention, diagnostics, and treatments. Multiple centers are developing ...

Integrating centralized and decentralized organization structures: an education and development model.

PubMed

Sheriff, R; Banks, A

2001-01-01

Organization change efforts have led to critically examining the structure of education and development departments within hospitals. This qualitative study evaluated an education and development model in an academic health sciences center. The model combines centralization and decentralization. The study results can be used by staff development educators and administrators when organization structure is questioned. This particular model maximizes the benefits and minimizes the limitations of centralized and decentralized structures.

Modeling of gas turbine - solid oxide fuel cell systems for combined propulsion and power on aircraft

NASA Astrophysics Data System (ADS)

Waters, Daniel Francis

This dissertation investigates the use of gas turbine (GT) engine integrated solid oxide fuel cells (SOFCs) to reduce fuel burn in aircraft with large electrical loads like sensor-laden unmanned air vehicles (UAVs). The concept offers a number of advantages: the GT absorbs many SOFC balance of plant functions (supplying fuel, air, and heat to the fuel cell) thereby reducing the number of components in the system; the GT supplies fuel and pressurized air that significantly increases SOFC performance; heat and unreacted fuel from the SOFC are recaptured by the GT cycle offsetting system-level losses; good transient response of the GT cycle compensates for poor transient response of the SOFC. The net result is a system that can supply more electrical power more efficiently than comparable engine-generator systems with only modest (<10%) decrease in power density. Thermodynamic models of SOFCs, catalytic partial oxidation (CPOx) reactors, and three GT engine types (turbojet, combined exhaust turbofan, separate exhaust turbofan) are developed that account for equilibrium gas phase and electrochemical reaction, pressure losses, and heat losses in ways that capture `down-the-channel' effects (a level of fidelity necessary for making meaningful performance, mass, and volume estimates). Models are created in a NASA-developed environment called Numerical Propulsion System Simulation (NPSS). A sensitivity analysis identifies important design parameters and translates uncertainties in model parameters into uncertainties in overall performance. GT-SOFC integrations reduce fuel burn 3-4% in 50 kW systems on 35 kN rated engines (all types) with overall uncertainty <1%. Reductions of 15-20% are possible at the 200 kW power level. GT-SOFCs are also able to provide more electric power (factors >3 in some cases) than generator-based systems before encountering turbine inlet temperature limits. Aerodynamic drag effects of engine-airframe integration are by far the most important limiter of the combined propulsion/electrical generation concept. However, up to 100-200 kW can be produced in a bypass ratio = 8, overall pressure ratio = 40 turbofan with little or no drag penalty. This study shows that it is possible to create cooperatively integrated GT-SOFC systems for combined propulsion and power with better overall performance than stand-alone components.

A semantic web framework to integrate cancer omics data with biological knowledge

PubMed Central

2012-01-01

Background The RDF triple provides a simple linguistic means of describing limitless types of information. Triples can be flexibly combined into a unified data source we call a semantic model. Semantic models open new possibilities for the integration of variegated biological data. We use Semantic Web technology to explicate high throughput clinical data in the context of fundamental biological knowledge. We have extended Corvus, a data warehouse which provides a uniform interface to various forms of Omics data, by providing a SPARQL endpoint. With the querying and reasoning tools made possible by the Semantic Web, we were able to explore quantitative semantic models retrieved from Corvus in the light of systematic biological knowledge. Results For this paper, we merged semantic models containing genomic, transcriptomic and epigenomic data from melanoma samples with two semantic models of functional data - one containing Gene Ontology (GO) data, the other, regulatory networks constructed from transcription factor binding information. These two semantic models were created in an ad hoc manner but support a common interface for integration with the quantitative semantic models. Such combined semantic models allow us to pose significant translational medicine questions. Here, we study the interplay between a cell's molecular state and its response to anti-cancer therapy by exploring the resistance of cancer cells to Decitabine, a demethylating agent. Conclusions We were able to generate a testable hypothesis to explain how Decitabine fights cancer - namely, that it targets apoptosis-related gene promoters predominantly in Decitabine-sensitive cell lines, thus conveying its cytotoxic effect by activating the apoptosis pathway. Our research provides a framework whereby similar hypotheses can be developed easily. PMID:22373303

Ecological connectivity networks in rapidly expanding cities.

PubMed

Nor, Amal Najihah M; Corstanje, Ron; Harris, Jim A; Grafius, Darren R; Siriwardena, Gavin M

2017-06-01

Urban expansion increases fragmentation of the landscape. In effect, fragmentation decreases connectivity, causes green space loss and impacts upon the ecology and function of green space. Restoration of the functionality of green space often requires restoring the ecological connectivity of this green space within the city matrix. However, identifying ecological corridors that integrate different structural and functional connectivity of green space remains vague. Assessing connectivity for developing an ecological network by using efficient models is essential to improve these networks under rapid urban expansion. This paper presents a novel methodological approach to assess and model connectivity for the Eurasian tree sparrow ( Passer montanus ) and Yellow-vented bulbul ( Pycnonotus goiavier ) in three cities (Kuala Lumpur, Malaysia; Jakarta, Indonesia and Metro Manila, Philippines). The approach identifies potential priority corridors for ecological connectivity networks. The study combined circuit models, connectivity analysis and least-cost models to identify potential corridors by integrating structure and function of green space patches to provide reliable ecological connectivity network models in the cities. Relevant parameters such as landscape resistance and green space structure (vegetation density, patch size and patch distance) were derived from an expert and literature-based approach based on the preference of bird behaviour. The integrated models allowed the assessment of connectivity for both species using different measures of green space structure revealing the potential corridors and least-cost pathways for both bird species at the patch sites. The implementation of improvements to the identified corridors could increase the connectivity of green space. This study provides examples of how combining models can contribute to the improvement of ecological networks in rapidly expanding cities and demonstrates the usefulness of such models for biodiversity conservation and urban planning.

Dynamic modeling and evaluation of solid oxide fuel cell - combined heat and power system operating strategies

NASA Astrophysics Data System (ADS)

Nanaeda, Kimihiro; Mueller, Fabian; Brouwer, Jacob; Samuelsen, Scott

Operating strategies of solid oxide fuel cell (SOFC) combined heat and power (CHP) systems are developed and evaluated from a utility, and end-user perspective using a fully integrated SOFC-CHP system dynamic model that resolves the physical states, thermal integration and overall efficiency of the system. The model can be modified for any SOFC-CHP system, but the present analysis is applied to a hotel in southern California based on measured electric and heating loads. Analysis indicates that combined heat and power systems can be operated to benefit both the end-users and the utility, providing more efficient electric generation as well as grid ancillary services, namely dispatchable urban power. Design and operating strategies considered in the paper include optimal sizing of the fuel cell, thermal energy storage to dispatch heat, and operating the fuel cell to provide flexible grid power. Analysis results indicate that with a 13.1% average increase in price-of-electricity (POE), the system can provide the grid with a 50% operating range of dispatchable urban power at an overall thermal efficiency of 80%. This grid-support operating mode increases the operational flexibility of the SOFC-CHP system, which may make the technology an important utility asset for accommodating the increased penetration of intermittent renewable power.

Integrating a Detailed Agricultural Model in a Global Economic Framework: New methods for assessment of climate mitigation and adaptation opportunities

NASA Astrophysics Data System (ADS)

Thomson, A. M.; Izaurralde, R. C.; Calvin, K.; Zhang, X.; Wise, M.; West, T. O.

2010-12-01

Climate change and food security are global issues increasingly linked through human decision making that takes place across all scales from on-farm management actions to international climate negotiations. Understanding how agricultural systems can respond to climate change, through mitigation or adaptation, while still supplying sufficient food to feed a growing global population, thus requires a multi-sector tool in a global economic framework. Integrated assessment models are one such tool, however they are typically driven by historical aggregate statistics of production in combination with exogenous assumptions of future trends in agricultural productivity; they are not yet capable of exploring agricultural management practices as climate adaptation or mitigation strategies. Yet there are agricultural models capable of detailed biophysical modeling of farm management and climate impacts on crop yield, soil erosion and C and greenhouse gas emissions, although these are typically applied at point scales that are incompatible with coarse resolution integrated assessment modeling. To combine the relative strengths of these modeling systems, we are using the agricultural model EPIC (Environmental Policy Integrated Climate), applied in a geographic data framework for regional analyses, to provide input to the global economic model GCAM (Global Change Assessment Model). The initial phase of our approach focuses on a pilot region of the Midwest United States, a highly productive agricultural area. We apply EPIC, a point based biophysical process model, at 60 m spatial resolution within this domain and aggregate the results to GCAM agriculture and land use subregions for the United States. GCAM is then initialized with multiple management options for key food and bioenergy crops. Using EPIC to distinguish these management options based on grain yield, residue yield, soil C change and cost differences, GCAM then simulates the optimum distribution of the available management options to meet demands for food and energy over the next century. The coupled models provide a new platform for evaluating future changes in agricultural management based on food demand, bioenergy demand, and changes in crop yield and soil C under a changing climate. This framework can be applied to evaluate the economically and biophysically optimal distribution of management under future climates.

Evidence-based integrative medicine in clinical veterinary oncology.

PubMed

Raditic, Donna M; Bartges, Joseph W

2014-09-01

Integrative medicine is the combined use of complementary and alternative medicine with conventional or traditional Western medicine systems. The demand for integrative veterinary medicine is growing, but evidence-based research on its efficacy is limited. In veterinary clinical oncology, such research could be translated to human medicine, because veterinary patients with spontaneous tumors are valuable translational models for human cancers. An overview of specific herbs, botanics, dietary supplements, and acupuncture evaluated in dogs, in vitro canine cells, and other relevant species both in vivo and in vitro is presented for their potential use as integrative therapies in veterinary clinical oncology. Published by Elsevier Inc.

Recovery Act: An Integrated Experimental and Numerical Study: Developing a Reaction Transport Model that Couples Chemical Reactions of Mineral Dissolution/Precipitation with Spatial and Temporal Flow Variations.

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

Saar, Martin O.; Seyfried, Jr., William E.; Longmire, Ellen K.

2016-06-24

A total of 12 publications and 23 abstracts were produced as a result of this study. In particular, the compilation of a thermodynamic database utilizing consistent, current thermodynamic data is a major step toward accurately modeling multi-phase fluid interactions with solids. Existing databases designed for aqueous fluids did not mesh well with existing solid phase databases. Addition of a second liquid phase (CO2) magnifies the inconsistencies between aqueous and solid thermodynamic databases. Overall, the combination of high temperature and pressure lab studies (task 1), using a purpose built apparatus, and solid characterization (task 2), using XRCT and more developed technologies,more » allowed observation of dissolution and precipitation processes under CO2 reservoir conditions. These observations were combined with results from PIV experiments on multi-phase fluids (task 3) in typical flow path geometries. The results of the tasks 1, 2, and 3 were compiled and integrated into numerical models utilizing Lattice-Boltzmann simulations (task 4) to realistically model the physical processes and were ultimately folded into TOUGH2 code for reservoir scale modeling (task 5). Compilation of the thermodynamic database assisted comparisons to PIV experiments (Task 3) and greatly improved Lattice Boltzmann (Task 4) and TOUGH2 simulations (Task 5). PIV (Task 3) and experimental apparatus (Task 1) have identified problem areas in TOUGHREACT code. Additional lab experiments and coding work has been integrated into an improved numerical modeling code.« less

Peptide neuromodulation in invertebrate model systems

PubMed Central

Taghert, Paul H.; Nitabach, Michael N.

2012-01-01

Neuropeptides modulate neural circuits controlling adaptive animal behaviors and physiological processes, such as feeding/metabolism, reproductive behaviors, circadian rhythms, central pattern generation, and sensorimotor integration. Invertebrate model systems have enabled detailed experimental analysis using combined genetic, behavioral, and physiological approaches. Here we review selected examples of neuropeptide modulation in crustaceans, mollusks, insects, and nematodes, with a particular emphasis on the genetic model organisms Drosophila melanogaster and Caenorhabditis elegans, where remarkable progress has been made. On the basis of this survey, we provide several integrating conceptual principles for understanding how neuropeptides modulate circuit function, and also propose that continued progress in this area requires increased emphasis on the development of richer, more sophisticated behavioral paradigms. PMID:23040808

Integration of Five Health Behaviour Models: Common Strengths and Unique Contributions to Understanding Condom Use

PubMed Central

Reid, Allecia E.; Aiken, Leona S.

2011-01-01

The purpose of this research was to select from the health belief model (HBM), theories of reasoned action (TRA) and planned behaviour (TPB), information-motivation-behavioural skills model (IMB), and social cognitive theory (SCT) the strongest longitudinal predictors of women’s condom use and to combine these constructs into a single integrated model of condom use. The integrated model was evaluated for prediction of condom use among young women who had steady versus casual partners. At Time 1, all constructs of the five models and condom use were assessed in an initial and a replication sample (n= 193, n= 161). Condom use reassessed 8 weeks later (Time 2) served as the main outcome. Information from IMB, perceived susceptibility, benefits, and barriers from HBM, self-efficacy and self-evaluative expectancies from SCT, and partner norm and attitudes from TPB served as indirect or direct predictors of condom use. All paths replicated across samples. Direct predictors of behaviour varied with relationship status: self-efficacy significantly predicted condom use for women with casual partners, while attitude and partner norm predicted for those with steady partners. Integrated psychosocial models, rich in constructs and relationships drawn from multiple theories of behaviour, may provide a more complete characterization of health protective behaviour. PMID:21678166

Dissecting Cell-Fate Determination Through Integrated Mathematical Modeling of the ERK/MAPK Signaling Pathway.

PubMed

Shin, Sung-Young; Nguyen, Lan K

2017-01-01

The past three decades have witnessed an enormous progress in the elucidation of the ERK/MAPK signaling pathway and its involvement in various cellular processes. Because of its importance and complex wiring, the ERK pathway has been an intensive subject for mathematical modeling, which facilitates the unraveling of key dynamic properties and behaviors of the pathway. Recently, however, it became evident that the pathway does not act in isolation but closely interacts with many other pathways to coordinate various cellular outcomes under different pathophysiological contexts. This has led to an increasing number of integrated, large-scale models that link the ERK pathway to other functionally important pathways. In this chapter, we first discuss the essential steps in model development and notable models of the ERK pathway. We then use three examples of integrated, multipathway models to investigate how crosstalk of ERK signaling with other pathways regulates cell-fate decision-making in various physiological and disease contexts. Specifically, we focus on ERK interactions with the phosphoinositide-3 kinase (PI3K), c-Jun N-terminal kinase (JNK), and β-adrenergic receptor (β-AR) signaling pathways. We conclude that integrated modeling in combination with wet-lab experimentation have been and will be instrumental in gaining an in-depth understanding of ERK signaling in multiple biological contexts.

Integrating statistical and process-based models to produce probabilistic landslide hazard at regional scale

NASA Astrophysics Data System (ADS)

Strauch, R. L.; Istanbulluoglu, E.

2017-12-01

We develop a landslide hazard modeling approach that integrates a data-driven statistical model and a probabilistic process-based shallow landslide model for mapping probability of landslide initiation, transport, and deposition at regional scales. The empirical model integrates the influence of seven site attribute (SA) classes: elevation, slope, curvature, aspect, land use-land cover, lithology, and topographic wetness index, on over 1,600 observed landslides using a frequency ratio (FR) approach. A susceptibility index is calculated by adding FRs for each SA on a grid-cell basis. Using landslide observations we relate susceptibility index to an empirically-derived probability of landslide impact. This probability is combined with results from a physically-based model to produce an integrated probabilistic map. Slope was key in landslide initiation while deposition was linked to lithology and elevation. Vegetation transition from forest to alpine vegetation and barren land cover with lower root cohesion leads to higher frequency of initiation. Aspect effects are likely linked to differences in root cohesion and moisture controlled by solar insulation and snow. We demonstrate the model in the North Cascades of Washington, USA and identify locations of high and low probability of landslide impacts that can be used by land managers in their design, planning, and maintenance.

The Balance-Scale Task Revisited: A Comparison of Statistical Models for Rule-Based and Information-Integration Theories of Proportional Reasoning

PubMed Central

Hofman, Abe D.; Visser, Ingmar; Jansen, Brenda R. J.; van der Maas, Han L. J.

2015-01-01

We propose and test three statistical models for the analysis of children’s responses to the balance scale task, a seminal task to study proportional reasoning. We use a latent class modelling approach to formulate a rule-based latent class model (RB LCM) following from a rule-based perspective on proportional reasoning and a new statistical model, the Weighted Sum Model, following from an information-integration approach. Moreover, a hybrid LCM using item covariates is proposed, combining aspects of both a rule-based and information-integration perspective. These models are applied to two different datasets, a standard paper-and-pencil test dataset (N = 779), and a dataset collected within an online learning environment that included direct feedback, time-pressure, and a reward system (N = 808). For the paper-and-pencil dataset the RB LCM resulted in the best fit, whereas for the online dataset the hybrid LCM provided the best fit. The standard paper-and-pencil dataset yielded more evidence for distinct solution rules than the online data set in which quantitative item characteristics are more prominent in determining responses. These results shed new light on the discussion on sequential rule-based and information-integration perspectives of cognitive development. PMID:26505905

PARAGON: A Systematic, Integrated Approach to Aerosol Observation and Modeling

NASA Technical Reports Server (NTRS)

Diner, David J.; Kahn, Ralph A.; Braverman, Amy J.; Davies, Roger; Martonchik, John V.; Menzies, Robert T.; Ackerman, Thomas P.; Seinfeld, John H.; Anderson, Theodore L.; Charlson, Robert J.;

Massive integration of diverse protein quality assessment methods to improve template based modeling in CASP11

PubMed Central

Cao, Renzhi; Bhattacharya, Debswapna; Adhikari, Badri; Li, Jilong; Cheng, Jianlin

2015-01-01

Model evaluation and selection is an important step and a big challenge in template-based protein structure prediction. Individual model quality assessment methods designed for recognizing some specific properties of protein structures often fail to consistently select good models from a model pool because of their limitations. Therefore, combining multiple complimentary quality assessment methods is useful for improving model ranking and consequently tertiary structure prediction. Here, we report the performance and analysis of our human tertiary structure predictor (MULTICOM) based on the massive integration of 14 diverse complementary quality assessment methods that was successfully benchmarked in the 11th Critical Assessment of Techniques of Protein Structure prediction (CASP11). The predictions of MULTICOM for 39 template-based domains were rigorously assessed by six scoring metrics covering global topology of Cα trace, local all-atom fitness, side chain quality, and physical reasonableness of the model. The results show that the massive integration of complementary, diverse single-model and multi-model quality assessment methods can effectively leverage the strength of single-model methods in distinguishing quality variation among similar good models and the advantage of multi-model quality assessment methods of identifying reasonable average-quality models. The overall excellent performance of the MULTICOM predictor demonstrates that integrating a large number of model quality assessment methods in conjunction with model clustering is a useful approach to improve the accuracy, diversity, and consequently robustness of template-based protein structure prediction. PMID:26369671

Model-based analysis of pattern motion processing in mouse primary visual cortex

PubMed Central

Muir, Dylan R.; Roth, Morgane M.; Helmchen, Fritjof; Kampa, Björn M.

2015-01-01

Neurons in sensory areas of neocortex exhibit responses tuned to specific features of the environment. In visual cortex, information about features such as edges or textures with particular orientations must be integrated to recognize a visual scene or object. Connectivity studies in rodent cortex have revealed that neurons make specific connections within sub-networks sharing common input tuning. In principle, this sub-network architecture enables local cortical circuits to integrate sensory information. However, whether feature integration indeed occurs locally in rodent primary sensory areas has not been examined directly. We studied local integration of sensory features in primary visual cortex (V1) of the mouse by presenting drifting grating and plaid stimuli, while recording the activity of neuronal populations with two-photon calcium imaging. Using a Bayesian model-based analysis framework, we classified single-cell responses as being selective for either individual grating components or for moving plaid patterns. Rather than relying on trial-averaged responses, our model-based framework takes into account single-trial responses and can easily be extended to consider any number of arbitrary predictive models. Our analysis method was able to successfully classify significantly more responses than traditional partial correlation (PC) analysis, and provides a rigorous statistical framework to rank any number of models and reject poorly performing models. We also found a large proportion of cells that respond strongly to only one stimulus class. In addition, a quarter of selectively responding neurons had more complex responses that could not be explained by any simple integration model. Our results show that a broad range of pattern integration processes already take place at the level of V1. This diversity of integration is consistent with processing of visual inputs by local sub-networks within V1 that are tuned to combinations of sensory features. PMID:26300738

The Kyoto protocol and payments for tropical forest: An interdisciplinary method for estimating carbon-offset supply and increasing the feasibility of a carbon market under the CDM

USGS Publications Warehouse

Pfaff, Alexander S.P.; Kerr, Suzi; Hughes, R. Flint; Liu, Shuguang; Sanchez-Azofeifa, G. Arturo; Schimel, David; Tosi, Joseph; Watson, Vicente

2000-01-01

Protecting tropical forests under the Clean Development Mechanism (CDM) could reduce the cost of emissions limitations set in Kyoto. However, while society must soon decide whether or not to use tropical forest-based offsets, evidence regarding tropical carbon sinks is sparse. This paper presents a general method for constructing an integrated model (based on detailed historical, remote sensing and field data) that can produce land-use and carbon baselines, predict carbon sequestration supply to a carbon-offsets market and also help to evaluate optimal market rules. Creating such integrated models requires close collaboration between social and natural scientists. Our project combines varied disciplinary expertise (in economics, ecology and geography) with local knowledge in order to create high-quality, empirically grounded, integrated models for Costa Rica.

Integrating modelling and phenotyping approaches to identify and screen complex traits - Illustration for transpiration efficiency in cereals.

PubMed

Chenu, K; van Oosterom, E J; McLean, G; Deifel, K S; Fletcher, A; Geetika, G; Tirfessa, A; Mace, E S; Jordan, D R; Sulman, R; Hammer, G L

2018-02-21

Following advances in genetics, genomics, and phenotyping, trait selection in breeding is limited by our ability to understand interactions within the plants and with their environments, and to target traits of most relevance for the target population of environments. We propose an integrated approach that combines insights from crop modelling, physiology, genetics, and breeding to identify traits valuable for yield gain in the target population of environments, develop relevant high-throughput phenotyping platforms, and identify genetic controls and their values in production environments. This paper uses transpiration efficiency (biomass produced per unit of water used) as an example of a complex trait of interest to illustrate how the approach can guide modelling, phenotyping, and selection in a breeding program. We believe that this approach, by integrating insights from diverse disciplines, can increase the resource use efficiency of breeding programs for improving yield gains in target populations of environments.

Integrative strategies to identify candidate genes in rodent models of human alcoholism.

PubMed

Treadwell, Julie A

2006-01-01

The search for genes underlying alcohol-related behaviours in rodent models of human alcoholism has been ongoing for many years with only limited success. Recently, new strategies that integrate several of the traditional approaches have provided new insights into the molecular mechanisms underlying ethanol's actions in the brain. We have used alcohol-preferring C57BL/6J (B6) and alcohol-avoiding DBA/2J (D2) genetic strains of mice in an integrative strategy combining high-throughput gene expression screening, genetic segregation analysis, and mapping to previously published quantitative trait loci to uncover candidate genes for the ethanol-preference phenotype. In our study, 2 genes, retinaldehyde binding protein 1 (Rlbp1) and syntaxin 12 (Stx12), were found to be strong candidates for ethanol preference. Such experimental approaches have the power and the potential to greatly speed up the laborious process of identifying candidate genes for the animal models of human alcoholism.

Statistical Methodologies to Integrate Experimental and Computational Research

NASA Technical Reports Server (NTRS)

Parker, P. A.; Johnson, R. T.; Montgomery, D. C.

2008-01-01

Development of advanced algorithms for simulating engine flow paths requires the integration of fundamental experiments with the validation of enhanced mathematical models. In this paper, we provide an overview of statistical methods to strategically and efficiently conduct experiments and computational model refinement. Moreover, the integration of experimental and computational research efforts is emphasized. With a statistical engineering perspective, scientific and engineering expertise is combined with statistical sciences to gain deeper insights into experimental phenomenon and code development performance; supporting the overall research objectives. The particular statistical methods discussed are design of experiments, response surface methodology, and uncertainty analysis and planning. Their application is illustrated with a coaxial free jet experiment and a turbulence model refinement investigation. Our goal is to provide an overview, focusing on concepts rather than practice, to demonstrate the benefits of using statistical methods in research and development, thereby encouraging their broader and more systematic application.

Steady-state probability density function of the phase error for a DPLL with an integrate-and-dump device

NASA Technical Reports Server (NTRS)

Simon, M.; Mileant, A.

1986-01-01

The steady-state behavior of a particular type of digital phase-locked loop (DPLL) with an integrate-and-dump circuit following the phase detector is characterized in terms of the probability density function (pdf) of the phase error in the loop. Although the loop is entirely digital from an implementation standpoint, it operates at two extremely different sampling rates. In particular, the combination of a phase detector and an integrate-and-dump circuit operates at a very high rate whereas the loop update rate is very slow by comparison. Because of this dichotomy, the loop can be analyzed by hybrid analog/digital (s/z domain) techniques. The loop is modeled in such a general fashion that previous analyses of the Real-Time Combiner (RTC), Subcarrier Demodulator Assembly (SDA), and Symbol Synchronization Assembly (SSA) fall out as special cases.

[2-stage group psychotherapy with integrated autogenic training within the scope of a general integrated psychotherapy concept].

PubMed

Barolin, Gerhard S

2003-01-01

Group-therapy and autogenic training in combination show mutual potentiation. Our results have proved the hypothesis to be true and we have also been able to explain it by an analysis of the neurophysiological and psychological findings concerning both methods. Our "model" has proved to be very economical in time and can be easily applied. It needs basic psychotherapeutical education but no special additive schooling. It is particularly well employed in rehabilitation patients, elderly patients and geronto-rehabilitation patients. As numbers of such patients are steadily increasing, it could soon become highly important, and in the technically dominated medicine of today, the particularly communicative component that we postulate in integrated psychotherapy could also grow in importance. By combining the two methods, it is not method that is at the centre of our endeavours but the patient.

Prediction of clinical behaviour and treatment for cancers.

PubMed

Futschik, Matthias E; Sullivan, Mike; Reeve, Anthony; Kasabov, Nikola

2003-01-01

Prediction of clinical behaviour and treatment for cancers is based on the integration of clinical and pathological parameters. Recent reports have demonstrated that gene expression profiling provides a powerful new approach for determining disease outcome. If clinical and microarray data each contain independent information then it should be possible to combine these datasets to gain more accurate prognostic information. Here, we have used existing clinical information and microarray data to generate a combined prognostic model for outcome prediction for diffuse large B-cell lymphoma (DLBCL). A prediction accuracy of 87.5% was achieved. This constitutes a significant improvement compared to the previously most accurate prognostic model with an accuracy of 77.6%. The model introduced here may be generally applicable to the combination of various types of molecular and clinical data for improving medical decision support systems and individualising patient care.

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

Nose, Y.

Methods were developed for generating an integrated, statistical model of the anatomical structures within the human thorax relevant to radioisotope powered artificial heart implantation. These methods involve measurement and analysis of anatomy in four areas: chest wall, pericardium, vascular connections, and great vessels. A model for the prediction of thorax outline from radiograms was finalized. These models were combined with 100 radiograms to arrive at a size distribution representing the adult male and female populations. (CH)

Validation of a Sensor-Driven Modeling Paradigm for Multiple Source Reconstruction with FFT-07 Data

DTIC Science & Technology

2009-05-01

operational warning and reporting (information) systems that combine automated data acquisition, analysis , source reconstruction, display and distribution of...report and to incorporate this operational ca- pability into the integrative multiscale urban modeling system implemented in the com- putational...Journal of Fluid Mechanics, 180, 529–556. [27] Flesch, T., Wilson, J. D., and Yee, E. (1995), Backward- time Lagrangian stochastic dispersion models

A Comparative Analysis of Computer End-User Support in the Air Force and Civilian Organizations

DTIC Science & Technology

1991-12-01

This explanation implies a further stratification of end users based on the specific tasks they perform, a new model of application combinations, and a...its support efforts to meet the needs of its end-uiser clientele iore closely. 79 INTEGRATED .9 VERBAL ANALYTIC Figure 14. Test Model of Applications ...The IC Model : IEM, Canada. ...............19 Proliferation of ICs ... ............... 20 Services ... ..................... 21 IC States

Evaluating Site-Specific and Generic Spatial Models of Aboveground Forest Biomass Based on Landsat Time-Series and LiDAR Strip Samples in the Eastern USA

Treesearch

Ram Deo; Matthew Russell; Grant Domke; Hans-Erik Andersen; Warren Cohen; Christopher Woodall

2017-01-01

Large-area assessment of aboveground tree biomass (AGB) to inform regional or national forest monitoring programs can be efficiently carried out by combining remotely sensed data and field sample measurements through a generic statistical model, in contrast to site-specific models. We integrated forest inventory plot data with spatial predictors from Landsat time-...

Modelling the Factors that Affect Individuals' Utilisation of Online Learning Systems: An Empirical Study Combining the Task Technology Fit Model with the Theory of Planned Behaviour

ERIC Educational Resources Information Center

Yu, Tai-Kuei; Yu, Tai-Yi

2010-01-01

Understanding learners' behaviour, perceptions and influence in terms of learner performance is crucial to predict the use of electronic learning systems. By integrating the task-technology fit (TTF) model and the theory of planned behaviour (TPB), this paper investigates the online learning utilisation of Taiwanese students. This paper provides a…

77 FR 59166 - South Mississippi Electric Cooperative: Plant Ratcliffe, Kemper County Integrated Gasification...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-26

... Ratcliffe, Kemper County Integrated Gasification Combined-Cycle (IGCC) Project AGENCY: Rural Utilities... Plant Ratcliffe, an Integrated Gasification Combined-Cycle Facility located in Kemper County... Company (MPCo), and will demonstrate the feasibility of the Integrated Gasification Combined-Cycle (IGCC...

Detection of pulmonary nodules in CT images based on fuzzy integrated active contour model and hybrid parametric mixture model.

PubMed

Li, Bin; Chen, Kan; Tian, Lianfang; Yeboah, Yao; Ou, Shanxing

2013-01-01

The segmentation and detection of various types of nodules in a Computer-aided detection (CAD) system present various challenges, especially when (1) the nodule is connected to a vessel and they have very similar intensities; (2) the nodule with ground-glass opacity (GGO) characteristic possesses typical weak edges and intensity inhomogeneity, and hence it is difficult to define the boundaries. Traditional segmentation methods may cause problems of boundary leakage and "weak" local minima. This paper deals with the above mentioned problems. An improved detection method which combines a fuzzy integrated active contour model (FIACM)-based segmentation method, a segmentation refinement method based on Parametric Mixture Model (PMM) of juxta-vascular nodules, and a knowledge-based C-SVM (Cost-sensitive Support Vector Machines) classifier, is proposed for detecting various types of pulmonary nodules in computerized tomography (CT) images. Our approach has several novel aspects: (1) In the proposed FIACM model, edge and local region information is incorporated. The fuzzy energy is used as the motivation power for the evolution of the active contour. (2) A hybrid PMM Model of juxta-vascular nodules combining appearance and geometric information is constructed for segmentation refinement of juxta-vascular nodules. Experimental results of detection for pulmonary nodules show desirable performances of the proposed method.

OPTIMIZATION OF INTEGRATED URBAN WET-WEATHER CONTROL STRATEGIES

EPA Science Inventory

An optimization method for urban wet weather control (WWC) strategies is presented. The developed optimization model can be used to determine the most cost-effective strategies for the combination of centralized storage-release systems and distributed on-site WWC alternatives. T...

Combining patient journey modelling and visual multi-agent computer simulation: a framework to improving knowledge translation in a healthcare environment.

PubMed

Curry, Joanne; Fitzgerald, Anneke; Prodan, Ante; Dadich, Ann; Sloan, Terry

2014-01-01

This article focuses on a framework that will investigate the integration of two disparate methodologies: patient journey modelling and visual multi-agent simulation, and its impact on the speed and quality of knowledge translation to healthcare stakeholders. Literature describes patient journey modelling and visual simulation as discrete activities. This paper suggests that their combination and their impact on translating knowledge to practitioners are greater than the sum of the two technologies. The test-bed is ambulatory care and the goal is to determine if this approach can improve health services delivery, workflow, and patient outcomes and satisfaction. The multidisciplinary research team is comprised of expertise in patient journey modelling, simulation, and knowledge translation.

An automated and integrated framework for dust storm detection based on ogc web processing services

NASA Astrophysics Data System (ADS)

Xiao, F.; Shea, G. Y. K.; Wong, M. S.; Campbell, J.

2014-11-01

Dust storms are known to have adverse effects on public health. Atmospheric dust loading is also one of the major uncertainties in global climatic modelling as it is known to have a significant impact on the radiation budget and atmospheric stability. The complexity of building scientific dust storm models is coupled with the scientific computation advancement, ongoing computing platform development, and the development of heterogeneous Earth Observation (EO) networks. It is a challenging task to develop an integrated and automated scheme for dust storm detection that combines Geo-Processing frameworks, scientific models and EO data together to enable the dust storm detection and tracking processes in a dynamic and timely manner. This study develops an automated and integrated framework for dust storm detection and tracking based on the Web Processing Services (WPS) initiated by Open Geospatial Consortium (OGC). The presented WPS framework consists of EO data retrieval components, dust storm detecting and tracking component, and service chain orchestration engine. The EO data processing component is implemented based on OPeNDAP standard. The dust storm detecting and tracking component combines three earth scientific models, which are SBDART model (for computing aerosol optical depth (AOT) of dust particles), WRF model (for simulating meteorological parameters) and HYSPLIT model (for simulating the dust storm transport processes). The service chain orchestration engine is implemented based on Business Process Execution Language for Web Service (BPEL4WS) using open-source software. The output results, including horizontal and vertical AOT distribution of dust particles as well as their transport paths, were represented using KML/XML and displayed in Google Earth. A serious dust storm, which occurred over East Asia from 26 to 28 Apr 2012, is used to test the applicability of the proposed WPS framework. Our aim here is to solve a specific instance of a complex EO data and scientific model integration problem by using a framework and scientific workflow approach together. The experimental result shows that this newly automated and integrated framework can be used to give advance near real-time warning of dust storms, for both environmental authorities and public. The methods presented in this paper might be also generalized to other types of Earth system models, leading to improved ease of use and flexibility.

Integrated navigation fusion strategy of INS/UWB for indoor carrier attitude angle and position synchronous tracking.

PubMed

Fan, Qigao; Wu, Yaheng; Hui, Jing; Wu, Lei; Yu, Zhenzhong; Zhou, Lijuan

2014-01-01

In some GPS failure conditions, positioning for mobile target is difficult. This paper proposed a new method based on INS/UWB for attitude angle and position synchronous tracking of indoor carrier. Firstly, error model of INS/UWB integrated system is built, including error equation of INS and UWB. And combined filtering model of INS/UWB is researched. Simulation results show that the two subsystems are complementary. Secondly, integrated navigation data fusion strategy of INS/UWB based on Kalman filtering theory is proposed. Simulation results show that FAKF method is better than the conventional Kalman filtering. Finally, an indoor experiment platform is established to verify the integrated navigation theory of INS/UWB, which is geared to the needs of coal mine working environment. Static and dynamic positioning results show that the INS/UWB integrated navigation system is stable and real-time, positioning precision meets the requirements of working condition and is better than any independent subsystem.

Integrated decision strategies for skin sensitization hazard.

PubMed

Strickland, Judy; Zang, Qingda; Kleinstreuer, Nicole; Paris, Michael; Lehmann, David M; Choksi, Neepa; Matheson, Joanna; Jacobs, Abigail; Lowit, Anna; Allen, David; Casey, Warren

2016-09-01

One of the top priorities of the Interagency Coordinating Committee for the Validation of Alternative Methods (ICCVAM) is the identification and evaluation of non-animal alternatives for skin sensitization testing. Although skin sensitization is a complex process, the key biological events of the process have been well characterized in an adverse outcome pathway (AOP) proposed by the Organisation for Economic Co-operation and Development (OECD). Accordingly, ICCVAM is working to develop integrated decision strategies based on the AOP using in vitro, in chemico and in silico information. Data were compiled for 120 substances tested in the murine local lymph node assay (LLNA), direct peptide reactivity assay (DPRA), human cell line activation test (h-CLAT) and KeratinoSens assay. Data for six physicochemical properties, which may affect skin penetration, were also collected, and skin sensitization read-across predictions were performed using OECD QSAR Toolbox. All data were combined into a variety of potential integrated decision strategies to predict LLNA outcomes using a training set of 94 substances and an external test set of 26 substances. Fifty-four models were built using multiple combinations of machine learning approaches and predictor variables. The seven models with the highest accuracy (89-96% for the test set and 96-99% for the training set) for predicting LLNA outcomes used a support vector machine (SVM) approach with different combinations of predictor variables. The performance statistics of the SVM models were higher than any of the non-animal tests alone and higher than simple test battery approaches using these methods. These data suggest that computational approaches are promising tools to effectively integrate data sources to identify potential skin sensitizers without animal testing. Published 2016. This article has been contributed to by US Government employees and their work is in the public domain in the USA. Published 2016. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Multidisciplinary optimization in aircraft design using analytic technology models

NASA Technical Reports Server (NTRS)

Malone, Brett; Mason, W. H.

1991-01-01

An approach to multidisciplinary optimization is presented which combines the Global Sensitivity Equation method, parametric optimization, and analytic technology models. The result is a powerful yet simple procedure for identifying key design issues. It can be used both to investigate technology integration issues very early in the design cycle, and to establish the information flow framework between disciplines for use in multidisciplinary optimization projects using much more computational intense representations of each technology. To illustrate the approach, an examination of the optimization of a short takeoff heavy transport aircraft is presented for numerous combinations of performance and technology constraints.

Building a model for disease classification integration in oncology, an approach based on the national cancer institute thesaurus.

PubMed

Jouhet, Vianney; Mougin, Fleur; Bréchat, Bérénice; Thiessard, Frantz

2017-02-07

Identifying incident cancer cases within a population remains essential for scientific research in oncology. Data produced within electronic health records can be useful for this purpose. Due to the multiplicity of providers, heterogeneous terminologies such as ICD-10 and ICD-O-3 are used for oncology diagnosis recording purpose. To enable disease identification based on these diagnoses, there is a need for integrating disease classifications in oncology. Our aim was to build a model integrating concepts involved in two disease classifications, namely ICD-10 (diagnosis) and ICD-O-3 (topography and morphology), despite their structural heterogeneity. Based on the NCIt, a "derivative" model for linking diagnosis and topography-morphology combinations was defined and built. ICD-O-3 and ICD-10 codes were then used to instantiate classes of the "derivative" model. Links between terminologies obtained through the model were then compared to mappings provided by the Surveillance, Epidemiology, and End Results (SEER) program. The model integrated 42% of neoplasm ICD-10 codes (excluding metastasis), 98% of ICD-O-3 morphology codes (excluding metastasis) and 68% of ICD-O-3 topography codes. For every codes instantiating at least a class in the "derivative" model, comparison with SEER mappings reveals that all mappings were actually available in the model as a link between the corresponding codes. We have proposed a method to automatically build a model for integrating ICD-10 and ICD-O-3 based on the NCIt. The resulting "derivative" model is a machine understandable resource that enables an integrated view of these heterogeneous terminologies. The NCIt structure and the available relationships can help to bridge disease classifications taking into account their structural and granular heterogeneities. However, (i) inconsistencies exist within the NCIt leading to misclassifications in the "derivative" model, (ii) the "derivative" model only integrates a part of ICD-10 and ICD-O-3. The NCIt is not sufficient for integration purpose and further work based on other termino-ontological resources is needed in order to enrich the model and avoid identified inconsistencies.

An integrated model of communication influence on beliefs

PubMed Central

Eveland, William P.; Cooper, Kathryn E.

2013-01-01

How do people develop and maintain their beliefs about science? Decades of social science research exist to help us answer this question. The Integrated Model of Communication Influence on Beliefs presented here combines multiple theories that have considered aspects of this process into a comprehensive model to explain how individuals arrive at their scientific beliefs. In this article, we (i) summarize what is known about how science is presented in various news and entertainment media forms; (ii) describe how individuals differ in their choices to be exposed to various forms and sources of communication; (iii) discuss the implications of how individuals mentally process information on the effects of communication; (iv) consider how communication effects can be altered depending on background characteristics and motivations of individuals; and (v) emphasize that the process of belief formation is not unidirectional but rather, feeds back on itself over time. We conclude by applying the Integrated Model of Communication Influence on Beliefs to the complex issue of beliefs about climate change. PMID:23940328

Using the Integrative Model to Explain How Exposure to Sexual Media Content Influences Adolescent Sexual Behavior

PubMed Central

Bleakley, Amy; Hennessy, Michael; Fishbein, Martin; Jordan, Amy

2017-01-01

Published research demonstrates an association between exposure to media sexual content and a variety of sex-related outcomes for adolescents. What is not known is the mechanism through which sexual content produces this “media effect” on adolescent beliefs, attitudes, and behavior. Using the Integrative Model of Behavioral Prediction, this paper uses data from a longitudinal study of adolescents ages 16–18 (n=460) to determine how exposure to sexual media content influences sexual behavior. Path analysis and structural equation modeling demonstrated that intention to engage in sexual intercourse is determined by a combination of attitudes, normative pressure, and self efficacy but that exposure to sexual media content only affects normative pressure beliefs. By applying the Integrative Model, we are able to identify which beliefs are influenced by exposure to media sex and improve the ability of health educators, researchers, and others to design effective messages for health communication campaigns and messages pertaining to adolescents’ engaging in sexual intercourse. PMID:21606378

Understanding electricity generation in osmotic microbial fuel cells through integrated experimental investigation and mathematical modeling.

PubMed

Qin, Mohan; Ping, Qingyun; Lu, Yaobin; Abu-Reesh, Ibrahim M; He, Zhen

2015-11-01

Osmotic microbial fuel cells (OsMFCs) are a new type of MFCs with integrating forward osmosis (FO). However, it is not well understood why electricity generation is improved in OsMFCs compared to regular MFCs. Herein, an approach integrating experimental investigation and mathematical model was adopted to address the question. Both an OsMFC and an MFC achieved similar organic removal efficiency, but the OsMFC generated higher current than the MFC with or without water flux, resulting from the lower resistance of FO membrane. Combining NaCl and glucose as a catholyte demonstrated that the catholyte conductivity affected the electricity generation in the OsMFC. A mathematical model of OsMFCs was developed and validated with the experimental data. The model predicated the variation of internal resistance with increasing water flux, and confirmed the importance of membrane resistance. Increasing water flux with higher catholyte conductivity could decrease the membrane resistance. Copyright © 2015 Elsevier Ltd. All rights reserved.

An integrated model of communication influence on beliefs.

PubMed

Eveland, William P; Cooper, Kathryn E

2013-08-20

How do people develop and maintain their beliefs about science? Decades of social science research exist to help us answer this question. The Integrated Model of Communication Influence on Beliefs presented here combines multiple theories that have considered aspects of this process into a comprehensive model to explain how individuals arrive at their scientific beliefs. In this article, we (i) summarize what is known about how science is presented in various news and entertainment media forms; (ii) describe how individuals differ in their choices to be exposed to various forms and sources of communication; (iii) discuss the implications of how individuals mentally process information on the effects of communication; (iv) consider how communication effects can be altered depending on background characteristics and motivations of individuals; and (v) emphasize that the process of belief formation is not unidirectional but rather, feeds back on itself over time. We conclude by applying the Integrated Model of Communication Influence on Beliefs to the complex issue of beliefs about climate change.

Integrated Modeling Activities for the James Webb Space Telescope: Optical Jitter Analysis

NASA Technical Reports Server (NTRS)

Hyde, T. Tupper; Ha, Kong Q.; Johnston, John D.; Howard, Joseph M.; Mosier, Gary E.

2004-01-01

This is a continuation of a series of papers on the integrated modeling activities for the James Webb Space Telescope(JWST). Starting with the linear optical model discussed in part one, and using the optical sensitivities developed in part two, we now assess the optical image motion and wavefront errors from the structural dynamics. This is often referred to as "jitter: analysis. The optical model is combined with the structural model and the control models to create a linear structural/optical/control model. The largest jitter is due to spacecraft reaction wheel assembly disturbances which are harmonic in nature and will excite spacecraft and telescope structural. The structural/optic response causes image quality degradation due to image motion (centroid error) as well as dynamic wavefront error. Jitter analysis results are used to predict imaging performance, improve the structural design, and evaluate the operational impact of the disturbance sources.

Building the Capacity for Climate Services: Thoughts on Training Next Generation Climate Science Integrators

NASA Astrophysics Data System (ADS)

Garfin, G. M.; Brugger, J.; Gordon, E. S.; Barsugli, J. J.; Rangwala, I.; Travis, W.

2015-12-01

For more than a decade, stakeholder needs assessments and reports, including the recent National Climate Assessment, have pointed out the need for climate "science translators" or "science integrators" who can help bridge the gap between the cultures and contexts of researchers and decision-makers. Integration is important for exchanging and enhancing knowledge, building capacity to use climate information in decision making, and fostering more robust planning for decision-making in the context of climate change. This talk will report on the characteristics of successful climate science integrators, and a variety of models for training the upcoming generation of climate science integrators. Science integration characteristics identified by an experienced vanguard in the U.S. include maintaining credibility in both the scientific and stakeholder communities, a basic respect for stakeholders demonstrated through active listening, and a deep understanding of the decision-making context. Drawing upon the lessons of training programs for Cooperative Extension, public health professionals, and natural resource managers, we offer ideas about training next generation climate science integrators. Our model combines training and development of skills in interpersonal relations, communication of science, project implementation, education techniques and practices - integrated with a strong foundation in disciplinary knowledge.

Top-down systems biology integration of conditional prebiotic modulated transgenomic interactions in a humanized microbiome mouse model

PubMed Central

Martin, Francois-Pierre J; Wang, Yulan; Sprenger, Norbert; Yap, Ivan K S; Rezzi, Serge; Ramadan, Ziad; Peré-Trepat, Emma; Rochat, Florence; Cherbut, Christine; van Bladeren, Peter; Fay, Laurent B; Kochhar, Sunil; Lindon, John C; Holmes, Elaine; Nicholson, Jeremy K

2008-01-01

Gut microbiome–host metabolic interactions affect human health and can be modified by probiotic and prebiotic supplementation. Here, we have assessed the effects of consumption of a combination of probiotics (Lactobacillus paracasei or L. rhamnosus) and two galactosyl-oligosaccharide prebiotics on the symbiotic microbiome–mammalian supersystem using integrative metabolic profiling and modeling of multiple compartments in germ-free mice inoculated with a model of human baby microbiota. We have shown specific impacts of two prebiotics on the microbial populations of HBM mice when co-administered with two probiotics. We observed an increase in the populations of Bifidobacterium longum and B. breve, and a reduction in Clostridium perfringens, which were more marked when combining prebiotics with L. rhamnosus. In turn, these microbial effects were associated with modulation of a range of host metabolic pathways observed via changes in lipid profiles, gluconeogenesis, and amino-acid and methylamine metabolism associated to fermentation of carbohydrates by different bacterial strains. These results provide evidence for the potential use of prebiotics for beneficially modifying the gut microbial balance as well as host energy and lipid homeostasis. PMID:18628745

Brahms Mobile Agents: Architecture and Field Tests

NASA Technical Reports Server (NTRS)

Clancey, William J.; Sierhuis, Maarten; Kaskiris, Charis; vanHoof, Ron

2002-01-01

We have developed a model-based, distributed architecture that integrates diverse components in a system designed for lunar and planetary surface operations: an astronaut's space suit, cameras, rover/All-Terrain Vehicle (ATV), robotic assistant, other personnel in a local habitat, and a remote mission support team (with time delay). Software processes, called agents, implemented in the Brahms language, run on multiple, mobile platforms. These mobile agents interpret and transform available data to help people and robotic systems coordinate their actions to make operations more safe and efficient. The Brahms-based mobile agent architecture (MAA) uses a novel combination of agent types so the software agents may understand and facilitate communications between people and between system components. A state-of-the-art spoken dialogue interface is integrated with Brahms models, supporting a speech-driven field observation record and rover command system (e.g., return here later and bring this back to the habitat ). This combination of agents, rover, and model-based spoken dialogue interface constitutes a personal assistant. An important aspect of the methodology involves first simulating the entire system in Brahms, then configuring the agents into a run-time system.

Vision and air flow combine to streamline flying honeybees

PubMed Central

Taylor, Gavin J.; Luu, Tien; Ball, David; Srinivasan, Mandyam V.

2013-01-01

Insects face the challenge of integrating multi-sensory information to control their flight. Here we study a ‘streamlining' response in honeybees, whereby honeybees raise their abdomen to reduce drag. We find that this response, which was recently reported to be mediated by optic flow, is also strongly modulated by the presence of air flow simulating a head wind. The Johnston's organs in the antennae were found to play a role in the measurement of the air speed that is used to control the streamlining response. The response to a combination of visual motion and wind is complex and can be explained by a model that incorporates a non-linear combination of the two stimuli. The use of visual and mechanosensory cues increases the strength of the streamlining response when the stimuli are present concurrently. We propose this multisensory integration will make the response more robust to transient disturbances in either modality. PMID:24019053

Complex Building Detection Through Integrating LIDAR and Aerial Photos

NASA Astrophysics Data System (ADS)

Zhai, R.

2015-02-01

This paper proposes a new approach on digital building detection through the integration of LiDAR data and aerial imagery. It is known that most building rooftops are represented by different regions from different seed pixels. Considering the principals of image segmentation, this paper employs a new region based technique to segment images, combining both the advantages of LiDAR and aerial images together. First, multiple seed points are selected by taking several constraints into consideration in an automated way. Then, the region growing procedures proceed by combining the elevation attribute from LiDAR data, visibility attribute from DEM (Digital Elevation Model), and radiometric attribute from warped images in the segmentation. Through this combination, the pixels with similar height, visibility, and spectral attributes are merged into one region, which are believed to represent the whole building area. The proposed methodology was implemented on real data and competitive results were achieved.

Integration of aerial oblique imagery and terrestrial imagery for optimized 3D modeling in urban areas

NASA Astrophysics Data System (ADS)

Wu, Bo; Xie, Linfu; Hu, Han; Zhu, Qing; Yau, Eric

2018-05-01

Photorealistic three-dimensional (3D) models are fundamental to the spatial data infrastructure of a digital city, and have numerous potential applications in areas such as urban planning, urban management, urban monitoring, and urban environmental studies. Recent developments in aerial oblique photogrammetry based on aircraft or unmanned aerial vehicles (UAVs) offer promising techniques for 3D modeling. However, 3D models generated from aerial oblique imagery in urban areas with densely distributed high-rise buildings may show geometric defects and blurred textures, especially on building façades, due to problems such as occlusion and large camera tilt angles. Meanwhile, mobile mapping systems (MMSs) can capture terrestrial images of close-range objects from a complementary view on the ground at a high level of detail, but do not offer full coverage. The integration of aerial oblique imagery with terrestrial imagery offers promising opportunities to optimize 3D modeling in urban areas. This paper presents a novel method of integrating these two image types through automatic feature matching and combined bundle adjustment between them, and based on the integrated results to optimize the geometry and texture of the 3D models generated from aerial oblique imagery. Experimental analyses were conducted on two datasets of aerial and terrestrial images collected in Dortmund, Germany and in Hong Kong. The results indicate that the proposed approach effectively integrates images from the two platforms and thereby improves 3D modeling in urban areas.

A new spatial integration method for luminous flux determination of light-emitting diodes

NASA Astrophysics Data System (ADS)

Zhou, Xiaoli; Zhu, Shaolong; Shen, Haiping; Liu, Muqing

2010-10-01

Spatial integrated measurement using an integrating sphere is usually used for the luminous flux determination of light sources. Devices using an integrating sphere are bulky for use on a production assembly line. This paper proposes an alternative spatial integration method for accurately measuring the total luminous flux of light-emitting diodes (LEDs) having no backward emission. A compound parabolic concentrator is introduced to collect the light from an LED in conjunction with a detector which in turn measures the luminous flux. The study reported here combines both modeling and experiment to show the applicability of this novel method. The uncertainty in the measurements is then evaluated for the total luminous flux measurement from an LED.

Monolithic integration of SOI waveguide photodetectors and transimpedance amplifiers

NASA Astrophysics Data System (ADS)

Li, Shuxia; Tarr, N. Garry; Ye, Winnie N.

2018-02-01

In the absence of commercial foundry technologies offering silicon-on-insulator (SOI) photonics combined with Complementary Metal Oxide Semiconductor (CMOS) transistors, monolithic integration of conventional electronics with SOI photonics is difficult. Here we explore the implementation of lateral bipolar junction transistors (LBJTs) and Junction Field Effect Transistors (JFETs) in a commercial SOI photonics technology lacking MOS devices but offering a variety of n- and p-type ion implants intended to provide waveguide modulators and photodetectors. The fabrication makes use of the commercial Institute of Microelectronics (IME) SOI photonics technology. Based on knowledge of device doping and geometry, simple compact LBJT and JFET device models are developed. These models are then used to design basic transimpedance amplifiers integrated with optical waveguides. The devices' experimental current-voltage characteristics results are reported.

Religion and suicide acceptability: a cross-national analysis.

PubMed

Stack, Steven; Kposowa, Augustine J

2011-01-01

Four perspectives (moral community thesis, religious integration, religious commitment, and social networks) guide the selection of variables in this study. Data are from the combined World Values/European Values Surveys for 2000 (50,547 individuals nested in 56 nations). The results of a multivariate hierarchical linear model support all four perspectives. Persons residing in nations with relatively high levels of religiosity, who are affiliated with one of four major faiths, are religiously committed, and are engaged with a religious network are found to be lower in suicide acceptability. The religious integration perspective, in particular, is empirically supported; affiliation with Islam is associated with low suicide acceptability. The findings provide strong support for an integrated model and demonstrate the usefulness of the moral community thesis in understanding suicide acceptability.

Impact of Media Richness and Flow on E-Learning Technology Acceptance

ERIC Educational Resources Information Center

Liu, Su-Houn; Liao, Hsiu-Li; Pratt, Jean A.

2009-01-01

Advances in e-learning technologies parallels a general increase in sophistication by computer users. The use of just one theory or model, such as the technology acceptance model, is no longer sufficient to study the intended use of e-learning systems. Rather, a combination of theories must be integrated in order to fully capture the complexity of…

Adolescent Marijuana Use Intentions: Using Theory to Plan an Intervention

ERIC Educational Resources Information Center

Sayeed, Sarah; Fishbein, Martin; Hornik, Robert; Cappella, Joseph; Kirkland Ahern, R.

2005-01-01

This paper uses an integrated model of behavior change to predict intentions to use marijuana occasionally and regularly in a US-based national sample of male and female 12 to 18 year olds (n = 600). The model combines key constructs from the theory of reasoned action and social cognitive theory. The survey was conducted on laptop computers, and…

Counseling Female Offenders and Victims: A Strengths-Restorative Approach. Springer Series on Family Violence.

ERIC Educational Resources Information Center

van Wormer, Katherine

This books considers the many aspects of how the criminal justice system can be reshaped to address the needs of victims of violence and offenders who themselves are often the victims of abuse. It presents a new model that offers an integrated framework to combine tenets of social work's strengths framework with the restorative justice model. It…

Integration of Watershed Model AnnAGNPS and Stream Network Model CCHE1D for the Development of a New GIS-Based BMP Planning Tool

USDA-ARS?s Scientific Manuscript database

This paper presents a new GIS-based Best Management Practice (BMP) Tool developed for watershed managers to assist in the decision making process by simulating various scenarios using various combinations of Best Management Practices (BMPs). The development of this BMPTool is based on the integratio...

Incorporation of Chemical Contaminants into the Combined ICM/SEDZLJ Models

DTIC Science & Technology

2012-03-01

concentration of toxicant 1 in water column (g m-3) Δt = model integration time step (s) The deposition of toxicant 2 is: ERDC/EL TR-12-6 13 Δ Dpoc ...D Fpw TOX w t POC     1 2 (10) in which: Dpoc = deposition of labile and refractory particulate organic carbon (g m-2) POC = labile plus

A case study for the integration of predictive mineral potential maps

NASA Astrophysics Data System (ADS)

Lee, Saro; Oh, Hyun-Joo; Heo, Chul-Ho; Park, Inhye

2014-09-01

This study aims to elaborate on the mineral potential maps using various models and verify the accuracy for the epithermal gold (Au) — silver (Ag) deposits in a Geographic Information System (GIS) environment assuming that all deposits shared a common genesis. The maps of potential Au and Ag deposits were produced by geological data in Taebaeksan mineralized area, Korea. The methodological framework consists of three main steps: 1) identification of spatial relationships 2) quantification of such relationships and 3) combination of multiple quantified relationships. A spatial database containing 46 Au-Ag deposits was constructed using GIS. The spatial association between training deposits and 26 related factors were identified and quantified by probabilistic and statistical modelling. The mineral potential maps were generated by integrating all factors using the overlay method and recombined afterwards using the likelihood ratio model. They were verified by comparison with test mineral deposit locations. The verification revealed that the combined mineral potential map had the greatest accuracy (83.97%), whereas it was 72.24%, 65.85%, 72.23% and 71.02% for the likelihood ratio, weight of evidence, logistic regression and artificial neural network models, respectively. The mineral potential map can provide useful information for the mineral resource development.

High-resolution spatiotemporal mapping of PM2.5 concentrations at Mainland China using a combined BME-GWR technique

NASA Astrophysics Data System (ADS)

Xiao, Lu; Lang, Yichao; Christakos, George

2018-01-01

With rapid economic development, industrialization and urbanization, the ambient air PM2.5 has become a major pollutant linked to respiratory, heart and lung diseases. In China, PM2.5 pollution constitutes an extreme environmental and social problem of widespread public concern. In this work we estimate ground-level PM2.5 from satellite-derived aerosol optical depth (AOD), topography data, meteorological data, and pollutant emission using an integrative technique. In particular, Geographically Weighted Regression (GWR) analysis was combined with Bayesian Maximum Entropy (BME) theory to assess the spatiotemporal characteristics of PM2.5 exposure in a large region of China and generate informative PM2.5 space-time predictions (estimates). It was found that, due to its integrative character, the combined BME-GWR method offers certain improvements in the space-time prediction of PM2.5 concentrations over China compared to previous techniques. The combined BME-GWR technique generated realistic maps of space-time PM2.5 distribution, and its performance was superior to that of seven previous studies of satellite-derived PM2.5 concentrations in China in terms of prediction accuracy. The purely spatial GWR model can only be used at a fixed time, whereas the integrative BME-GWR approach accounts for cross space-time dependencies and can predict PM2.5 concentrations in the composite space-time domain. The 10-fold results of BME-GWR modeling (R2 = 0.883, RMSE = 11.39 μg /m3) demonstrated a high level of space-time PM2.5 prediction (estimation) accuracy over China, revealing a definite trend of severe PM2.5 levels from the northern coast toward inland China (Nov 2015-Feb 2016). Future work should focus on the addition of higher resolution AOD data, developing better satellite-based prediction models, and related air pollutants for space-time PM2.5 prediction purposes.

A hadoop-based method to predict potential effective drug combination.

PubMed

Sun, Yifan; Xiong, Yi; Xu, Qian; Wei, Dongqing

2014-01-01

Combination drugs that impact multiple targets simultaneously are promising candidates for combating complex diseases due to their improved efficacy and reduced side effects. However, exhaustive screening of all possible drug combinations is extremely time-consuming and impractical. Here, we present a novel Hadoop-based approach to predict drug combinations by taking advantage of the MapReduce programming model, which leads to an improvement of scalability of the prediction algorithm. By integrating the gene expression data of multiple drugs, we constructed data preprocessing and the support vector machines and naïve Bayesian classifiers on Hadoop for prediction of drug combinations. The experimental results suggest that our Hadoop-based model achieves much higher efficiency in the big data processing steps with satisfactory performance. We believed that our proposed approach can help accelerate the prediction of potential effective drugs with the increasing of the combination number at an exponential rate in future. The source code and datasets are available upon request.

A Hadoop-Based Method to Predict Potential Effective Drug Combination

PubMed Central

Xiong, Yi; Xu, Qian; Wei, Dongqing

2014-01-01

Combination drugs that impact multiple targets simultaneously are promising candidates for combating complex diseases due to their improved efficacy and reduced side effects. However, exhaustive screening of all possible drug combinations is extremely time-consuming and impractical. Here, we present a novel Hadoop-based approach to predict drug combinations by taking advantage of the MapReduce programming model, which leads to an improvement of scalability of the prediction algorithm. By integrating the gene expression data of multiple drugs, we constructed data preprocessing and the support vector machines and naïve Bayesian classifiers on Hadoop for prediction of drug combinations. The experimental results suggest that our Hadoop-based model achieves much higher efficiency in the big data processing steps with satisfactory performance. We believed that our proposed approach can help accelerate the prediction of potential effective drugs with the increasing of the combination number at an exponential rate in future. The source code and datasets are available upon request. PMID:25147789

Particle-in-a-box model of one-dimensional excitons in conjugated polymers

NASA Astrophysics Data System (ADS)

Pedersen, Thomas G.; Johansen, Per M.; Pedersen, Henrik C.

2000-04-01

A simple two-particle model of excitons in conjugated polymers is proposed as an alternative to usual highly computationally demanding quantum chemical methods. In the two-particle model, the exciton is described as an electron-hole pair interacting via Coulomb forces and confined to the polymer backbone by rigid walls. Furthermore, by integrating out the transverse part, the two-particle equation is reduced to one-dimensional form. It is demonstrated how essentially exact solutions are obtained in the cases of short and long conjugation length, respectively. From a linear combination of these cases an approximate solution for the general case is obtained. As an application of the model the influence of a static electric field on the electron-hole overlap integral and exciton energy is considered.

A Smart Modeling Framework for Integrating BMI-enabled Models as Web Services

NASA Astrophysics Data System (ADS)

Jiang, P.; Elag, M.; Kumar, P.; Peckham, S. D.; Liu, R.; Marini, L.; Hsu, L.

2015-12-01

Serviced-oriented computing provides an opportunity to couple web service models using semantic web technology. Through this approach, models that are exposed as web services can be conserved in their own local environment, thus making it easy for modelers to maintain and update the models. In integrated modeling, the serviced-oriented loose-coupling approach requires (1) a set of models as web services, (2) the model metadata describing the external features of a model (e.g., variable name, unit, computational grid, etc.) and (3) a model integration framework. We present the architecture of coupling web service models that are self-describing by utilizing a smart modeling framework. We expose models that are encapsulated with CSDMS (Community Surface Dynamics Modeling System) Basic Model Interfaces (BMI) as web services. The BMI-enabled models are self-describing by uncovering models' metadata through BMI functions. After a BMI-enabled model is serviced, a client can initialize, execute and retrieve the meta-information of the model by calling its BMI functions over the web. Furthermore, a revised version of EMELI (Peckham, 2015), an Experimental Modeling Environment for Linking and Interoperability, is chosen as the framework for coupling BMI-enabled web service models. EMELI allows users to combine a set of component models into a complex model by standardizing model interface using BMI as well as providing a set of utilities smoothing the integration process (e.g., temporal interpolation). We modify the original EMELI so that the revised modeling framework is able to initialize, execute and find the dependencies of the BMI-enabled web service models. By using the revised EMELI, an example will be presented on integrating a set of topoflow model components that are BMI-enabled and exposed as web services. Reference: Peckham, S.D. (2014) EMELI 1.0: An experimental smart modeling framework for automatic coupling of self-describing models, Proceedings of HIC 2014, 11th International Conf. on Hydroinformatics, New York, NY.

CheckMATE 2: From the model to the limit

NASA Astrophysics Data System (ADS)

Dercks, Daniel; Desai, Nishita; Kim, Jong Soo; Rolbiecki, Krzysztof; Tattersall, Jamie; Weber, Torsten

2017-12-01

We present the latest developments to the CheckMATE program that allows models of new physics to be easily tested against the recent LHC data. To achieve this goal, the core of CheckMATE now contains over 60 LHC analyses of which 12 are from the 13 TeV run. The main new feature is that CheckMATE 2 now integrates the Monte Carlo event generation via MadGraph5_aMC@NLO and Pythia 8. This allows users to go directly from a SLHA file or UFO model to the result of whether a model is allowed or not. In addition, the integration of the event generation leads to a significant increase in the speed of the program. Many other improvements have also been made, including the possibility to now combine signal regions to give a total likelihood for a model.

Integrated Model for E-Learning Acceptance

NASA Astrophysics Data System (ADS)

Ramadiani; Rodziah, A.; Hasan, S. M.; Rusli, A.; Noraini, C.

2016-01-01

E-learning is not going to work if the system is not used in accordance with user needs. User Interface is very important to encourage using the application. Many theories had discuss about user interface usability evaluation and technology acceptance separately, actually why we do not make it correlation between interface usability evaluation and user acceptance to enhance e-learning process. Therefore, the evaluation model for e-learning interface acceptance is considered important to investigate. The aim of this study is to propose the integrated e-learning user interface acceptance evaluation model. This model was combined some theories of e-learning interface measurement such as, user learning style, usability evaluation, and the user benefit. We formulated in constructive questionnaires which were shared at 125 English Language School (ELS) students. This research statistics used Structural Equation Model using LISREL v8.80 and MANOVA analysis.

Application of GIS Technology for Town Planning Tasks Solving

NASA Astrophysics Data System (ADS)

Kiyashko, G. A.

2017-11-01

For developing territories, one of the most actual town-planning tasks is to find out the suitable sites for building projects. The geographic information system (GIS) allows one to model complex spatial processes and can provide necessary effective tools to solve these tasks. We propose several GIS analysis models which can define suitable settlement allocations and select appropriate parcels for construction objects. We implement our models in the ArcGIS Desktop package and verify by application to the existing objects in Primorsky Region (Primorye Territory). These suitability models use several variations of the analysis method combinations and include various ways to resolve the suitability task using vector data and a raster data set. The suitability models created in this study can be combined, and one model can be integrated into another as its part. Our models can be updated by other suitability models for further detailed planning.

Modeling acclimatization by hybrid systems: condition changes alter biological system behavior models.

PubMed

Assar, Rodrigo; Montecino, Martín A; Maass, Alejandro; Sherman, David J

2014-07-01

In order to describe the dynamic behavior of a complex biological system, it is useful to combine models integrating processes at different levels and with temporal dependencies. Such combinations are necessary for modeling acclimatization, a phenomenon where changes in environmental conditions can induce drastic changes in the behavior of a biological system. In this article we formalize the use of hybrid systems as a tool to model this kind of biological behavior. A modeling scheme called strong switches is proposed. It allows one to take into account both minor adjustments to the coefficients of a continuous model, and, more interestingly, large-scale changes to the structure of the model. We illustrate the proposed methodology with two applications: acclimatization in wine fermentation kinetics, and acclimatization of osteo-adipo differentiation system linking stimulus signals to bone mass. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

The small length scale effect for a non-local cantilever beam: a paradox solved.

PubMed

Challamel, N; Wang, C M

2008-08-27

Non-local continuum mechanics allows one to account for the small length scale effect that becomes significant when dealing with microstructures or nanostructures. This paper presents some simplified non-local elastic beam models, for the bending analyses of small scale rods. Integral-type or gradient non-local models abandon the classical assumption of locality, and admit that stress depends not only on the strain value at that point but also on the strain values of all points on the body. There is a paradox still unresolved at this stage: some bending solutions of integral-based non-local elastic beams have been found to be identical to the classical (local) solution, i.e. the small scale effect is not present at all. One example is the Euler-Bernoulli cantilever nanobeam model with a point load which has application in microelectromechanical systems and nanoelectromechanical systems as an actuator. In this paper, it will be shown that this paradox may be overcome with a gradient elastic model as well as an integral non-local elastic model that is based on combining the local and the non-local curvatures in the constitutive elastic relation. The latter model comprises the classical gradient model and Eringen's integral model, and its application produces small length scale terms in the non-local elastic cantilever beam solution.

An integrated land change model for projecting future climate and land change scenarios

USGS Publications Warehouse

Wimberly, Michael; Sohl, Terry L.; Lamsal, Aashis; Liu, Zhihua; Hawbaker, Todd J.

2013-01-01

Climate change will have myriad effects on ecosystems worldwide, and natural and anthropogenic disturbances will be key drivers of these dynamics. In addition to climatic effects, continual expansion of human settlement into fire-prone forests will alter fire regimes, increase human vulnerability, and constrain future forest management options. There is a need for modeling tools to support the simulation and assessment of new management strategies over large regions in the context of changing climate, shifting development patterns, and an expanding wildland-urban interface. To address this need, we developed a prototype land change simulator that combines human-driven land use change (derived from the FORE-SCE model) with natural disturbances and vegetation dynamics (derived from the LADS model) and incorporates novel feedbacks between human land use and disturbance regimes. The prototype model was implemented in a test region encompassing the Denver metropolitan area along with its surrounding forested and agricultural landscapes. Initial results document the feasibility of integrated land change modeling at a regional scale but also highlighted conceptual and technical challenges for this type of model integration. Ongoing development will focus on improving climate sensitivities and modeling constraints imposed by climate change and human population growth on forest management activities.

Joint parameter and state estimation algorithms for real-time traffic monitoring.

DOT National Transportation Integrated Search

2013-12-01

A common approach to traffic monitoring is to combine a macroscopic traffic flow model with traffic sensor data in a process called state estimation, data fusion, or data assimilation. The main challenge of traffic state estimation is the integration...

Combining Bayesian Networks and Agent Based Modeling to develop a decision-support model in Vietnam

NASA Astrophysics Data System (ADS)

Nong, Bao Anh; Ertsen, Maurits; Schoups, Gerrit

2016-04-01

Complexity and uncertainty in natural resources management have been focus themes in recent years. Within these debates, with the aim to define an approach feasible for water management practice, we are developing an integrated conceptual modeling framework for simulating decision-making processes of citizens, in our case in the Day river area, Vietnam. The model combines Bayesian Networks (BNs) and Agent-Based Modeling (ABM). BNs are able to combine both qualitative data from consultants / experts / stakeholders, and quantitative data from observations on different phenomena or outcomes from other models. Further strengths of BNs are that the relationship between variables in the system is presented in a graphical interface, and that components of uncertainty are explicitly related to their probabilistic dependencies. A disadvantage is that BNs cannot easily identify the feedback of agents in the system once changes appear. Hence, ABM was adopted to represent the reaction among stakeholders under changes. The modeling framework is developed as an attempt to gain better understanding about citizen's behavior and factors influencing their decisions in order to reduce uncertainty in the implementation of water management policy.

Teaching at the interface of dance science and somatics.

PubMed

Geber, Pamela; Wilson, Margaret

2010-01-01

This article introduces a combined scientific and somatic approach to teaching and learning about the body, and explains how it can be of benefit to dancers and dance educators. The study of the science of movement (kinesiology) and a somatic approach to teaching are initially defined and described as distinct entities; following this, a model for integration of the two is presented. The authors advocate for such a combination in order to enhance dancing.

Multiscale digital Arabidopsis predicts individual organ and whole-organism growth.

PubMed

Chew, Yin Hoon; Wenden, Bénédicte; Flis, Anna; Mengin, Virginie; Taylor, Jasper; Davey, Christopher L; Tindal, Christopher; Thomas, Howard; Ougham, Helen J; de Reffye, Philippe; Stitt, Mark; Williams, Mathew; Muetzelfeldt, Robert; Halliday, Karen J; Millar, Andrew J

2014-09-30

Understanding how dynamic molecular networks affect whole-organism physiology, analogous to mapping genotype to phenotype, remains a key challenge in biology. Quantitative models that represent processes at multiple scales and link understanding from several research domains can help to tackle this problem. Such integrated models are more common in crop science and ecophysiology than in the research communities that elucidate molecular networks. Several laboratories have modeled particular aspects of growth in Arabidopsis thaliana, but it was unclear whether these existing models could productively be combined. We test this approach by constructing a multiscale model of Arabidopsis rosette growth. Four existing models were integrated with minimal parameter modification (leaf water content and one flowering parameter used measured data). The resulting framework model links genetic regulation and biochemical dynamics to events at the organ and whole-plant levels, helping to understand the combined effects of endogenous and environmental regulators on Arabidopsis growth. The framework model was validated and tested with metabolic, physiological, and biomass data from two laboratories, for five photoperiods, three accessions, and a transgenic line, highlighting the plasticity of plant growth strategies. The model was extended to include stochastic development. Model simulations gave insight into the developmental control of leaf production and provided a quantitative explanation for the pleiotropic developmental phenotype caused by overexpression of miR156, which was an open question. Modular, multiscale models, assembling knowledge from systems biology to ecophysiology, will help to understand and to engineer plant behavior from the genome to the field.

Target and Tissue Selectivity Prediction by Integrated Mechanistic Pharmacokinetic-Target Binding and Quantitative Structure Activity Modeling.

PubMed

Vlot, Anna H C; de Witte, Wilhelmus E A; Danhof, Meindert; van der Graaf, Piet H; van Westen, Gerard J P; de Lange, Elizabeth C M

2017-12-04

Selectivity is an important attribute of effective and safe drugs, and prediction of in vivo target and tissue selectivity would likely improve drug development success rates. However, a lack of understanding of the underlying (pharmacological) mechanisms and availability of directly applicable predictive methods complicates the prediction of selectivity. We explore the value of combining physiologically based pharmacokinetic (PBPK) modeling with quantitative structure-activity relationship (QSAR) modeling to predict the influence of the target dissociation constant (K D ) and the target dissociation rate constant on target and tissue selectivity. The K D values of CB1 ligands in the ChEMBL database are predicted by QSAR random forest (RF) modeling for the CB1 receptor and known off-targets (TRPV1, mGlu5, 5-HT1a). Of these CB1 ligands, rimonabant, CP-55940, and Δ 8 -tetrahydrocanabinol, one of the active ingredients of cannabis, were selected for simulations of target occupancy for CB1, TRPV1, mGlu5, and 5-HT1a in three brain regions, to illustrate the principles of the combined PBPK-QSAR modeling. Our combined PBPK and target binding modeling demonstrated that the optimal values of the K D and k off for target and tissue selectivity were dependent on target concentration and tissue distribution kinetics. Interestingly, if the target concentration is high and the perfusion of the target site is low, the optimal K D value is often not the lowest K D value, suggesting that optimization towards high drug-target affinity can decrease the benefit-risk ratio. The presented integrative structure-pharmacokinetic-pharmacodynamic modeling provides an improved understanding of tissue and target selectivity.

The integration of probabilistic information during sensorimotor estimation is unimpaired in children with Cerebral Palsy

PubMed Central

Sokhey, Taegh; Gaebler-Spira, Deborah; Kording, Konrad P.

2017-01-01

Background It is important to understand the motor deficits of children with Cerebral Palsy (CP). Our understanding of this motor disorder can be enriched by computational models of motor control. One crucial stage in generating movement involves combining uncertain information from different sources, and deficits in this process could contribute to reduced motor function in children with CP. Healthy adults can integrate previously-learned information (prior) with incoming sensory information (likelihood) in a close-to-optimal way when estimating object location, consistent with the use of Bayesian statistics. However, there are few studies investigating how children with CP perform sensorimotor integration. We compare sensorimotor estimation in children with CP and age-matched controls using a model-based analysis to understand the process. Methods and findings We examined Bayesian sensorimotor integration in children with CP, aged between 5 and 12 years old, with Gross Motor Function Classification System (GMFCS) levels 1–3 and compared their estimation behavior with age-matched typically-developing (TD) children. We used a simple sensorimotor estimation task which requires participants to combine probabilistic information from different sources: a likelihood distribution (current sensory information) with a prior distribution (learned target information). In order to examine sensorimotor integration, we quantified how participants weighed statistical information from the two sources (prior and likelihood) and compared this to the statistical optimal weighting. We found that the weighing of statistical information in children with CP was as statistically efficient as that of TD children. Conclusions We conclude that Bayesian sensorimotor integration is not impaired in children with CP and therefore, does not contribute to their motor deficits. Future research has the potential to enrich our understanding of motor disorders by investigating the stages of motor processing set out by computational models. Therapeutic interventions should exploit the ability of children with CP to use statistical information. PMID:29186196

Using the framework of corporate culture in "mergers" to support the development of a cultural basis for integrative medicine - guidance for building an integrative medicine department or service.

PubMed

Witt, Claudia M; Pérard, Marion; Berman, Brian; Berman, Susan; Birdsall, Timothy C; Defren, Horst; Kümmel, Sherko; Deng, Gary; Dobos, Gustav; Drexler, Atje; Holmberg, Christine; Horneber, Markus; Jütte, Robert; Knutson, Lori; Kummer, Christopher; Volpers, Susanne; Schweiger, David

2015-01-01

An increasing number of clinics offer complementary or integrative medicine services; however, clear guidance about how complementary medicine could be successfully and efficiently integrated into conventional health care settings is still lacking. Combining conventional and complementary medicine into integrative medicine can be regarded as a kind of merger. In a merger, two or more organizations - usually companies - are combined into one in order to strengthen the companies financially and strategically. The corporate culture of both merger partners has an important influence on the integration. The aim of this project was to transfer the concept of corporate culture in mergers to the merging of two medical systems. A two-step approach (literature analyses and expert consensus procedure) was used to develop practical guidance for the development of a cultural basis for integrative medicine, based on the framework of corporate culture in "mergers," which could be used to build an integrative medicine department or integrative medicine service. Results include recommendations for general strategic dimensions (definition of the medical model, motivation for integration, clarification of the available resources, development of the integration team, and development of a communication strategy), and recommendations to overcome cultural differences (the clinic environment, the professional language, the professional image, and the implementation of evidence-based medicine). The framework of mergers in corporate culture provides an understanding of the difficulties involved in integrative medicine projects. The specific recommendations provide a good basis for more efficient implementation.

Using the framework of corporate culture in “mergers” to support the development of a cultural basis for integrative medicine – guidance for building an integrative medicine department or service

PubMed Central

Witt, Claudia M; Pérard, Marion; Berman, Brian; Berman, Susan; Birdsall, Timothy C; Defren, Horst; Kümmel, Sherko; Deng, Gary; Dobos, Gustav; Drexler, Atje; Holmberg, Christine; Horneber, Markus; Jütte, Robert; Knutson, Lori; Kummer, Christopher; Volpers, Susanne; Schweiger, David

2015-01-01

Background An increasing number of clinics offer complementary or integrative medicine services; however, clear guidance about how complementary medicine could be successfully and efficiently integrated into conventional health care settings is still lacking. Combining conventional and complementary medicine into integrative medicine can be regarded as a kind of merger. In a merger, two or more organizations − usually companies − are combined into one in order to strengthen the companies financially and strategically. The corporate culture of both merger partners has an important influence on the integration. Purpose The aim of this project was to transfer the concept of corporate culture in mergers to the merging of two medical systems. Methods A two-step approach (literature analyses and expert consensus procedure) was used to develop practical guidance for the development of a cultural basis for integrative medicine, based on the framework of corporate culture in “mergers,” which could be used to build an integrative medicine department or integrative medicine service. Results Results include recommendations for general strategic dimensions (definition of the medical model, motivation for integration, clarification of the available resources, development of the integration team, and development of a communication strategy), and recommendations to overcome cultural differences (the clinic environment, the professional language, the professional image, and the implementation of evidence-based medicine). Conclusion The framework of mergers in corporate culture provides an understanding of the difficulties involved in integrative medicine projects. The specific recommendations provide a good basis for more efficient implementation. PMID:25632226

PDC-SGB: Prediction of effective drug combinations using a stochastic gradient boosting algorithm.

PubMed

Xu, Qian; Xiong, Yi; Dai, Hao; Kumari, Kotni Meena; Xu, Qin; Ou, Hong-Yu; Wei, Dong-Qing

2017-03-21

Combinatorial therapy is a promising strategy for combating complex diseases by improving the efficacy and reducing the side effects. To facilitate the identification of drug combinations in pharmacology, we proposed a new computational model, termed PDC-SGB, to predict effective drug combinations by integrating biological, chemical and pharmacological information based on a stochastic gradient boosting algorithm. To begin with, a set of 352 golden positive samples were collected from the public drug combination database. Then, a set of 732 dimensional feature vector involving biological, chemical and pharmaceutical information was constructed for each drug combination to describe its properties. To avoid overfitting, the maximum relevance & minimum redundancy (mRMR) method was performed to extract useful ones by removing redundant subsets. Based on the selected features, the three different type of classification algorithms were employed to build the drug combination prediction models. Our results demonstrated that the model based on the stochastic gradient boosting algorithm yield out the best performance. Furthermore, it is indicated that the feature patterns of therapy had powerful ability to discriminate effective drug combinations from non-effective ones. By analyzing various features, it is shown that the enriched features occurred frequently in golden positive samples can help predict novel drug combinations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multi-Hypothesis Modelling Capabilities for Robust Data-Model Integration

NASA Astrophysics Data System (ADS)

Walker, A. P.; De Kauwe, M. G.; Lu, D.; Medlyn, B.; Norby, R. J.; Ricciuto, D. M.; Rogers, A.; Serbin, S.; Weston, D. J.; Ye, M.; Zaehle, S.

2017-12-01

Large uncertainty is often inherent in model predictions due to imperfect knowledge of how to describe the mechanistic processes (hypotheses) that a model is intended to represent. Yet this model hypothesis uncertainty (MHU) is often overlooked or informally evaluated, as methods to quantify and evaluate MHU are limited. MHU is increased as models become more complex because each additional processes added to a model comes with inherent MHU as well as parametric unceratinty. With the current trend of adding more processes to Earth System Models (ESMs), we are adding uncertainty, which can be quantified for parameters but not MHU. Model inter-comparison projects do allow for some consideration of hypothesis uncertainty but in an ad hoc and non-independent fashion. This has stymied efforts to evaluate ecosystem models against data and intepret the results mechanistically because it is not simple to interpret exactly why a model is producing the results it does and identify which model assumptions are key as they combine models of many sub-systems and processes, each of which may be conceptualised and represented mathematically in various ways. We present a novel modelling framework—the multi-assumption architecture and testbed (MAAT)—that automates the combination, generation, and execution of a model ensemble built with different representations of process. We will present the argument that multi-hypothesis modelling needs to be considered in conjunction with other capabilities (e.g. the Predictive Ecosystem Analyser; PecAn) and statistical methods (e.g. sensitivity anaylsis, data assimilation) to aid efforts in robust data model integration to enhance our predictive understanding of biological systems.

A Novel Multisensory Integration Task Reveals Robust Deficits in Rodent Models of Schizophrenia: Converging Evidence for Remediation via Nicotinic Receptor Stimulation of Inhibitory Transmission in the Prefrontal Cortex.

PubMed

Cloke, Jacob M; Nguyen, Robin; Chung, Beryl Y T; Wasserman, David I; De Lisio, Stephanie; Kim, Jun Chul; Bailey, Craig D C; Winters, Boyer D

2016-12-14

Atypical multisensory integration is an understudied cognitive symptom in schizophrenia. Procedures to evaluate multisensory integration in rodent models are lacking. We developed a novel multisensory object oddity (MSO) task to assess multisensory integration in ketamine-treated rats, a well established model of schizophrenia. Ketamine-treated rats displayed a selective MSO task impairment with tactile-visual and olfactory-visual sensory combinations, whereas basic unisensory perception was unaffected. Orbitofrontal cortex (OFC) administration of nicotine or ABT-418, an α 4 β 2 nicotinic acetylcholine receptor (nAChR) agonist, normalized MSO task performance in ketamine-treated rats and this effect was blocked by GABA A receptor antagonism. GABAergic currents were also decreased in OFC of ketamine-treated rats and were normalized by activation of α 4 β 2 nAChRs. Furthermore, parvalbumin (PV) immunoreactivity was decreased in the OFC of ketamine-treated rats. Accordingly, silencing of PV interneurons in OFC of PV-Cre mice using DREADDs (Designer Receptors Exclusively Activated by Designer Drugs) selectively impaired MSO task performance and this was reversed by ABT-418. Likewise, clozapine-N-oxide-induced inhibition of PV interneurons in brain slices was reversed by activation of α 4 β 2 nAChRs. These findings strongly imply a role for prefrontal GABAergic transmission in the integration of multisensory object features, a cognitive process with relevance to schizophrenia. Accordingly, nAChR agonism, which improves various facets of cognition in schizophrenia, reversed the severe MSO task impairment in this study and appears to do so via a GABAergic mechanism. Interactions between GABAergic and nAChR receptor systems warrant further investigation for potential therapeutic applications. The novel behavioral procedure introduced in the current study is acutely sensitive to schizophrenia-relevant cognitive impairment and should prove highly valuable for such research. Adaptive behaviors are driven by integration of information from different sensory modalities. Multisensory integration is disrupted in patients with schizophrenia, but little is known about the neural basis of this cognitive symptom. Development and validation of multisensory integration tasks for animal models is essential given the strong link between functional outcome and cognitive impairment in schizophrenia. We present a novel multisensory object oddity procedure that detects selective multisensory integration deficits in a rat model of schizophrenia using various combinations of sensory modalities. Moreover, converging data are consistent with a nicotinic-GABAergic mechanism of multisensory integration in the prefrontal cortex, results with strong clinical relevance to the study of cognitive impairment and treatment in schizophrenia. Copyright © 2016 the authors 0270-6474/16/3612571-16$15.00/0.

The roots of violence: converging psychoanalytic explanatory models for power struggles and violence in schools.

PubMed

Twemlow, S W

2000-10-01

This paper demonstrates that several psychoanalytic models taken together converge to collectively explain school violence and power struggles better than each does alone. Using my own experience in doing psychoanalytically informed community intervention, I approach the problem of school violence from a combination of Adlerian, Stollerian, dialectical social systems, and Klein-Bion perspectives. This integrated model is then applied to the Columbine High School massacre in Littleton, Colorado.

Results of experimental tests in the MSFC 14 x 14 inch trisonic wind tunnel on a .004 scale model space shuttle integrated vehicle 5 (model 77-O, 74-TS) to relieve wing loads during ascent (IA71)

NASA Technical Reports Server (NTRS)

Allen, E. C.

1975-01-01

Results are presented for the 0.004-scale orbiter, external tank, and solid rocket boosters combined as an integrated vehicle in a trisonic wind tunnel at mach numbers from 0.6 to 2.0. The primary test objective was to determine the effectiveness of several methods in relieving the Orbiter wing bending and torsion loads and moments during launch. Effects of several midwing spoilers, termed flipper doors, and Orbiter/external tank incidence were investigated. Photographs are included.

Integrated Pest Management in a Predator-Prey System with Allee Effects.

PubMed

Costa, M I S; dos Anjos, L

2015-08-01

A commonly used biocontrol strategy to control invasive pests with Allee effects consists of the deliberate introduction of natural enemies. To enhance the effectiveness of this strategy, several tactics of control of invasive species (e.g., mass-trapping, manual removal of individuals, and pesticide spraying) are combined so as to impair pest outbreaks. This combination of strategies to control pest species dynamics are usually named integrated pest management (IPM). In this work, we devise a predator-prey dynamical model in order to assess the influence of the intensity of chemical killing on the success of an IPM. The biological and mathematical framework presented in this study can also be analyzed in the light of species conservation and food web dynamics theory.

Solving the Integral of Quadratic Forms of Covariance Matrices for Applications in Polarimetric Radar Imagery

NASA Astrophysics Data System (ADS)

Marino, Armando; Hajnsek, Irena

2015-04-01

In this work, the solution of quadratic forms with special application to polarimetric and interferometric covariance matrices is investigated. An analytical solution for the integral of a single quadratic form is derived. Additionally, the integral of the Pol-InSAR coherence (expressed as combination of quadratic forms) is investigated. An approximation for such integral is proposed and defined as Trace coherence. Such approximation is tested on real data to verify that the error is acceptable. The trace coherence can be used for tackle problems related to change detection. Moreover, the use of the Trace coherence in model inversion (as for the RVoG three stage inversion) will be investigated in the future.

Protecting Digital Evidence Integrity by Using Smart Cards

NASA Astrophysics Data System (ADS)

Saleem, Shahzad; Popov, Oliver

RFC 3227 provides general guidelines for digital evidence collection and archiving, while the International Organization on Computer Evidence offers guidelines for best practice in the digital forensic examination. In the light of these guidelines we will analyze integrity protection mechanism provided by EnCase and FTK which is mainly based on Message Digest Codes (MDCs). MDCs for integrity protection are not tamper proof, hence they can be forged. With the proposed model for protecting digital evidence integrity by using smart cards (PIDESC) that establishes a secure platform for digitally signing the MDC (in general for a whole range of cryptographic services) in combination with Public Key Cryptography (PKC), one can show that this weakness might be overcome.

Design of Xen Hybrid Multiple Police Model

NASA Astrophysics Data System (ADS)

Sun, Lei; Lin, Renhao; Zhu, Xianwei

2017-10-01

Virtualization Technology has attracted more and more attention. As a popular open-source virtualization tools, XEN is used more and more frequently. Xsm, XEN security model, has also been widespread concern. The safety status classification has not been established in the XSM, and it uses the virtual machine as a managed object to make Dom0 a unique administrative domain that does not meet the minimum privilege. According to these questions, we design a Hybrid multiple police model named SV_HMPMD that organically integrates multiple single security policy models include DTE,RBAC,BLP. It can fullfill the requirement of confidentiality and integrity for security model and use different particle size to different domain. In order to improve BLP’s practicability, the model introduce multi-level security labels. In order to divide the privilege in detail, we combine DTE with RBAC. In order to oversize privilege, we limit the privilege of domain0.

Modeling the Development of Audiovisual Cue Integration in Speech Perception

PubMed Central

Getz, Laura M.; Nordeen, Elke R.; Vrabic, Sarah C.; Toscano, Joseph C.

2017-01-01

Adult speech perception is generally enhanced when information is provided from multiple modalities. In contrast, infants do not appear to benefit from combining auditory and visual speech information early in development. This is true despite the fact that both modalities are important to speech comprehension even at early stages of language acquisition. How then do listeners learn how to process auditory and visual information as part of a unified signal? In the auditory domain, statistical learning processes provide an excellent mechanism for acquiring phonological categories. Is this also true for the more complex problem of acquiring audiovisual correspondences, which require the learner to integrate information from multiple modalities? In this paper, we present simulations using Gaussian mixture models (GMMs) that learn cue weights and combine cues on the basis of their distributional statistics. First, we simulate the developmental process of acquiring phonological categories from auditory and visual cues, asking whether simple statistical learning approaches are sufficient for learning multi-modal representations. Second, we use this time course information to explain audiovisual speech perception in adult perceivers, including cases where auditory and visual input are mismatched. Overall, we find that domain-general statistical learning techniques allow us to model the developmental trajectory of audiovisual cue integration in speech, and in turn, allow us to better understand the mechanisms that give rise to unified percepts based on multiple cues. PMID:28335558

Modeling the Development of Audiovisual Cue Integration in Speech Perception.

PubMed

Getz, Laura M; Nordeen, Elke R; Vrabic, Sarah C; Toscano, Joseph C

2017-03-21

Adult speech perception is generally enhanced when information is provided from multiple modalities. In contrast, infants do not appear to benefit from combining auditory and visual speech information early in development. This is true despite the fact that both modalities are important to speech comprehension even at early stages of language acquisition. How then do listeners learn how to process auditory and visual information as part of a unified signal? In the auditory domain, statistical learning processes provide an excellent mechanism for acquiring phonological categories. Is this also true for the more complex problem of acquiring audiovisual correspondences, which require the learner to integrate information from multiple modalities? In this paper, we present simulations using Gaussian mixture models (GMMs) that learn cue weights and combine cues on the basis of their distributional statistics. First, we simulate the developmental process of acquiring phonological categories from auditory and visual cues, asking whether simple statistical learning approaches are sufficient for learning multi-modal representations. Second, we use this time course information to explain audiovisual speech perception in adult perceivers, including cases where auditory and visual input are mismatched. Overall, we find that domain-general statistical learning techniques allow us to model the developmental trajectory of audiovisual cue integration in speech, and in turn, allow us to better understand the mechanisms that give rise to unified percepts based on multiple cues.

Modeling global vector fields of chaotic systems from noisy time series with the aid of structure-selection techniques.

PubMed

Xu, Daolin; Lu, Fangfang

2006-12-01

We address the problem of reconstructing a set of nonlinear differential equations from chaotic time series. A method that combines the implicit Adams integration and the structure-selection technique of an error reduction ratio is proposed for system identification and corresponding parameter estimation of the model. The structure-selection technique identifies the significant terms from a pool of candidates of functional basis and determines the optimal model through orthogonal characteristics on data. The technique with the Adams integration algorithm makes the reconstruction available to data sampled with large time intervals. Numerical experiment on Lorenz and Rossler systems shows that the proposed strategy is effective in global vector field reconstruction from noisy time series.

Integrated Modeling of Complex Optomechanical Systems

NASA Astrophysics Data System (ADS)

Andersen, Torben; Enmark, Anita

2011-09-01

Mathematical modeling and performance simulation are playing an increasing role in large, high-technology projects. There are two reasons; first, projects are now larger than they were before, and the high cost calls for detailed performance prediction before construction. Second, in particular for space-related designs, it is often difficult to test systems under realistic conditions beforehand, and mathematical modeling is then needed to verify in advance that a system will work as planned. Computers have become much more powerful, permitting calculations that were not possible before. At the same time mathematical tools have been further developed and found acceptance in the community. Particular progress has been made in the fields of structural mechanics, optics and control engineering, where new methods have gained importance over the last few decades. Also, methods for combining optical, structural and control system models into global models have found widespread use. Such combined models are usually called integrated models and were the subject of this symposium. The objective was to bring together people working in the fields of groundbased optical telescopes, ground-based radio telescopes, and space telescopes. We succeeded in doing so and had 39 interesting presentations and many fruitful discussions during coffee and lunch breaks and social arrangements. We are grateful that so many top ranked specialists found their way to Kiruna and we believe that these proceedings will prove valuable during much future work.

Monte Carlo simulations for generic granite repository studies

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

Chu, Shaoping; Lee, Joon H; Wang, Yifeng

In a collaborative study between Los Alamos National Laboratory (LANL) and Sandia National Laboratories (SNL) for the DOE-NE Office of Fuel Cycle Technologies Used Fuel Disposition (UFD) Campaign project, we have conducted preliminary system-level analyses to support the development of a long-term strategy for geologic disposal of high-level radioactive waste. A general modeling framework consisting of a near- and a far-field submodel for a granite GDSE was developed. A representative far-field transport model for a generic granite repository was merged with an integrated systems (GoldSim) near-field model. Integrated Monte Carlo model runs with the combined near- and farfield transport modelsmore » were performed, and the parameter sensitivities were evaluated for the combined system. In addition, a sub-set of radionuclides that are potentially important to repository performance were identified and evaluated for a series of model runs. The analyses were conducted with different waste inventory scenarios. Analyses were also conducted for different repository radionuelide release scenarios. While the results to date are for a generic granite repository, the work establishes the method to be used in the future to provide guidance on the development of strategy for long-term disposal of high-level radioactive waste in a granite repository.« less

3D automatic anatomy recognition based on iterative graph-cut-ASM

NASA Astrophysics Data System (ADS)

Chen, Xinjian; Udupa, Jayaram K.; Bagci, Ulas; Alavi, Abass; Torigian, Drew A.

2010-02-01

We call the computerized assistive process of recognizing, delineating, and quantifying organs and tissue regions in medical imaging, occurring automatically during clinical image interpretation, automatic anatomy recognition (AAR). The AAR system we are developing includes five main parts: model building, object recognition, object delineation, pathology detection, and organ system quantification. In this paper, we focus on the delineation part. For the modeling part, we employ the active shape model (ASM) strategy. For recognition and delineation, we integrate several hybrid strategies of combining purely image based methods with ASM. In this paper, an iterative Graph-Cut ASM (IGCASM) method is proposed for object delineation. An algorithm called GC-ASM was presented at this symposium last year for object delineation in 2D images which attempted to combine synergistically ASM and GC. Here, we extend this method to 3D medical image delineation. The IGCASM method effectively combines the rich statistical shape information embodied in ASM with the globally optimal delineation capability of the GC method. We propose a new GC cost function, which effectively integrates the specific image information with the ASM shape model information. The proposed methods are tested on a clinical abdominal CT data set. The preliminary results show that: (a) it is feasible to explicitly bring prior 3D statistical shape information into the GC framework; (b) the 3D IGCASM delineation method improves on ASM and GC and can provide practical operational time on clinical images.

ChlamyCyc: an integrative systems biology database and web-portal for Chlamydomonas reinhardtii.

PubMed

May, Patrick; Christian, Jan-Ole; Kempa, Stefan; Walther, Dirk

2009-05-04

The unicellular green alga Chlamydomonas reinhardtii is an important eukaryotic model organism for the study of photosynthesis and plant growth. In the era of modern high-throughput technologies there is an imperative need to integrate large-scale data sets from high-throughput experimental techniques using computational methods and database resources to provide comprehensive information about the molecular and cellular organization of a single organism. In the framework of the German Systems Biology initiative GoFORSYS, a pathway database and web-portal for Chlamydomonas (ChlamyCyc) was established, which currently features about 250 metabolic pathways with associated genes, enzymes, and compound information. ChlamyCyc was assembled using an integrative approach combining the recently published genome sequence, bioinformatics methods, and experimental data from metabolomics and proteomics experiments. We analyzed and integrated a combination of primary and secondary database resources, such as existing genome annotations from JGI, EST collections, orthology information, and MapMan classification. ChlamyCyc provides a curated and integrated systems biology repository that will enable and assist in systematic studies of fundamental cellular processes in Chlamydomonas. The ChlamyCyc database and web-portal is freely available under http://chlamycyc.mpimp-golm.mpg.de.

Integrated three-dimensional shape and reflection properties measurement system.

PubMed

Krzesłowski, Jakub; Sitnik, Robert; Maczkowski, Grzegorz

2011-02-01

Creating accurate three-dimensional (3D) digitalized models of cultural heritage objects requires that information about surface geometry be integrated with measurements of other material properties like color and reflectance. Up until now, these measurements have been performed in laboratories using manually integrated (subjective) data analyses. We describe an out-of-laboratory bidirectional reflectance distribution function (BRDF) and 3D shape measurement system that implements shape and BRDF measurement in a single setup with BRDF uncertainty evaluation. The setup aligns spatial data with the angular reflectance distribution, yielding a better estimation of the surface's reflective properties by integrating these two modality measurements into one setup using a single detector. This approach provides a better picture of an object's intrinsic material features, which in turn produces a higher-quality digitalized model reconstruction. Furthermore, this system simplifies the data processing by combining structured light projection and photometric stereo. The results of our method of data analysis describe the diffusive and specular attributes corresponding to every measured geometric point and can be used to render intricate 3D models in an arbitrarily illuminated scene.

Automation for System Safety Analysis

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Fleming, Land; Throop, David; Thronesbery, Carroll; Flores, Joshua; Bennett, Ted; Wennberg, Paul

2009-01-01

This presentation describes work to integrate a set of tools to support early model-based analysis of failures and hazards due to system-software interactions. The tools perform and assist analysts in the following tasks: 1) extract model parts from text for architecture and safety/hazard models; 2) combine the parts with library information to develop the models for visualization and analysis; 3) perform graph analysis and simulation to identify and evaluate possible paths from hazard sources to vulnerable entities and functions, in nominal and anomalous system-software configurations and scenarios; and 4) identify resulting candidate scenarios for software integration testing. There has been significant technical progress in model extraction from Orion program text sources, architecture model derivation (components and connections) and documentation of extraction sources. Models have been derived from Internal Interface Requirements Documents (IIRDs) and FMEA documents. Linguistic text processing is used to extract model parts and relationships, and the Aerospace Ontology also aids automated model development from the extracted information. Visualizations of these models assist analysts in requirements overview and in checking consistency and completeness.

Massive integration of diverse protein quality assessment methods to improve template based modeling in CASP11.

PubMed

Cao, Renzhi; Bhattacharya, Debswapna; Adhikari, Badri; Li, Jilong; Cheng, Jianlin

2016-09-01

Model evaluation and selection is an important step and a big challenge in template-based protein structure prediction. Individual model quality assessment methods designed for recognizing some specific properties of protein structures often fail to consistently select good models from a model pool because of their limitations. Therefore, combining multiple complimentary quality assessment methods is useful for improving model ranking and consequently tertiary structure prediction. Here, we report the performance and analysis of our human tertiary structure predictor (MULTICOM) based on the massive integration of 14 diverse complementary quality assessment methods that was successfully benchmarked in the 11th Critical Assessment of Techniques of Protein Structure prediction (CASP11). The predictions of MULTICOM for 39 template-based domains were rigorously assessed by six scoring metrics covering global topology of Cα trace, local all-atom fitness, side chain quality, and physical reasonableness of the model. The results show that the massive integration of complementary, diverse single-model and multi-model quality assessment methods can effectively leverage the strength of single-model methods in distinguishing quality variation among similar good models and the advantage of multi-model quality assessment methods of identifying reasonable average-quality models. The overall excellent performance of the MULTICOM predictor demonstrates that integrating a large number of model quality assessment methods in conjunction with model clustering is a useful approach to improve the accuracy, diversity, and consequently robustness of template-based protein structure prediction. Proteins 2016; 84(Suppl 1):247-259. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Integrity monitoring of vehicle positioning in urban environment using RTK-GNSS, IMU and speedometer

NASA Astrophysics Data System (ADS)

El-Mowafy, Ahmed; Kubo, Nobuaki

2017-05-01

Continuous and trustworthy positioning is a critical capability for advanced driver assistance systems (ADAS). To achieve continuous positioning, methods such as global navigation satellite systems real-time kinematic (RTK), Doppler-based positioning, and positioning using low-cost inertial measurement unit (IMU) with car speedometer data are combined in this study. To ensure reliable positioning, the system should have integrity monitoring above a certain level, such as 99%. Achieving this level when combining different types of measurements that have different characteristics and different types of errors is a challenge. In this study, a novel integrity monitoring approach is presented for the proposed integrated system. A threat model of the measurements of the system components is discussed, which includes both the nominal performance and possible fault modes. A new protection level is presented to bound the maximum directional position error. The proposed approach was evaluated through a kinematic test in an urban area in Japan with a focus on horizontal positioning. Test results show that by integrating RTK, Doppler with IMU/speedometer, 100% positioning availability was achieved. The integrity monitoring availability was assessed and found to meet the target value where the position errors were bounded by the protection level, which was also less than an alert level, indicating the effectiveness of the proposed approach.

Group Membership, Group Change, and Intergroup Attitudes: A Recategorization Model Based on Cognitive Consistency Principles.

PubMed

Roth, Jenny; Steffens, Melanie C; Vignoles, Vivian L

2018-01-01

The present article introduces a model based on cognitive consistency principles to predict how new identities become integrated into the self-concept, with consequences for intergroup attitudes. The model specifies four concepts (self-concept, stereotypes, identification, and group compatibility) as associative connections. The model builds on two cognitive principles, balance-congruity and imbalance-dissonance, to predict identification with social groups that people currently belong to, belonged to in the past, or newly belong to. More precisely, the model suggests that the relative strength of self-group associations (i.e., identification) depends in part on the (in)compatibility of the different social groups. Combining insights into cognitive representation of knowledge, intergroup bias, and explicit/implicit attitude change, we further derive predictions for intergroup attitudes. We suggest that intergroup attitudes alter depending on the relative associative strength between the social groups and the self, which in turn is determined by the (in)compatibility between social groups. This model unifies existing models on the integration of social identities into the self-concept by suggesting that basic cognitive mechanisms play an important role in facilitating or hindering identity integration and thus contribute to reducing or increasing intergroup bias.

Integrated performance and reliability specification for digital avionics systems

NASA Technical Reports Server (NTRS)

Brehm, Eric W.; Goettge, Robert T.

1995-01-01

This paper describes an automated tool for performance and reliability assessment of digital avionics systems, called the Automated Design Tool Set (ADTS). ADTS is based on an integrated approach to design assessment that unifies traditional performance and reliability views of system designs, and that addresses interdependencies between performance and reliability behavior via exchange of parameters and result between mathematical models of each type. A multi-layer tool set architecture has been developed for ADTS that separates the concerns of system specification, model generation, and model solution. Performance and reliability models are generated automatically as a function of candidate system designs, and model results are expressed within the system specification. The layered approach helps deal with the inherent complexity of the design assessment process, and preserves long-term flexibility to accommodate a wide range of models and solution techniques within the tool set structure. ADTS research and development to date has focused on development of a language for specification of system designs as a basis for performance and reliability evaluation. A model generation and solution framework has also been developed for ADTS, that will ultimately encompass an integrated set of analytic and simulated based techniques for performance, reliability, and combined design assessment.

Modeling of anomalous electron mobility in Hall thrusters

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

Koo, Justin W.; Boyd, Iain D.

Accurate modeling of the anomalous electron mobility is absolutely critical for successful simulation of Hall thrusters. In this work, existing computational models for the anomalous electron mobility are used to simulate the UM/AFRL P5 Hall thruster (a 5 kW laboratory model) in a two-dimensional axisymmetric hybrid particle-in-cell Monte Carlo collision code. Comparison to experimental results indicates that, while these computational models can be tuned to reproduce the correct thrust or discharge current, it is very difficult to match all integrated performance parameters (thrust, power, discharge current, etc.) simultaneously. Furthermore, multiple configurations of these computational models can produce reasonable integrated performancemore » parameters. A semiempirical electron mobility profile is constructed from a combination of internal experimental data and modeling assumptions. This semiempirical electron mobility profile is used in the code and results in more accurate simulation of both the integrated performance parameters and the mean potential profile of the thruster. Results indicate that the anomalous electron mobility, while absolutely necessary in the near-field region, provides a substantially smaller contribution to the total electron mobility in the high Hall current region near the thruster exit plane.« less

Group Membership, Group Change, and Intergroup Attitudes: A Recategorization Model Based on Cognitive Consistency Principles

PubMed Central

Roth, Jenny; Steffens, Melanie C.; Vignoles, Vivian L.

2018-01-01

The present article introduces a model based on cognitive consistency principles to predict how new identities become integrated into the self-concept, with consequences for intergroup attitudes. The model specifies four concepts (self-concept, stereotypes, identification, and group compatibility) as associative connections. The model builds on two cognitive principles, balance–congruity and imbalance–dissonance, to predict identification with social groups that people currently belong to, belonged to in the past, or newly belong to. More precisely, the model suggests that the relative strength of self-group associations (i.e., identification) depends in part on the (in)compatibility of the different social groups. Combining insights into cognitive representation of knowledge, intergroup bias, and explicit/implicit attitude change, we further derive predictions for intergroup attitudes. We suggest that intergroup attitudes alter depending on the relative associative strength between the social groups and the self, which in turn is determined by the (in)compatibility between social groups. This model unifies existing models on the integration of social identities into the self-concept by suggesting that basic cognitive mechanisms play an important role in facilitating or hindering identity integration and thus contribute to reducing or increasing intergroup bias. PMID:29681878

Exposure Space: Integrating Exposure Data and Modeling with Toxicity Information

EPA Science Inventory

Recent advances have been made in high-throughput (HTP) toxicity testing, e.g. from ToxCast, which will ultimately be combined with HTP predictions of exposure potential to support next-generation chemical safety assessment. Rapid exposure methods are essential in selecting chemi...

Integrated Assessment Methodologies For Land Use Changes and Flood Plain Restoration As Alternative Flood Protection Strategies In The River Basins of Rhine and Meuse

NASA Astrophysics Data System (ADS)

Brouwer, Roy; van Ek, Remco; Bouma, Jetske

Water policy and management decisions become increasingly better informed. Often a large number of studies is carried out before a decision is taken. In the Netherlands, some of these studies, such as environmental impact assessment, are obligatory by law if serious environmental impacts are expected. However, an integrated assessment based on these separate studies is lacking. In this study, an attempt was made to combine and where possible integrate procedures and methods from environmental, social and economic impact assessment. The main objective of the study is to assess, separately and in combination, the ecological, social and economic consequences of land use changes and floodplain restoration as alternative flood protection strategies in the river basins of the rivers Rhine and Meuse in the Netherlands. Based on scenarios of climate change, land subsidence and sea level rise over the next fifty years the associated hy drological changes are translated into the corresponding ecological, economic and social impacts, using a combination of expert judgement and advanced modelling techniques. These impacts are assessed and evaluated with the help of integrated assessment methods such as cost-benefit and multi-criteria analysis in order to support decision-making towards the implementation of new policy regarding flood protection. The outcome of the integrated assessment is related to other water policy objectives, including restoration of the resilience of water systems and nature conservation.

A combined approach of AHP and TOPSIS methods applied in the field of integrated software systems

NASA Astrophysics Data System (ADS)

Berdie, A. D.; Osaci, M.; Muscalagiu, I.; Barz, C.

2017-05-01

Adopting the most appropriate technology for developing applications on an integrated software system for enterprises, may result in great savings both in cost and hours of work. This paper proposes a research study for the determination of a hierarchy between three SAP (System Applications and Products in Data Processing) technologies. The technologies Web Dynpro -WD, Floorplan Manager - FPM and CRM WebClient UI - CRM WCUI are multi-criteria evaluated in terms of the obtained performances through the implementation of the same web business application. To establish the hierarchy a multi-criteria analysis model that combines the AHP (Analytic Hierarchy Process) and the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) methods was proposed. This model was built with the help of the SuperDecision software. This software is based on the AHP method and determines the weights for the selected sets of criteria. The TOPSIS method was used to obtain the final ranking and the technologies hierarchy.

Ontology Design Patterns as Interfaces (invited)

NASA Astrophysics Data System (ADS)

Janowicz, K.

2015-12-01

In recent years ontology design patterns (ODP) have gained popularity among knowledge engineers. ODPs are modular but self-contained building blocks that are reusable and extendible. They minimize the amount of ontological commitments and thereby are easier to integrate than large monolithic ontologies. Typically, patterns are not directly used to annotate data or to model certain domain problems but are combined and extended to form data and purpose-driven local ontologies that serve the needs of specific applications or communities. By relying on a common set of patterns these local ontologies can be aligned to improve interoperability and enable federated queries without enforcing a top-down model of the domain. In previous work, we introduced ontological views as layer on top of ontology design patterns to ease the reuse, combination, and integration of patterns. While the literature distinguishes multiple types of patterns, e.g., content patterns or logical patterns, we propose to use them as interfaces here to guide the development of ontology-driven systems.

Methods for integrating moderation and mediation: a general analytical framework using moderated path analysis.

PubMed

Edwards, Jeffrey R; Lambert, Lisa Schurer

2007-03-01

Studies that combine moderation and mediation are prevalent in basic and applied psychology research. Typically, these studies are framed in terms of moderated mediation or mediated moderation, both of which involve similar analytical approaches. Unfortunately, these approaches have important shortcomings that conceal the nature of the moderated and the mediated effects under investigation. This article presents a general analytical framework for combining moderation and mediation that integrates moderated regression analysis and path analysis. This framework clarifies how moderator variables influence the paths that constitute the direct, indirect, and total effects of mediated models. The authors empirically illustrate this framework and give step-by-step instructions for estimation and interpretation. They summarize the advantages of their framework over current approaches, explain how it subsumes moderated mediation and mediated moderation, and describe how it can accommodate additional moderator and mediator variables, curvilinear relationships, and structural equation models with latent variables. (c) 2007 APA, all rights reserved.

Multisensory Integration and Internal Models for Sensing Gravity Effects in Primates

PubMed Central

Lacquaniti, Francesco; La Scaleia, Barbara; Maffei, Vincenzo

2014-01-01

Gravity is crucial for spatial perception, postural equilibrium, and movement generation. The vestibular apparatus is the main sensory system involved in monitoring gravity. Hair cells in the vestibular maculae respond to gravitoinertial forces, but they cannot distinguish between linear accelerations and changes of head orientation relative to gravity. The brain deals with this sensory ambiguity (which can cause some lethal airplane accidents) by combining several cues with the otolith signals: angular velocity signals provided by the semicircular canals, proprioceptive signals from muscles and tendons, visceral signals related to gravity, and visual signals. In particular, vision provides both static and dynamic signals about body orientation relative to the vertical, but it poorly discriminates arbitrary accelerations of moving objects. However, we are able to visually detect the specific acceleration of gravity since early infancy. This ability depends on the fact that gravity effects are stored in brain regions which integrate visual, vestibular, and neck proprioceptive signals and combine this information with an internal model of gravity effects. PMID:25061610

Multisensory integration and internal models for sensing gravity effects in primates.

PubMed

Lacquaniti, Francesco; Bosco, Gianfranco; Gravano, Silvio; Indovina, Iole; La Scaleia, Barbara; Maffei, Vincenzo; Zago, Myrka

2014-01-01

Gravity is crucial for spatial perception, postural equilibrium, and movement generation. The vestibular apparatus is the main sensory system involved in monitoring gravity. Hair cells in the vestibular maculae respond to gravitoinertial forces, but they cannot distinguish between linear accelerations and changes of head orientation relative to gravity. The brain deals with this sensory ambiguity (which can cause some lethal airplane accidents) by combining several cues with the otolith signals: angular velocity signals provided by the semicircular canals, proprioceptive signals from muscles and tendons, visceral signals related to gravity, and visual signals. In particular, vision provides both static and dynamic signals about body orientation relative to the vertical, but it poorly discriminates arbitrary accelerations of moving objects. However, we are able to visually detect the specific acceleration of gravity since early infancy. This ability depends on the fact that gravity effects are stored in brain regions which integrate visual, vestibular, and neck proprioceptive signals and combine this information with an internal model of gravity effects.

A Large-Scale Design Integration Approach Developed in Conjunction with the Ares Launch Vehicle Program

NASA Technical Reports Server (NTRS)

Redmon, John W.; Shirley, Michael C.; Kinard, Paul S.

2012-01-01

This paper presents a method for performing large-scale design integration, taking a classical 2D drawing envelope and interface approach and applying it to modern three dimensional computer aided design (3D CAD) systems. Today, the paradigm often used when performing design integration with 3D models involves a digital mockup of an overall vehicle, in the form of a massive, fully detailed, CAD assembly; therefore, adding unnecessary burden and overhead to design and product data management processes. While fully detailed data may yield a broad depth of design detail, pertinent integration features are often obscured under the excessive amounts of information, making them difficult to discern. In contrast, the envelope and interface method results in a reduction in both the amount and complexity of information necessary for design integration while yielding significant savings in time and effort when applied to today's complex design integration projects. This approach, combining classical and modern methods, proved advantageous during the complex design integration activities of the Ares I vehicle. Downstream processes, benefiting from this approach by reducing development and design cycle time, include: Creation of analysis models for the Aerodynamic discipline; Vehicle to ground interface development; Documentation development for the vehicle assembly.

Enhanced Sensitivity to Rapid Input Fluctuations by Nonlinear Threshold Dynamics in Neocortical Pyramidal Neurons.

PubMed

Mensi, Skander; Hagens, Olivier; Gerstner, Wulfram; Pozzorini, Christian

2016-02-01

The way in which single neurons transform input into output spike trains has fundamental consequences for network coding. Theories and modeling studies based on standard Integrate-and-Fire models implicitly assume that, in response to increasingly strong inputs, neurons modify their coding strategy by progressively reducing their selective sensitivity to rapid input fluctuations. Combining mathematical modeling with in vitro experiments, we demonstrate that, in L5 pyramidal neurons, the firing threshold dynamics adaptively adjust the effective timescale of somatic integration in order to preserve sensitivity to rapid signals over a broad range of input statistics. For that, a new Generalized Integrate-and-Fire model featuring nonlinear firing threshold dynamics and conductance-based adaptation is introduced that outperforms state-of-the-art neuron models in predicting the spiking activity of neurons responding to a variety of in vivo-like fluctuating currents. Our model allows for efficient parameter extraction and can be analytically mapped to a Generalized Linear Model in which both the input filter--describing somatic integration--and the spike-history filter--accounting for spike-frequency adaptation--dynamically adapt to the input statistics, as experimentally observed. Overall, our results provide new insights on the computational role of different biophysical processes known to underlie adaptive coding in single neurons and support previous theoretical findings indicating that the nonlinear dynamics of the firing threshold due to Na+-channel inactivation regulate the sensitivity to rapid input fluctuations.

A model of the temporal dynamics of multisensory enhancement

PubMed Central

Rowland, Benjamin A.; Stein, Barry E.

2014-01-01

The senses transduce different forms of environmental energy, and the brain synthesizes information across them to enhance responses to salient biological events. We hypothesize that the potency of multisensory integration is attributable to the convergence of independent and temporally aligned signals derived from cross-modal stimulus configurations onto multisensory neurons. The temporal profile of multisensory integration in neurons of the deep superior colliculus (SC) is consistent with this hypothesis. The responses of these neurons to visual, auditory, and combinations of visual–auditory stimuli reveal that multisensory integration takes place in real-time; that is, the input signals are integrated as soon as they arrive at the target neuron. Interactions between cross-modal signals may appear to reflect linear or nonlinear computations on a moment-by-moment basis, the aggregate of which determines the net product of multisensory integration. Modeling observations presented here suggest that the early nonlinear components of the temporal profile of multisensory integration can be explained with a simple spiking neuron model, and do not require more sophisticated assumptions about the underlying biology. A transition from nonlinear “super-additive” computation to linear, additive computation can be accomplished via scaled inhibition. The findings provide a set of design constraints for artificial implementations seeking to exploit the basic principles and potency of biological multisensory integration in contexts of sensory substitution or augmentation. PMID:24374382

An integrated network of Arabidopsis growth regulators and its use for gene prioritization.

PubMed

Sabaghian, Ehsan; Drebert, Zuzanna; Inzé, Dirk; Saeys, Yvan

2015-12-01

Elucidating the molecular mechanisms that govern plant growth has been an important topic in plant research, and current advances in large-scale data generation call for computational tools that efficiently combine these different data sources to generate novel hypotheses. In this work, we present a novel, integrated network that combines multiple large-scale data sources to characterize growth regulatory genes in Arabidopsis, one of the main plant model organisms. The contributions of this work are twofold: first, we characterized a set of carefully selected growth regulators with respect to their connectivity patterns in the integrated network, and, subsequently, we explored to which extent these connectivity patterns can be used to suggest new growth regulators. Using a large-scale comparative study, we designed new supervised machine learning methods to prioritize growth regulators. Our results show that these methods significantly improve current state-of-the-art prioritization techniques, and are able to suggest meaningful new growth regulators. In addition, the integrated network is made available to the scientific community, providing a rich data source that will be useful for many biological processes, not necessarily restricted to plant growth.

Model-Based Localization and Tracking Using Bluetooth Low-Energy Beacons

PubMed Central

Cemgil, Ali Taylan

2017-01-01

We introduce a high precision localization and tracking method that makes use of cheap Bluetooth low-energy (BLE) beacons only. We track the position of a moving sensor by integrating highly unreliable and noisy BLE observations streaming from multiple locations. A novel aspect of our approach is the development of an observation model, specifically tailored for received signal strength indicator (RSSI) fingerprints: a combination based on the optimal transport model of Wasserstein distance. The tracking results of the entire system are compared with alternative baseline estimation methods, such as nearest neighboring fingerprints and an artificial neural network. Our results show that highly accurate estimation from noisy Bluetooth data is practically feasible with an observation model based on Wasserstein distance interpolation combined with the sequential Monte Carlo (SMC) method for tracking. PMID:29109375

Model-Based Localization and Tracking Using Bluetooth Low-Energy Beacons.

PubMed

Daniş, F Serhan; Cemgil, Ali Taylan

2017-10-29

We introduce a high precision localization and tracking method that makes use of cheap Bluetooth low-energy (BLE) beacons only. We track the position of a moving sensor by integrating highly unreliable and noisy BLE observations streaming from multiple locations. A novel aspect of our approach is the development of an observation model, specifically tailored for received signal strength indicator (RSSI) fingerprints: a combination based on the optimal transport model of Wasserstein distance. The tracking results of the entire system are compared with alternative baseline estimation methods, such as nearest neighboring fingerprints and an artificial neural network. Our results show that highly accurate estimation from noisy Bluetooth data is practically feasible with an observation model based on Wasserstein distance interpolation combined with the sequential Monte Carlo (SMC) method for tracking.

Lie integrable cases of the simplified multistrain/two-stream model for tuberculosis and dengue fever

NASA Astrophysics Data System (ADS)

Nucci, M. C.; Leach, P. G. L.

2007-09-01

We apply the techniques of Lie's symmetry analysis to a caricature of the simplified multistrain model of Castillo-Chavez and Feng [C. Castillo-Chavez, Z. Feng, To treat or not to treat: The case of tuberculosis, J. Math. Biol. 35 (1997) 629-656] for the transmission of tuberculosis and the coupled two-stream vector-based model of Feng and Velasco-Hernandez [Z. Feng, J.X. Velasco-Hernandez, Competitive exclusion in a vector-host model for the dengue fever, J. Math. Biol. 35 (1997) 523-544] to identify the combinations of parameters which lead to the existence of nontrivial symmetries. In particular we identify those combinations which lead to the possibility of the linearization of the system and provide the corresponding solutions. Many instances of additional symmetry are analyzed.

Integration of Point Clouds Dataset from Different Sensors

NASA Astrophysics Data System (ADS)

Abdullah, C. K. A. F. Che Ku; Baharuddin, N. Z. S.; Ariff, M. F. M.; Majid, Z.; Lau, C. L.; Yusoff, A. R.; Idris, K. M.; Aspuri, A.

2017-02-01

Laser Scanner technology become an option in the process of collecting data nowadays. It is composed of Airborne Laser Scanner (ALS) and Terrestrial Laser Scanner (TLS). ALS like Phoenix AL3-32 can provide accurate information from the viewpoint of rooftop while TLS as Leica C10 can provide complete data for building facade. However if both are integrated, it is able to produce more accurate data. The focus of this study is to integrate both types of data acquisition of ALS and TLS and determine the accuracy of the data obtained. The final results acquired will be used to generate models of three-dimensional (3D) buildings. The scope of this study is focusing on data acquisition of UTM Eco-home through laser scanning methods such as ALS which scanning on the roof and the TLS which scanning on building façade. Both device is used to ensure that no part of the building that are not scanned. In data integration process, both are registered by the selected points among the manmade features which are clearly visible in Cyclone 7.3 software. The accuracy of integrated data is determined based on the accuracy assessment which is carried out using man-made registration methods. The result of integration process can achieve below 0.04m. This integrated data then are used to generate a 3D model of UTM Eco-home building using SketchUp software. In conclusion, the combination of the data acquisition integration between ALS and TLS would produce the accurate integrated data and able to use for generate a 3D model of UTM eco-home. For visualization purposes, the 3D building model which generated is prepared in Level of Detail 3 (LOD3) which recommended by City Geographic Mark-Up Language (CityGML).

The psychological factor 'self-blame' predicts overuse injury among top-level Swedish track and field athletes: a 12-month cohort study.

PubMed

Timpka, Toomas; Jacobsson, Jenny; Dahlström, Örjan; Kowalski, Jan; Bargoria, Victor; Ekberg, Joakim; Nilsson, Sverker; Renström, Per

2015-11-01

Athletes' psychological characteristics are important for understanding sports injury mechanisms. We examined the relevance of psychological factors in an integrated model of overuse injury risk in athletics/track and field. Swedish track and field athletes (n=278) entering a 12-month injury surveillance in March 2009 were also invited to complete a psychological survey. Simple Cox proportional hazards models were compiled for single explanatory variables. We also tested multiple models for 3 explanatory variable groupings: an epidemiological model without psychological variables, a psychological model excluding epidemiological variables and an integrated (combined) model. The integrated multiple model included the maladaptive coping behaviour self-blame (p=0.007; HR 1.32; 95% CI 1.08 to 1.61), and an interaction between athlete category and injury history (p<0.001). Youth female (p=0.034; HR 0.51; 95% CI 0.27 to 0.95) and youth male (p=0.047; HR 0.49; 95% CI 0.24 to 0.99) athletes with no severe injury the previous year were at half the risk of sustaining a new injury compared with the reference group. A training load index entered the epidemiological multiple model, but not the integrated model. The coping behaviour self-blame replaced training load in an integrated explanatory model of overuse injury risk in athletes. What seemed to be more strongly related to the likelihood of overuse injury was not the athletics load per se, but, rather, the load applied in situations when the athlete's body was in need of rest. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Performance and Reliability Optimization for Aerospace Systems subject to Uncertainty and Degradation

NASA Technical Reports Server (NTRS)

Miller, David W.; Uebelhart, Scott A.; Blaurock, Carl

2004-01-01

This report summarizes work performed by the Space Systems Laboratory (SSL) for NASA Langley Research Center in the field of performance optimization for systems subject to uncertainty. The objective of the research is to develop design methods and tools to the aerospace vehicle design process which take into account lifecycle uncertainties. It recognizes that uncertainty between the predictions of integrated models and data collected from the system in its operational environment is unavoidable. Given the presence of uncertainty, the goal of this work is to develop means of identifying critical sources of uncertainty, and to combine these with the analytical tools used with integrated modeling. In this manner, system uncertainty analysis becomes part of the design process, and can motivate redesign. The specific program objectives were: 1. To incorporate uncertainty modeling, propagation and analysis into the integrated (controls, structures, payloads, disturbances, etc.) design process to derive the error bars associated with performance predictions. 2. To apply modern optimization tools to guide in the expenditure of funds in a way that most cost-effectively improves the lifecycle productivity of the system by enhancing the subsystem reliability and redundancy. The results from the second program objective are described. This report describes the work and results for the first objective: uncertainty modeling, propagation, and synthesis with integrated modeling.

Synthesizing models useful for ecohydrology and ecohydraulic approaches: An emphasis on integrating models to address complex research questions

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

Brewer, Shannon K.; Worthington, Thomas A.; Mollenhauer, Robert

Ecohydrology combines empiricism, data analytics, and the integration of models to characterize linkages between ecological and hydrological processes. A challenge for practitioners is determining which models best generalizes heterogeneity in hydrological behaviour, including water fluxes across spatial and temporal scales, integrating environmental and socio–economic activities to determine best watershed management practices and data requirements. We conducted a literature review and synthesis of hydrologic, hydraulic, water quality, and ecological models designed for solving interdisciplinary questions. We reviewed 1,275 papers and identified 178 models that have the capacity to answer an array of research questions about ecohydrology or ecohydraulics. Of these models,more » 43 were commonly applied due to their versatility, accessibility, user–friendliness, and excellent user–support. Forty–one of 43 reviewed models were linked to at least 1 other model especially: Water Quality Analysis Simulation Program (linked to 21 other models), Soil and Water Assessment Tool (19), and Hydrologic Engineering Center's River Analysis System (15). However, model integration was still relatively infrequent. There was substantial variation in model applications, possibly an artefact of the regional focus of research questions, simplicity of use, quality of user–support efforts, or a limited understanding of model applicability. Simply increasing the interoperability of model platforms, transformation of models to user–friendly forms, increasing user–support, defining the reliability and risk associated with model results, and increasing awareness of model applicability may promote increased use of models across subdisciplines. Furthermore, the current availability of models allows an array of interdisciplinary questions to be addressed, and model choice relates to several factors including research objective, model complexity, ability to link to other models, and interface choice.« less

Synthesizing models useful for ecohydrology and ecohydraulic approaches: An emphasis on integrating models to address complex research questions

USGS Publications Warehouse

Brewer, Shannon K.; Worthington, Thomas; Mollenhauer, Robert; Stewart, David; McManamay, Ryan; Guertault, Lucie; Moore, Desiree

2018-01-01

Ecohydrology combines empiricism, data analytics, and the integration of models to characterize linkages between ecological and hydrological processes. A challenge for practitioners is determining which models best generalizes heterogeneity in hydrological behaviour, including water fluxes across spatial and temporal scales, integrating environmental and socio‐economic activities to determine best watershed management practices and data requirements. We conducted a literature review and synthesis of hydrologic, hydraulic, water quality, and ecological models designed for solving interdisciplinary questions. We reviewed 1,275 papers and identified 178 models that have the capacity to answer an array of research questions about ecohydrology or ecohydraulics. Of these models, 43 were commonly applied due to their versatility, accessibility, user‐friendliness, and excellent user‐support. Forty‐one of 43 reviewed models were linked to at least 1 other model especially: Water Quality Analysis Simulation Program (linked to 21 other models), Soil and Water Assessment Tool (19), and Hydrologic Engineering Center's River Analysis System (15). However, model integration was still relatively infrequent. There was substantial variation in model applications, possibly an artefact of the regional focus of research questions, simplicity of use, quality of user‐support efforts, or a limited understanding of model applicability. Simply increasing the interoperability of model platforms, transformation of models to user‐friendly forms, increasing user‐support, defining the reliability and risk associated with model results, and increasing awareness of model applicability may promote increased use of models across subdisciplines. Nonetheless, the current availability of models allows an array of interdisciplinary questions to be addressed, and model choice relates to several factors including research objective, model complexity, ability to link to other models, and interface choice.

Synthesizing models useful for ecohydrology and ecohydraulic approaches: An emphasis on integrating models to address complex research questions

DOE PAGES

Brewer, Shannon K.; Worthington, Thomas A.; Mollenhauer, Robert; ...

2018-04-06

Ecohydrology combines empiricism, data analytics, and the integration of models to characterize linkages between ecological and hydrological processes. A challenge for practitioners is determining which models best generalizes heterogeneity in hydrological behaviour, including water fluxes across spatial and temporal scales, integrating environmental and socio–economic activities to determine best watershed management practices and data requirements. We conducted a literature review and synthesis of hydrologic, hydraulic, water quality, and ecological models designed for solving interdisciplinary questions. We reviewed 1,275 papers and identified 178 models that have the capacity to answer an array of research questions about ecohydrology or ecohydraulics. Of these models,more » 43 were commonly applied due to their versatility, accessibility, user–friendliness, and excellent user–support. Forty–one of 43 reviewed models were linked to at least 1 other model especially: Water Quality Analysis Simulation Program (linked to 21 other models), Soil and Water Assessment Tool (19), and Hydrologic Engineering Center's River Analysis System (15). However, model integration was still relatively infrequent. There was substantial variation in model applications, possibly an artefact of the regional focus of research questions, simplicity of use, quality of user–support efforts, or a limited understanding of model applicability. Simply increasing the interoperability of model platforms, transformation of models to user–friendly forms, increasing user–support, defining the reliability and risk associated with model results, and increasing awareness of model applicability may promote increased use of models across subdisciplines. Furthermore, the current availability of models allows an array of interdisciplinary questions to be addressed, and model choice relates to several factors including research objective, model complexity, ability to link to other models, and interface choice.« less

Creating a FIESTA (Framework for Integrated Earth Science and Technology Applications) with MagIC

NASA Astrophysics Data System (ADS)

Minnett, R.; Koppers, A. A. P.; Jarboe, N.; Tauxe, L.; Constable, C.

2017-12-01

The Magnetics Information Consortium (https://earthref.org/MagIC) has recently developed a containerized web application to considerably reduce the friction in contributing, exploring and combining valuable and complex datasets for the paleo-, geo- and rock magnetic scientific community. The data produced in this scientific domain are inherently hierarchical and the communities evolving approaches to this scientific workflow, from sampling to taking measurements to multiple levels of interpretations, require a large and flexible data model to adequately annotate the results and ensure reproducibility. Historically, contributing such detail in a consistent format has been prohibitively time consuming and often resulted in only publishing the highly derived interpretations. The new open-source (https://github.com/earthref/MagIC) application provides a flexible upload tool integrated with the data model to easily create a validated contribution and a powerful search interface for discovering datasets and combining them to enable transformative science. MagIC is hosted at EarthRef.org along with several interdisciplinary geoscience databases. A FIESTA (Framework for Integrated Earth Science and Technology Applications) is being created by generalizing MagIC's web application for reuse in other domains. The application relies on a single configuration document that describes the routing, data model, component settings and external services integrations. The container hosts an isomorphic Meteor JavaScript application, MongoDB database and ElasticSearch search engine. Multiple containers can be configured as microservices to serve portions of the application or rely on externally hosted MongoDB, ElasticSearch, or third-party services to efficiently scale computational demands. FIESTA is particularly well suited for many Earth Science disciplines with its flexible data model, mapping, account management, upload tool to private workspaces, reference metadata, image galleries, full text searches and detailed filters. EarthRef's Seamount Catalog of bathymetry and morphology data, EarthRef's Geochemical Earth Reference Model (GERM) databases, and Oregon State University's Marine and Geology Repository (http://osu-mgr.org) will benefit from custom adaptations of FIESTA.

Challenges in treatment of posttraumatic stress disorder in refugees: towards integration of evidence-based treatments with contextual and culture-sensitive perspectives

PubMed Central

Drožđek, Boris

2015-01-01

Background Research shows that trauma-focused therapy and multimodal interventions are the two most often used strategies in treatment of refugees suffering from posttraumatic stress disorder (PTSD). While preliminary evidence suggests that trauma-focused approaches may have some efficacy, this could not be established for multimodal interventions. However, it may be that multimodal interventions have been studied in more treatment-resistant refugees with very high levels of psychopathology, disability, and chronicity. In the past decades, various models for understanding of the complex relationship between mental health problems and well-being have emerged. They aim at framing mental health problems in individualized, contextual, epigenetic, and culturally sensitive ways, and may be useful in tailoring content and timing of multimodal interventions. Objective To draw clinicians’ attention to the possibility of using the Integrative Contextual Model for understanding and assessment of posttrauma mental health sequelae while tailoring multimodal interventions; to present a possible way of combining multimodal with evidence-based trauma-focused approaches; and to improve the understanding and treatment of PTSD and other mental health problems in refugee survivors of prolonged and repeated trauma. Method Based on literature, clinical experience, and presentation of a fictional case, the use of the Integrative Contextual Model in tailoring the treatment of severe PTSD in a refugee patient is presented and discussed. Results The Integrative Contextual Model for understanding and assessing factors, which may play a role in causing and maintaining of PTSD and comorbidity in refugees, may help tailoring of multimodal interventions. These interventions can be combined with evidence-based trauma-focused treatments. Conclusion The field of refugee mental health intervention and clinical practice with traumatized refugees may be enriched with the use of contextual and developmental models for assessment and conceptualization of posttrauma sequelae. Multimodal and trauma-focused interventions may be applied sequentially in a course of the treatment trajectory. PMID:25573504

The Efficacy and Potential of Renewable Energy from Carbon Dioxide that is Sequestered in Sedimentary Basin Geothermal Resources

NASA Astrophysics Data System (ADS)

Bielicki, J. M.; Adams, B. M.; Choi, H.; Saar, M. O.; Taff, S. J.; Jamiyansuren, B.; Buscheck, T. A.; Ogland-Hand, J.

2015-12-01

Mitigating climate change requires increasing the amount of electricity that is generated from renewable energy technologies and while simultaneously reducing the amount of carbon dioxide (CO2) that is emitted to the atmosphere from present energy and industrial facilities. We investigated the efficacy of generating electricity using renewable geothermal heat that is extracted by CO2 that is sequestered in sedimentary basins. To determine the efficacy of CO2-Geothermal power production in the United States, we conducted a geospatial resource assessment of the combination of subsurface CO2 storage capacity and heat flow in sedimentary basins and developed an integrated systems model that combines reservoir modeling with power plant modeling and economic costs. The geospatial resource assessment estimates the potential resource base for CO2-Geothermal power plants, and the integrated systems model estimates the physical (e.g., net power) and economic (e.g., levelized cost of electricity, capital cost) performance of an individual CO2-Geothermal power plant for a range of reservoir characteristics (permeability, depth, geothermal temperature gradient). Using coupled inverted five-spot injection patterns that are common in CO2-enhanced oil recovery operations, we determined the well pattern size that best leveraged physical and economic economies of scale for the integrated system. Our results indicate that CO2-Geothermal plants can be cost-effectively deployed in a much larger region of the United States than typical approaches to geothermal electricity production. These cost-effective CO2-Geothermal electricity facilities can also be capacity-competitive with many existing baseload and renewable energy technologies over a range of reservoir parameters. For example, our results suggest that, given the right combination of reservoir parameters, LCOEs can be as low as $25/MWh and capacities can be as high as a few hundred MW.

A SINS/SRS/GNS Autonomous Integrated Navigation System Based on Spectral Redshift Velocity Measurements.

PubMed

Wei, Wenhui; Gao, Zhaohui; Gao, Shesheng; Jia, Ke

2018-04-09

In order to meet the requirements of autonomy and reliability for the navigation system, combined with the method of measuring speed by using the spectral redshift information of the natural celestial bodies, a new scheme, consisting of Strapdown Inertial Navigation System (SINS)/Spectral Redshift (SRS)/Geomagnetic Navigation System (GNS), is designed for autonomous integrated navigation systems. The principle of this SINS/SRS/GNS autonomous integrated navigation system is explored, and the corresponding mathematical model is established. Furthermore, a robust adaptive central difference particle filtering algorithm is proposed for this autonomous integrated navigation system. The simulation experiments are conducted and the results show that the designed SINS/SRS/GNS autonomous integrated navigation system possesses good autonomy, strong robustness and high reliability, thus providing a new solution for autonomous navigation technology.

78 FR 52764 - Extension of Public Comment Period Hydrogen Energy California's Integrated Gasification Combined...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-26

... DEPARTMENT OF ENERGY Extension of Public Comment Period Hydrogen Energy California's Integrated Gasification Combined Cycle Project Preliminary Staff Assessment and Draft Environmental Impact Statement... California's Integrated Gasification Combined Cycle Project Preliminary Staff Assessment/Draft Environmental...

A model of collaborative agency and common ground.

PubMed

Kuziemsky, Craig E; Cornett, Janet Alexandra

2013-01-01

As more healthcare delivery is provided via collaborative means there is a need to understand how to design information and communication technologies (ICTs) to support collaboration. Existing research has largely focused on individual aspects of ICT usage and not how they can support the coordination of collaborative activities. In order to understand how we can design ICTs to support collaboration we need to understand how agents, technologies, information and processes integrate while providing collaborative care delivery. Co-agency and common ground have both provided insight about the integration of different entities as part of collaboration practices. However there is still a lack of understanding about how to coordinate the integration of agents, processes and technologies to support collaboration. This paper combines co-agency and common ground to develop a model of collaborative agency and specific categories of common ground to facilitate its coordination.

Study of surface integrity AISI 4140 as result of hard, dry and high speed machining using CBN

NASA Astrophysics Data System (ADS)

Ginting, B.; Sembiring, R. W.; Manurung, N.

2017-09-01

The concept of hard, dry and high speed machining can be combined, to produce high productivity, with lower production costs in manufacturing industry. Hard lathe process can be a solution to reduce production time. In lathe hard alloy steels reported problems relating to the integrity of such surface roughness, residual stress, the white layer and the surface integrity. AISI 4140 material is used for high reliable hydraulic system components. This material includes in cold work tool steel. Consideration election is because this material is able to be hardened up to 55 HRC. In this research, the experimental design using CCD model fit with three factors, each factor is composed of two levels, and six central point, experiments were conducted with 1 replications. The experimental design research using CCD model fit.

Renewable Hydrogen-Economically Viable: Integration into the U.S. Transportation Sector

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

Kurtz, Jennifer; Peters, Mike; Muratori, Matteo

The U.S. transportation sector is expected to meet numerous goals in differing applications. These goals address security, safety, fuel source, emissions reductions, advanced mobility models, and improvements in quality and accessibility. Solutions to meeting these goals include a variety of alternative-fuel technologies, including batteries, fuel cells, synthetic fuels, and biofuels, as well as modifying how current transportation systems are used and integrating new systems, such as storing renewable energy. Overall, there are many combinations of problems, objectives, and solutions.

Parameter Sweep and Optimization of Loosely Coupled Simulations Using the DAKOTA Toolkit

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

Elwasif, Wael R; Bernholdt, David E; Pannala, Sreekanth

2012-01-01

The increasing availability of large scale computing capabilities has accelerated the development of high-fidelity coupled simulations. Such simulations typically involve the integration of models that implement various aspects of the complex phenomena under investigation. Coupled simulations are playing an integral role in fields such as climate modeling, earth systems modeling, rocket simulations, computational chemistry, fusion research, and many other computational fields. Model coupling provides scientists with systematic ways to virtually explore the physical, mathematical, and computational aspects of the problem. Such exploration is rarely done using a single execution of a simulation, but rather by aggregating the results from manymore » simulation runs that, together, serve to bring to light novel knowledge about the system under investigation. Furthermore, it is often the case (particularly in engineering disciplines) that the study of the underlying system takes the form of an optimization regime, where the control parameter space is explored to optimize an objective functions that captures system realizability, cost, performance, or a combination thereof. Novel and flexible frameworks that facilitate the integration of the disparate models into a holistic simulation are used to perform this research, while making efficient use of the available computational resources. In this paper, we describe the integration of the DAKOTA optimization and parameter sweep toolkit with the Integrated Plasma Simulator (IPS), a component-based framework for loosely coupled simulations. The integration allows DAKOTA to exploit the internal task and resource management of the IPS to dynamically instantiate simulation instances within a single IPS instance, allowing for greater control over the trade-off between efficiency of resource utilization and time to completion. We present a case study showing the use of the combined DAKOTA-IPS system to aid in the design of a lithium ion battery (LIB) cell, by studying a coupled system involving the electrochemistry and ion transport at the lower length scales and thermal energy transport at the device scales. The DAKOTA-IPS system provides a flexible tool for use in optimization and parameter sweep studies involving loosely coupled simulations that is suitable for use in situations where changes to the constituent components in the coupled simulation are impractical due to intellectual property or code heritage issues.« less

GOBF-ARMA based model predictive control for an ideal reactive distillation column.

PubMed

Seban, Lalu; Kirubakaran, V; Roy, B K; Radhakrishnan, T K

2015-11-01

This paper discusses the control of an ideal reactive distillation column (RDC) using model predictive control (MPC) based on a combination of deterministic generalized orthonormal basis filter (GOBF) and stochastic autoregressive moving average (ARMA) models. Reactive distillation (RD) integrates reaction and distillation in a single process resulting in process and energy integration promoting green chemistry principles. Improved selectivity of products, increased conversion, better utilization and control of reaction heat, scope for difficult separations and the avoidance of azeotropes are some of the advantages that reactive distillation offers over conventional technique of distillation column after reactor. The introduction of an in situ separation in the reaction zone leads to complex interactions between vapor-liquid equilibrium, mass transfer rates, diffusion and chemical kinetics. RD with its high order and nonlinear dynamics, and multiple steady states is a good candidate for testing and verification of new control schemes. Here a combination of GOBF-ARMA models is used to catch and represent the dynamics of the RDC. This GOBF-ARMA model is then used to design an MPC scheme for the control of product purity of RDC under different operating constraints and conditions. The performance of proposed modeling and control using GOBF-ARMA based MPC is simulated and analyzed. The proposed controller is found to perform satisfactorily for reference tracking and disturbance rejection in RDC. Copyright © 2015 Elsevier Inc. All rights reserved.

Are Three Sheets Enough? Using Toilet Paper to Teach Science and Mathematics

ERIC Educational Resources Information Center

Woolverton, Christopher J.; Woolverton, Lyssa N.

2006-01-01

Toilet paper (TP) composition and physical characteristics were used to model scientific investigations that combined several "National Science Education Standards." Experiments with TP permitted the integration of TP history, societal change resulting from invention, mathematics (including geometry and statistics), germ theory, and personal…

Oil City PREP: Putting Positive Principles into Practice

ERIC Educational Resources Information Center

Eisenman, Jessica; Barnhill, Rachelle; Riley, Ben

2013-01-01

Tamara Shepard from Southwest Behavioral Health Management (SBHM) proposed a plan to schools in Venango County, Pennsylvania. School districts would collaborate with mental health agencies to create a school-based integrated classroom model that would combine education and behavioral health interventions in one setting. When she initially…

Adding a Systemic Touch to Rational-Emotive Therapy for Families.

ERIC Educational Resources Information Center

Russell, Todd T.; Morrill, Correen M.

1989-01-01

Proposes a theoretical and practical hybrid model for family counseling based on integrating the rational-emotive and family systems approach. Notes that these combined approaches offer the counselor a systematic theoretical structure for conceptualizing family dysfunction, from which additional strategies for changing inappropriate belief systems…

A Neurocomputational Model of Goal-Directed Navigation in Insect-Inspired Artificial Agents

PubMed Central

Goldschmidt, Dennis; Manoonpong, Poramate; Dasgupta, Sakyasingha

2017-01-01

Despite their small size, insect brains are able to produce robust and efficient navigation in complex environments. Specifically in social insects, such as ants and bees, these navigational capabilities are guided by orientation directing vectors generated by a process called path integration. During this process, they integrate compass and odometric cues to estimate their current location as a vector, called the home vector for guiding them back home on a straight path. They further acquire and retrieve path integration-based vector memories globally to the nest or based on visual landmarks. Although existing computational models reproduced similar behaviors, a neurocomputational model of vector navigation including the acquisition of vector representations has not been described before. Here we present a model of neural mechanisms in a modular closed-loop control—enabling vector navigation in artificial agents. The model consists of a path integration mechanism, reward-modulated global learning, random search, and action selection. The path integration mechanism integrates compass and odometric cues to compute a vectorial representation of the agent's current location as neural activity patterns in circular arrays. A reward-modulated learning rule enables the acquisition of vector memories by associating the local food reward with the path integration state. A motor output is computed based on the combination of vector memories and random exploration. In simulation, we show that the neural mechanisms enable robust homing and localization, even in the presence of external sensory noise. The proposed learning rules lead to goal-directed navigation and route formation performed under realistic conditions. Consequently, we provide a novel approach for vector learning and navigation in a simulated, situated agent linking behavioral observations to their possible underlying neural substrates. PMID:28446872

A Neurocomputational Model of Goal-Directed Navigation in Insect-Inspired Artificial Agents.

PubMed

Goldschmidt, Dennis; Manoonpong, Poramate; Dasgupta, Sakyasingha

2017-01-01

Despite their small size, insect brains are able to produce robust and efficient navigation in complex environments. Specifically in social insects, such as ants and bees, these navigational capabilities are guided by orientation directing vectors generated by a process called path integration. During this process, they integrate compass and odometric cues to estimate their current location as a vector, called the home vector for guiding them back home on a straight path. They further acquire and retrieve path integration-based vector memories globally to the nest or based on visual landmarks. Although existing computational models reproduced similar behaviors, a neurocomputational model of vector navigation including the acquisition of vector representations has not been described before. Here we present a model of neural mechanisms in a modular closed-loop control-enabling vector navigation in artificial agents. The model consists of a path integration mechanism, reward-modulated global learning, random search, and action selection. The path integration mechanism integrates compass and odometric cues to compute a vectorial representation of the agent's current location as neural activity patterns in circular arrays. A reward-modulated learning rule enables the acquisition of vector memories by associating the local food reward with the path integration state. A motor output is computed based on the combination of vector memories and random exploration. In simulation, we show that the neural mechanisms enable robust homing and localization, even in the presence of external sensory noise. The proposed learning rules lead to goal-directed navigation and route formation performed under realistic conditions. Consequently, we provide a novel approach for vector learning and navigation in a simulated, situated agent linking behavioral observations to their possible underlying neural substrates.

The application of a Web-geographic information system for improving urban water cycle modelling.

PubMed

Mair, M; Mikovits, C; Sengthaler, M; Schöpf, M; Kinzel, H; Urich, C; Kleidorfer, M; Sitzenfrei, R; Rauch, W

2014-01-01

Research in urban water management has experienced a transition from traditional model applications to modelling water cycles as an integrated part of urban areas. This includes the interlinking of models of many research areas (e.g. urban development, socio-economy, urban water management). The integration and simulation is realized in newly developed frameworks (e.g. DynaMind and OpenMI) and often assumes a high knowledge in programming. This work presents a Web based urban water management modelling platform which simplifies the setup and usage of complex integrated models. The platform is demonstrated with a small application example on a case study within the Alpine region. The used model is a DynaMind model benchmarking the impact of newly connected catchments on the flooding behaviour of an existing combined sewer system. As a result the workflow of the user within a Web browser is demonstrated and benchmark results are shown. The presented platform hides implementation specific aspects behind Web services based technologies such that the user can focus on his main aim, which is urban water management modelling and benchmarking. Moreover, this platform offers a centralized data management, automatic software updates and access to high performance computers accessible with desktop computers and mobile devices.

Static and dynamic behaviour of nonlocal elastic bar using integral strain-based and peridynamic models

NASA Astrophysics Data System (ADS)

Challamel, Noël

2018-04-01

The static and dynamic behaviour of a nonlocal bar of finite length is studied in this paper. The nonlocal integral models considered in this paper are strain-based and relative displacement-based nonlocal models; the latter one is also labelled as a peridynamic model. For infinite media, and for sufficiently smooth displacement fields, both integral nonlocal models can be equivalent, assuming some kernel correspondence rules. For infinite media (or finite media with extended reflection rules), it is also shown that Eringen's differential model can be reformulated into a consistent strain-based integral nonlocal model with exponential kernel, or into a relative displacement-based integral nonlocal model with a modified exponential kernel. A finite bar in uniform tension is considered as a paradigmatic static case. The strain-based nonlocal behaviour of this bar in tension is analyzed for different kernels available in the literature. It is shown that the kernel has to fulfil some normalization and end compatibility conditions in order to preserve the uniform strain field associated with this homogeneous stress state. Such a kernel can be built by combining a local and a nonlocal strain measure with compatible boundary conditions, or by extending the domain outside its finite size while preserving some kinematic compatibility conditions. The same results are shown for the nonlocal peridynamic bar where a homogeneous strain field is also analytically obtained in the elastic bar for consistent compatible kinematic boundary conditions at the vicinity of the end conditions. The results are extended to the vibration of a fixed-fixed finite bar where the natural frequencies are calculated for both the strain-based and the peridynamic models.

78 FR 54640 - Extension of Public Comment Period Hydrogen Energy California's Integrated Gasification Combined...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-05

... DEPARTMENT OF ENERGY Extension of Public Comment Period Hydrogen Energy California's Integrated Gasification Combined Cycle Project Preliminary Staff Assessment and Draft Environmental Impact Statement... Integrated Gasification Combined Cycle Project Preliminary Staff Assessment and Draft Environmental Impact...

Methodology and application of combined watershed and ground-water models in Kansas

USGS Publications Warehouse

Sophocleous, M.; Perkins, S.P.

2000-01-01

Increased irrigation in Kansas and other regions during the last several decades has caused serious water depletion, making the development of comprehensive strategies and tools to resolve such problems increasingly important. This paper makes the case for an intermediate complexity, quasi-distributed, comprehensive, large-watershed model, which falls between the fully distributed, physically based hydrological modeling system of the type of the SHE model and the lumped, conceptual rainfall-runoff modeling system of the type of the Stanford watershed model. This is achieved by integrating the quasi-distributed watershed model SWAT with the fully-distributed ground-water model MODFLOW. The advantage of this approach is the appreciably smaller input data requirements and the use of readily available data (compared to the fully distributed, physically based models), the statistical handling of watershed heterogeneities by employing the hydrologic-response-unit concept, and the significantly increased flexibility in handling stream-aquifer interactions, distributed well withdrawals, and multiple land uses. The mechanics of integrating the component watershed and ground-water models are outlined, and three real-world management applications of the integrated model from Kansas are briefly presented. Three different aspects of the integrated model are emphasized: (1) management applications of a Decision Support System for the integrated model (Rattlesnake Creek subbasin); (2) alternative conceptual models of spatial heterogeneity related to the presence or absence of an underlying aquifer with shallow or deep water table (Lower Republican River basin); and (3) the general nature of the integrated model linkage by employing a watershed simulator other than SWAT (Wet Walnut Creek basin). These applications demonstrate the practicality and versatility of this relatively simple and conceptually clear approach, making public acceptance of the integrated watershed modeling system much easier. This approach also enhances model calibration and thus the reliability of model results. (C) 2000 Elsevier Science B.V.Increased irrigation in Kansas and other regions during the last several decades has caused serious water depletion, making the development of comprehensive strategies and tools to resolve such problems increasingly important. This paper makes the case for an intermediate complexity, quasi-distributed, comprehensive, large-watershed model, which falls between the fully distributed, physically based hydrological modeling system of the type of the SHE model and the lumped, conceptual rainfall-runoff modeling system of the type of the Stanford watershed model. This is achieved by integrating the quasi-distributed watershed model SWAT with the fully-distributed ground-water model MODFLOW. The advantage of this approach is the appreciably smaller input data requirements and the use of readily available data (compared to the fully distributed, physically based models), the statistical handling of watershed heterogeneities by employing the hydrologic-response-unit concept, and the significantly increased flexibility in handling stream-aquifer interactions, distributed well withdrawals, and multiple land uses. The mechanics of integrating the component watershed and ground-water models are outlined, and three real-world management applications of the integrated model from Kansas are briefly presented. Three different aspects of the integrated model are emphasized: (1) management applications of a Decision Support System for the integrated model (Rattlesnake Creek subbasin); (2) alternative conceptual models of spatial heterogeneity related to the presence or absence of an underlying aquifer with shallow or deep water table (Lower Republican River basin); and (3) the general nature of the integrated model linkage by employing a watershed simulator other than SWAT (Wet Walnut Creek basin). These applications demonstrate the practicality and ve

Satellite Remote Sensing is Key to Water Cycle Integrator

NASA Astrophysics Data System (ADS)

Koike, T.

2016-12-01

To promote effective multi-sectoral, interdisciplinary collaboration based on coordinated and integrated efforts, the Global Earth Observation System of Systems (GEOSS) is now developing a "GEOSS Water Cycle Integrator (WCI)", which integrates "Earth observations", "modeling", "data and information", "management systems" and "education systems". GEOSS/WCI sets up "work benches" by which partners can share data, information and applications in an interoperable way, exchange knowledge and experiences, deepen mutual understanding and work together effectively to ultimately respond to issues of both mitigation and adaptation. (A work bench is a virtual geographical or phenomenological space where experts and managers collaborate to use information to address a problem within that space). GEOSS/WCI enhances the coordination of efforts to strengthen individual, institutional and infrastructure capacities, especially for effective interdisciplinary coordination and integration. GEOSS/WCI archives various satellite data to provide various hydrological information such as cloud, rainfall, soil moisture, or land-surface snow. These satellite products were validated using land observation in-situ data. Water cycle models can be developed by coupling in-situ and satellite data. River flows and other hydrological parameters can be simulated and validated by in-situ data. Model outputs from weather-prediction, seasonal-prediction, and climate-prediction models are archived. Some of these model outputs are archived on an online basis, but other models, e.g., climate-prediction models are archived on an offline basis. After models are evaluated and biases corrected, the outputs can be used as inputs into the hydrological models for predicting the hydrological parameters. Additionally, we have already developed a data-assimilation system by combining satellite data and the models. This system can improve our capability to predict hydrological phenomena. The WCI can provide better predictions of the hydrological parameters for integrated water resources management (IWRM) and also assess the impact of climate change and calculate adaptation needs.

A combined mean dynamic topography model - DTU17cMDT

NASA Astrophysics Data System (ADS)

Knudsen, P.; Andersen, O. B.; Nielsen, K.; Maximenko, N. A.

2017-12-01

Within the ESA supported Optimal Geoid for Modelling Ocean Circulation (OGMOC) project a new geoid model have been derived. It is based on the GOCO05C setup though the newer DTU15GRA altimetric surface gravity has been used in the combination. Subsequently the model has been augmented using the EIGEN-6C4 coefficients to d/o 2160. Compared to the DTU13MSS, the DTU15MSS has been derived by including re-tracked CRYOSAT-2 altimetry also, hence, increasing its resolution. Also, some issues in the Polar regions have been solved. The new DTU17MDT has been derived using this new geoid model and the DTU15MSS mean sea surface. Compared to other geoid models the new OGMOC geoid model has been optimized to avoid striations and orange skin like features. The filtering was re-evaluated by adjusting the quasi-gaussian filter width to optimize the fit to drifter velocities. The results show that the new MDT improves the resolution of the details of the ocean circulation. Subsequently, the drifter velocities were integrated to enhance the resolution of the MDT. As a contribution to the ESA supported GOCE++ project DYCOT a special concern was devoted to the coastal areas to optimize the extrapolation towards the coast and to integrate mean sea levels at tide gauges into that process. The presentation will focus on the coastal zone when assessing the methodology, the data and the final model DTU17cMDT.

Vibration and acoustic frequency spectra for industrial process modeling using selective fusion multi-condition samples and multi-source features

NASA Astrophysics Data System (ADS)

Tang, Jian; Qiao, Junfei; Wu, ZhiWei; Chai, Tianyou; Zhang, Jian; Yu, Wen

2018-01-01

Frequency spectral data of mechanical vibration and acoustic signals relate to difficult-to-measure production quality and quantity parameters of complex industrial processes. A selective ensemble (SEN) algorithm can be used to build a soft sensor model of these process parameters by fusing valued information selectively from different perspectives. However, a combination of several optimized ensemble sub-models with SEN cannot guarantee the best prediction model. In this study, we use several techniques to construct mechanical vibration and acoustic frequency spectra of a data-driven industrial process parameter model based on selective fusion multi-condition samples and multi-source features. Multi-layer SEN (MLSEN) strategy is used to simulate the domain expert cognitive process. Genetic algorithm and kernel partial least squares are used to construct the inside-layer SEN sub-model based on each mechanical vibration and acoustic frequency spectral feature subset. Branch-and-bound and adaptive weighted fusion algorithms are integrated to select and combine outputs of the inside-layer SEN sub-models. Then, the outside-layer SEN is constructed. Thus, "sub-sampling training examples"-based and "manipulating input features"-based ensemble construction methods are integrated, thereby realizing the selective information fusion process based on multi-condition history samples and multi-source input features. This novel approach is applied to a laboratory-scale ball mill grinding process. A comparison with other methods indicates that the proposed MLSEN approach effectively models mechanical vibration and acoustic signals.

Spectral combination of spherical gravitational curvature boundary-value problems

NASA Astrophysics Data System (ADS)

PitoÅák, Martin; Eshagh, Mehdi; Šprlák, Michal; Tenzer, Robert; Novák, Pavel

2018-04-01

Four solutions of the spherical gravitational curvature boundary-value problems can be exploited for the determination of the Earth's gravitational potential. In this article we discuss the combination of simulated satellite gravitational curvatures, i.e., components of the third-order gravitational tensor, by merging these solutions using the spectral combination method. For this purpose, integral estimators of biased- and unbiased-types are derived. In numerical studies, we investigate the performance of the developed mathematical models for the gravitational field modelling in the area of Central Europe based on simulated satellite measurements. Firstly, we verify the correctness of the integral estimators for the spectral downward continuation by a closed-loop test. Estimated errors of the combined solution are about eight orders smaller than those from the individual solutions. Secondly, we perform a numerical experiment by considering the Gaussian noise with the standard deviation of 6.5× 10-17 m-1s-2 in the input data at the satellite altitude of 250 km above the mean Earth sphere. This value of standard deviation is equivalent to a signal-to-noise ratio of 10. Superior results with respect to the global geopotential model TIM-r5 are obtained by the spectral downward continuation of the vertical-vertical-vertical component with the standard deviation of 2.104 m2s-2, but the root mean square error is the largest and reaches 9.734 m2s-2. Using the spectral combination of all gravitational curvatures the root mean square error is more than 400 times smaller but the standard deviation reaches 17.234 m2s-2. The combination of more components decreases the root mean square error of the corresponding solutions while the standard deviations of the combined solutions do not improve as compared to the solution from the vertical-vertical-vertical component. The presented method represents a weight mean in the spectral domain that minimizes the root mean square error of the combined solutions and improves standard deviation of the solution based only on the least accurate components.

Building an Ontology for Identity Resolution in Healthcare and Public Health.

PubMed

Duncan, Jeffrey; Eilbeck, Karen; Narus, Scott P; Clyde, Stephen; Thornton, Sidney; Staes, Catherine

2015-01-01

Integration of disparate information from electronic health records, clinical data warehouses, birth certificate registries and other public health information systems offers great potential for clinical care, public health practice, and research. Such integration, however, depends on correctly matching patient-specific records using demographic identifiers. Without standards for these identifiers, record linkage is complicated by issues of structural and semantic heterogeneity. Our objectives were to develop and validate an ontology to: 1) identify components of identity and events subsequent to birth that result in creation, change, or sharing of identity information; 2) develop an ontology to facilitate data integration from multiple healthcare and public health sources; and 3) validate the ontology's ability to model identity-changing events over time. We interviewed domain experts in area hospitals and public health programs and developed process models describing the creation and transmission of identity information among various organizations for activities subsequent to a birth event. We searched for existing relevant ontologies. We validated the content of our ontology with simulated identity information conforming to scenarios identified in our process models. We chose the Simple Event Model (SEM) to describe events in early childhood and integrated the Clinical Element Model (CEM) for demographic information. We demonstrated the ability of the combined SEM-CEM ontology to model identity events over time. The use of an ontology can overcome issues of semantic and syntactic heterogeneity to facilitate record linkage.

Inhibitory neurons promote robust critical firing dynamics in networks of integrate-and-fire neurons.

PubMed

Lu, Zhixin; Squires, Shane; Ott, Edward; Girvan, Michelle

2016-12-01

We study the firing dynamics of a discrete-state and discrete-time version of an integrate-and-fire neuronal network model with both excitatory and inhibitory neurons. When the integer-valued state of a neuron exceeds a threshold value, the neuron fires, sends out state-changing signals to its connected neurons, and returns to the resting state. In this model, a continuous phase transition from non-ceaseless firing to ceaseless firing is observed. At criticality, power-law distributions of avalanche size and duration with the previously derived exponents, -3/2 and -2, respectively, are observed. Using a mean-field approach, we show analytically how the critical point depends on model parameters. Our main result is that the combined presence of both inhibitory neurons and integrate-and-fire dynamics greatly enhances the robustness of critical power-law behavior (i.e., there is an increased range of parameters, including both sub- and supercritical values, for which several decades of power-law behavior occurs).

Equilibrium control of nonlinear verticum-type systems, applied to integrated pest control.

PubMed

Molnár, S; Gámez, M; López, I; Cabello, T

2013-08-01

Linear verticum-type control and observation systems have been introduced for modelling certain industrial systems, consisting of subsystems, vertically connected by certain state variables. Recently the concept of verticum-type observation systems and the corresponding observability condition have been extended by the authors to the nonlinear case. In the present paper the general concept of a nonlinear verticum-type control system is introduced, and a sufficient condition for local controllability to equilibrium is obtained. In addition to a usual linearization, the basic idea is a decomposition of the control of the whole system into the control of the subsystems. Starting from the integrated pest control model of Rafikov and Limeira (2012) and Rafikov et al. (2012), a nonlinear verticum-type model has been set up an equilibrium control is obtained. Furthermore, a corresponding bioeconomical problem is solved minimizing the total cost of integrated pest control (combining chemical control with a biological one). Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

The monopolistic integrated model and health care reform: the Swedish experience.

PubMed

Anell, A

1996-07-01

This article reviews recent reforms geared to creating internal markets in the Swedish health-care sector. The main purpose is to describe driving forces behind reforms, and to analyse the limitations of reforms oriented towards internal markets within a monopolistic integrated health-care model. The principal part of the article is devoted to a discussion of incentives within Swedish county councils, and of how these incentives have influenced reforms in the direction of more choices for consumers and a separation between purchasers and providers. It is argued that the current incentives, in combination with criticism against county council activities in the early 1990's, account for the present inconsistencies as regards reforms. Furthermore, the article maintains that a weak form of separation between purchasers and providers will lead to distorted incentives, restricting innovative behaviour and structural change. In conclusion, the process of reforming the Swedish monopolistic integrated health-care model in the direction of some form of internal market is said to rest on shaky ground.

Cytoscape: a software environment for integrated models of biomolecular interaction networks.

PubMed

Shannon, Paul; Markiel, Andrew; Ozier, Owen; Baliga, Nitin S; Wang, Jonathan T; Ramage, Daniel; Amin, Nada; Schwikowski, Benno; Ideker, Trey

2003-11-01

Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

Simulation of Halocarbon Production and Emissions and Effects on Ozone Depletion

PubMed

Holmes; Ellis

1997-09-01

/ This paper describes an integrated model that simulates future halocarbon production/emissions and potential ozone depletion. Applications and historical production levels for various halocarbons are discussed first. A framework is then presented for modeling future halocarbon impacts incorporating differences in underlying demands, applications, regulatory mandates, and environmental characteristics. The model is used to simulate the potential impacts of several prominent issues relating to halocarbon production, regulation, and environmental interactions, notably: changes in agricultural methyl bromide use, increases in effectiveness of bromine for ozone depletion, modifications to the elimination schedule for HCFCs, short-term expansion of CFC demand in low use compliance countries, and delays in Russian Federation compliance. Individually, each issue does not unequivocally represent a significant likely increase in long-term atmospheric halogen loading and stratospheric ozone depletion. In combination, however, these impacts could increase peak halogen concentrations and long-term integral halogen loading, resulting in higher levels of stratospheric ozone depletion and longer exposure to increased levels of UV radiation.KEY WORDS: Halocarbons; Ozone depletion; Montreal Protocol; Integrated assessment

Integration of depression and primary care: barriers to adoption.

PubMed

Grazier, Kyle L; Smith, Judith E; Song, Jean; Smiley, Mary L

2014-01-01

Despite the prevailing consensus as to its value, the adoption of integrated care models is not widespread. Thus, the objective of this article it to examine the barriers to the adoption of depression and primary care models in the United States. A literature search focused on peer-reviewed journal literature in Medline and PsycInfo. The search strategy focused on barriers to integrated mental health care services in primary care, and was based on previously existing searches. The search included: MeSH terms combined with targeted keywords; iterative citation searches in Scopus; searches for grey literature (literature not traditionally indexed by commercial publishers) in Google and organization websites, examination of reference lists, and discussions with researchers. Integration of depression care and primary care faces multiple barriers. Patients and families face numerous barriers, linked inextricably to create challenges not easily remedied by any one party, including the following: vulnerable populations with special needs, patient and family factors, medical and mental health comorbidities, provider supply and culture, financing and costs, and organizational issues. An analysis of barriers impeding integration of depression and primary care presents information for future implementation of services.

An Integrated and Interdisciplinary Model for Predicting the Risk of Injury and Death in Future Earthquakes.

PubMed

Shapira, Stav; Novack, Lena; Bar-Dayan, Yaron; Aharonson-Daniel, Limor

2016-01-01

A comprehensive technique for earthquake-related casualty estimation remains an unmet challenge. This study aims to integrate risk factors related to characteristics of the exposed population and to the built environment in order to improve communities' preparedness and response capabilities and to mitigate future consequences. An innovative model was formulated based on a widely used loss estimation model (HAZUS) by integrating four human-related risk factors (age, gender, physical disability and socioeconomic status) that were identified through a systematic review and meta-analysis of epidemiological data. The common effect measures of these factors were calculated and entered to the existing model's algorithm using logistic regression equations. Sensitivity analysis was performed by conducting a casualty estimation simulation in a high-vulnerability risk area in Israel. the integrated model outcomes indicated an increase in the total number of casualties compared with the prediction of the traditional model; with regard to specific injury levels an increase was demonstrated in the number of expected fatalities and in the severely and moderately injured, and a decrease was noted in the lightly injured. Urban areas with higher populations at risk rates were found more vulnerable in this regard. The proposed model offers a novel approach that allows quantification of the combined impact of human-related and structural factors on the results of earthquake casualty modelling. Investing efforts in reducing human vulnerability and increasing resilience prior to an occurrence of an earthquake could lead to a possible decrease in the expected number of casualties.

MT+, integrating magnetotellurics to determine earth structure, physical state, and processes

USGS Publications Warehouse

Bedrosian, P.A.

2007-01-01

As one of the few deep-earth imaging techniques, magnetotellurics provides information on both the structure and physical state of the crust and upper mantle. Magnetotellurics is sensitive to electrical conductivity, which varies within the earth by many orders of magnitude and is modified by a range of earth processes. As with all geophysical techniques, magnetotellurics has a non-unique inverse problem and has limitations in resolution and sensitivity. As such, an integrated approach, either via the joint interpretation of independent geophysical models, or through the simultaneous inversion of independent data sets is valuable, and at times essential to an accurate interpretation. Magnetotelluric data and models are increasingly integrated with geological, geophysical and geochemical information. This review considers recent studies that illustrate the ways in which such information is combined, from qualitative comparisons to statistical correlation studies to multi-property inversions. Also emphasized are the range of problems addressed by these integrated approaches, and their value in elucidating earth structure, physical state, and processes. ?? Springer Science+Business Media B.V. 2007.

Systems Analysis Of Advanced Coal-Based Power Plants

NASA Technical Reports Server (NTRS)

Ferrall, Joseph F.; Jennings, Charles N.; Pappano, Alfred W.

1988-01-01

Report presents appraisal of integrated coal-gasification/fuel-cell power plants. Based on study comparing fuel-cell technologies with each other and with coal-based alternatives and recommends most promising ones for research and development. Evaluates capital cost, cost of electricity, fuel consumption, and conformance with environmental standards. Analyzes sensitivity of cost of electricity to changes in fuel cost, to economic assumptions, and to level of technology. Recommends further evaluation of integrated coal-gasification/fuel-cell integrated coal-gasification/combined-cycle, and pulverized-coal-fired plants. Concludes with appendixes detailing plant-performance models, subsystem-performance parameters, performance goals, cost bases, plant-cost data sheets, and plant sensitivity to fuel-cell performance.

Multisource Data Integration in Remote Sensing

NASA Technical Reports Server (NTRS)

Tilton, James C. (Editor)

1991-01-01

Papers presented at the workshop on Multisource Data Integration in Remote Sensing are compiled. The full text of these papers is included. New instruments and new sensors are discussed that can provide us with a large variety of new views of the real world. This huge amount of data has to be combined and integrated in a (computer-) model of this world. Multiple sources may give complimentary views of the world - consistent observations from different (and independent) data sources support each other and increase their credibility, while contradictions may be caused by noise, errors during processing, or misinterpretations, and can be identified as such. As a consequence, integration results are very reliable and represent a valid source of information for any geographical information system.

Integrating water and agricultural management: collaborative governance for a complex policy problem.

PubMed

Fish, Rob D; Ioris, Antonio A R; Watson, Nigel M

2010-11-01

This paper examines governance requirements for integrating water and agricultural management (IWAM). The institutional arrangements for the agriculture and water sectors are complex and multi-dimensional, and integration cannot therefore be achieved through a simplistic 'additive' policy process. Effective integration requires the development of a new collaborative approach to governance that is designed to cope with scale dependencies and interactions, uncertainty and contested knowledge, and interdependency among diverse and unequal interests. When combined with interdisciplinary research, collaborative governance provides a viable normative model because of its emphasis on reciprocity, relationships, learning and creativity. Ultimately, such an approach could lead to the sorts of system adaptations and transformations that are required for IWAM. Copyright © 2009 Elsevier B.V. All rights reserved.

An integrated remote sensing approach for identifying ecological range sites. [parker mountain

NASA Technical Reports Server (NTRS)

Jaynes, R. A.

1983-01-01

A model approach for identifying ecological range sites was applied to high elevation sagebrush-dominated rangelands on Parker Mountain, in south-central Utah. The approach utilizes map information derived from both high altitude color infrared photography and LANDSAT digital data, integrated with soils, geological, and precipitation maps. Identification of the ecological range site for a given area requires an evaluation of all relevant environmental factors which combine to give that site the potential to produce characteristic types and amounts of vegetation. A table is presented which allows the user to determine ecological range site based upon an integrated use of the maps which were prepared. The advantages of identifying ecological range sites through an integrated photo interpretation/LANDSAT analysis are discussed.

Operationally Efficient Propulsion System Study (OEPSS) Data Book. Volume 8; Integrated Booster Propulsion Module (BPM) Engine Start Dynamics

NASA Technical Reports Server (NTRS)

Kemp, Victoria R.

1992-01-01

A fluid-dynamic, digital-transient computer model of an integrated, parallel propulsion system was developed for the CDC mainframe and the SUN workstation computers. Since all STME component designs were used for the integrated system, computer subroutines were written characterizing the performance and geometry of all the components used in the system, including the manifolds. Three transient analysis reports were completed. The first report evaluated the feasibility of integrated engine systems in regards to the start and cutoff transient behavior. The second report evaluated turbopump out and combined thrust chamber/turbopump out conditions. The third report presented sensitivity study results in staggered gas generator spin start and in pump performance characteristics.

A comparison between different error modeling of MEMS applied to GPS/INS integrated systems.

PubMed

Quinchia, Alex G; Falco, Gianluca; Falletti, Emanuela; Dovis, Fabio; Ferrer, Carles

2013-07-24

Advances in the development of micro-electromechanical systems (MEMS) have made possible the fabrication of cheap and small dimension accelerometers and gyroscopes, which are being used in many applications where the global positioning system (GPS) and the inertial navigation system (INS) integration is carried out, i.e., identifying track defects, terrestrial and pedestrian navigation, unmanned aerial vehicles (UAVs), stabilization of many platforms, etc. Although these MEMS sensors are low-cost, they present different errors, which degrade the accuracy of the navigation systems in a short period of time. Therefore, a suitable modeling of these errors is necessary in order to minimize them and, consequently, improve the system performance. In this work, the most used techniques currently to analyze the stochastic errors that affect these sensors are shown and compared: we examine in detail the autocorrelation, the Allan variance (AV) and the power spectral density (PSD) techniques. Subsequently, an analysis and modeling of the inertial sensors, which combines autoregressive (AR) filters and wavelet de-noising, is also achieved. Since a low-cost INS (MEMS grade) presents error sources with short-term (high-frequency) and long-term (low-frequency) components, we introduce a method that compensates for these error terms by doing a complete analysis of Allan variance, wavelet de-nosing and the selection of the level of decomposition for a suitable combination between these techniques. Eventually, in order to assess the stochastic models obtained with these techniques, the Extended Kalman Filter (EKF) of a loosely-coupled GPS/INS integration strategy is augmented with different states. Results show a comparison between the proposed method and the traditional sensor error models under GPS signal blockages using real data collected in urban roadways.

A Comparison between Different Error Modeling of MEMS Applied to GPS/INS Integrated Systems

PubMed Central

Quinchia, Alex G.; Falco, Gianluca; Falletti, Emanuela; Dovis, Fabio; Ferrer, Carles

2013-01-01

Advances in the development of micro-electromechanical systems (MEMS) have made possible the fabrication of cheap and small dimension accelerometers and gyroscopes, which are being used in many applications where the global positioning system (GPS) and the inertial navigation system (INS) integration is carried out, i.e., identifying track defects, terrestrial and pedestrian navigation, unmanned aerial vehicles (UAVs), stabilization of many platforms, etc. Although these MEMS sensors are low-cost, they present different errors, which degrade the accuracy of the navigation systems in a short period of time. Therefore, a suitable modeling of these errors is necessary in order to minimize them and, consequently, improve the system performance. In this work, the most used techniques currently to analyze the stochastic errors that affect these sensors are shown and compared: we examine in detail the autocorrelation, the Allan variance (AV) and the power spectral density (PSD) techniques. Subsequently, an analysis and modeling of the inertial sensors, which combines autoregressive (AR) filters and wavelet de-noising, is also achieved. Since a low-cost INS (MEMS grade) presents error sources with short-term (high-frequency) and long-term (low-frequency) components, we introduce a method that compensates for these error terms by doing a complete analysis of Allan variance, wavelet de-nosing and the selection of the level of decomposition for a suitable combination between these techniques. Eventually, in order to assess the stochastic models obtained with these techniques, the Extended Kalman Filter (EKF) of a loosely-coupled GPS/INS integration strategy is augmented with different states. Results show a comparison between the proposed method and the traditional sensor error models under GPS signal blockages using real data collected in urban roadways. PMID:23887084

Earth Observations for Global Water Security

NASA Technical Reports Server (NTRS)

Lawford, Richard; Strauch, Adrian; Toll, David; Fekete, Balazs; Cripe, Douglas

2013-01-01

The combined effects of population growth, increasing demands for water to support agriculture, energy security, and industrial expansion, and the challenges of climate change give rise to an urgent need to carefully monitor and assess trends and variations in water resources. Doing so will ensure that sustainable access to adequate quantities of safe and useable water will serve as a foundation for water security. Both satellite and in situ observations combined with data assimilation and models are needed for effective, integrated monitoring of the water cycle's trends and variability in terms of both quantity and quality. On the basis of a review of existing observational systems, we argue that a new integrated monitoring capability for water security purposes is urgently needed. Furthermore, the components for this capability exist and could be integrated through the cooperation of national observational programmes. The Group on Earth Observations should play a central role in the design, implementation, management and analysis of this system and its products.

Integration of biotechnological wastewater treatment units in textile finishing factories: from end of the pipe solutions to combined production and wastewater treatment units.

PubMed

Feitkenhauer, H; Meyer, U

2001-08-23

Increasing costs for water, wastewater and energy put pressure on textile finishing plants to increase the efficiency of wet processing. An improved water management can decrease the use of these resources and is a prerequisite for the integration of an efficient, anaerobic on-site pretreatment of effluents that will further cut wastewater costs. A two-phase anaerobic treatment is proposed, and successful laboratory experiments with model effluents from the cotton finishing industry are reported. The chemical oxygen demand of this wastewater was reduced by over 88% at retention times of 1 day or longer. The next step to boost the efficiency is to combine the production and wastewater treatment. The example of cotton fabric desizing (removing size from the fabric) illustrates how this final step of integration uses the acidic phase bioreactor as a part of the production and allows to close the water cycle of the system.

An experimental study of wall adaptation and interference assessment using Cauchy integral formula

NASA Technical Reports Server (NTRS)

Murthy, A. V.

1991-01-01

This paper summarizes the results of an experimental study of combined wall adaptation and residual interference assessment using the Cauchy integral formula. The experiments were conducted on a supercritical airfoil model in the Langley 0.3-m Transonic Cryogenic Tunnel solid flexible wall test section. The ratio of model chord to test section height was about 0.7. The method worked satisfactorily in reducing the blockage interference and demonstrated the primary requirement for correcting for the blockage effects at high model incidences to correctly determine high lift characteristics. The studies show that the method has potential for reducing the residual interference to considerably low levels. However, corrections to blockage and upwash velocities gradients may still be required for the final adapted wall shapes.

Application of a Combined Model with Autoregressive Integrated Moving Average (ARIMA) and Generalized Regression Neural Network (GRNN) in Forecasting Hepatitis Incidence in Heng County, China

PubMed Central

Liang, Hao; Gao, Lian; Liang, Bingyu; Huang, Jiegang; Zang, Ning; Liao, Yanyan; Yu, Jun; Lai, Jingzhen; Qin, Fengxiang; Su, Jinming; Ye, Li; Chen, Hui

2016-01-01

Background Hepatitis is a serious public health problem with increasing cases and property damage in Heng County. It is necessary to develop a model to predict the hepatitis epidemic that could be useful for preventing this disease. Methods The autoregressive integrated moving average (ARIMA) model and the generalized regression neural network (GRNN) model were used to fit the incidence data from the Heng County CDC (Center for Disease Control and Prevention) from January 2005 to December 2012. Then, the ARIMA-GRNN hybrid model was developed. The incidence data from January 2013 to December 2013 were used to validate the models. Several parameters, including mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE) and mean square error (MSE), were used to compare the performance among the three models. Results The morbidity of hepatitis from Jan 2005 to Dec 2012 has seasonal variation and slightly rising trend. The ARIMA(0,1,2)(1,1,1)12 model was the most appropriate one with the residual test showing a white noise sequence. The smoothing factor of the basic GRNN model and the combined model was 1.8 and 0.07, respectively. The four parameters of the hybrid model were lower than those of the two single models in the validation. The parameters values of the GRNN model were the lowest in the fitting of the three models. Conclusions The hybrid ARIMA-GRNN model showed better hepatitis incidence forecasting in Heng County than the single ARIMA model and the basic GRNN model. It is a potential decision-supportive tool for controlling hepatitis in Heng County. PMID:27258555

An Integrated Systems Approach to Designing Climate Change Adaptation Policy in Water Resources

NASA Astrophysics Data System (ADS)

Ryu, D.; Malano, H. M.; Davidson, B.; George, B.

2014-12-01

Climate change projections are characterised by large uncertainties with rainfall variability being the key challenge in designing adaptation policies. Climate change adaptation in water resources shows all the typical characteristics of 'wicked' problems typified by cognitive uncertainty as new scientific knowledge becomes available, problem instability, knowledge imperfection and strategic uncertainty due to institutional changes that inevitably occur over time. Planning that is characterised by uncertainties and instability requires an approach that can accommodate flexibility and adaptive capacity for decision-making. An ability to take corrective measures in the event that scenarios and responses envisaged initially derive into forms at some future stage. We present an integrated-multidisciplinary and comprehensive framework designed to interface and inform science and decision making in the formulation of water resource management strategies to deal with climate change in the Musi Catchment of Andhra Pradesh, India. At the core of this framework is a dialogue between stakeholders, decision makers and scientists to define a set of plausible responses to an ensemble of climate change scenarios derived from global climate modelling. The modelling framework used to evaluate the resulting combination of climate scenarios and adaptation responses includes the surface and groundwater assessment models (SWAT & MODFLOW) and the water allocation modelling (REALM) to determine the water security of each adaptation strategy. Three climate scenarios extracted from downscaled climate models were selected for evaluation together with four agreed responses—changing cropping patterns, increasing watershed development, changing the volume of groundwater extraction and improving irrigation efficiency. Water security in this context is represented by the combination of level of water availability and its associated security of supply for three economic activities (agriculture, urban, industrial) on a spatially distributed basis. The resulting combinations of climate scenarios and adaptation responses were subjected to a combined hydro-economic assessment based on the degree of water security together with its cost-effectiveness against the Business-as-usual scenario.

Combining Mechanistic Approaches for Studying Eco-Hydro-Geomorphic Coupling

NASA Astrophysics Data System (ADS)

Francipane, A.; Ivanov, V.; Akutina, Y.; Noto, V.; Istanbullouglu, E.

2008-12-01

Vegetation interacts with hydrology and geomorphic form and processes of a river basin in profound ways. Despite recent advances in hydrological modeling, the dynamic coupling between these processes is yet to be adequately captured at the basin scale to elucidate key features of process interaction and their role in the organization of vegetation and landscape morphology. In this study, we present a blueprint for integrating a geomorphic component into the physically-based, spatially distributed ecohydrological model, tRIBS- VEGGIE, which reproduces essential water and energy processes over the complex topography of a river basin and links them to the basic plant life regulatory processes. We present a preliminary design of the integrated modeling framework in which hillslope and channel erosion processes at the catchment scale, will be coupled with vegetation-hydrology dynamics. We evaluate the developed framework by applying the integrated model to Lucky Hills basin, a sub-catchment of the Walnut Gulch Experimental Watershed (Arizona). The evaluation is carried out by comparing sediment yields at the basin outlet, that follows a detailed verification of simulated land-surface energy partition, biomass dynamics, and soil moisture states.

True Concurrent Thermal Engineering Integrating CAD Model Building with Finite Element and Finite Difference Methods

NASA Technical Reports Server (NTRS)

Panczak, Tim; Ring, Steve; Welch, Mark

1999-01-01

Thermal engineering has long been left out of the concurrent engineering environment dominated by CAD (computer aided design) and FEM (finite element method) software. Current tools attempt to force the thermal design process into an environment primarily created to support structural analysis, which results in inappropriate thermal models. As a result, many thermal engineers either build models "by hand" or use geometric user interfaces that are separate from and have little useful connection, if any, to CAD and FEM systems. This paper describes the development of a new thermal design environment called the Thermal Desktop. This system, while fully integrated into a neutral, low cost CAD system, and which utilizes both FEM and FD methods, does not compromise the needs of the thermal engineer. Rather, the features needed for concurrent thermal analysis are specifically addressed by combining traditional parametric surface based radiation and FD based conduction modeling with CAD and FEM methods. The use of flexible and familiar temperature solvers such as SINDA/FLUINT (Systems Improved Numerical Differencing Analyzer/Fluid Integrator) is retained.

Integrative Approaches for Predicting in vivo Effects of Chemicals from their Structural Descriptors and the Results of Short-term Biological Assays

PubMed Central

Low, Yen S.; Sedykh, Alexander; Rusyn, Ivan; Tropsha, Alexander

2017-01-01

Cheminformatics approaches such as Quantitative Structure Activity Relationship (QSAR) modeling have been used traditionally for predicting chemical toxicity. In recent years, high throughput biological assays have been increasingly employed to elucidate mechanisms of chemical toxicity and predict toxic effects of chemicals in vivo. The data generated in such assays can be considered as biological descriptors of chemicals that can be combined with molecular descriptors and employed in QSAR modeling to improve the accuracy of toxicity prediction. In this review, we discuss several approaches for integrating chemical and biological data for predicting biological effects of chemicals in vivo and compare their performance across several data sets. We conclude that while no method consistently shows superior performance, the integrative approaches rank consistently among the best yet offer enriched interpretation of models over those built with either chemical or biological data alone. We discuss the outlook for such interdisciplinary methods and offer recommendations to further improve the accuracy and interpretability of computational models that predict chemical toxicity. PMID:24805064

Bayesian Model Development for Analysis of Open Source Information to Support the Assessment of Nuclear Programs

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

Gastelum, Zoe N.; Whitney, Paul D.; White, Amanda M.

2013-07-15

Pacific Northwest National Laboratory has spent several years researching, developing, and validating large Bayesian network models to support integration of open source data sets for nuclear proliferation research. Our current work focuses on generating a set of interrelated models for multi-source assessment of nuclear programs, as opposed to a single comprehensive model. By using this approach, we can break down the models to cover logical sub-problems that can utilize different expertise and data sources. This approach allows researchers to utilize the models individually or in combination to detect and characterize a nuclear program and identify data gaps. The models operatemore » at various levels of granularity, covering a combination of state-level assessments with more detailed models of site or facility characteristics. This paper will describe the current open source-driven, nuclear nonproliferation models under development, the pros and cons of the analytical approach, and areas for additional research.« less

On the engineering design for systematic integration of agent-orientation in industrial automation.

PubMed

Yu, Liyong; Schüller, Andreas; Epple, Ulrich

2014-09-01

In today's automation industry, agent-oriented development of system functionalities appears to have a great potential for increasing autonomy and flexibility of complex operations, while lowering the workload of users. In this paper, we present a reference model for the harmonious and systematical integration of agent-orientation in industrial automation. Considering compatibility with existing automation systems and best practice, this model combines advantages of function block technology, service orientation and native description methods from the automation standard IEC 61131-3. This approach can be applied as a guideline for the engineering design of future agent-oriented automation systems. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Technology developments integrating a space network communications testbed

NASA Technical Reports Server (NTRS)

Kwong, Winston; Jennings, Esther; Clare, Loren; Leang, Dee

2006-01-01

As future manned and robotic space explorations missions involve more complex systems, it is essential to verify, validate, and optimize such systems through simulation and emulation in a low cost testbed environment. The goal of such a testbed is to perform detailed testing of advanced space and ground communications networks, technologies, and client applications that are essential for future space exploration missions. We describe the development of new technologies enhancing our Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) that enables its integration in a distributed space communications testbed. MACHETE combines orbital modeling, link analysis, and protocol and service modeling to quantify system performance based on comprehensive considerations of different aspects of space missions.

Astronomical Data Integration Beyond the Virtual Observatory

NASA Astrophysics Data System (ADS)

Lemson, G.; Laurino, O.

2015-09-01

"Data integration" generally refers to the process of combining data from different source data bases into a unified view. Much work has been devoted in this area by the International Virtual Observatory Alliance (IVOA), allowing users to discover and access databases through standard protocols. However, different archives present their data through their own schemas and users must still select, filter, and combine data for each archive individually. An important reason for this is that the creation of common data models that satisfy all sub-disciplines is fraught with difficulties. Furthermore it requires a substantial amount of work for data providers to present their data according to some standard representation. We will argue that existing standards allow us to build a data integration framework that works around these problems. The particular framework requires the implementation of the IVOA Table Access Protocol (TAP) only. It uses the newly developed VO data modelling language (VO-DML) specification, which allows one to define extensible object-oriented data models using a subset of UML concepts through a simple XML serialization language. A rich mapping language allows one to describe how instances of VO-DML data models are represented by the TAP service, bridging the possible mismatch between a local archive's schema and some agreed-upon representation of the astronomical domain. In this so called local-as-view approach to data integration, “mediators" use the mapping prescriptions to translate queries phrased in terms of the common schema to the underlying TAP service. This mapping language has a graphical representation, which we expose through a web based graphical “drag-and-drop-and-connect" interface. This service allows any user to map the holdings of any TAP service to the data model(s) of choice. The mappings are defined and stored outside of the data sources themselves, which allows the interface to be used in a kind of crowd-sourcing effort to annotate any remote database of interest. This reduces the burden of publishing one's data and allows a great flexibility in the definition of the views through which particular communities might wish to access remote archives. At the same time, the framework easies the user's effort to select, filter, and combine data from many different archives, so as to build knowledge bases for their analysis. We will present the framework and demonstrate a prototype implementation. We will discuss ideas for producing the missing elements, in particular the query language and the implementation of mediator tools to translate object queries to ADQL

The state of the art of nanobioscience in Japan.

PubMed

Ueno, Shoogo; Ando, Joji; Fujita, Hiroyuki; Sugawara, Tadashi; Jimbo, Yasuhiko; Itaka, Keiji; Kataoka, Kazunori; Ushida, Takashi

2006-03-01

This paper reviews a part of the state of the art of nanobioscience in Japan. The importance of combination and integration of interdisciplinary principles is emphasized for the development of nanobioscience. Biomagnetics, biomechanics, nanomachining, self-replicating cell model, neuronal network, drug delivery system, and tissue engineering are discussed.

Maximizing Educator Enhancement: Aligned Seminar and Online Professional Development

ERIC Educational Resources Information Center

Shaha, Steven; Glassett, Kelly; Copas, Aimee; Huddleston, T. Lisa

2016-01-01

Professional development and learning has a long history in seminar-like models, as well as in the more educator-personal delivery approaches. The question is whether an intentionally coordinated, integrated combination of the two PDL approaches will have best impacts for educators as quantified in improved student performance. Contrasts between…

Peter Hacke | NREL

Science.gov Websites

photovoltaic (PV) modules, inspections for root cause of module failures in the field, and accelerated lifetime delamination. His research interests are in modeling of degradation processes of PV modules, module integrated analysis of PV degradation data. He also explores accelerated multi-stress and combined stress testing to

Combining data visualization and statistical approaches for interpreting measurements and meta-data: Integrating heatmaps, variable clustering, and mixed regression models

EPA Science Inventory

The advent of new higher throughput analytical instrumentation has put a strain on interpreting and explaining the results from complex studies. Contemporary human, environmental, and biomonitoring data sets are comprised of tens or hundreds of analytes, multiple repeat measures...

Coping with Stigma: An Integrated Approach to Counseling Physically Disabled Persons.

ERIC Educational Resources Information Center

Heinemann, Allen W.; Shontz, Franklin C.

1982-01-01

Describes a short-term group counseling approach to use with physically disabled clients that combines assertion-training with attitude clarification and information approaches. Discusses rationale for the program and describes the coping skills group model. Details purposes and activities for each of 10 sessions. (RC)

The Sources of the Relationship between Sustained Attention and Reasoning

ERIC Educational Resources Information Center

Ren, Xuezhu; Schweizer, Karl; Xu, Fen

2013-01-01

Although a substantial relationship of sustained attention and reasoning was consistently found, little is known about what drives this relationship. The present study aims at revealing the underlying sources that are responsible for the relationship by means of an integrative approach combining experimental manipulation and psychometric modeling.…

Reinventing Gerocounseling in Counselor Education as a Specialization

ERIC Educational Resources Information Center

Foster, Thomas; Kreider, Val

2009-01-01

Recent trends in counselor education are moving away from a standardized academic track in gerocounseling. We propose three types of academic models (integrated in-house, out-of-house, and combined) that provide greater academic freedom to counselor education faculty who wish to construct a gero-specialization specific in their program.

Economic assessments of potato production systems in Maine

USDA-ARS?s Scientific Manuscript database

Using an integrated enterprise and whole-farm budget model for a 324-ha medium-sized potato farm, the profitability of potatoes grown in combination with fifteen common potato rotation crops in Maine are evaluated. Enterprise budgets for all sixteen crops are calculated while a whole-farm budget syn...

Developmental Pathways and Technology: The Foundations of Enhanced Intellectual Excellence.

ERIC Educational Resources Information Center

Williamson, Edward A.; Slye, Gail L.

The combination of technology applications and an understanding of developmental pathways theory enhances intellectual growth for preservice teachers. Utilizing the theories developed by Dr. James Comer and integrating them with state of the art technological applications, this paper describes one model of preservice education that has been…

Wind tunnel test IA300 analysis and results, volume 1

NASA Technical Reports Server (NTRS)

Kelley, P. B.; Beaufait, W. B.; Kitchens, L. L.; Pace, J. P.

1987-01-01

The analysis and interpretation of wind tunnel pressure data from the Space Shuttle wind tunnel test IA300 are presented. The primary objective of the test was to determine the effects of the Space Shuttle Main Engine (SSME) and the Solid Rocket Booster (SRB) plumes on the integrated vehicle forebody pressure distributions, the elevon hinge moments, and wing loads. The results of this test will be combined with flight test results to form a new data base to be employed in the IVBC-3 airloads analysis. A secondary objective was to obtain solid plume data for correlation with the results of gaseous plume tests. Data from the power level portion was used in conjunction with flight base pressures to evaluate nominal power levels to be used during the investigation of changes in model attitude, eleveon deflection, and nozzle gimbal angle. The plume induced aerodynamic loads were developed for the Space Shuttle bases and forebody areas. A computer code was developed to integrate the pressure data. Using simplified geometrical models of the Space Shuttle elements and components, the pressure data were integrated to develop plume induced force and moments coefficients that can be combined with a power-off data base to develop a power-on data base.

SPIRE: Systematic protein investigative research environment.

PubMed

Kolker, Eugene; Higdon, Roger; Morgan, Phil; Sedensky, Margaret; Welch, Dean; Bauman, Andrew; Stewart, Elizabeth; Haynes, Winston; Broomall, William; Kolker, Natali

2011-12-10

The SPIRE (Systematic Protein Investigative Research Environment) provides web-based experiment-specific mass spectrometry (MS) proteomics analysis (https://www.proteinspire.org). Its emphasis is on usability and integration of the best analytic tools. SPIRE provides an easy to use web-interface and generates results in both interactive and simple data formats. In contrast to run-based approaches, SPIRE conducts the analysis based on the experimental design. It employs novel methods to generate false discovery rates and local false discovery rates (FDR, LFDR) and integrates the best and complementary open-source search and data analysis methods. The SPIRE approach of integrating X!Tandem, OMSSA and SpectraST can produce an increase in protein IDs (52-88%) over current combinations of scoring and single search engines while also providing accurate multi-faceted error estimation. One of SPIRE's primary assets is combining the results with data on protein function, pathways and protein expression from model organisms. We demonstrate some of SPIRE's capabilities by analyzing mitochondrial proteins from the wild type and 3 mutants of C. elegans. SPIRE also connects results to publically available proteomics data through its Model Organism Protein Expression Database (MOPED). SPIRE can also provide analysis and annotation for user supplied protein ID and expression data. Copyright © 2011. Published by Elsevier B.V.

Advanced Technology Training System on Motor-Operated Valves

NASA Technical Reports Server (NTRS)

Wiederholt, Bradley J.; Widjaja, T. Kiki; Yasutake, Joseph Y.; Isoda, Hachiro

1993-01-01

This paper describes how features from the field of Intelligent Tutoring Systems are applied to the Motor-Operated Valve (MOV) Advanced Technology Training System (ATTS). The MOV ATTS is a training system developed at Galaxy Scientific Corporation for the Central Research Institute of Electric Power Industry in Japan and the Electric Power Research Institute in the United States. The MOV ATTS combines traditional computer-based training approaches with system simulation, integrated expert systems, and student and expert modeling. The primary goal of the MOV ATTS is to reduce human errors that occur during MOV overhaul and repair. The MOV ATTS addresses this goal by providing basic operational information of the MOV, simulating MOV operation, providing troubleshooting practice of MOV failures, and tailoring this training to the needs of each individual student. The MOV ATTS integrates multiple expert models (functional and procedural) to provide advice and feedback to students. The integration also provides expert model validation support to developers. Student modeling is supported by two separate student models: one model registers and updates the student's current knowledge of basic MOV information, while another model logs the student's actions and errors during troubleshooting exercises. These two models are used to provide tailored feedback to the student during the MOV course.

Producer-retailer integrated EMQ system with machine breakdown, rework failures, and a discontinuous inventory issuing policy.

PubMed

Chiu, Singa Wang; Chen, Shin-Wei; Chiu, Yuan-Shyi Peter; Li, Ting-Wei

2016-01-01

This study develops two extended economic manufacturing quantity (EMQ)-based models with a discontinuous product issuing policy, random machine breakdown, and rework failures. Various real conditions in production processes, end-product delivery, and intra-supply chains such as a producer-retailer integrated scheme are examined. The first model incorporates a discontinuous multi-delivery policy into a prior work (Chiu et al. in Proc Inst Mech Eng B J Eng 223:183-194, 2009) in lieu of their continuous policy. Such an enhanced model can address situations in supply chain environments, where finished products are transported to outside retail stores (or customers). The second model further combines retailer's stock holding costs into the first model. This extended EMQ model is applicable in situations in present-day manufacturing firms where finished products are distributed to company's own retail stores (or regional sales offices) and stocked there for sale. Two aforementioned extended EMQ models are investigated, respectively. Mathematical modeling along with iterative algorithms are employed to derive the optimal production run times that minimize the expected total system costs, including the costs incurred in production units, transportation, and retail stores, for these integrated EMQ systems. Numerical examples are provided to demonstrate the practical application of the research results.

Force on Force Modeling with Formal Task Structures and Dynamic Geometry

DTIC Science & Technology

2017-03-24

task framework, derived using the MMF methodology to structure a complex mission. It further demonstrated the integration of effects from a range of...application methodology was intended to support a combined developmental testing (DT) and operational testing (OT) strategy for selected systems under test... methodology to develop new or modify existing Models and Simulations (M&S) to: • Apply data from multiple, distributed sources (including test

Optimizing variable radius plot size and LiDAR resolution to model standing volume in conifer forests

Treesearch

Ram Kumar Deo; Robert E. Froese; Michael J. Falkowski; Andrew T. Hudak

2016-01-01

The conventional approach to LiDAR-based forest inventory modeling depends on field sample data from fixed-radius plots (FRP). Because FRP sampling is cost intensive, combining variable-radius plot (VRP) sampling and LiDAR data has the potential to improve inventory efficiency. The overarching goal of this study was to evaluate the integration of LiDAR and VRP data....

Finite Element Modeling of Coupled Flexible Multibody Dynamics and Liquid Sloshing

DTIC Science & Technology

2006-09-01

tanks is presented. The semi-discrete combined solid and fluid equations of motions are integrated using a time- accurate parallel explicit solver...Incompressible fluid flow in a moving/deforming container including accurate modeling of the free-surface, turbulence, and viscous effects ...paper, a single computational code which uses a time- accurate explicit solution procedure is used to solve both the solid and fluid equations of

Aerodynamic Design of a Dual-Flow Mach 7 Hypersonic Inlet System for a Turbine-Based Combined-Cycle Hypersonic Propulsion System

NASA Technical Reports Server (NTRS)

Sanders, Bobby W.; Weir, Lois J.

2008-01-01

A new hypersonic inlet for a turbine-based combined-cycle (TBCC) engine has been designed. This split-flow inlet is designed to provide flow to an over-under propulsion system with turbofan and dual-mode scramjet engines for flight from takeoff to Mach 7. It utilizes a variable-geometry ramp, high-speed cowl lip rotation, and a rotating low-speed cowl that serves as a splitter to divide the flow between the low-speed turbofan and the high-speed scramjet and to isolate the turbofan at high Mach numbers. The low-speed inlet was designed for Mach 4, the maximum mode transition Mach number. Integration of the Mach 4 inlet into the Mach 7 inlet imposed significant constraints on the low-speed inlet design, including a large amount of internal compression. The inlet design was used to develop mechanical designs for two inlet mode transition test models: small-scale (IMX) and large-scale (LIMX) research models. The large-scale model is designed to facilitate multi-phase testing including inlet mode transition and inlet performance assessment, controls development, and integrated systems testing with turbofan and scramjet engines.

Improving UK Chalk hydrometeorology across spatial scales using a small hydrometeorological network

NASA Astrophysics Data System (ADS)

Rosolem, Rafael; Iwema, Joost; Rahman, Mostaquimur; Desilets, Darin; Koltermann da Silva, Juliana

2016-04-01

Chalk in the UK acts as a primary aquifer providing up to 80% of the public water supply locally. Chalk outcrops are located over most of southern and eastern England. Despite its importance, the characterization of Chalk in hydrometeorological models is still very limited. There is a need for a comprehensive and coherent integration of observations and modeling efforts across spatial scales for better understanding Chalk hydrometeorology. Here we introduce the "A MUlti-scale Soil moisture-Evapotranspiration Dynamics" (AMUSED) project. AMUSED goal is to better identify the key dominant processes controlling changes in soil moisture and surface fluxes (e.g., evapotranspiration) across spatial scales by combining ground-based observations with hydrometeorological models and satellite remote sensing products. The AMUSED observational platform consists of three sites located in Upper Chalk region of the Lambourn Catchment located in southern England covering approximately 2 square-km characterized by distinct combinations of soil and vegetation types. The network includes standard meteorological measurements, an eddy covariance system for turbulent fluxes and cosmic-ray neutron sensors for integrated soil moisture estimates at intermediate scales. Here we present our initial results from our three sites.

[Competence development in undergraduate medical schools: a model with entrusted professional activities].

PubMed

Torruco-García, Uri; Ortiz-Montalvo, Armando; Varela-Ruiz, Margarita Elena; Hamui-Sutton, Alicia

2016-01-01

Today´s relevant educational models emphasize that a great part of learning be situated and reflexive; one of those is the Entrusted Professional Activities model. The study objective was to develop a model that integrates Entrusted Professional Activities with a medical school curriculum. From October 2012 a multidisciplinary group met to develop a model with the specialty of obstetrics and gynecology. From two published models of Entrusted Professional Activities and the curriculum of a school of medicine, blocks, units, and daily clinical practice charts were developed. The thematic content of the curriculum was integrated with the appropriate milestones for undergraduate students and the clinical practice needed to achieve it. We wrote a manual with 37 daily clinical practice charts for students (18 of gynecology and 19 of obstetrics) and 37 for teachers. Each chart content was the daily clinical practice, reflection activities, assessment instruments, and bibliography. It is feasible to combine a model of Entrusted Professional Activities with an undergraduate curriculum, which establishes a continuum with postgraduate education.

Scattering of elastic waves from thin shapes in three dimensions using the composite boundary integral equation formulation

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

Liu, Y.; Rizzo, F.J.

1997-08-01

In this paper, the composite boundary integral equation (BIE) formulation is applied to scattering of elastic waves from thin shapes with small but {ital finite} thickness (open cracks or thin voids, thin inclusions, thin-layer interfaces, etc.), which are modeled with {ital two surfaces}. This composite BIE formulation, which is an extension of the Burton and Miller{close_quote}s formulation for acoustic waves, uses a linear combination of the conventional BIE and the hypersingular BIE. For thin shapes, the conventional BIE, as well as the hypersingular BIE, will degenerate (or nearly degenerate) if they are applied {ital individually} on the two surfaces. Themore » composite BIE formulation, however, will not degenerate for such problems, as demonstrated in this paper. Nearly singular and hypersingular integrals, which arise in problems involving thin shapes modeled with two surfaces, are transformed into sums of weakly singular integrals and nonsingular line integrals. Thus, no finer mesh is needed to compute these nearly singular integrals. Numerical examples of elastic waves scattered from penny-shaped cracks with varying openings are presented to demonstrate the effectiveness of the composite BIE formulation. {copyright} {ital 1997 Acoustical Society of America.}« less

A combined PHREEQC-2/parallel fracture model for the simulation of laminar/non-laminar flow and contaminant transport with reactions

NASA Astrophysics Data System (ADS)

Masciopinto, Costantino; Volpe, Angela; Palmiotta, Domenico; Cherubini, Claudia

2010-09-01

A combination of a parallel fracture model with the PHREEQC-2 geochemical model was developed to simulate sequential flow and chemical transport with reactions in fractured media where both laminar and turbulent flows occur. The integration of non-laminar flow resistances in one model produced relevant effects on water flow velocities, thus improving model prediction capabilities on contaminant transport. The proposed conceptual model consists of 3D rock-blocks, separated by horizontal bedding plane fractures with variable apertures. Particle tracking solved the transport equations for conservative compounds and provided input for PHREEQC-2. For each cluster of contaminant pathways, PHREEQC-2 determined the concentration for mass-transfer, sorption/desorption, ion exchange, mineral dissolution/precipitation and biodegradation, under kinetically controlled reactive processes of equilibrated chemical species. Field tests have been performed for the code verification. As an example, the combined model has been applied to a contaminated fractured aquifer of southern Italy in order to simulate the phenol transport. The code correctly fitted the field available data and also predicted a possible rapid depletion of phenols as a result of an increased biodegradation rate induced by a simulated artificial injection of nitrates, upgradient to the sources.

Attributing runoff changes to climate variability and human activities: uncertainty analysis using four monthly water balance models

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

Li, Shuai; Xiong, Lihua; Li, Hong-Yi

2015-05-26

Hydrological simulations to delineate the impacts of climate variability and human activities are subjected to uncertainties related to both parameter and structure of the hydrological models. To analyze the impact of these uncertainties on the model performance and to yield more reliable simulation results, a global calibration and multimodel combination method that integrates the Shuffled Complex Evolution Metropolis (SCEM) and Bayesian Model Averaging (BMA) of four monthly water balance models was proposed. The method was applied to the Weihe River Basin (WRB), the largest tributary of the Yellow River, to determine the contribution of climate variability and human activities tomore » runoff changes. The change point, which was used to determine the baseline period (1956-1990) and human-impacted period (1991-2009), was derived using both cumulative curve and Pettitt’s test. Results show that the combination method from SCEM provides more skillful deterministic predictions than the best calibrated individual model, resulting in the smallest uncertainty interval of runoff changes attributed to climate variability and human activities. This combination methodology provides a practical and flexible tool for attribution of runoff changes to climate variability and human activities by hydrological models.« less

New Insight into Combined Model and Revised Model for RTD Curves in a Multi-strand Tundish

NASA Astrophysics Data System (ADS)

Lei, Hong

2015-12-01

The analysis for the residence time distribution (RTD) curve is one of the important experimental technologies to optimize the tundish design. But there are some issues about RTD analysis model. Firstly, the combined (or mixed) model and the revised model give different analysis results for the same RTD curve. Secondly, different upper limits of integral in the numerator for the mean residence time give different results for the same RTD curve. Thirdly, the negative dead volume fraction sometimes appears at the outer strand of the multi-strand tundish. In order to solve the above problems, it is necessary to have a deep insight into the RTD curve and to propose a reasonable method to analyze the RTD curve. The results show that (1) the revised model is not appropriate to treat with the RTD curve; (2) the conception of the visual single-strand tundish and the combined model with the dimensionless time at the cut-off point are applied to estimate the flow characteristics in the multi-strand tundish; and that (3) the mean residence time at each exit is the key parameter to estimate the similarity of fluid flow among strands.

On meta- and mega-analyses for gene–environment interactions

PubMed Central

Huang, Jing; Liu, Yulun; Vitale, Steve; Penning, Trevor M.; Whitehead, Alexander S.; Blair, Ian A.; Vachani, Anil; Clapper, Margie L.; Muscat, Joshua E.; Lazarus, Philip; Scheet, Paul; Moore, Jason H.; Chen, Yong

2017-01-01

Gene-by-environment (G × E) interactions are important in explaining the missing heritability and understanding the causation of complex diseases, but a single, moderately sized study often has limited statistical power to detect such interactions. With the increasing need for integrating data and reporting results from multiple collaborative studies or sites, debate over choice between mega- versus meta-analysis continues. In principle, data from different sites can be integrated at the individual level into a “mega” data set, which can be fit by a joint “mega-analysis.” Alternatively, analyses can be done at each site, and results across sites can be combined through a “meta-analysis” procedure without integrating individual level data across sites. Although mega-analysis has been advocated in several recent initiatives, meta-analysis has the advantages of simplicity and feasibility, and has recently led to several important findings in identifying main genetic effects. In this paper, we conducted empirical and simulation studies, using data from a G × E study of lung cancer, to compare the mega- and meta-analyses in four commonly used G × E analyses under the scenario that the number of studies is small and sample sizes of individual studies are relatively large. We compared the two data integration approaches in the context of fixed effect models and random effects models separately. Our investigations provide valuable insights in understanding the differences between mega- and meta-analyses in practice of combining small number of studies in identifying G × E interactions. PMID:29110346

On meta- and mega-analyses for gene-environment interactions.

PubMed

Huang, Jing; Liu, Yulun; Vitale, Steve; Penning, Trevor M; Whitehead, Alexander S; Blair, Ian A; Vachani, Anil; Clapper, Margie L; Muscat, Joshua E; Lazarus, Philip; Scheet, Paul; Moore, Jason H; Chen, Yong

2017-12-01

Gene-by-environment (G × E) interactions are important in explaining the missing heritability and understanding the causation of complex diseases, but a single, moderately sized study often has limited statistical power to detect such interactions. With the increasing need for integrating data and reporting results from multiple collaborative studies or sites, debate over choice between mega- versus meta-analysis continues. In principle, data from different sites can be integrated at the individual level into a "mega" data set, which can be fit by a joint "mega-analysis." Alternatively, analyses can be done at each site, and results across sites can be combined through a "meta-analysis" procedure without integrating individual level data across sites. Although mega-analysis has been advocated in several recent initiatives, meta-analysis has the advantages of simplicity and feasibility, and has recently led to several important findings in identifying main genetic effects. In this paper, we conducted empirical and simulation studies, using data from a G × E study of lung cancer, to compare the mega- and meta-analyses in four commonly used G × E analyses under the scenario that the number of studies is small and sample sizes of individual studies are relatively large. We compared the two data integration approaches in the context of fixed effect models and random effects models separately. Our investigations provide valuable insights in understanding the differences between mega- and meta-analyses in practice of combining small number of studies in identifying G × E interactions. © 2017 WILEY PERIODICALS, INC.

An in vivo model of functional and vascularized human brain organoids.

PubMed

Mansour, Abed AlFatah; Gonçalves, J Tiago; Bloyd, Cooper W; Li, Hao; Fernandes, Sarah; Quang, Daphne; Johnston, Stephen; Parylak, Sarah L; Jin, Xin; Gage, Fred H

2018-06-01

Differentiation of human pluripotent stem cells to small brain-like structures known as brain organoids offers an unprecedented opportunity to model human brain development and disease. To provide a vascularized and functional in vivo model of brain organoids, we established a method for transplanting human brain organoids into the adult mouse brain. Organoid grafts showed progressive neuronal differentiation and maturation, gliogenesis, integration of microglia, and growth of axons to multiple regions of the host brain. In vivo two-photon imaging demonstrated functional neuronal networks and blood vessels in the grafts. Finally, in vivo extracellular recording combined with optogenetics revealed intragraft neuronal activity and suggested graft-to-host functional synaptic connectivity. This combination of human neural organoids and an in vivo physiological environment in the animal brain may facilitate disease modeling under physiological conditions.

Integrated PK-PD and agent-based modeling in oncology.

PubMed

Wang, Zhihui; Butner, Joseph D; Cristini, Vittorio; Deisboeck, Thomas S

2015-04-01

Mathematical modeling has become a valuable tool that strives to complement conventional biomedical research modalities in order to predict experimental outcome, generate new medical hypotheses, and optimize clinical therapies. Two specific approaches, pharmacokinetic-pharmacodynamic (PK-PD) modeling, and agent-based modeling (ABM), have been widely applied in cancer research. While they have made important contributions on their own (e.g., PK-PD in examining chemotherapy drug efficacy and resistance, and ABM in describing and predicting tumor growth and metastasis), only a few groups have started to combine both approaches together in an effort to gain more insights into the details of drug dynamics and the resulting impact on tumor growth. In this review, we focus our discussion on some of the most recent modeling studies building on a combined PK-PD and ABM approach that have generated experimentally testable hypotheses. Some future directions are also discussed.

Integrated PK-PD and Agent-Based Modeling in Oncology

PubMed Central

Wang, Zhihui; Butner, Joseph D.; Cristini, Vittorio

2016-01-01

Mathematical modeling has become a valuable tool that strives to complement conventional biomedical research modalities in order to predict experimental outcome, generate new medical hypotheses, and optimize clinical therapies. Two specific approaches, pharmacokinetic-pharmacodynamic (PK-PD) modeling, and agent-based modeling (ABM), have been widely applied in cancer research. While they have made important contributions on their own (e.g., PK-PD in examining chemotherapy drug efficacy and resistance, and ABM in describing and predicting tumor growth and metastasis), only a few groups have started to combine both approaches together in an effort to gain more insights into the details of drug dynamics and the resulting impact on tumor growth. In this review, we focus our discussion on some of the most recent modeling studies building on a combined PK-PD and ABM approach that have generated experimentally testable hypotheses. Some future directions are also discussed. PMID:25588379

Aeroelastic stability analyses of two counter rotating propfan designs for a cruise missile model

NASA Technical Reports Server (NTRS)

Mahajan, Aparajit J.; Lucero, John M.; Mehmed, Oral; Stefko, George L.

1992-01-01

A modal aeroelastic analysis combining structural and aerodynamic models is applied to counterrotating propfans to evaluate their structural integrity for wind-tunnel testing. The aeroelastic analysis code is an extension of the 2D analysis code called the Aeroelastic Stability and Response of Propulsion Systems. Rotational speed and freestream Mach number are the parameters for calculating the stability of the two blade designs with a modal method combining a finite-element structural model with 2D steady and unsteady cascade aerodynamic models. The model demonstrates convergence to the least stable aeroelastic mode, describes the effects of a nonuniform inflow, and permits the modification of geometry and rotation. The analysis shows that the propfan designs are suitable for the wind-tunnel test and confirms that the propfans should be flutter-free under the range of conditions of the testing.

Unified constitutive material models for nonlinear finite-element structural analysis. [gas turbine engine blades and vanes

NASA Technical Reports Server (NTRS)

Kaufman, A.; Laflen, J. H.; Lindholm, U. S.

1985-01-01

Unified constitutive material models were developed for structural analyses of aircraft gas turbine engine components with particular application to isotropic materials used for high-pressure stage turbine blades and vanes. Forms or combinations of models independently proposed by Bodner and Walker were considered. These theories combine time-dependent and time-independent aspects of inelasticity into a continuous spectrum of behavior. This is in sharp contrast to previous classical approaches that partition inelastic strain into uncoupled plastic and creep components. Predicted stress-strain responses from these models were evaluated against monotonic and cyclic test results for uniaxial specimens of two cast nickel-base alloys, B1900+Hf and Rene' 80. Previously obtained tension-torsion test results for Hastelloy X alloy were used to evaluate multiaxial stress-strain cycle predictions. The unified models, as well as appropriate algorithms for integrating the constitutive equations, were implemented in finite-element computer codes.

An Integrated Environment for Efficient Formal Design and Verification

NASA Technical Reports Server (NTRS)

1998-01-01

The general goal of this project was to improve the practicality of formal methods by combining techniques from model checking and theorem proving. At the time the project was proposed, the model checking and theorem proving communities were applying different tools to similar problems, but there was not much cross-fertilization. This project involved a group from SRI that had substantial experience in the development and application of theorem-proving technology, and a group at Stanford that specialized in model checking techniques. Now, over five years after the proposal was submitted, there are many research groups working on combining theorem-proving and model checking techniques, and much more communication between the model checking and theorem proving research communities. This project contributed significantly to this research trend. The research work under this project covered a variety of topics: new theory and algorithms; prototype tools; verification methodology; and applications to problems in particular domains.

Revealing the Effects of the Herbal Pair of Euphorbia kansui and Glycyrrhiza on Hepatocellular Carcinoma Ascites with Integrating Network Target Analysis and Experimental Validation

PubMed Central

Zhang, Yanqiong; Lin, Ya; Zhao, Haiyu; Guo, Qiuyan; Yan, Chen; Lin, Na

2016-01-01

Although the herbal pair of Euphorbia kansui (GS) and Glycyrrhiza (GC) is one of the so-called "eighteen antagonistic medicaments" in Chinese medicinal literature, it is prescribed in a classic Traditional Chinese Medicine (TCM) formula Gansui-Banxia-Tang for cancerous ascites, suggesting that GS and GC may exhibit synergistic or antagonistic effects in different combination designs. Here, we modeled the effects of GS/GC combination with a target interaction network and clarified the associations between the network topologies involving the drug targets and the drug combination effects. Moreover, the "edge-betweenness" values, which is defined as the frequency with which edges are placed on the shortest paths between all pairs of modules in network, were calculated, and the ADRB1-PIK3CG interaction exhibited the greatest edge-betweenness value, suggesting its crucial role in connecting the other edges in the network. Because ADRB1 and PIK3CG were putative targets of GS and GC, respectively, and both had functional interactions with AVPR2 approved as known therapeutic target for ascites, we proposed that the ADRB1-PIK3CG-AVPR2 signal axis might be involved in the effects of the GS-GC combination on ascites. This proposal was further experimentally validated in a H22 hepatocellular carcinoma (HCC) ascites model. Collectively, this systems-level investigation integrated drug target prediction and network analysis to reveal the combination principles of the herbal pair of GS and GC. Experimental validation in an in vivo system provided convincing evidence that different combination designs of GS and GC might result in synergistic or antagonistic effects on HCC ascites that might be partially related to their regulation of the ADRB1-PIK3CG-AVPR2 signal axis. PMID:27143956

Application of MAGSAT to Lithospheric Modeling in South America. Part 2: Synthesis of Geologic and Seismic Data for Development of Integrated Crustal Models

NASA Technical Reports Server (NTRS)

Keller, G. R.; Lidiak, E. G.; Hinze, W. J.; Braile, L. W.; Vonfrese, R. R. B. (Principal Investigator)

1984-01-01

Research activities performed on MAGSAT scalar data over South America, Central America, and the adjacent marine areas are summarized. The geologic utility of magnetic anomalies detected by satellite is demonstrated by focusing on the spherical-Earth interpretation of scalar MAGSAT data in combination with ancillary geological and geophysical data to obtain lithospheric models for these regions related to their contemporary crustal dynamics processes, geologic history, current volcanism seismicity and natural resources.

Mathematical Modeling Approaches in Plant Metabolomics.

PubMed

Fürtauer, Lisa; Weiszmann, Jakob; Weckwerth, Wolfram; Nägele, Thomas

2018-01-01

The experimental analysis of a plant metabolome typically results in a comprehensive and multidimensional data set. To interpret metabolomics data in the context of biochemical regulation and environmental fluctuation, various approaches of mathematical modeling have been developed and have proven useful. In this chapter, a general introduction to mathematical modeling is presented and discussed in context of plant metabolism. A particular focus is laid on the suitability of mathematical approaches to functionally integrate plant metabolomics data in a metabolic network and combine it with other biochemical or physiological parameters.

Modeling energy/economy interactions for conservation and renewable energy-policy analysis

NASA Astrophysics Data System (ADS)

Groncki, P. J.

Energy policy and the implications for policy analysis and the methodological tools are discussed. The evolution of one methodological approach and the combined modeling system of the component models, their evolution in response to changing analytic needs, and the development of the integrated framework are reported. The analyses performed over the past several years are summarized. The current philosophy behind energy policy is discussed and compared to recent history. Implications for current policy analysis and methodological approaches are drawn.

Robust Combining of Disparate Classifiers Through Order Statistics

NASA Technical Reports Server (NTRS)

Tumer, Kagan; Ghosh, Joydeep

2001-01-01

Integrating the outputs of multiple classifiers via combiners or meta-learners has led to substantial improvements in several difficult pattern recognition problems. In this article we investigate a family of combiners based on order statistics, for robust handling of situations where there are large discrepancies in performance of individual classifiers. Based on a mathematical modeling of how the decision boundaries are affected by order statistic combiners, we derive expressions for the reductions in error expected when simple output combination methods based on the the median, the maximum and in general, the ith order statistic, are used. Furthermore, we analyze the trim and spread combiners, both based on linear combinations of the ordered classifier outputs, and show that in the presence of uneven classifier performance, they often provide substantial gains over both linear and simple order statistics combiners. Experimental results on both real world data and standard public domain data sets corroborate these findings.

Combining 3d Volume and Mesh Models for Representing Complicated Heritage Buildings

NASA Astrophysics Data System (ADS)

Tsai, F.; Chang, H.; Lin, Y.-W.

2017-08-01

This study developed a simple but effective strategy to combine 3D volume and mesh models for representing complicated heritage buildings and structures. The idea is to seamlessly integrate 3D parametric or polyhedral models and mesh-based digital surfaces to generate a hybrid 3D model that can take advantages of both modeling methods. The proposed hybrid model generation framework is separated into three phases. Firstly, after acquiring or generating 3D point clouds of the target, these 3D points are partitioned into different groups. Secondly, a parametric or polyhedral model of each group is generated based on plane and surface fitting algorithms to represent the basic structure of that region. A "bare-bones" model of the target can subsequently be constructed by connecting all 3D volume element models. In the third phase, the constructed bare-bones model is used as a mask to remove points enclosed by the bare-bones model from the original point clouds. The remaining points are then connected to form 3D surface mesh patches. The boundary points of each surface patch are identified and these boundary points are projected onto the surfaces of the bare-bones model. Finally, new meshes are created to connect the projected points and original mesh boundaries to integrate the mesh surfaces with the 3D volume model. The proposed method was applied to an open-source point cloud data set and point clouds of a local historical structure. Preliminary results indicated that the reconstructed hybrid models using the proposed method can retain both fundamental 3D volume characteristics and accurate geometric appearance with fine details. The reconstructed hybrid models can also be used to represent targets in different levels of detail according to user and system requirements in different applications.

Quantitative Structure-Activity Relationship Modeling Coupled with Molecular Docking Analysis in Screening of Angiotensin I-Converting Enzyme Inhibitory Peptides from Qula Casein Hydrolysates Obtained by Two-Enzyme Combination Hydrolysis.

PubMed

Lin, Kai; Zhang, Lanwei; Han, Xue; Meng, Zhaoxu; Zhang, Jianming; Wu, Yifan; Cheng, Dayou

2018-03-28

In this study, Qula casein derived from yak milk casein was hydrolyzed using a two-enzyme combination approach, and high angiotensin I-converting enzyme (ACE) inhibitory activity peptides were screened by quantitative structure-activity relationship (QSAR) modeling integrated with molecular docking analysis. Hydrolysates (<3 kDa) derived from combinations of thermolysin + alcalase and thermolysin + proteinase K demonstrated high ACE inhibitory activities. Peptide sequences in hydrolysates derived from these two combinations were identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). On the basis of the QSAR modeling prediction, a total of 16 peptides were selected for molecular docking analysis. The docking study revealed that four of the peptides (KFPQY, MPFPKYP, MFPPQ, and QWQVL) bound the active site of ACE. These four novel peptides were chemically synthesized, and their IC 50 was determined. Among these peptides, KFPQY showed the highest ACE inhibitory activity (IC 50 = 12.37 ± 0.43 μM). Our study indicated that Qula casein presents an excellent source to produce ACE inhibitory peptides.

Evaluation of patritumab with or without erlotinib in combination with standard cytotoxic agents against pediatric sarcoma xenograft models.

PubMed

Bandyopadhyay, Abhik; Favours, Edward; Phelps, Doris A; Pozo, Vanessa Del; Ghilu, Samson; Kurmashev, Dias; Michalek, Joel; Trevino, Aron; Guttridge, Denis; London, Cheryl; Hirotani, Kenji; Zhang, Ling; Kurmasheva, Raushan T; Houghton, Peter J

2018-02-01

Integrating molecularly targeted agents with cytotoxic drugs used in curative treatment of pediatric cancers is complex. An evaluation was undertaken with the ERBB3/Her3-specific antibody patritumab (P) either alone or with the ERBB1/epidermal growth factor receptor inhibitor erlotinib (E) in combination with standard cytotoxic agents, cisplatin, vincristine, and cyclophosphamide, in pediatric sarcoma xenograft models that express receptors and ligands targeted by these agents. Tumor models were selected based upon ERBB3 expression and phosphorylation, and ligand (heregulin) expression. Patritumab, E, or these agents combined was evaluated without or with concomitant cytotoxic agents using procedures developed by the Pediatric Preclinical Testing Program. Full doses of cytotoxic agents were tolerated when combined with P, whereas dose reductions of 25% (vincristine, cisplatin) or 50% (cyclophosphamide) were required when combined with P + E. Patritumab, E alone, or in combination did not significantly inhibit growth of any tumor model, except for Rh18 xenografts (E alone). Patritumab had no single-agent activity and marginally enhanced the activity of vincristine and cisplatin only in Ewing sarcoma ES-4. P + E did not increase the antitumor activity of vincristine or cisplatin, whereas dose-reduced cyclophosphamide was significantly less active than cyclophosphamide administered at its maximum tolerated dose when combined with P + E. P had no single-agent activity, although it marginally potentiated the activity of vincristine and cisplatin in one of three models studied. However, the addition of E necessitated dose reduction of each cytotoxic agent, abrogating the enhancement observed with P alone. © 2017 Wiley Periodicals, Inc.

An Active Broad Area Cooling Model of a Cryogenic Propellant Tank with a Single Stage Reverse Turbo-Brayton Cycle Cryocooler

NASA Technical Reports Server (NTRS)

Guzik, Monica C.; Tomsik, Thomas M.

2011-01-01

As focus shifts towards long-duration space exploration missions, an increased interest in active thermal control of cryogenic propellants to achieve zero boil-off of cryogens has emerged. An active thermal control concept of considerable merit is the integration of a broad area cooling system for a cryogenic propellant tank with a combined cryocooler and circulator system that can be used to reduce or even eliminate liquid cryogen boil-off. One prospective cryocooler and circulator combination is the reverse turbo-Brayton cycle cryocooler. This system is unique in that it has the ability to both cool and circulate the coolant gas efficiently in the same loop as the broad area cooling lines, allowing for a single cooling gas loop, with the primary heat rejection occurring by way of a radiator and/or aftercooler. Currently few modeling tools exist that can size and characterize an integrated reverse turbo-Brayton cycle cryocooler in combination with a broad area cooling design. This paper addresses efforts to create such a tool to assist in gaining a broader understanding of these systems, and investigate their performance in potential space missions. The model uses conventional engineering and thermodynamic relationships to predict the preliminary design parameters, including input power requirements, pressure drops, flow rate, cycle performance, cooling lift, broad area cooler line sizing, and component operating temperatures and pressures given the cooling load operating temperature, heat rejection temperature, compressor inlet pressure, compressor rotational speed, and cryogenic tank geometry. In addition, the model allows for the preliminary design analysis of the broad area cooling tubing, to determine the effect of tube sizing on the reverse turbo-Brayton cycle system performance. At the time this paper was written, the model was verified to match existing theoretical documentation within a reasonable margin. While further experimental data is needed for full validation, this tool has already made significant steps towards giving a clearer understanding of the performance of a reverse turbo-Brayton cycle cryocooler integrated with broad area cooling technology for zero boil-off active thermal control.

Metamodeling and the Critic-based approach to multi-level optimization.

PubMed

Werbos, Ludmilla; Kozma, Robert; Silva-Lugo, Rodrigo; Pazienza, Giovanni E; Werbos, Paul J

2012-08-01

Large-scale networks with hundreds of thousands of variables and constraints are becoming more and more common in logistics, communications, and distribution domains. Traditionally, the utility functions defined on such networks are optimized using some variation of Linear Programming, such as Mixed Integer Programming (MIP). Despite enormous progress both in hardware (multiprocessor systems and specialized processors) and software (Gurobi) we are reaching the limits of what these tools can handle in real time. Modern logistic problems, for example, call for expanding the problem both vertically (from one day up to several days) and horizontally (combining separate solution stages into an integrated model). The complexity of such integrated models calls for alternative methods of solution, such as Approximate Dynamic Programming (ADP), which provide a further increase in the performance necessary for the daily operation. In this paper, we present the theoretical basis and related experiments for solving the multistage decision problems based on the results obtained for shorter periods, as building blocks for the models and the solution, via Critic-Model-Action cycles, where various types of neural networks are combined with traditional MIP models in a unified optimization system. In this system architecture, fast and simple feed-forward networks are trained to reasonably initialize more complicated recurrent networks, which serve as approximators of the value function (Critic). The combination of interrelated neural networks and optimization modules allows for multiple queries for the same system, providing flexibility and optimizing performance for large-scale real-life problems. A MATLAB implementation of our solution procedure for a realistic set of data and constraints shows promising results, compared to the iterative MIP approach. Copyright © 2012 Elsevier Ltd. All rights reserved.

Combining operational models and data into a dynamic vessel risk assessment tool for coastal regions

NASA Astrophysics Data System (ADS)

Fernandes, R.; Braunschweig, F.; Lourenço, F.; Neves, R.

2015-07-01

The technological evolution in terms of computational capacity, data acquisition systems, numerical modelling and operational oceanography is supplying opportunities for designing and building holistic approaches and complex tools for newer and more efficient management (planning, prevention and response) of coastal water pollution risk events. A combined methodology to dynamically estimate time and space variable shoreline risk levels from ships has been developed, integrating numerical metocean forecasts and oil spill simulations with vessel tracking automatic identification systems (AIS). The risk rating combines the likelihood of an oil spill occurring from a vessel navigating in a study area - Portuguese Continental shelf - with the assessed consequences to the shoreline. The spill likelihood is based on dynamic marine weather conditions and statistical information from previous accidents. The shoreline consequences reflect the virtual spilled oil amount reaching shoreline and its environmental and socio-economic vulnerabilities. The oil reaching shoreline is quantified with an oil spill fate and behaviour model running multiple virtual spills from vessels along time. Shoreline risks can be computed in real-time or from previously obtained data. Results show the ability of the proposed methodology to estimate the risk properly sensitive to dynamic metocean conditions and to oil transport behaviour. The integration of meteo-oceanic + oil spill models with coastal vulnerability and AIS data in the quantification of risk enhances the maritime situational awareness and the decision support model, providing a more realistic approach in the assessment of shoreline impacts. The risk assessment from historical data can help finding typical risk patterns, "hot spots" or developing sensitivity analysis to specific conditions, whereas real time risk levels can be used in the prioritization of individual ships, geographical areas, strategic tug positioning and implementation of dynamic risk-based vessel traffic monitoring.

Geo-Semantic Framework for Integrating Long-Tail Data and Model Resources for Advancing Earth System Science

NASA Astrophysics Data System (ADS)

Elag, M.; Kumar, P.

2014-12-01

Often, scientists and small research groups collect data, which target to address issues and have limited geographic or temporal range. A large number of such collections together constitute a large database that is of immense value to Earth Science studies. Complexity of integrating these data include heterogeneity in dimensions, coordinate systems, scales, variables, providers, users and contexts. They have been defined as long-tail data. Similarly, we use "long-tail models" to characterize a heterogeneous collection of models and/or modules developed for targeted problems by individuals and small groups, which together provide a large valuable collection. Complexity of integrating across these models include differing variable names and units for the same concept, model runs at different time steps and spatial resolution, use of differing naming and reference conventions, etc. Ability to "integrate long-tail models and data" will provide an opportunity for the interoperability and reusability of communities' resources, where not only models can be combined in a workflow, but each model will be able to discover and (re)use data in application specific context of space, time and questions. This capability is essential to represent, understand, predict, and manage heterogeneous and interconnected processes and activities by harnessing the complex, heterogeneous, and extensive set of distributed resources. Because of the staggering production rate of long-tail models and data resulting from the advances in computational, sensing, and information technologies, an important challenge arises: how can geoinformatics bring together these resources seamlessly, given the inherent complexity among model and data resources that span across various domains. We will present a semantic-based framework to support integration of "long-tail" models and data. This builds on existing technologies including: (i) SEAD (Sustainable Environmental Actionable Data) which supports curation and preservation of long-tail data during its life-cycle; (ii) BrownDog, which enhances the machine interpretability of large unstructured and uncurated data; and (iii) CSDMS (Community Surface Dynamics Modeling System), which "componentizes" models by providing plug-and-play environment for models integration.

Divergent modes of integration: the Canadian way.

PubMed

Jiwani, Izzat; Fleury, Marie-Josée

2011-01-01

The paper highlights key trajectories and outcomes of the recent policy developments toward integrated health care delivery systems in Quebec and Ontario in the primary care sector and in the development of regional networks of health and social services. It particularly explores how policy legacies, interests and cultures may be mitigated to develop and sustain different models of integrated health care that are pertinent to the local contexts. In Quebec, three decades of iterative developments in health and social services evolved in 2005 into integrated centres for health and social services at the local levels (CSSSs). Four integrated university-based health care networks provide ultra-specialised services. Family Medicine Groups and network clinics are designed to enhance access and continuity of care. Ontario's Family Health Teams (2004) constitute an innovative public funding for private delivery model that is set up to enhance the capacity of primary care and to facilitate patient-based care. Ontario's Local Health Integration Networks (LHINs) with autonomous boards of provider organisations are intended to coordinate and integrate care. Integration strategies in Quebec and Ontario yield clinical autonomy and power to physicians while simultaneously making them key partners in change. Contextual factors combined with increased and varied forms of physician remunerations and incentives mitigated some of the challenges from policy legacies, interests and cultures. Virtual partnerships and accountability agreements between providers promise positive but gradual movement toward integrated health service systems.

Combining fungal biopesticides and insecticide-treated bednets to enhance malaria control.

PubMed

Hancock, Penelope A

2009-10-01

In developing strategies to control malaria vectors, there is increased interest in biological methods that do not cause instant vector mortality, but have sublethal and lethal effects at different ages and stages in the mosquito life cycle. These techniques, particularly if integrated with other vector control interventions, may produce substantial reductions in malaria transmission due to the total effect of alterations to multiple life history parameters at relevant points in the life-cycle and transmission-cycle of the vector. To quantify this effect, an analytically tractable gonotrophic cycle model of mosquito-malaria interactions is developed that unites existing continuous and discrete feeding cycle approaches. As a case study, the combined use of fungal biopesticides and insecticide treated bednets (ITNs) is considered. Low values of the equilibrium EIR and human prevalence were obtained when fungal biopesticides and ITNs were combined, even for scenarios where each intervention acting alone had relatively little impact. The effect of the combined interventions on the equilibrium EIR was at least as strong as the multiplicative effect of both interventions. For scenarios representing difficult conditions for malaria control, due to high transmission intensity and widespread insecticide resistance, the effect of the combined interventions on the equilibrium EIR was greater than the multiplicative effect, as a result of synergistic interactions between the interventions. Fungal biopesticide application was found to be most effective when ITN coverage was high, producing significant reductions in equilibrium prevalence for low levels of biopesticide coverage. By incorporating biological mechanisms relevant to vectorial capacity, continuous-time vector population models can increase their applicability to integrated vector management.

Spatial reference frames of visual, vestibular, and multimodal heading signals in the dorsal subdivision of the medial superior temporal area.

PubMed

Fetsch, Christopher R; Wang, Sentao; Gu, Yong; Deangelis, Gregory C; Angelaki, Dora E

2007-01-17

Heading perception is a complex task that generally requires the integration of visual and vestibular cues. This sensory integration is complicated by the fact that these two modalities encode motion in distinct spatial reference frames (visual, eye-centered; vestibular, head-centered). Visual and vestibular heading signals converge in the primate dorsal subdivision of the medial superior temporal area (MSTd), a region thought to contribute to heading perception, but the reference frames of these signals remain unknown. We measured the heading tuning of MSTd neurons by presenting optic flow (visual condition), inertial motion (vestibular condition), or a congruent combination of both cues (combined condition). Static eye position was varied from trial to trial to determine the reference frame of tuning (eye-centered, head-centered, or intermediate). We found that tuning for optic flow was predominantly eye-centered, whereas tuning for inertial motion was intermediate but closer to head-centered. Reference frames in the two unimodal conditions were rarely matched in single neurons and uncorrelated across the population. Notably, reference frames in the combined condition varied as a function of the relative strength and spatial congruency of visual and vestibular tuning. This represents the first investigation of spatial reference frames in a naturalistic, multimodal condition in which cues may be integrated to improve perceptual performance. Our results compare favorably with the predictions of a recent neural network model that uses a recurrent architecture to perform optimal cue integration, suggesting that the brain could use a similar computational strategy to integrate sensory signals expressed in distinct frames of reference.

Damage modeling and statistical analysis of optics damage performance in MJ-class laser systems.

PubMed

Liao, Zhi M; Raymond, B; Gaylord, J; Fallejo, R; Bude, J; Wegner, P

2014-11-17

Modeling the lifetime of a fused silica optic is described for a multiple beam, MJ-class laser system. This entails combining optic processing data along with laser shot data to account for complete history of optic processing and shot exposure. Integrating with online inspection data allows for the construction of a performance metric to describe how an optic performs with respect to the model. This methodology helps to validate the damage model as well as allows strategic planning and identifying potential hidden parameters that are affecting the optic's performance.

A SINS/SRS/GNS Autonomous Integrated Navigation System Based on Spectral Redshift Velocity Measurements

PubMed Central

Wei, Wenhui; Gao, Zhaohui; Gao, Shesheng; Jia, Ke

2018-01-01

In order to meet the requirements of autonomy and reliability for the navigation system, combined with the method of measuring speed by using the spectral redshift information of the natural celestial bodies, a new scheme, consisting of Strapdown Inertial Navigation System (SINS)/Spectral Redshift (SRS)/Geomagnetic Navigation System (GNS), is designed for autonomous integrated navigation systems. The principle of this SINS/SRS/GNS autonomous integrated navigation system is explored, and the corresponding mathematical model is established. Furthermore, a robust adaptive central difference particle filtering algorithm is proposed for this autonomous integrated navigation system. The simulation experiments are conducted and the results show that the designed SINS/SRS/GNS autonomous integrated navigation system possesses good autonomy, strong robustness and high reliability, thus providing a new solution for autonomous navigation technology. PMID:29642549

Understanding the effect of carbon status on stem diameter variations

PubMed Central

De Swaef, Tom; Driever, Steven M.; Van Meulebroek, Lieven; Vanhaecke, Lynn; Marcelis, Leo F. M.; Steppe, Kathy

2013-01-01

Background Carbon assimilation and leaf-to-fruit sugar transport are, along with plant water status, the driving mechanisms for fruit growth. An integrated comprehension of the plant water and carbon relationships is therefore essential to better understand water and dry matter accumulation. Variations in stem diameter result from an integrated response to plant water and carbon status and are as such a valuable source of information. Methods A mechanistic water flow and storage model was used to relate variations in stem diameter to phloem sugar loading and sugar concentration dynamics in tomato. The simulation results were compared with an independent model, simulating phloem sucrose loading at the leaf level based on photosynthesis and sugar metabolism kinetics and enabled a mechanistic interpretation of the ‘one common assimilate pool’ concept for tomato. Key Results Combining stem diameter variation measurements and mechanistic modelling allowed us to distinguish instantaneous dynamics in the plant water relations and gradual variations in plant carbon status. Additionally, the model combined with stem diameter measurements enabled prediction of dynamic variables which are difficult to measure in a continuous and non-destructive way, such as xylem water potential and phloem hydrostatic potential. Finally, dynamics in phloem sugar loading and sugar concentration were distilled from stem diameter variations. Conclusions Stem diameter variations, when used in mechanistic models, have great potential to continuously monitor and interpret plant water and carbon relations under natural growing conditions. PMID:23186836