Estimating parameter values of a socio-hydrological flood model

NASA Astrophysics Data System (ADS)

Holkje Barendrecht, Marlies; Viglione, Alberto; Kreibich, Heidi; Vorogushyn, Sergiy; Merz, Bruno; Blöschl, Günter

2018-06-01

Socio-hydrological modelling studies that have been published so far show that dynamic coupled human-flood models are a promising tool to represent the phenomena and the feedbacks in human-flood systems. So far these models are mostly generic and have not been developed and calibrated to represent specific case studies. We believe that applying and calibrating these type of models to real world case studies can help us to further develop our understanding about the phenomena that occur in these systems. In this paper we propose a method to estimate the parameter values of a socio-hydrological model and we test it by applying it to an artificial case study. We postulate a model that describes the feedbacks between floods, awareness and preparedness. After simulating hypothetical time series with a given combination of parameters, we sample few data points for our variables and try to estimate the parameters given these data points using Bayesian Inference. The results show that, if we are able to collect data for our case study, we would, in theory, be able to estimate the parameter values for our socio-hydrological flood model.

Case management: a randomized controlled study comparing a neighborhood team and a centralized individual model.

PubMed

Eggert, G M; Zimmer, J G; Hall, W J; Friedman, B

1991-10-01

This randomized controlled study compared two types of case management for skilled nursing level patients living at home: the centralized individual model and the neighborhood team model. The team model differed from the individual model in that team case managers performed client assessments, care planning, some direct services, and reassessments; they also had much smaller caseloads and were assigned a specific catchment area. While patients in both groups incurred very high estimated health services costs, the average annual cost during 1983-85 for team cases was 13.6 percent less than that of individual model cases. While the team cases were 18.3 percent less expensive among "old" patients (patients who entered the study from the existing ACCESS caseload), they were only 2.7 percent less costly among "new" cases. The lower costs were due to reductions in hospital days and home care. Team cases averaged 26 percent fewer hospital days per year and 17 percent fewer home health aide hours. Nursing home use was 48 percent higher for the team group than for the individual model group. Mortality was almost exactly the same for both groups during the first year (about 30 percent), but was lower for team patients during the second year (11 percent as compared to 16 percent). Probable mechanisms for the observed results are discussed.

Case Studies' Effect on Undergraduates' Achievement, Attitudes, and Team Shared Mental Models in Educational Psychology

ERIC Educational Resources Information Center

Razzouk, Rim; Johnson, Tristan E.

2013-01-01

The purpose of this study was to examine the effect of case studies on learning outcomes, attitudes toward instructions, and team shared mental models (SMM) in a team-based learning environment in an undergraduate educational psychology course. Approximately 105 students who participated in this study were randomly assigned to either a case-study…

Conceptualizing race in economic models of medical utilization: a case study of community-based elders and the emergency room.

PubMed Central

White-Means, S I

1995-01-01

There is no consensus on the appropriate conceptualization of race in economic models of health care. This is because race is rarely the primary focus for analysis of the market. This article presents an alternative framework for conceptualizing race in health economic models. A case study is analyzed to illustrate the value of the alternative conceptualization. The case study findings clearly document the importance of model stratification according to race. Moreover, the findings indicate that empirical results are improved when medical utilization models are refined in a way that reflects the unique experiences of the population that is studied. PMID:7721593

Case Study Teaching

ERIC Educational Resources Information Center

Herreid, Clyde Freeman

2011-01-01

This chapter describes the history of case study teaching, types of cases, and experimental data supporting their effectiveness. It also describes a model for comparing the efficacy of the various case study methods. (Contains 1 figure.)

Model-based methods for case definitions from administrative health data: application to rheumatoid arthritis

PubMed Central

Kroeker, Kristine; Widdifield, Jessica; Muthukumarana, Saman; Jiang, Depeng; Lix, Lisa M

2017-01-01

Objective This research proposes a model-based method to facilitate the selection of disease case definitions from validation studies for administrative health data. The method is demonstrated for a rheumatoid arthritis (RA) validation study. Study design and setting Data were from 148 definitions to ascertain cases of RA in hospital, physician and prescription medication administrative data. We considered: (A) separate univariate models for sensitivity and specificity, (B) univariate model for Youden’s summary index and (C) bivariate (ie, joint) mixed-effects model for sensitivity and specificity. Model covariates included the number of diagnoses in physician, hospital and emergency department records, physician diagnosis observation time, duration of time between physician diagnoses and number of RA-related prescription medication records. Results The most common case definition attributes were: 1+ hospital diagnosis (65%), 2+ physician diagnoses (43%), 1+ specialist physician diagnosis (51%) and 2+ years of physician diagnosis observation time (27%). Statistically significant improvements in sensitivity and/or specificity for separate univariate models were associated with (all p values <0.01): 2+ and 3+ physician diagnoses, unlimited physician diagnosis observation time, 1+ specialist physician diagnosis and 1+ RA-related prescription medication records (65+ years only). The bivariate model produced similar results. Youden’s index was associated with these same case definition criteria, except for the length of the physician diagnosis observation time. Conclusion A model-based method provides valuable empirical evidence to aid in selecting a definition(s) for ascertaining diagnosed disease cases from administrative health data. The choice between univariate and bivariate models depends on the goals of the validation study and number of case definitions. PMID:28645978

Modeling zero-modified count and semicontinuous data in health services research part 2: case studies.

PubMed

Neelon, Brian; O'Malley, A James; Smith, Valerie A

2016-11-30

This article is the second installment of a two-part tutorial on the analysis of zero-modified count and semicontinuous data. Part 1, which appears as a companion piece in this issue of Statistics in Medicine, provides a general background and overview of the topic, with particular emphasis on applications to health services research. Here, we present three case studies highlighting various approaches for the analysis of zero-modified data. The first case study describes methods for analyzing zero-inflated longitudinal count data. Case study 2 considers the use of hurdle models for the analysis of spatiotemporal count data. The third case study discusses an application of marginalized two-part models to the analysis of semicontinuous health expenditure data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Errors in Representing Regional Acid Deposition with Spatially Sparse Monitoring: Case Studies of the Eastern US Using Model Predictions

EPA Science Inventory

The current study uses case studies of model-estimated regional precipitation and wet ion deposition to estimate errors in corresponding regional values derived from the means of site-specific values within regions of interest located in the eastern US. The mean of model-estimate...

Additive Partial Least Squares for efficient modelling of independent variance sources demonstrated on practical case studies.

PubMed

Luoma, Pekka; Natschläger, Thomas; Malli, Birgit; Pawliczek, Marcin; Brandstetter, Markus

2018-05-12

A model recalibration method based on additive Partial Least Squares (PLS) regression is generalized for multi-adjustment scenarios of independent variance sources (referred to as additive PLS - aPLS). aPLS allows for effortless model readjustment under changing measurement conditions and the combination of independent variance sources with the initial model by means of additive modelling. We demonstrate these distinguishing features on two NIR spectroscopic case-studies. In case study 1 aPLS was used as a readjustment method for an emerging offset. The achieved RMS error of prediction (1.91 a.u.) was of similar level as before the offset occurred (2.11 a.u.). In case-study 2 a calibration combining different variance sources was conducted. The achieved performance was of sufficient level with an absolute error being better than 0.8% of the mean concentration, therefore being able to compensate negative effects of two independent variance sources. The presented results show the applicability of the aPLS approach. The main advantages of the method are that the original model stays unadjusted and that the modelling is conducted on concrete changes in the spectra thus supporting efficient (in most cases straightforward) modelling. Additionally, the method is put into context of existing machine learning algorithms. Copyright © 2018 Elsevier B.V. All rights reserved.

Experiences Using Formal Methods for Requirements Modeling

NASA Technical Reports Server (NTRS)

Easterbrook, Steve; Lutz, Robyn; Covington, Rick; Kelly, John; Ampo, Yoko; Hamilton, David

1996-01-01

This paper describes three cases studies in the lightweight application of formal methods to requirements modeling for spacecraft fault protection systems. The case studies differ from previously reported applications of formal methods in that formal methods were applied very early in the requirements engineering process, to validate the evolving requirements. The results were fed back into the projects, to improve the informal specifications. For each case study, we describe what methods were applied, how they were applied, how much effort was involved, and what the findings were. In all three cases, the formal modeling provided a cost effective enhancement of the existing verification and validation processes. We conclude that the benefits gained from early modeling of unstable requirements more than outweigh the effort needed to maintain multiple representations.

A Collective Case Study of Secondary Students' Model-Based Inquiry on Natural Selection through Programming in an Agent-Based Modeling Environment

ERIC Educational Resources Information Center

Xiang, Lin

2011-01-01

This is a collective case study seeking to develop detailed descriptions of how programming an agent-based simulation influences a group of 8th grade students' model-based inquiry (MBI) by examining students' agent-based programmable modeling (ABPM) processes and the learning outcomes. The context of the present study was a biology unit on…

[Comparing case management care models for people with dementia and their caregivers: the design of the COMPAS study].

PubMed

van Hout, H P J; Macneil Vroomen, J L; Van Mierlo, L D; Meiland, F J M; Moll van Charante, E P; Joling, K J; van den Dungen, P; Dröes, R M; van der Horst, H E; de Rooij, S E J A

2014-04-01

Dementia care in The Netherlands is shifting from fragmented, ad hoc care to more coordinated and personalized care. Case management contributes to this shift. The linkage model and a combination of intensive case management and joint agency care models were selected based on their emerging prominence in The Netherlands. It is unclear if these different forms of case management are more effective than usual care in improving or preserving the functioning and well-being at the patient and caregiver level and at the societal cost. The objective of this article is to describe the design of a study comparing these two case management care models against usual care. Clinical and cost outcomes are investigated while care processes and the facilitators and barriers for implementation of these models are considered. Mixed methods include a prospective, observational, controlled, cohort study among persons with dementia and their primary informal caregiver in regions of The Netherlands with and without case management including a qualitative process evaluation. Community-dwelling individuals with a dementia diagnosis with an informal caregiver are included. The primary outcome measure is the Neuropsychiatric Inventory for the people with dementia and the General Health Questionnaire for their caregivers. Costs are measured from a societal perspective. Semi-structured interviews with stakeholders based on the theoretical model of adaptive implementation are planned. 521 pairs of persons with dementia and their primary informal caregiver were included and are followed over two years. In the linked model substantially more impeding factors for implementation were identified compared with the model. This article describes the design of an evaluation study of two case management models along with clinical and economic data from persons with dementia and caregivers. The impeding and facilitating factors differed substantially between the two models. Further results on cost-effectiveness are expected by the beginning of 2015. This is a Dutch adaptation of MacNeil Vroomen et al., Comparing Dutch case management care models for people with dementia and their caregivers: The design of the COMPAS study.

LAVA Simulations for the 3rd AIAA CFD High Lift Prediction Workshop with Body Fitted Grids

NASA Technical Reports Server (NTRS)

Jensen, James C.; Stich, Gerrit-Daniel; Housman, Jeffrey A.; Denison, Marie; Kiris, Cetin C.

2018-01-01

In response to the 3rd AIAA CFD High Lift Prediction Workshop, the workshop cases were analyzed using Reynolds-averaged Navier-Stokes flow solvers within the Launch Ascent and Vehicle Aerodynamics (LAVA) solver framework. For the workshop cases the advantages and limitations of both overset-structured an unstructured polyhedral meshes were assessed. The workshop included 3 cases: a 2D airfoil validation case, a mesh convergence study using the High Lift Common Research Model, and a nacelle/pylon integration study using the JAXA (Japan Aerospace Exploration Agency) Standard Model. The 2D airfoil case from the workshop is used to verify the implementation of the Spalart-Allmaras turbulence model along with some of its variants within the solver. The High Lift Common Research Model case is used to assess solver performance and accuracy at varying mesh resolutions, as well as identify the minimum mesh fidelity required for LAVA on this class of problem. The JAXA Standard Model case is used to assess the solver's sensitivity to the turbulence model and to compare the structured and unstructured mesh paradigms. These workshop cases have helped establish best practices for high lift flow configurations for the LAVA solver.

Case Studies Comparing System Advisor Model (SAM) Results to Real Performance Data: Preprint

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

Blair, N.; Dobos, A.; Sather, N.

2012-06-01

NREL has completed a series of detailed case studies comparing the simulations of the System Advisor Model (SAM) and measured performance data or published performance expectations. These case studies compare PV measured performance data with simulated performance data using appropriate weather data. The measured data sets were primarily taken from NREL onsite PV systems and weather monitoring stations.

A regularized variable selection procedure in additive hazards model with stratified case-cohort design.

PubMed

Ni, Ai; Cai, Jianwen

2018-07-01

Case-cohort designs are commonly used in large epidemiological studies to reduce the cost associated with covariate measurement. In many such studies the number of covariates is very large. An efficient variable selection method is needed for case-cohort studies where the covariates are only observed in a subset of the sample. Current literature on this topic has been focused on the proportional hazards model. However, in many studies the additive hazards model is preferred over the proportional hazards model either because the proportional hazards assumption is violated or the additive hazards model provides more relevent information to the research question. Motivated by one such study, the Atherosclerosis Risk in Communities (ARIC) study, we investigate the properties of a regularized variable selection procedure in stratified case-cohort design under an additive hazards model with a diverging number of parameters. We establish the consistency and asymptotic normality of the penalized estimator and prove its oracle property. Simulation studies are conducted to assess the finite sample performance of the proposed method with a modified cross-validation tuning parameter selection methods. We apply the variable selection procedure to the ARIC study to demonstrate its practical use.

Spatio-temporal Bayesian model selection for disease mapping

PubMed Central

Carroll, R; Lawson, AB; Faes, C; Kirby, RS; Aregay, M; Watjou, K

2016-01-01

Spatio-temporal analysis of small area health data often involves choosing a fixed set of predictors prior to the final model fit. In this paper, we propose a spatio-temporal approach of Bayesian model selection to implement model selection for certain areas of the study region as well as certain years in the study time line. Here, we examine the usefulness of this approach by way of a large-scale simulation study accompanied by a case study. Our results suggest that a special case of the model selection methods, a mixture model allowing a weight parameter to indicate if the appropriate linear predictor is spatial, spatio-temporal, or a mixture of the two, offers the best option to fitting these spatio-temporal models. In addition, the case study illustrates the effectiveness of this mixture model within the model selection setting by easily accommodating lifestyle, socio-economic, and physical environmental variables to select a predominantly spatio-temporal linear predictor. PMID:28070156

Geomagnetic field models for satellite angular motion studies

NASA Astrophysics Data System (ADS)

Ovchinnikov, M. Yu.; Penkov, V. I.; Roldugin, D. S.; Pichuzhkina, A. V.

2018-03-01

Four geomagnetic field models are discussed: IGRF, inclined, direct and simplified dipoles. Geomagnetic induction vector expressions are provided in different reference frames. Induction vector behavior is compared for different models. Models applicability for the analysis of satellite motion is studied from theoretical and engineering perspectives. Relevant satellite dynamics analysis cases using analytical and numerical techniques are provided. These cases demonstrate the benefit of a certain model for a specific dynamics study. Recommendations for models usage are summarized in the end.

Proof of Economic Viability of Blended Learning Business Models

ERIC Educational Resources Information Center

Druhmann, Carsten; Hohenberg, Gregor

2014-01-01

The discussion on economically sustainable business models with respect to information technology is lacking in many aspects of proven approaches. In the following contribution the economic viability is valued based on a procedural model for design and evaluation of e-learning business models in the form of a case study. As a case study object a…

The Use of an Autoregressive Integrated Moving Average Model for Prediction of the Incidence of Dysentery in Jiangsu, China.

PubMed

Wang, Kewei; Song, Wentao; Li, Jinping; Lu, Wu; Yu, Jiangang; Han, Xiaofeng

2016-05-01

The aim of this study is to forecast the incidence of bacillary dysentery with a prediction model. We collected the annual and monthly laboratory data of confirmed cases from January 2004 to December 2014. In this study, we applied an autoregressive integrated moving average (ARIMA) model to forecast bacillary dysentery incidence in Jiangsu, China. The ARIMA (1, 1, 1) × (1, 1, 2)12 model fitted exactly with the number of cases during January 2004 to December 2014. The fitted model was then used to predict bacillary dysentery incidence during the period January to August 2015, and the number of cases fell within the model's CI for the predicted number of cases during January-August 2015. This study shows that the ARIMA model fits the fluctuations in bacillary dysentery frequency, and it can be used for future forecasting when applied to bacillary dysentery prevention and control. © 2016 APJPH.

A case study on modeling and independent practice cycles in teaching beginning science inquiry

NASA Astrophysics Data System (ADS)

Sadeghpour-Kramer, Margaret Ann Plattenberger

With increasing pressure to produce high standardized test scores, school systems will be looking for the surest ways to increase scores. Decision makers uninformed about the value of inquiry science may recommend more direct teaching methods and curricula in the hope that students will more quickly accumulate factual information for high test scores. This researcher and other proponents of inquiry science suggest that the best preparation for any test is the ability to use all available information and problem solving skills to think through to a solution. This study proposes to test the theory that inquiry problem solving skills need to be modeled and practiced in increasingly independent situations to be learned. Students tend to copy what they have been led to believe is correct, and to avoid continued copying, their skills must be applied in new situations requiring independent practice and improvement. This study follows ten sixth grade students, selected for maximum variation, as they participate in a series of five cycles of modeling and practicing inquiry science investigations as part of an ongoing unit on water quality. The cycles were designed to make the students increasingly independent in their use of inquiry. The results showed that all ten students made significant progress from copying teacher modeling in investigation #1 towards independent inquiry, with nine of the ten achieving acceptable to good beginning independent inquiry in investigation #5. Each case was analyzed independently using such case study methodology as pattern matching, case study protocols, and theoretical propositions. Constant comparison and other case study methods were used in a cross-case analysis. Eight cases confirmed a matching set of propositions and the hypothesis, in literal replication, and the other two cases confirmed a set of propositions and the hypothesis through theoretical replication. The study suggests to educators that repeated cycles of modeling and increasingly independent practice serve three purposes; first to develop independent inquiry skills by providing multiple opportunities with intermittent modeling, second to repeat the modeling initially in very similar situations and then encourage transfer to new situations, and third to provide repeated modeling for those students who do not grasp the concepts as quickly as do their classmates.

Resilience in Utility Technologies

NASA Astrophysics Data System (ADS)

Seaton, Roger

The following sections are included: * Scope of paper * Preamble * Background to the case-study projects * Source projects * Resilience * Case study 1: Electricity generation * Context * Model * Case study 2: Water recycling * Context * Model * Case study 3: Ecotechnology and water treatment * Context * The problem of classification: Finding a classificatory solution * Application of the new taxonomy to water treatment * Concluding comments and questions * Conclusions * Questions and issues * Purposive or Purposeful? * Resilience: Flexibility and adaptivity? * Resilience: With respect of what? * Risk, uncertainty, surprise, emergence - What sort of shock, and who says so? * Co-evolutionary friction * References

Technology Modeling by Mathematics Professors in Required Courses for Secondary Mathematics Pre-Service Teachers: A Case Study in Two Universities

ERIC Educational Resources Information Center

Asing-Cashman, Joyce G.

2011-01-01

The purpose of this qualitative case study was to examine the modeling of technology by mathematics professors in two universities in teaching required courses for secondary level pre-service mathematics teachers. Six professors participated in this case study. Their responses were documented in pre- and post-interviews and data were gathered from…

Campus Stories: Three Case Studies. Part C: Putting Experiential Education into Practice--Using Kolb as a Learning Model for Implementing Organizational Change

ERIC Educational Resources Information Center

Johnson, James R.; Kovach, Ronald J.; Roberson, Patricia N.

2010-01-01

This article is the third of three case studies of successful implementation of experiential education at very different types of institutions. This case study discusses the use of David A. Kolb's Experiential Learning Model in the implementation of innovative graduation requirements in experiential education that began in 2008. Purdue University…

Comparative study: TQ and Lean Production ownership models in health services

PubMed Central

Eiro, Natalia Yuri; Torres-Junior, Alvair Silveira

2015-01-01

Objective: compare the application of Total Quality (TQ) models used in processes of a health service, cases of lean healthcare and literature from another institution that has also applied this model. Method: this is a qualitative research that was conducted through a descriptive case study. Results: through critical analysis of the institutions studied it was possible to make a comparison between the traditional quality approach checked in one case and the theoretical and practice lean production approach used in another case and the specifications are described below. Conclusion: the research identified that the lean model was better suited for people that work systemically and generate the flow. It also pointed towards some potential challenges in the introduction and implementation of lean methods in health. PMID:26487134

Case Study on the Effect of Word Repetition Method Supported by Neurological Affecting Model on Fluent Reading

ERIC Educational Resources Information Center

Duran, Erol

2013-01-01

This research is a case study which is a qualitative study model and named as example event as well. The purpose of this research is determining the effect of word repetitive reading method supported with neurological affecting model on fluent reading. In this study, False Analysis Inventory was used in order to determine the student's oral…

The effect of a loss of model structural detail due to network skeletonization on contamination warning system design: case studies.

PubMed

Davis, Michael J; Janke, Robert

2018-01-04

The effect of limitations in the structural detail available in a network model on contamination warning system (CWS) design was examined in case studies using the original and skeletonized network models for two water distribution systems (WDSs). The skeletonized models were used as proxies for incomplete network models. CWS designs were developed by optimizing sensor placements for worst-case and mean-case contamination events. Designs developed using the skeletonized network models were transplanted into the original network model for evaluation. CWS performance was defined as the number of people who ingest more than some quantity of a contaminant in tap water before the CWS detects the presence of contamination. Lack of structural detail in a network model can result in CWS designs that (1) provide considerably less protection against worst-case contamination events than that obtained when a more complete network model is available and (2) yield substantial underestimates of the consequences associated with a contamination event. Nevertheless, CWSs developed using skeletonized network models can provide useful reductions in consequences for contaminants whose effects are not localized near the injection location. Mean-case designs can yield worst-case performances similar to those for worst-case designs when there is uncertainty in the network model. Improvements in network models for WDSs have the potential to yield significant improvements in CWS designs as well as more realistic evaluations of those designs. Although such improvements would be expected to yield improved CWS performance, the expected improvements in CWS performance have not been quantified previously. The results presented here should be useful to those responsible for the design or implementation of CWSs, particularly managers and engineers in water utilities, and encourage the development of improved network models.

The effect of a loss of model structural detail due to network skeletonization on contamination warning system design: case studies

NASA Astrophysics Data System (ADS)

Davis, Michael J.; Janke, Robert

2018-05-01

The effect of limitations in the structural detail available in a network model on contamination warning system (CWS) design was examined in case studies using the original and skeletonized network models for two water distribution systems (WDSs). The skeletonized models were used as proxies for incomplete network models. CWS designs were developed by optimizing sensor placements for worst-case and mean-case contamination events. Designs developed using the skeletonized network models were transplanted into the original network model for evaluation. CWS performance was defined as the number of people who ingest more than some quantity of a contaminant in tap water before the CWS detects the presence of contamination. Lack of structural detail in a network model can result in CWS designs that (1) provide considerably less protection against worst-case contamination events than that obtained when a more complete network model is available and (2) yield substantial underestimates of the consequences associated with a contamination event. Nevertheless, CWSs developed using skeletonized network models can provide useful reductions in consequences for contaminants whose effects are not localized near the injection location. Mean-case designs can yield worst-case performances similar to those for worst-case designs when there is uncertainty in the network model. Improvements in network models for WDSs have the potential to yield significant improvements in CWS designs as well as more realistic evaluations of those designs. Although such improvements would be expected to yield improved CWS performance, the expected improvements in CWS performance have not been quantified previously. The results presented here should be useful to those responsible for the design or implementation of CWSs, particularly managers and engineers in water utilities, and encourage the development of improved network models.

From translational research to open technology innovation systems.

PubMed

Savory, Clive; Fortune, Joyce

2015-01-01

The purpose of this paper is to question whether the emphasis placed within translational research on a linear model of innovation provides the most effective model for managing health technology innovation. Several alternative perspectives are presented that have potential to enhance the existing model of translational research. A case study is presented of innovation of a clinical decision support system. The paper concludes from the case study that an extending the triple helix model of technology transfer, to one based on a quadruple helix, present a basis for improving the performance translational research. A case study approach is used to help understand development of an innovative technology within a teaching hospital. The case is then used to develop and refine a model of the health technology innovation system. The paper concludes from the case study that existing models of translational research could be refined further through the development of a quadruple helix model of heath technology innovation that encompasses greater emphasis on user-led and open innovation perspectives. The paper presents several implications for future research based on the need to enhance the model of health technology innovation used to guide policy and practice. The quadruple helix model of innovation that is proposed can potentially guide alterations to the existing model of translational research in the healthcare sector. Several suggestions are made for how innovation activity can be better supported at both a policy and operational level. This paper presents a synthesis of the innovation literature applied to a theoretically important case of open innovation in the UK National Health Service. It draws in perspectives from other industrial sectors and applies them specifically to the management and organisation of innovation activities around health technology and the services in which they are embedded.

Model-It: A Case Study of Learner-Centered Software Design for Supporting Model Building.

ERIC Educational Resources Information Center

Jackson, Shari L.; Stratford, Steven J.; Krajcik, Joseph S.; Soloway, Elliot

Learner-centered software design (LCSD) guides the design of tasks, tools, and interfaces in order to support the unique needs of learners: growth, diversity and motivation. This paper presents a framework for LCSD and describes a case study of its application to the ScienceWare Model-It, a learner-centered tool to support scientific modeling and…

Case studies of simulation models of recreation use

Treesearch

David N. Cole

2005-01-01

Computer simulation models can be usefully applied to many different outdoor recreation situations. Model outputs can also be used for a wide variety of planning and management purposes. The intent of this chapter is to use a collection of 12 case studies to illustrate how simulation models have been used in a wide range of recreation situations and for diverse...

Sample Invariance of the Structural Equation Model and the Item Response Model: A Case Study.

ERIC Educational Resources Information Center

Breithaupt, Krista; Zumbo, Bruno D.

2002-01-01

Evaluated the sample invariance of item discrimination statistics in a case study using real data, responses of 10 random samples of 500 people to a depression scale. Results lend some support to the hypothesized superiority of a two-parameter item response model over the common form of structural equation modeling, at least when responses are…

Strongly Correlated Electron Systems: An Operatorial Perspective

NASA Astrophysics Data System (ADS)

Di Ciolo, Andrea; Avella, Adolfo

2018-05-01

We discuss the operatorial approach to the study of strongly correlated electron systems and show how the exact solution of target models on small clusters chosen ad-hoc (minimal models) can suggest very efficient bulk approximations. We use the Hubbard model as case study (target model) and we analyze and discuss the crucial role of spin fluctuations in its 2-site realization (minimal model). Accordingly, we devise a novel three-pole approximation for the 2D case, including in the basic field an operator describing the dressing of the electronic one by the nearest-neighbor spin-fluctuations. Such a solution is in very good agreement with the exact one in the minimal model (2-site case) and performs very well once compared to advanced (semi-)numerical methods in the 2D case, being by far less computational-resource demanding.

Experiment evaluates ocean models and data assimiliation in the Gulf Stream

NASA Astrophysics Data System (ADS)

Willems, Robert C.; Glenn, S. M.; Crowley, M. F.; Malanotte-Rizzoli, P.; Young, R. E.; Ezer, T.; Mellor, G. L.; Arango, H. G.; Robinson, A. R.; Lai, C.-C. A.

Using data sets of known quality as the basis for comparison, a recent experiment explored the Gulf Stream Region at 27°-47°N and 80°-50°W to assess the nowcast/forecast capability of specific ocean models and the impact of data assimilation. Scientists from five universities and the Naval Research Laboratory/Stennis Space Center participated in the Data Assimilation and Model Evaluation Experiment (DAMEÉ-GSR).DAMEÉ-GSR was based on case studies, each successively more complex, and was divided into three phases using case studies (data) from 1987 and 1988. Phase I evaluated models' forecast capability using common initial conditions and comparing model forecast fields with observational data at forecast time over a 2-week period. Phase II added data assimilation and assessed its impact on forecast capability, using the same case studies as in phase I, and phase III added a 2-month case study overlapping some periods in Phases I and II.

Bifurcation study of phase oscillator systems with attractive and repulsive interaction.

PubMed

Burylko, Oleksandr; Kazanovich, Yakov; Borisyuk, Roman

2014-08-01

We study a model of globally coupled phase oscillators that contains two groups of oscillators with positive (synchronizing) and negative (desynchronizing) incoming connections for the first and second groups, respectively. This model was previously studied by Hong and Strogatz (the Hong-Strogatz model) in the case of a large number of oscillators. We consider a generalized Hong-Strogatz model with a constant phase shift in coupling. Our approach is based on the study of invariant manifolds and bifurcation analysis of the system. In the case of zero phase shift, various invariant manifolds are analytically described and a new dynamical mode is found. In the case of a nonzero phase shift we obtained a set of bifurcation diagrams for various systems with three or four oscillators. It is shown that in these cases system dynamics can be complex enough and include multistability and chaotic oscillations.

Bifurcation study of phase oscillator systems with attractive and repulsive interaction

NASA Astrophysics Data System (ADS)

Burylko, Oleksandr; Kazanovich, Yakov; Borisyuk, Roman

2014-08-01

We study a model of globally coupled phase oscillators that contains two groups of oscillators with positive (synchronizing) and negative (desynchronizing) incoming connections for the first and second groups, respectively. This model was previously studied by Hong and Strogatz (the Hong-Strogatz model) in the case of a large number of oscillators. We consider a generalized Hong-Strogatz model with a constant phase shift in coupling. Our approach is based on the study of invariant manifolds and bifurcation analysis of the system. In the case of zero phase shift, various invariant manifolds are analytically described and a new dynamical mode is found. In the case of a nonzero phase shift we obtained a set of bifurcation diagrams for various systems with three or four oscillators. It is shown that in these cases system dynamics can be complex enough and include multistability and chaotic oscillations.

Comparing Dutch case management care models for people with dementia and their caregivers: The design of the COMPAS study.

PubMed

MacNeil Vroomen, Janet; Van Mierlo, Lisa D; van de Ven, Peter M; Bosmans, Judith E; van den Dungen, Pim; Meiland, Franka J M; Dröes, Rose-Marie; Moll van Charante, Eric P; van der Horst, Henriëtte E; de Rooij, Sophia E; van Hout, Hein P J

2012-05-28

Dementia care in the Netherlands is shifting from fragmented, ad hoc care to more coordinated and personalised care. Case management contributes to this shift. The linkage model and a combination of intensive case management and joint agency care models were selected based on their emerging prominence in the Netherlands. It is unclear if these different forms of case management are more effective than usual care in improving or preserving the functioning and well-being at the patient and caregiver level and at the societal cost. The objective of this article is to describe the design of a study comparing these two case management care models against usual care. Clinical and cost outcomes are investigated while care processes and the facilitators and barriers for implementation of these models are considered. Mixed methods include a prospective, observational, controlled, cohort study among persons with dementia and their primary informal caregiver in regions of the Netherlands with and without case management including a qualitative process evaluation. Inclusion criteria for the cohort study are: community-dwelling individuals with a dementia diagnosis who are not terminally-ill or anticipate admission to a nursing home within 6 months and with an informal caregiver who speaks fluent Dutch. Person with dementia-informal caregiver dyads are followed for two years. The primary outcome measure is the Neuropsychiatric Inventory for the people with dementia and the General Health Questionnaire for their caregivers. Secondary outcomes include: quality of life and needs assessment in both persons with dementia and caregivers, activity of daily living, competence of care, and number of crises. Costs are measured from a societal perspective using cost diaries. Process indicators measure the quality of care from the participant's perspective. The qualitative study uses purposive sampling methods to ensure a wide variation of respondents. Semi-structured interviews with stakeholders based on the theoretical model of adaptive implementation are planned. This study provides relevant insights into care processes, description of two case management models along with clinical and economic data from persons with dementia and caregivers to clarify important differences in two case management care models compared to usual care.

Comparing Dutch Case management care models for people with dementia and their caregivers: The design of the COMPAS study

PubMed Central

2012-01-01

Background Dementia care in the Netherlands is shifting from fragmented, ad hoc care to more coordinated and personalised care. Case management contributes to this shift. The linkage model and a combination of intensive case management and joint agency care models were selected based on their emerging prominence in the Netherlands. It is unclear if these different forms of case management are more effective than usual care in improving or preserving the functioning and well-being at the patient and caregiver level and at the societal cost. The objective of this article is to describe the design of a study comparing these two case management care models against usual care. Clinical and cost outcomes are investigated while care processes and the facilitators and barriers for implementation of these models are considered. Design Mixed methods include a prospective, observational, controlled, cohort study among persons with dementia and their primary informal caregiver in regions of the Netherlands with and without case management including a qualitative process evaluation. Inclusion criteria for the cohort study are: community-dwelling individuals with a dementia diagnosis who are not terminally-ill or anticipate admission to a nursing home within 6 months and with an informal caregiver who speaks fluent Dutch. Person with dementia-informal caregiver dyads are followed for two years. The primary outcome measure is the Neuropsychiatric Inventory for the people with dementia and the General Health Questionnaire for their caregivers. Secondary outcomes include: quality of life and needs assessment in both persons with dementia and caregivers, activity of daily living, competence of care, and number of crises. Costs are measured from a societal perspective using cost diaries. Process indicators measure the quality of care from the participant’s perspective. The qualitative study uses purposive sampling methods to ensure a wide variation of respondents. Semi-structured interviews with stakeholders based on the theoretical model of adaptive implementation are planned. Discussion This study provides relevant insights into care processes, description of two case management models along with clinical and economic data from persons with dementia and caregivers to clarify important differences in two case management care models compared to usual care. PMID:22640695

Lung Cancer Risk from Occupational and Environmental Radon and Role of Smoking in Two Czech Nested Case-Control Studies

PubMed Central

Tomasek, Ladislav

2013-01-01

The aim of the present study was to evaluate the risk of lung cancer from combined exposure to radon and smoking. Methodologically, it is based on case-control studies nested within two Czech cohort studies of nearly 11,000 miners followed-up for mortality in 1952–2010 and nearly 12,000 inhabitants exposed to high levels of radon in homes, with mortality follow-up in 1960–2010. In addition to recorded radon exposure, these studies use information on smoking collected from the subjects or their relatives. A total of 1,029 and 370 cases with smoking information have been observed in the occupational and environmental (residential) studies, respectively. Three or four control subjects have been individually matched to cases according to sex, year of birth, and age. The combined effect from radon and smoking is analyzed in terms of geometric mixture models of which the additive and multiplicative models are special cases. The resulting models are relatively close to the additive interaction (mixing parameter 0.2 and 0.3 in the occupational and residential studies, respectively). The impact of the resulting model in the residential radon study is illustrated by estimates of lifetime risk in hypothetical populations of smokers and non-smokers. In comparison to the multiplicative risk model, the lifetime risk from the best geometric mixture model is considerably higher, particularly in the non-smoking population. PMID:23470882

An Illustrative Case Study of the Heuristic Practices of a High-Performing Research Department: Toward Building a Model Applicable in the Context of Large Urban Districts

ERIC Educational Resources Information Center

Munoz, Marco A.; Rodosky, Robert J.

2011-01-01

This case study provides an illustration of the heuristic practices of a high-performing research department, which in turn, will help build much needed models applicable in the context of large urban districts. This case study examines the accountability, planning, evaluation, testing, and research functions of a research department in a large…

Crisis Management Systems: A Case Study for Aspect-Oriented Modeling

NASA Astrophysics Data System (ADS)

Kienzle, Jörg; Guelfi, Nicolas; Mustafiz, Sadaf

The intent of this document is to define a common case study for the aspect-oriented modeling research community. The domain of the case study is crisis management systems, i.e., systems that help in identifying, assessing, and handling a crisis situation by orchestrating the communication between all parties involved in handling the crisis, by allocating and managing resources, and by providing access to relevant crisis-related information to authorized users. This document contains informal requirements of crisis management systems (CMSs) in general, a feature model for a CMS product line, use case models for a car crash CMS (CCCMS), a domain model for the CCCMS, an informal physical architecture description of the CCCMS, as well as some design models of a possible object-oriented implementation of parts of the CCCMS backend. AOM researchers who want to demonstrate the power of their AOM approach or technique can hence apply the approach at the most appropriate level of abstraction.

Quantitative image quality evaluation of MR images using perceptual difference models

PubMed Central

Miao, Jun; Huo, Donglai; Wilson, David L.

2008-01-01

The authors are using a perceptual difference model (Case-PDM) to quantitatively evaluate image quality of the thousands of test images which can be created when optimizing fast magnetic resonance (MR) imaging strategies and reconstruction techniques. In this validation study, they compared human evaluation of MR images from multiple organs and from multiple image reconstruction algorithms to Case-PDM and similar models. The authors found that Case-PDM compared very favorably to human observers in double-stimulus continuous-quality scale and functional measurement theory studies over a large range of image quality. The Case-PDM threshold for nonperceptible differences in a 2-alternative forced choice study varied with the type of image under study, but was ≈1.1 for diffuse image effects, providing a rule of thumb. Ordering the image quality evaluation models, we found in overall Case-PDM ≈ IDM (Sarnoff Corporation) ≈ SSIM [Wang et al. IEEE Trans. Image Process. 13, 600–612 (2004)] > mean squared error ≈ NR [Wang et al. (2004) (unpublished)] > DCTune (NASA) > IQM (MITRE Corporation). The authors conclude that Case-PDM is very useful in MR image evaluation but that one should probably restrict studies to similar images and similar processing, normally not a limitation in image reconstruction studies. PMID:18649487

A POPULATION EXPOSURE MODEL FOR PARTICULATE MATTER: CASE STUDY RESULTS FOR PM 2.5 IN PHILADELPHIA, PA

EPA Science Inventory

A population exposure model for particulate matter (PM), called the Stochastic Human Exposure and Dose Simulation (SHEDS-PM) model, has been developed and applied in a case study of daily PM2.5 exposures for the population living in Philadelphia, PA. SHEDS-PM is a probabilisti...

Knowledge Management Model: Practical Application for Competency Development

ERIC Educational Resources Information Center

Lustri, Denise; Miura, Irene; Takahashi, Sergio

2007-01-01

Purpose: This paper seeks to present a knowledge management (KM) conceptual model for competency development and a case study in a law service firm, which implemented the KM model in a competencies development program. Design/methodology/approach: The case study method was applied according to Yin (2003) concepts, focusing a six-professional group…

Development of temporal modelling for forecasting and prediction of malaria infections using time-series and ARIMAX analyses: a case study in endemic districts of Bhutan.

PubMed

Wangdi, Kinley; Singhasivanon, Pratap; Silawan, Tassanee; Lawpoolsri, Saranath; White, Nicholas J; Kaewkungwal, Jaranit

2010-09-03

Malaria still remains a public health problem in some districts of Bhutan despite marked reduction of cases in last few years. To strengthen the country's prevention and control measures, this study was carried out to develop forecasting and prediction models of malaria incidence in the endemic districts of Bhutan using time series and ARIMAX. This study was carried out retrospectively using the monthly reported malaria cases from the health centres to Vector-borne Disease Control Programme (VDCP) and the meteorological data from Meteorological Unit, Department of Energy, Ministry of Economic Affairs. Time series analysis was performed on monthly malaria cases, from 1994 to 2008, in seven malaria endemic districts. The time series models derived from a multiplicative seasonal autoregressive integrated moving average (ARIMA) was deployed to identify the best model using data from 1994 to 2006. The best-fit model was selected for each individual district and for the overall endemic area was developed and the monthly cases from January to December 2009 and 2010 were forecasted. In developing the prediction model, the monthly reported malaria cases and the meteorological factors from 1996 to 2008 of the seven districts were analysed. The method of ARIMAX modelling was employed to determine predictors of malaria of the subsequent month. It was found that the ARIMA (p, d, q) (P, D, Q)s model (p and P representing the auto regressive and seasonal autoregressive; d and D representing the non-seasonal differences and seasonal differencing; and q and Q the moving average parameters and seasonal moving average parameters, respectively and s representing the length of the seasonal period) for the overall endemic districts was (2,1,1)(0,1,1)12; the modelling data from each district revealed two most common ARIMA models including (2,1,1)(0,1,1)12 and (1,1,1)(0,1,1)12. The forecasted monthly malaria cases from January to December 2009 and 2010 varied from 15 to 82 cases in 2009 and 67 to 149 cases in 2010, where population in 2009 was 285,375 and the expected population of 2010 to be 289,085. The ARIMAX model of monthly cases and climatic factors showed considerable variations among the different districts. In general, the mean maximum temperature lagged at one month was a strong positive predictor of an increased malaria cases for four districts. The monthly number of cases of the previous month was also a significant predictor in one district, whereas no variable could predict malaria cases for two districts. The ARIMA models of time-series analysis were useful in forecasting the number of cases in the endemic areas of Bhutan. There was no consistency in the predictors of malaria cases when using ARIMAX model with selected lag times and climatic predictors. The ARIMA forecasting models could be employed for planning and managing malaria prevention and control programme in Bhutan.

Censored Hurdle Negative Binomial Regression (Case Study: Neonatorum Tetanus Case in Indonesia)

NASA Astrophysics Data System (ADS)

Yuli Rusdiana, Riza; Zain, Ismaini; Wulan Purnami, Santi

2017-06-01

Hurdle negative binomial model regression is a method that can be used for discreate dependent variable, excess zero and under- and overdispersion. It uses two parts approach. The first part estimates zero elements from dependent variable is zero hurdle model and the second part estimates not zero elements (non-negative integer) from dependent variable is called truncated negative binomial models. The discrete dependent variable in such cases is censored for some values. The type of censor that will be studied in this research is right censored. This study aims to obtain the parameter estimator hurdle negative binomial regression for right censored dependent variable. In the assessment of parameter estimation methods used Maximum Likelihood Estimator (MLE). Hurdle negative binomial model regression for right censored dependent variable is applied on the number of neonatorum tetanus cases in Indonesia. The type data is count data which contains zero values in some observations and other variety value. This study also aims to obtain the parameter estimator and test statistic censored hurdle negative binomial model. Based on the regression results, the factors that influence neonatorum tetanus case in Indonesia is the percentage of baby health care coverage and neonatal visits.

A Case Study on the Effects of an L2 Writing Instructional Model for Blended Learning in Higher Education

ERIC Educational Resources Information Center

So, Lee; Lee, Chung Hyun

2013-01-01

This case study explores EFL (English as a foreign language) students' perceptions toward a prototype of an instructional model for second language (L2) writing in blended learning and the effects of the model on the development of L2 writing skills in higher education. This model is primarily founded on the process-oriented writing approach…

A Model of Human Orientation and Self Motion Perception during Body Acceleration: The Orientation Modeling System

DTIC Science & Technology

2016-09-28

previous research and modeling results. The OMS and Perception Toolbox were used to perform a case study of an F18 mishap. Model results imply that...request documents from DTIC. Change of Address Organizations receiving reports from the U.S. Army Aeromedical Research Laboratory on automatic...54  Coriolis head movement during a coordinated turn. .............................................55  Case Study

On the equivalence of case-crossover and time series methods in environmental epidemiology.

PubMed

Lu, Yun; Zeger, Scott L

2007-04-01

The case-crossover design was introduced in epidemiology 15 years ago as a method for studying the effects of a risk factor on a health event using only cases. The idea is to compare a case's exposure immediately prior to or during the case-defining event with that same person's exposure at otherwise similar "reference" times. An alternative approach to the analysis of daily exposure and case-only data is time series analysis. Here, log-linear regression models express the expected total number of events on each day as a function of the exposure level and potential confounding variables. In time series analyses of air pollution, smooth functions of time and weather are the main confounders. Time series and case-crossover methods are often viewed as competing methods. In this paper, we show that case-crossover using conditional logistic regression is a special case of time series analysis when there is a common exposure such as in air pollution studies. This equivalence provides computational convenience for case-crossover analyses and a better understanding of time series models. Time series log-linear regression accounts for overdispersion of the Poisson variance, while case-crossover analyses typically do not. This equivalence also permits model checking for case-crossover data using standard log-linear model diagnostics.

Discursive Hierarchical Patterning in Economics Cases

ERIC Educational Resources Information Center

Lung, Jane

2011-01-01

This paper attempts to apply Lung's (2008) model of the discursive hierarchical patterning of cases to a closer and more specific study of Economics cases and proposes a model of the distinct discursive hierarchical patterning of the same. It examines a corpus of 150 Economics cases with a view to uncovering the patterns of discourse construction.…

Ethical issues in engineering models: an operations researcher's reflections.

PubMed

Kleijnen, J

2011-09-01

This article starts with an overview of the author's personal involvement--as an Operations Research consultant--in several engineering case-studies that may raise ethical questions; e.g., case-studies on nuclear waste, water management, sustainable ecology, military tactics, and animal welfare. All these case studies employ computer simulation models. In general, models are meant to solve practical problems, which may have ethical implications for the various stakeholders; namely, the modelers, the clients, and the public at large. The article further presents an overview of codes of ethics in a variety of disciples. It discusses the role of mathematical models, focusing on the validation of these models' assumptions. Documentation of these model assumptions needs special attention. Some ethical norms and values may be quantified through the model's multiple performance measures, which might be optimized. The uncertainty about the validity of the model leads to risk or uncertainty analysis and to a search for robust models. Ethical questions may be pressing in military models, including war games. However, computer games and the related experimental economics may also provide a special tool to study ethical issues. Finally, the article briefly discusses whistleblowing. Its many references to publications and websites enable further study of ethical issues in modeling.

A general regression framework for a secondary outcome in case-control studies.

PubMed

Tchetgen Tchetgen, Eric J

2014-01-01

Modern case-control studies typically involve the collection of data on a large number of outcomes, often at considerable logistical and monetary expense. These data are of potentially great value to subsequent researchers, who, although not necessarily concerned with the disease that defined the case series in the original study, may want to use the available information for a regression analysis involving a secondary outcome. Because cases and controls are selected with unequal probability, regression analysis involving a secondary outcome generally must acknowledge the sampling design. In this paper, the author presents a new framework for the analysis of secondary outcomes in case-control studies. The approach is based on a careful re-parameterization of the conditional model for the secondary outcome given the case-control outcome and regression covariates, in terms of (a) the population regression of interest of the secondary outcome given covariates and (b) the population regression of the case-control outcome on covariates. The error distribution for the secondary outcome given covariates and case-control status is otherwise unrestricted. For a continuous outcome, the approach sometimes reduces to extending model (a) by including a residual of (b) as a covariate. However, the framework is general in the sense that models (a) and (b) can take any functional form, and the methodology allows for an identity, log or logit link function for model (a).

CONTROL FUNCTION ASSISTED IPW ESTIMATION WITH A SECONDARY OUTCOME IN CASE-CONTROL STUDIES.

PubMed

Sofer, Tamar; Cornelis, Marilyn C; Kraft, Peter; Tchetgen Tchetgen, Eric J

2017-04-01

Case-control studies are designed towards studying associations between risk factors and a single, primary outcome. Information about additional, secondary outcomes is also collected, but association studies targeting such secondary outcomes should account for the case-control sampling scheme, or otherwise results may be biased. Often, one uses inverse probability weighted (IPW) estimators to estimate population effects in such studies. IPW estimators are robust, as they only require correct specification of the mean regression model of the secondary outcome on covariates, and knowledge of the disease prevalence. However, IPW estimators are inefficient relative to estimators that make additional assumptions about the data generating mechanism. We propose a class of estimators for the effect of risk factors on a secondary outcome in case-control studies that combine IPW with an additional modeling assumption: specification of the disease outcome probability model. We incorporate this model via a mean zero control function. We derive the class of all regular and asymptotically linear estimators corresponding to our modeling assumption, when the secondary outcome mean is modeled using either the identity or the log link. We find the efficient estimator in our class of estimators and show that it reduces to standard IPW when the model for the primary disease outcome is unrestricted, and is more efficient than standard IPW when the model is either parametric or semiparametric.

Case Study Observational Research: A Framework for Conducting Case Study Research Where Observation Data Are the Focus.

PubMed

Morgan, Sonya J; Pullon, Susan R H; Macdonald, Lindsay M; McKinlay, Eileen M; Gray, Ben V

2017-06-01

Case study research is a comprehensive method that incorporates multiple sources of data to provide detailed accounts of complex research phenomena in real-life contexts. However, current models of case study research do not particularly distinguish the unique contribution observation data can make. Observation methods have the potential to reach beyond other methods that rely largely or solely on self-report. This article describes the distinctive characteristics of case study observational research, a modified form of Yin's 2014 model of case study research the authors used in a study exploring interprofessional collaboration in primary care. In this approach, observation data are positioned as the central component of the research design. Case study observational research offers a promising approach for researchers in a wide range of health care settings seeking more complete understandings of complex topics, where contextual influences are of primary concern. Future research is needed to refine and evaluate the approach.

An Algebraic Implicitization and Specialization of Minimum KL-Divergence Models

NASA Astrophysics Data System (ADS)

Dukkipati, Ambedkar; Manathara, Joel George

In this paper we study representation of KL-divergence minimization, in the cases where integer sufficient statistics exists, using tools from polynomial algebra. We show that the estimation of parametric statistical models in this case can be transformed to solving a system of polynomial equations. In particular, we also study the case of Kullback-Csisźar iteration scheme. We present implicit descriptions of these models and show that implicitization preserves specialization of prior distribution. This result leads us to a Gröbner bases method to compute an implicit representation of minimum KL-divergence models.

Forecasting malaria incidence based on monthly case reports and environmental factors in Karuzi, Burundi, 1997–2003

PubMed Central

Gomez-Elipe, Alberto; Otero, Angel; van Herp, Michel; Aguirre-Jaime, Armando

2007-01-01

Background The objective of this work was to develop a model to predict malaria incidence in an area of unstable transmission by studying the association between environmental variables and disease dynamics. Methods The study was carried out in Karuzi, a province in the Burundi highlands, using time series of monthly notifications of malaria cases from local health facilities, data from rain and temperature records, and the normalized difference vegetation index (NDVI). Using autoregressive integrated moving average (ARIMA) methodology, a model showing the relation between monthly notifications of malaria cases and the environmental variables was developed. Results The best forecasting model (R2adj = 82%, p < 0.0001 and 93% forecasting accuracy in the range ± 4 cases per 100 inhabitants) included the NDVI, mean maximum temperature, rainfall and number of malaria cases in the preceding month. Conclusion This model is a simple and useful tool for producing reasonably reliable forecasts of the malaria incidence rate in the study area. PMID:17892540

Development and External Validation of a Melanoma Risk Prediction Model Based on Self-assessed Risk Factors.

PubMed

Vuong, Kylie; Armstrong, Bruce K; Weiderpass, Elisabete; Lund, Eiliv; Adami, Hans-Olov; Veierod, Marit B; Barrett, Jennifer H; Davies, John R; Bishop, D Timothy; Whiteman, David C; Olsen, Catherine M; Hopper, John L; Mann, Graham J; Cust, Anne E; McGeechan, Kevin

2016-08-01

Identifying individuals at high risk of melanoma can optimize primary and secondary prevention strategies. To develop and externally validate a risk prediction model for incident first-primary cutaneous melanoma using self-assessed risk factors. We used unconditional logistic regression to develop a multivariable risk prediction model. Relative risk estimates from the model were combined with Australian melanoma incidence and competing mortality rates to obtain absolute risk estimates. A risk prediction model was developed using the Australian Melanoma Family Study (629 cases and 535 controls) and externally validated using 4 independent population-based studies: the Western Australia Melanoma Study (511 case-control pairs), Leeds Melanoma Case-Control Study (960 cases and 513 controls), Epigene-QSkin Study (44 544, of which 766 with melanoma), and Swedish Women's Lifestyle and Health Cohort Study (49 259 women, of which 273 had melanoma). We validated model performance internally and externally by assessing discrimination using the area under the receiver operating curve (AUC). Additionally, using the Swedish Women's Lifestyle and Health Cohort Study, we assessed model calibration and clinical usefulness. The risk prediction model included hair color, nevus density, first-degree family history of melanoma, previous nonmelanoma skin cancer, and lifetime sunbed use. On internal validation, the AUC was 0.70 (95% CI, 0.67-0.73). On external validation, the AUC was 0.66 (95% CI, 0.63-0.69) in the Western Australia Melanoma Study, 0.67 (95% CI, 0.65-0.70) in the Leeds Melanoma Case-Control Study, 0.64 (95% CI, 0.62-0.66) in the Epigene-QSkin Study, and 0.63 (95% CI, 0.60-0.67) in the Swedish Women's Lifestyle and Health Cohort Study. Model calibration showed close agreement between predicted and observed numbers of incident melanomas across all deciles of predicted risk. In the external validation setting, there was higher net benefit when using the risk prediction model to classify individuals as high risk compared with classifying all individuals as high risk. The melanoma risk prediction model performs well and may be useful in prevention interventions reliant on a risk assessment using self-assessed risk factors.

Postmortem time estimation using body temperature and a finite-element computer model.

PubMed

den Hartog, Emiel A; Lotens, Wouter A

2004-09-01

In the Netherlands most murder victims are found 2-24 h after the crime. During this period, body temperature decrease is the most reliable method to estimate the postmortem time (PMT). Recently, two murder cases were analysed in which currently available methods did not provide a sufficiently reliable estimate of the PMT. In both cases a study was performed to verify the statements of suspects. For this purpose a finite-element computer model was developed that simulates a human torso and its clothing. With this model, changes to the body and the environment can also be modelled; this was very relevant in one of the cases, as the body had been in the presence of a small fire. In both cases it was possible to falsify the statements of the suspects by improving the accuracy of the PMT estimate. The estimated PMT in both cases was within the range of Henssge's model. The standard deviation of the PMT estimate was 35 min in the first case and 45 min in the second case, compared to 168 min (2.8 h) in Henssge's model. In conclusion, the model as presented here can have additional value for improving the accuracy of the PMT estimate. In contrast to the simple model of Henssge, the current model allows for increased accuracy when more detailed information is available. Moreover, the sensitivity of the predicted PMT for uncertainty in the circumstances can be studied, which is crucial to the confidence of the judge in the results.

Pedagogy and Process: A Case Study of Writing in a Hybrid Learning Model

ERIC Educational Resources Information Center

Keiner, Jason F.

2017-01-01

This qualitative case study explored the perceived experiences and outcomes of writing in a hybrid model of instruction in a large suburban high school. In particular, the impact of a hybrid model on the writing process and on future writing performance were examined. In addition, teacher expectation and teacher attitude and their impact upon…

Use of travel cost models in planning: A case study

Treesearch

Allan Marsinko; William T. Zawacki; J. Michael Bowker

2002-01-01

This article examines the use of the travel cost, method in tourism-related decision making in the area of nonconsumptive wildlife-associated recreation. A travel cost model of nonconsumptive wildlife-associated recreation, developed by Zawacki, Maninko, and Bowker, is used as a case study for this analysis. The travel cost model estimates the demand for the activity...

Modelling the association of dengue fever cases with temperature and relative humidity in Jeddah, Saudi Arabia-A generalised linear model with break-point analysis.

PubMed

Alkhaldy, Ibrahim

2017-04-01

The aim of this study was to examine the role of environmental factors in the temporal distribution of dengue fever in Jeddah, Saudi Arabia. The relationship between dengue fever cases and climatic factors such as relative humidity and temperature was investigated during 2006-2009 to determine whether there is any relationship between dengue fever cases and climatic parameters in Jeddah City, Saudi Arabia. A generalised linear model (GLM) with a break-point was used to determine how different levels of temperature and relative humidity affected the distribution of the number of cases of dengue fever. Break-point analysis was performed to modelled the effect before and after a break-point (change point) in the explanatory parameters under various scenarios. Akaike information criterion (AIC) and cross validation (CV) were used to assess the performance of the models. The results showed that maximum temperature and mean relative humidity are most probably the better predictors of the number of dengue fever cases in Jeddah. In this study three scenarios were modelled: no time lag, 1-week lag and 2-weeks lag. Among these scenarios, the 1-week lag model using mean relative humidity as an explanatory variable showed better performance. This study showed a clear relationship between the meteorological variables and the number of dengue fever cases in Jeddah. The results also demonstrated that meteorological variables can be successfully used to estimate the number of dengue fever cases for a given period of time. Break-point analysis provides further insight into the association between meteorological parameters and dengue fever cases by dividing the meteorological parameters into certain break-points. Copyright © 2016 Elsevier B.V. All rights reserved.

Public private mix model in enhancing tuberculosis case detection in District Thatta, Sindh, Pakistan.

PubMed

Ahmed, Jameel; Ahmed, Mubashir; Laghari, A; Lohana, Wasdev; Ali, Sajid; Fatmi, Zafar

2009-02-01

To enhance the TB case detection through Public Private Mix (PPM) model by involving private practitioners in collaboration with National TB Control Program, (NTP) in district Thatta. Private practitioners (PPs) of district Thatta involved in treatment of TB cases were requested to participate in the study. All consenting physicians were provided with training on Directly Observed Treatment Short course (DOTS) module. In addition to routine cases, TB cases diagnosed by private practitioners through sputum microscopy were also registered with the district TB control program and medicines were provided by NTP. After intervention of PPM-DOTS change in Case Detection Rate (CDR) were estimated. An increased number of sputum smear positive cases were found in the intervention period--the third quarter of 2007, from 188 to 211 and CDR from 69% to 77%. The improvement in case detection rate was significant as this moderately added to the total number of cases detected from the whole of the district Thatta during the study period. Public private mix (PPM) model was effective in increasing the CDR of TB cases in district Thatta. It is recommended that the public private partnership model in Tuberculosis case detection needs to be taken on a larger scale so as to reduce the heavy TB burden in the country.

Equilibrium pricing in an order book environment: Case study for a spin model

NASA Astrophysics Data System (ADS)

Meudt, Frederik; Schmitt, Thilo A.; Schäfer, Rudi; Guhr, Thomas

2016-07-01

When modeling stock market dynamics, the price formation is often based on an equilibrium mechanism. In real stock exchanges, however, the price formation is governed by the order book. It is thus interesting to check if the resulting stylized facts of a model with equilibrium pricing change, remain the same or, more generally, are compatible with the order book environment. We tackle this issue in the framework of a case study by embedding the Bornholdt-Kaizoji-Fujiwara spin model into the order book dynamics. To this end, we use a recently developed agent based model that realistically incorporates the order book. We find realistic stylized facts. We conclude for the studied case that equilibrium pricing is not needed and that the corresponding assumption of a ;fundamental; price may be abandoned.

Naturalness, dark matter, and the muon anomalous magnetic moment in supersymmetric extensions of the standard model with a pseudo-Dirac gluino

NASA Astrophysics Data System (ADS)

Li, Chuang; Zhu, Bin; Li, Tianjun

2018-02-01

We study the naturalness, dark matter, and muon anomalous magnetic moment in the Supersymmetric Standard Models (SSMs) with a pseudo-Dirac gluino (PDGSSMs) from hybrid F- and D-term supersymmetry (SUSY) breakings. To obtain the observed dark matter relic density and explain the muon anomalous magnetic moment, we find that the low energy fine-tuning measures are larger than about 30 due to strong constraints from the LUX and PANDAX experiments. Thus, to study the natural PDGSSMs, we consider multi-component dark matter and then the relic density of the lightest supersymmetric particle (LSP) neutralino is smaller than the correct value. We classify our models into six kinds: (i) Case A is a general case, which has small low energy fine-tuning measure and can explain the anomalous magnetic moment of the muon; (ii) Case B with the LSP neutralino and light stau coannihilation; (iii) Case C with Higgs funnel; (iv) Case D with Higgsino LSP; (v) Case E with light stau coannihilation and Higgsino LSP; (vi) Case F with Higgs funnel and Higgsino LSP. We study these Cases in details, and show that our models can be natural and consistent with the LUX and PANDAX experiments, as well as explain the muon anomalous magnetic moment. In particular, all these cases except the stau coannihilation can even have low energy fine-tuning measures around 10.

Development of a traffic noise prediction model for an urban environment.

PubMed

Sharma, Asheesh; Bodhe, G L; Schimak, G

2014-01-01

The objective of this study is to develop a traffic noise model under diverse traffic conditions in metropolitan cities. The model has been developed to calculate equivalent traffic noise based on four input variables i.e. equivalent traffic flow (Q e ), equivalent vehicle speed (S e ) and distance (d) and honking (h). The traffic data is collected and statistically analyzed in three different cases for 15-min during morning and evening rush hours. Case I represents congested traffic where equivalent vehicle speed is <30 km/h while case II represents free-flowing traffic where equivalent vehicle speed is >30 km/h and case III represents calm traffic where no honking is recorded. The noise model showed better results than earlier developed noise model for Indian traffic conditions. A comparative assessment between present and earlier developed noise model has also been presented in the study. The model is validated with measured noise levels and the correlation coefficients between measured and predicted noise levels were found to be 0.75, 0.83 and 0.86 for case I, II and III respectively. The noise model performs reasonably well under different traffic conditions and could be implemented for traffic noise prediction at other region as well.

Integrated catchment modelling within a strategic planning and decision making process: Werra case study

NASA Astrophysics Data System (ADS)

Dietrich, Jörg; Funke, Markus

Integrated water resources management (IWRM) redefines conventional water management approaches through a closer cross-linkage between environment and society. The role of public participation and socio-economic considerations becomes more important within the planning and decision making process. In this paper we address aspects of the integration of catchment models into such a process taking the implementation of the European Water Framework Directive (WFD) as an example. Within a case study situated in the Werra river basin (Central Germany), a systems analytic decision process model was developed. This model uses the semantics of the Unified Modeling Language (UML) activity model. As an example application, the catchment model SWAT and the water quality model RWQM1 were applied to simulate the effect of phosphorus emissions from non-point and point sources on water quality. The decision process model was able to guide the participants of the case study through the interdisciplinary planning and negotiation of actions. Further improvements of the integration framework include tools for quantitative uncertainty analyses, which are crucial for real life application of models within an IWRM decision making toolbox. For the case study, the multi-criteria assessment of actions indicates that the polluter pays principle can be met at larger scales (sub-catchment or river basin) without significantly compromising cost efficiency for the local situation.

Analysis of a novel class of predictive microbial growth models and application to coculture growth.

PubMed

Poschet, F; Vereecken, K M; Geeraerd, A H; Nicolaï, B M; Van Impe, J F

2005-04-15

In this paper, a novel class of microbial growth models is analysed. In contrast with the currently used logistic type models (e.g., the model of Baranyi and Roberts [Baranyi, J., Roberts, T.A., 1994. A dynamic approach to predicting bacterial growth in food. International Journal of Food Microbiology 23, 277-294]), the novel model class, presented in Van Impe et al. (Van Impe, J.F., Poschet, F., Geeraerd, A.H., Vereecken, K.M., 2004. Towards a novel class of predictive microbial growth models. International Journal of Food Microbiology, this issue), explicitly incorporates nutrient exhaustion and/or metabolic waste product effects inducing stationary phase behaviour. As such, these novel model types can be extended in a natural way towards microbial interactions in cocultures and microbial growth in structured foods. Two illustrative case studies of the novel model types are thoroughly analysed and compared to the widely used model of Baranyi and Roberts. In a first case study, the stationary phase is assumed to be solely resulting from toxic product inhibition and is described as a function of the pH-evolution. In the second case study, substrate exhaustion is the sole cause of the stationary phase. Finally, a more complex case study of a so-called P-model is presented, dealing with a coculture inhibition of Listeria innocua mediated by lactic acid production of Lactococcus lactis.

Forecasting dengue hemorrhagic fever cases using ARIMA model: a case study in Asahan district

NASA Astrophysics Data System (ADS)

Siregar, Fazidah A.; Makmur, Tri; Saprin, S.

2018-01-01

Time series analysis had been increasingly used to forecast the number of dengue hemorrhagic fever in many studies. Since no vaccine exist and poor public health infrastructure, predicting the occurrence of dengue hemorrhagic fever (DHF) is crucial. This study was conducted to determine trend and forecasting the occurrence of DHF in Asahan district, North Sumatera Province. Monthly reported dengue cases for the years 2012-2016 were obtained from the district health offices. A time series analysis was conducted by Autoregressive integrated moving average (ARIMA) modeling to forecast the occurrence of DHF. The results demonstrated that the reported DHF cases showed a seasonal variation. The SARIMA (1,0,0)(0,1,1)12 model was the best model and adequate for the data. The SARIMA model for DHF is necessary and could applied to predict the incidence of DHF in Asahan district and assist with design public health maesures to prevent and control the diseases.

Determinants in the development of advanced nursing practice: a case study of primary-care settings in Hong Kong.

PubMed

Twinn, Sheila; Thompson, David R; Lopez, Violeta; Lee, Diana T F; Shiu, Ann T Y

2005-01-01

Different factors have been shown to influence the development of models of advanced nursing practice (ANP) in primary-care settings. Although ANP is being developed in hospitals in Hong Kong, China, it remains undeveloped in primary care and little is known about the factors determining the development of such a model. The aims of the present study were to investigate the contribution of different models of nursing practice to the care provided in primary-care settings in Hong Kong, and to examine the determinants influencing the development of a model of ANP in such settings. A multiple case study design was selected using both qualitative and quantitative methods of data collection. Sampling methods reflected the population groups and stage of the case study. Sampling included a total population of 41 nurses from whom a secondary volunteer sample was drawn for face-to-face interviews. In each case study, a convenience sample of 70 patients were recruited, from whom 10 were selected purposively for a semi-structured telephone interview. An opportunistic sample of healthcare professionals was also selected. The within-case and cross-case analysis demonstrated four major determinants influencing the development of ANP: (1) current models of nursing practice; (2) the use of skills mix; (3) the perceived contribution of ANP to patient care; and (4) patients' expectations of care. The level of autonomy of individual nurses was considered particularly important. These determinants were used to develop a model of ANP for a primary-care setting. In conclusion, although the findings highlight the complexity determining the development and implementation of ANP in primary care, the proposed model suggests that definitions of advanced practice are appropriate to a range of practice models and cultural settings. However, the findings highlight the importance of assessing the effectiveness of such models in terms of cost and long-term patient outcomes.

1+1 Gaudin Model

NASA Astrophysics Data System (ADS)

Zotov, Andrei V.

2011-07-01

We study 1+1 field-generalizations of the rational and elliptic Gaudin models. For sl(N) case we introduce equations of motion and L-A pair with spectral parameter on the Riemann sphere and elliptic curve. In sl(2) case we study the equations in detail and find the corresponding Hamiltonian densities. The n-site model describes n interacting Landau-Lifshitz models of magnets. The interaction depends on position of the sites (marked points on the curve). We also analyze the 2-site case in its own right and describe its relation to the principal chiral model. We emphasize that 1+1 version impose a restriction on a choice of flows on the level of the corresponding 0+1 classical mechanics.

The effect of improving task representativeness on capturing nurses’ risk assessment judgements: a comparison of written case simulations and physical simulations

PubMed Central

2013-01-01

Background The validity of studies describing clinicians’ judgements based on their responses to paper cases is questionable, because - commonly used - paper case simulations only partly reflect real clinical environments. In this study we test whether paper case simulations evoke similar risk assessment judgements to the more realistic simulated patients used in high fidelity physical simulations. Methods 97 nurses (34 experienced nurses and 63 student nurses) made dichotomous assessments of risk of acute deterioration on the same 25 simulated scenarios in both paper case and physical simulation settings. Scenarios were generated from real patient cases. Measures of judgement ‘ecology’ were derived from the same case records. The relationship between nurses’ judgements, actual patient outcomes (i.e. ecological criteria), and patient characteristics were described using the methodology of judgement analysis. Logistic regression models were constructed to calculate Lens Model Equation parameters. Parameters were then compared between the modeled paper-case and physical-simulation judgements. Results Participants had significantly less achievement (ra) judging physical simulations than when judging paper cases. They used less modelable knowledge (G) with physical simulations than with paper cases, while retaining similar cognitive control and consistency on repeated patients. Respiration rate, the most important cue for predicting patient risk in the ecological model, was weighted most heavily by participants. Conclusions To the extent that accuracy in judgement analysis studies is a function of task representativeness, improving task representativeness via high fidelity physical simulations resulted in lower judgement performance in risk assessments amongst nurses when compared to paper case simulations. Lens Model statistics could prove useful when comparing different options for the design of simulations used in clinical judgement analysis. The approach outlined may be of value to those designing and evaluating clinical simulations as part of education and training strategies aimed at improving clinical judgement and reasoning. PMID:23718556

A d-statistic for single-case designs that is equivalent to the usual between-groups d-statistic.

PubMed

Shadish, William R; Hedges, Larry V; Pustejovsky, James E; Boyajian, Jonathan G; Sullivan, Kristynn J; Andrade, Alma; Barrientos, Jeannette L

2014-01-01

We describe a standardised mean difference statistic (d) for single-case designs that is equivalent to the usual d in between-groups experiments. We show how it can be used to summarise treatment effects over cases within a study, to do power analyses in planning new studies and grant proposals, and to meta-analyse effects across studies of the same question. We discuss limitations of this d-statistic, and possible remedies to them. Even so, this d-statistic is better founded statistically than other effect size measures for single-case design, and unlike many general linear model approaches such as multilevel modelling or generalised additive models, it produces a standardised effect size that can be integrated over studies with different outcome measures. SPSS macros for both effect size computation and power analysis are available.

An evidence-based approach to case management model selection for an acute care facility: is there really a preferred model?

PubMed

Terra, Sandra M

2007-01-01

This research seeks to determine whether there is adequate evidence-based justification for selection of one acute care case management model over another. Acute Inpatient Hospital. This article presents a systematic review of published case management literature, resulting in classification specific to terms of level of evidence. This review examines the best available evidence in an effort to select an acute care case management model. Although no single case management model can be identified as preferred, it is clear that adequate evidence-based literature exists to acknowledge key factors driving the acute care model and to form a foundation for the efficacy of hospital case management practice. Although no single case management model can be identified as preferred, this systematic review demonstrates that adequate evidence-based literature exists to acknowledge key factors driving the acute care model and forming a foundation for the efficacy of hospital case management practice. Distinctive aspects of case management frameworks can be used to guide the development of an acute care case management model. The study illustrates: * The effectiveness of case management when there is direct patient contact by the case manager regardless of disease condition: not only does the quality of care increase but also length of stay (LOS) decreases, care is defragmented, and both patient and physician satisfaction can increase. * The preferred case management models result in measurable outcomes that can directly relate to, and demonstrate alignment with, organizational strategy. * Acute care management programs reduce cost and LOS, and improve outcomes. * An integrated case management program that includes social workers, as well as nursing, is the most effective acute care management model. * The successful case management model will recognize physicians, as well as patients, as valued customers with whom partnership can positively affect financial outcomes in terms of reduction in LOS, improvement in quality, and delivery of care.

A controlled experiment in ground water flow model calibration

USGS Publications Warehouse

Hill, M.C.; Cooley, R.L.; Pollock, D.W.

1998-01-01

Nonlinear regression was introduced to ground water modeling in the 1970s, but has been used very little to calibrate numerical models of complicated ground water systems. Apparently, nonlinear regression is thought by many to be incapable of addressing such complex problems. With what we believe to be the most complicated synthetic test case used for such a study, this work investigates using nonlinear regression in ground water model calibration. Results of the study fall into two categories. First, the study demonstrates how systematic use of a well designed nonlinear regression method can indicate the importance of different types of data and can lead to successive improvement of models and their parameterizations. Our method differs from previous methods presented in the ground water literature in that (1) weighting is more closely related to expected data errors than is usually the case; (2) defined diagnostic statistics allow for more effective evaluation of the available data, the model, and their interaction; and (3) prior information is used more cautiously. Second, our results challenge some commonly held beliefs about model calibration. For the test case considered, we show that (1) field measured values of hydraulic conductivity are not as directly applicable to models as their use in some geostatistical methods imply; (2) a unique model does not necessarily need to be identified to obtain accurate predictions; and (3) in the absence of obvious model bias, model error was normally distributed. The complexity of the test case involved implies that the methods used and conclusions drawn are likely to be powerful in practice.Nonlinear regression was introduced to ground water modeling in the 1970s, but has been used very little to calibrate numerical models of complicated ground water systems. Apparently, nonlinear regression is thought by many to be incapable of addressing such complex problems. With what we believe to be the most complicated synthetic test case used for such a study, this work investigates using nonlinear regression in ground water model calibration. Results of the study fall into two categories. First, the study demonstrates how systematic use of a well designed nonlinear regression method can indicate the importance of different types of data and can lead to successive improvement of models and their parameterizations. Our method differs from previous methods presented in the ground water literature in that (1) weighting is more closely related to expected data errors than is usually the case; (2) defined diagnostic statistics allow for more effective evaluation of the available data, the model, and their interaction; and (3) prior information is used more cautiously. Second, our results challenge some commonly held beliefs about model calibration. For the test case considered, we show that (1) field measured values of hydraulic conductivity are not as directly applicable to models as their use in some geostatistical methods imply; (2) a unique model does not necessarily need to be identified to obtain accurate predictions; and (3) in the absence of obvious model bias, model error was normally distributed. The complexity of the test case involved implies that the methods used and conclusions drawn are likely to be powerful in practice.

Using information communication technology in models of integrated community-based primary health care: learning from the iCOACH case studies.

PubMed

Steele Gray, Carolyn; Barnsley, Jan; Gagnon, Dominique; Belzile, Louise; Kenealy, Tim; Shaw, James; Sheridan, Nicolette; Wankah Nji, Paul; Wodchis, Walter P

2018-06-26

Information communication technology (ICT) is a critical enabler of integrated models of community-based primary health care; however, little is known about how existing technologies have been used to support new models of integrated care. To address this gap, we draw on data from an international study of integrated models, exploring how ICT is used to support activities of integrated care and the organizational and environmental barriers and enablers to its adoption. We take an embedded comparative multiple-case study approach using data from a study of implementation of nine models of integrated community-based primary health care, the Implementing Integrated Care for Older Adults with Complex Health Needs (iCOACH) study. Six cases from Canada, three each in Ontario and Quebec, and three in New Zealand, were studied. As part of the case studies, interviews were conducted with managers and front-line health care providers from February 2015 to March 2017. A qualitative descriptive approach was used to code data from 137 interviews and generate word tables to guide analysis. Despite different models and contexts, we found strikingly similar accounts of the types of activities supported through ICT systems in each of the cases. ICT systems were used most frequently to support activities like care coordination by inter-professional teams through information sharing. However, providers were limited in their ability to efficiently share patient data due to data access issues across organizational and professional boundaries and due to system functionality limitations, such as a lack of interoperability. Even in innovative models of care, managers and providers in our cases mainly use technology to enable traditional ways of working. Technology limitations prevent more innovative uses of technology that could support disruption necessary to improve care delivery. We argue the barriers to more innovative use of technology are linked to three factors: (1) information access barriers, (2) limited functionality of available technology, and (3) organizational and provider inertia.

A Case Study of the Partnership Schools Comprehensive School Reform (CSR) Model

ERIC Educational Resources Information Center

Epstein, Joyce L.

2005-01-01

This case study reports the feasibility of the Partnership Schools Comprehensive School Reform (CSR) model for school improvement in a Title I elementary school. Interviews were conducted and documents were collected for 3 years to study whether and how the school implemented key policy attributes--specificity, consistency, authority, power, and…

An Ethnographic Case Study of the Administrative Organization, Processes, and Behavior in a Model Comprehensive High School.

ERIC Educational Resources Information Center

Zimman, Richard N.

Using ethnographic case study methodology (involving open-ended interviews, participant observation, and document analysis) theories of administrative organization, processes, and behavior were tested during a three-week observation of a model comprehensive (experimental) high school. Although the study is limited in its general application, it…

Cooperative Attention: Using Qualitative Case Studies to Study Peer Institutions

ERIC Educational Resources Information Center

Lisi, Bethany

2017-01-01

This chapter provides a conceptual model that institutional research professionals can use to develop contextual intelligence of issues of interest in higher education with the use of case studies from peer institutions. The model draws from the metaphor of the "divided brain" and how the two hemispheres must work together with both…

An Interprofessional Model for Serving Youth at Risk for Substance Abuse: The Team Case Study.

ERIC Educational Resources Information Center

Cobia, Debra C.; And Others

1995-01-01

Three models of interprofessional education appropriate for serving youth at risk for substance abuse are described. The evaluation of the team case study model indicated that the participants were more sensitive to the needs of the youths, experienced increased comfort in consulting other agents, and were more confident in their ability to select…

History Places: A Case Study for Relational Database and Information Retrieval System Design

ERIC Educational Resources Information Center

Hendry, David G.

2007-01-01

This article presents a project-based case study that was developed for students with diverse backgrounds and varied inclinations for engaging technical topics. The project, called History Places, requires that student teams develop a vision for a kind of digital library, propose a conceptual model, and use the model to derive a logical model and…

An Application Practice of the IFLA FRBR Model: A Metadata Case Study for the National Palace Museum in Taipei.

ERIC Educational Resources Information Center

Chen, Ya-ning; Lin, Simon C.; Chen, Shu-jiun

2002-01-01

Explains the Functional Requirements for Bibliographic Records (FRBR) model which was proposed by the International Federation of Library Associations and Institutions (IFLA) as a framework to proceed content-based analysis and developing metadata format. Presents a case study that examines the feasibility of the FRBR model at the National Palace…

Case studies, cross-site comparisons, and the challenge of generalization: comparing agent-based models of land-use change in frontier regions

PubMed Central

Parker, Dawn C.; Entwisle, Barbara; Rindfuss, Ronald R.; Vanwey, Leah K.; Manson, Steven M.; Moran, Emilio; An, Li; Deadman, Peter; Evans, Tom P.; Linderman, Marc; Rizi, S. Mohammad Mussavi; Malanson, George

2009-01-01

Cross-site comparisons of case studies have been identified as an important priority by the land-use science community. From an empirical perspective, such comparisons potentially allow generalizations that may contribute to production of global-scale land-use and land-cover change projections. From a theoretical perspective, such comparisons can inform development of a theory of land-use science by identifying potential hypotheses and supporting or refuting evidence. This paper undertakes a structured comparison of four case studies of land-use change in frontier regions that follow an agent-based modeling approach. Our hypothesis is that each case study represents a particular manifestation of a common process. Given differences in initial conditions among sites and the time at which the process is observed, actual mechanisms and outcomes are anticipated to differ substantially between sites. Our goal is to reveal both commonalities and differences among research sites, model implementations, and ultimately, conclusions derived from the modeling process. PMID:19960107

Case studies, cross-site comparisons, and the challenge of generalization: comparing agent-based models of land-use change in frontier regions.

PubMed

Parker, Dawn C; Entwisle, Barbara; Rindfuss, Ronald R; Vanwey, Leah K; Manson, Steven M; Moran, Emilio; An, Li; Deadman, Peter; Evans, Tom P; Linderman, Marc; Rizi, S Mohammad Mussavi; Malanson, George

2008-01-01

Cross-site comparisons of case studies have been identified as an important priority by the land-use science community. From an empirical perspective, such comparisons potentially allow generalizations that may contribute to production of global-scale land-use and land-cover change projections. From a theoretical perspective, such comparisons can inform development of a theory of land-use science by identifying potential hypotheses and supporting or refuting evidence. This paper undertakes a structured comparison of four case studies of land-use change in frontier regions that follow an agent-based modeling approach. Our hypothesis is that each case study represents a particular manifestation of a common process. Given differences in initial conditions among sites and the time at which the process is observed, actual mechanisms and outcomes are anticipated to differ substantially between sites. Our goal is to reveal both commonalities and differences among research sites, model implementations, and ultimately, conclusions derived from the modeling process.

Development of temporal modelling for forecasting and prediction of malaria infections using time-series and ARIMAX analyses: A case study in endemic districts of Bhutan

PubMed Central

2010-01-01

Background Malaria still remains a public health problem in some districts of Bhutan despite marked reduction of cases in last few years. To strengthen the country's prevention and control measures, this study was carried out to develop forecasting and prediction models of malaria incidence in the endemic districts of Bhutan using time series and ARIMAX. Methods This study was carried out retrospectively using the monthly reported malaria cases from the health centres to Vector-borne Disease Control Programme (VDCP) and the meteorological data from Meteorological Unit, Department of Energy, Ministry of Economic Affairs. Time series analysis was performed on monthly malaria cases, from 1994 to 2008, in seven malaria endemic districts. The time series models derived from a multiplicative seasonal autoregressive integrated moving average (ARIMA) was deployed to identify the best model using data from 1994 to 2006. The best-fit model was selected for each individual district and for the overall endemic area was developed and the monthly cases from January to December 2009 and 2010 were forecasted. In developing the prediction model, the monthly reported malaria cases and the meteorological factors from 1996 to 2008 of the seven districts were analysed. The method of ARIMAX modelling was employed to determine predictors of malaria of the subsequent month. Results It was found that the ARIMA (p, d, q) (P, D, Q)s model (p and P representing the auto regressive and seasonal autoregressive; d and D representing the non-seasonal differences and seasonal differencing; and q and Q the moving average parameters and seasonal moving average parameters, respectively and s representing the length of the seasonal period) for the overall endemic districts was (2,1,1)(0,1,1)12; the modelling data from each district revealed two most common ARIMA models including (2,1,1)(0,1,1)12 and (1,1,1)(0,1,1)12. The forecasted monthly malaria cases from January to December 2009 and 2010 varied from 15 to 82 cases in 2009 and 67 to 149 cases in 2010, where population in 2009 was 285,375 and the expected population of 2010 to be 289,085. The ARIMAX model of monthly cases and climatic factors showed considerable variations among the different districts. In general, the mean maximum temperature lagged at one month was a strong positive predictor of an increased malaria cases for four districts. The monthly number of cases of the previous month was also a significant predictor in one district, whereas no variable could predict malaria cases for two districts. Conclusions The ARIMA models of time-series analysis were useful in forecasting the number of cases in the endemic areas of Bhutan. There was no consistency in the predictors of malaria cases when using ARIMAX model with selected lag times and climatic predictors. The ARIMA forecasting models could be employed for planning and managing malaria prevention and control programme in Bhutan. PMID:20813066

Logic models as a tool for sexual violence prevention program development.

PubMed

Hawkins, Stephanie R; Clinton-Sherrod, A Monique; Irvin, Neil; Hart, Laurie; Russell, Sarah Jane

2009-01-01

Sexual violence is a growing public health problem, and there is an urgent need to develop sexual violence prevention programs. Logic models have emerged as a vital tool in program development. The Centers for Disease Control and Prevention funded an empowerment evaluation designed to work with programs focused on the prevention of first-time male perpetration of sexual violence, and it included as one of its goals, the development of program logic models. Two case studies are presented that describe how significant positive changes can be made to programs as a result of their developing logic models that accurately describe desired outcomes. The first case study describes how the logic model development process made an organization aware of the importance of a program's environmental context for program success; the second case study demonstrates how developing a program logic model can elucidate gaps in organizational programming and suggest ways to close those gaps.

Experiences Using Lightweight Formal Methods for Requirements Modeling

NASA Technical Reports Server (NTRS)

Easterbrook, Steve; Lutz, Robyn; Covington, Rick; Kelly, John; Ampo, Yoko; Hamilton, David

1997-01-01

This paper describes three case studies in the lightweight application of formal methods to requirements modeling for spacecraft fault protection systems. The case studies differ from previously reported applications of formal methods in that formal methods were applied very early in the requirements engineering process, to validate the evolving requirements. The results were fed back into the projects, to improve the informal specifications. For each case study, we describe what methods were applied, how they were applied, how much effort was involved, and what the findings were. In all three cases, formal methods enhanced the existing verification and validation processes, by testing key properties of the evolving requirements, and helping to identify weaknesses. We conclude that the benefits gained from early modeling of unstable requirements more than outweigh the effort needed to maintain multiple representations.

Bayesian Inference for the Stereotype Regression Model: Application to a Case-control Study of Prostate Cancer

PubMed Central

Ahn, Jaeil; Mukherjee, Bhramar; Banerjee, Mousumi; Cooney, Kathleen A.

2011-01-01

Summary The stereotype regression model for categorical outcomes, proposed by Anderson (1984) is nested between the baseline category logits and adjacent category logits model with proportional odds structure. The stereotype model is more parsimonious than the ordinary baseline-category (or multinomial logistic) model due to a product representation of the log odds-ratios in terms of a common parameter corresponding to each predictor and category specific scores. The model could be used for both ordered and unordered outcomes. For ordered outcomes, the stereotype model allows more flexibility than the popular proportional odds model in capturing highly subjective ordinal scaling which does not result from categorization of a single latent variable, but are inherently multidimensional in nature. As pointed out by Greenland (1994), an additional advantage of the stereotype model is that it provides unbiased and valid inference under outcome-stratified sampling as in case-control studies. In addition, for matched case-control studies, the stereotype model is amenable to classical conditional likelihood principle, whereas there is no reduction due to sufficiency under the proportional odds model. In spite of these attractive features, the model has been applied less, as there are issues with maximum likelihood estimation and likelihood based testing approaches due to non-linearity and lack of identifiability of the parameters. We present comprehensive Bayesian inference and model comparison procedure for this class of models as an alternative to the classical frequentist approach. We illustrate our methodology by analyzing data from The Flint Men’s Health Study, a case-control study of prostate cancer in African-American men aged 40 to 79 years. We use clinical staging of prostate cancer in terms of Tumors, Nodes and Metastatsis (TNM) as the categorical response of interest. PMID:19731262

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

PubMed

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

2012-07-01

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

Numerical Modeling of River Ice Processes on the Lower Nelson River

NASA Astrophysics Data System (ADS)

Malenchak, Jarrod Joseph

Water resource infrastructure in cold regions of the world can be significantly impacted by the existence of river ice. Major engineering concerns related to river ice include ice jam flooding, the design and operation of hydropower facilities and other hydraulic structures, water supplies, as well as ecological, environmental, and morphological effects. The use of numerical simulation models has been identified as one of the most efficient means by which river ice processes can be studied and the effects of river ice be evaluated. The continued advancement of these simulation models will help to develop new theories and evaluate potential mitigation alternatives for these ice issues. In this thesis, a literature review of existing river ice numerical models, of anchor ice formation and modeling studies, and of aufeis formation and modeling studies is conducted. A high level summary of the two-dimensional CRISSP numerical model is presented as well as the developed freeze-up model with a focus specifically on the anchor ice and aufeis growth processes. This model includes development in the detailed heat transfer calculations, an improved surface ice mass exchange model which includes the rapids entrainment process, and an improved dry bed treatment model along with the expanded anchor ice and aufeis growth model. The developed sub-models are tested in an ideal channel setting as somewhat of a model confirmation. A case study of significant anchor ice and aufeis growth on the Nelson River in northern Manitoba, Canada, will be the primary field test case for the anchor ice and aufeis model. A second case study on the same river will be used to evaluate the surface ice components of the model in a field setting. The results from these cases studies will be used to highlight the capabilities and deficiencies in the numerical model and to identify areas of further research and model development.

Physiologically Based Absorption Modeling to Impact Biopharmaceutics and Formulation Strategies in Drug Development-Industry Case Studies.

PubMed

Kesisoglou, Filippos; Chung, John; van Asperen, Judith; Heimbach, Tycho

2016-09-01

In recent years, there has been a significant increase in use of physiologically based pharmacokinetic models in drug development and regulatory applications. Although most of the published examples have focused on aspects such as first-in-human (FIH) dose predictions or drug-drug interactions, several publications have highlighted the application of these models in the biopharmaceutics field and their use to inform formulation development. In this report, we present 5 case studies of use of such models in this biopharmaceutics/formulation space across different pharmaceutical companies. The case studies cover different aspects of biopharmaceutics or formulation questions including (1) prediction of absorption prior to FIH studies; (2) optimization of formulation and dissolution method post-FIH data; (3) early exploration of a modified-release formulation; (4) addressing bridging questions for late-stage formulation changes; and (5) prediction of pharmacokinetics in the fed state for a Biopharmaceutics Classification System class I drug with fasted state data. The discussion of the case studies focuses on how such models can facilitate decisions and biopharmaceutic understanding of drug candidates and the opportunities for increased use and acceptance of such models in drug development and regulatory interactions. Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Uncertainty and Variability in Physiologically-Based Pharmacokinetic (PBPK) Models: Key Issues and Case Studies (Final Report)

EPA Science Inventory

EPA announced the availability of the final report, Uncertainty and Variability in Physiologically-Based Pharmacokinetic (PBPK) Models: Key Issues and Case Studies. This report summarizes some of the recent progress in characterizing uncertainty and variability in physi...

Numerical simulations of atmospheric dispersion of iodine-131 by different models.

PubMed

Leelőssy, Ádám; Mészáros, Róbert; Kovács, Attila; Lagzi, István; Kovács, Tibor

2017-01-01

Nowadays, several dispersion models are available to simulate the transport processes of air pollutants and toxic substances including radionuclides in the atmosphere. Reliability of atmospheric transport models has been demonstrated in several recent cases from local to global scale; however, very few actual emission data are available to evaluate model results in real-life cases. In this study, the atmospheric dispersion of 131I emitted to the atmosphere during an industrial process was simulated with different models, namely the WRF-Chem Eulerian online coupled model and the HYSPLIT and the RAPTOR Lagrangian models. Although only limited data of 131I detections has been available, the accuracy of modeled plume direction could be evaluated in complex late autumn weather situations. For the studied cases, the general reliability of models has been demonstrated. However, serious uncertainties arise related to low level inversions, above all in case of an emission event on 4 November 2011, when an important wind shear caused a significant difference between simulated and real transport directions. Results underline the importance of prudent interpretation of dispersion model results and the identification of weather conditions with a potential to cause large model errors.

Numerical simulations of atmospheric dispersion of iodine-131 by different models

PubMed Central

Leelőssy, Ádám; Mészáros, Róbert; Kovács, Attila; Lagzi, István; Kovács, Tibor

2017-01-01

Nowadays, several dispersion models are available to simulate the transport processes of air pollutants and toxic substances including radionuclides in the atmosphere. Reliability of atmospheric transport models has been demonstrated in several recent cases from local to global scale; however, very few actual emission data are available to evaluate model results in real-life cases. In this study, the atmospheric dispersion of 131I emitted to the atmosphere during an industrial process was simulated with different models, namely the WRF-Chem Eulerian online coupled model and the HYSPLIT and the RAPTOR Lagrangian models. Although only limited data of 131I detections has been available, the accuracy of modeled plume direction could be evaluated in complex late autumn weather situations. For the studied cases, the general reliability of models has been demonstrated. However, serious uncertainties arise related to low level inversions, above all in case of an emission event on 4 November 2011, when an important wind shear caused a significant difference between simulated and real transport directions. Results underline the importance of prudent interpretation of dispersion model results and the identification of weather conditions with a potential to cause large model errors. PMID:28207853

Developing and pretesting case studies in dental and dental hygiene education: using the diffusion of innovations model.

PubMed

Cragun, Deborah L; DeBate, Rita DiGioacchino; Severson, Herbert H; Shaw, Tracy; Christiansen, Steve; Koerber, Anne; Tomar, Scott L; Brown, Kelli McCormack; Tedesco, Lisa A; Hendricson, William D

2012-05-01

Case-based learning offers exposure to clinical situations that health professions students may not encounter in their training. The purposes of this study were to apply the Diffusion of Innovations conceptual framework to 1) identify characteristics of case studies that would increase their adoption among dental and dental hygiene faculty members and 2) develop and pretest interactive web-based case studies on sensitive oral-systemic health issues. The formative study spanned two phases using mixed methods (Phase 1: eight focus groups and four interviews; Phase 2: ten interviews and satisfaction surveys). Triangulation of quantitative and qualitative data revealed the following positive attributes of the developed case studies: relative advantage of active learning and modeling; compatibility with a variety of courses; observability of case-related knowledge and skills; independent learning; and modifiability for use with other oral-systemic health issues. These positive attributes are expected to increase the likelihood that dental and dental hygiene faculty members will adopt the developed case study once it is available for use. The themes identified in this study could be applied to the development of future case studies and may provide broader insight that might prove useful for exploring differences in case study use across dental and dental hygiene curricula.

Low Speed and High Speed Correlation of SMART Active Flap Rotor Loads

NASA Technical Reports Server (NTRS)

Kottapalli, Sesi B. R.

2010-01-01

Measured, open loop and closed loop data from the SMART rotor test in the NASA Ames 40- by 80- Foot Wind Tunnel are compared with CAMRAD II calculations. One open loop high-speed case and four closed loop cases are considered. The closed loop cases include three high-speed cases and one low-speed case. Two of these high-speed cases include a 2 deg flap deflection at 5P case and a test maximum-airspeed case. This study follows a recent, open loop correlation effort that used a simple correction factor for the airfoil pitching moment Mach number. Compared to the earlier effort, the current open loop study considers more fundamental corrections based on advancing blade aerodynamic conditions. The airfoil tables themselves have been studied. Selected modifications to the HH-06 section flap airfoil pitching moment table are implemented. For the closed loop condition, the effect of the flap actuator is modeled by increased flap hinge stiffness. Overall, the open loop correlation is reasonable, thus confirming the basic correctness of the current semi-empirical modifications; the closed loop correlation is also reasonable considering that the current flap model is a first generation model. Detailed correlation results are given in the paper.

It’s Personal: Biology Instructors Prioritize Personal Evidence over Empirical Evidence in Teaching Decisions

PubMed Central

Andrews, Tessa C.; Lemons, Paula P.

2015-01-01

Despite many calls for undergraduate biology instructors to incorporate active learning into lecture courses, few studies have focused on what it takes for instructors to make this change. We sought to investigate the process of adopting and sustaining active-learning instruction. As a framework for our research, we used the innovation-decision model, a generalized model of how individuals adopt innovations. We interviewed 17 biology instructors who were attempting to implement case study teaching and conducted qualitative text analysis on interview data. The overarching theme that emerged from our analysis was that instructors prioritized personal experience—rather than empirical evidence—in decisions regarding case study teaching. We identified personal experiences that promote case study teaching, such as anecdotal observations of student outcomes, and those that hinder case study teaching, such as insufficient teaching skills. By analyzing the differences between experienced and new case study instructors, we discovered that new case study instructors need support to deal with unsupportive colleagues and to develop the skill set needed for an active-learning classroom. We generated hypotheses that are grounded in our data about effectively supporting instructors in adopting and sustaining active-learning strategies. We also synthesized our findings with existing literature to tailor the innovation-decision model. PMID:25713092

Modelling a flows in supply chain with analytical models: Case of a chemical industry

NASA Astrophysics Data System (ADS)

Benhida, Khalid; Azougagh, Yassine; Elfezazi, Said

2016-02-01

This study is interested on the modelling of the logistics flows in a supply chain composed on a production sites and a logistics platform. The contribution of this research is to develop an analytical model (integrated linear programming model), based on a case study of a real company operating in the phosphate field, considering a various constraints in this supply chain to resolve the planning problems for a better decision-making. The objectives of this model is to determine and define the optimal quantities of different products to route, to and from the various entities in the supply chain studied.

Cross-Border Collaboration in History among Nordic Students: A Case Study about Creating Innovative ICT Didactic Models

ERIC Educational Resources Information Center

Spante, Maria; Karlsen, Asgjerd Vea; Nortvig, Anne-Mette; Christiansen, Rene B.

2014-01-01

Gränsöverskridande Nordisk Undervisning/Utdanelse (GNU, meaning Cross-Border Nordic Education), the larger Nordic project, under which this case study was carried out, aims at developing innovative, cross-border teaching models in different subject domains in elementary school, including mathematics, language, science, social studies and history.…

Base stock system for patient vs impatient customers with varying demand distribution

NASA Astrophysics Data System (ADS)

Fathima, Dowlath; Uduman, P. Sheik

2013-09-01

An optimal Base-Stock inventory policy for Patient and Impatient Customers using finite-horizon models is examined. The Base stock system for Patient and Impatient customers is a different type of inventory policy. In case of the model I, Base stock for Patient customer case is evaluated using the Truncated Exponential Distribution. The model II involves the study of Base-stock inventory policies for Impatient customer. A study on these systems reveals that the Customers wait until the arrival of the next order or the customers leaves the system which leads to lost sale. In both the models demand during the period [0, t] is taken to be a random variable. In this paper, Truncated Exponential Distribution satisfies the Base stock policy for the patient customer as a continuous model. So far the Base stock for Impatient Customers leaded to a discrete case but, in this paper we have modeled this condition into a continuous case. We justify this approach mathematically and also numerically.

A study on the predictability of acute lymphoblastic leukaemia response to treatment using a hybrid oncosimulator.

PubMed

Ouzounoglou, Eleftherios; Kolokotroni, Eleni; Stanulla, Martin; Stamatakos, Georgios S

2018-02-06

Efficient use of Virtual Physiological Human (VPH)-type models for personalized treatment response prediction purposes requires a precise model parameterization. In the case where the available personalized data are not sufficient to fully determine the parameter values, an appropriate prediction task may be followed. This study, a hybrid combination of computational optimization and machine learning methods with an already developed mechanistic model called the acute lymphoblastic leukaemia (ALL) Oncosimulator which simulates ALL progression and treatment response is presented. These methods are used in order for the parameters of the model to be estimated for retrospective cases and to be predicted for prospective ones. The parameter value prediction is based on a regression model trained on retrospective cases. The proposed Hybrid ALL Oncosimulator system has been evaluated when predicting the pre-phase treatment outcome in ALL. This has been correctly achieved for a significant percentage of patient cases tested (approx. 70% of patients). Moreover, the system is capable of denying the classification of cases for which the results are not trustworthy enough. In that case, potentially misleading predictions for a number of patients are avoided, while the classification accuracy for the remaining patient cases further increases. The results obtained are particularly encouraging regarding the soundness of the proposed methodologies and their relevance to the process of achieving clinical applicability of the proposed Hybrid ALL Oncosimulator system and VPH models in general.

SetonWorldWide: A Case Study of Student Success

ERIC Educational Resources Information Center

DiSalvio, Philip

2009-01-01

This case study offers a strategic model of methods and services resulting in relatively high student success rates as defined by course completion of introductory first and second semester online courses. This strategic model is presented in the context of Sloan-C's "Five Pillars of Quality Online Education."

Transportation and socioeconomic impacts of bypasses on communities : an integrated synthesis of panel data, multilevel, and spatial econometric models with case studies.

DOT National Transportation Integrated Search

2011-09-21

Title: Transportation and Socioeconomic Impacts of Bypasses on Communities: An Integrated Synthesis of Panel Data, Multilevel, and Spatial Econometric Models with Case Studies. The title used at the start of this project was Transportation and Soc...

Innovations in Site Characterization Case Study: The Role of a Conceptual Site Model for Expedited Site Characterization Using the Triad Approach at the Poudre River Site, Fort Collins, Colorado

EPA Pesticide Factsheets

This case study examines how systematic planning, an evolving conceptual site model (CSM), dynamic work strategies, and real time measurement technologies can be used to unravel complex contaminant distribution patterns...

A Case Study of a School-Based Curriculum Development as a Model for INSET.

ERIC Educational Resources Information Center

Keiny, Shoshana; Weiss, Tzila

1986-01-01

Using a school-based curriculum development approach, the Israeli Environmental Education Project constructed a conceptual model for environmental education curriculum development. A team of teachers sharing knowledge developed a case study about water regulation and its consequences in a desert environment, which is described. (MT)

Lattice model for water-solute mixtures.

PubMed

Furlan, A P; Almarza, N G; Barbosa, M C

2016-10-14

A lattice model for the study of mixtures of associating liquids is proposed. Solvent and solute are modeled by adapting the associating lattice gas (ALG) model. The nature of interaction of solute/solvent is controlled by tuning the energy interactions between the patches of ALG model. We have studied three set of parameters, resulting in, hydrophilic, inert, and hydrophobic interactions. Extensive Monte Carlo simulations were carried out, and the behavior of pure components and the excess properties of the mixtures have been studied. The pure components, water (solvent) and solute, have quite similar phase diagrams, presenting gas, low density liquid, and high density liquid phases. In the case of solute, the regions of coexistence are substantially reduced when compared with both the water and the standard ALG models. A numerical procedure has been developed in order to attain series of results at constant pressure from simulations of the lattice gas model in the grand canonical ensemble. The excess properties of the mixtures, volume and enthalpy as the function of the solute fraction, have been studied for different interaction parameters of the model. Our model is able to reproduce qualitatively well the excess volume and enthalpy for different aqueous solutions. For the hydrophilic case, we show that the model is able to reproduce the excess volume and enthalpy of mixtures of small alcohols and amines. The inert case reproduces the behavior of large alcohols such as propanol, butanol, and pentanol. For the last case (hydrophobic), the excess properties reproduce the behavior of ionic liquids in aqueous solution.

Risky forward interest rates and swaptions: Quantum finance model and empirical results

NASA Astrophysics Data System (ADS)

Baaquie, Belal Ehsan; Yu, Miao; Bhanap, Jitendra

2018-02-01

Risk free forward interest rates (Diebold and Li, 2006 [1]; Jamshidian, 1991 [2 ]) - and their realization by US Treasury bonds as the leading exemplar - have been studied extensively. In Baaquie (2010), models of risk free bonds and their forward interest rates based on the quantum field theoretic formulation of the risk free forward interest rates have been discussed, including the empirical evidence supporting these models. The quantum finance formulation of risk free forward interest rates is extended to the case of risky forward interest rates. The examples of the Singapore and Malaysian forward interest rates are used as specific cases. The main feature of the quantum finance model is that the risky forward interest rates are modeled both a) as a stand-alone case as well as b) being driven by the US forward interest rates plus a spread - having its own term structure -above the US forward interest rates. Both the US forward interest rates and the term structure for the spread are modeled by a two dimensional Euclidean quantum field. As a precursor to the evaluation of put option of the Singapore coupon bond, the quantum finance model for swaptions is tested using empirical study of swaptions for the US Dollar -showing that the model is quite accurate. A prediction for the market price of the put option for the Singapore coupon bonds is obtained. The quantum finance model is generalized to study the Malaysian case and the Malaysian forward interest rates are shown to have anomalies absent for the US and Singapore case. The model's prediction for a Malaysian interest rate swap is obtained.

Simulations of the vortex in the Dellenback abrupt expansion, resembling a hydro turbine draft tube operating at part-load

NASA Astrophysics Data System (ADS)

Nilsson, H.

2012-11-01

This work presents an OpenFOAM case-study, based on the experimental studies of the swirling flow in the abrupt expansion by Dellenback et al.[1]. The case yields similar flow conditions as those of a helical vortex rope in a hydro turbine draft tube working at part-load. The case-study is set up similar to the ERCOFTAC Conical Diffuser and Centrifugal Pump OpenFOAM case-studies [2,3], making all the files available and the results fully reproducable using OpenSource software. The mesh generation is done using m4 scripting and the OpenFOAM built-in blockMesh mesh generator. The swirling inlet boundary condition is specified as an axi-symmetric profile. The outlet boundary condition uses the zeroGradient condition for all variables except for the pressure, which uses the fixed mean value boundary condition. The wall static pressure is probed at a number of locations during the simulations, and post-processing of the time-averaged solution is done using the OpenFOAM sample utility. Gnuplot scripts are provided for plotting the results. The computational results are compared to one of the operating conditions studied by Dellenback, and measurements for all the experimentally studied operating conditions are available in the case-study. Results from five cases are here presented, based on the kEpsilon model, the kOmegaSST model, and a filtered version of the same kOmegaSST model, named kOmegaSSTF [4,5]. Two different inlet boundary conditions are evaluated. It is shown that kEpsilon and kOmegaSST give steady solutions, while kOmegaSSTF gives a highly unsteady solution. The time-averaged solution of the kOmegaSSTF model is much more accurate than the other models. The kEpsilon and kOmegaSST models are thus unable to accurately model the effect of the large-scale unsteadiness, while kOmegaSSTF resolves those scales and models only the smaller scales. The use of two different boundary conditions shows that the boundary conditions are more important than the choice between kEpsilon and kOmegaSST, for the results just after the abrupt expansion.

Agent-Based vs. Equation-based Epidemiological Models:A Model Selection Case Study

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

Sukumar, Sreenivas R; Nutaro, James J

This paper is motivated by the need to design model validation strategies for epidemiological disease-spread models. We consider both agent-based and equation-based models of pandemic disease spread and study the nuances and complexities one has to consider from the perspective of model validation. For this purpose, we instantiate an equation based model and an agent based model of the 1918 Spanish flu and we leverage data published in the literature for our case- study. We present our observations from the perspective of each implementation and discuss the application of model-selection criteria to compare the risk in choosing one modeling paradigmmore » to another. We conclude with a discussion of our experience and document future ideas for a model validation framework.« less

Stochastic Robust Mathematical Programming Model for Power System Optimization

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

Liu, Cong; Changhyeok, Lee; Haoyong, Chen

2016-01-01

This paper presents a stochastic robust framework for two-stage power system optimization problems with uncertainty. The model optimizes the probabilistic expectation of different worst-case scenarios with ifferent uncertainty sets. A case study of unit commitment shows the effectiveness of the proposed model and algorithms.

New Horizons in a Next Generation School: A Case Study of Rural Alabama Middle School Students in a Transformational Initiative

ERIC Educational Resources Information Center

Lamey, Jack Harley, Sr.

2017-01-01

The purpose of this case study was to understand non-mastery for students in the mBolden Academic Model at Piedmont City Middle School (PCMS). The following research questions guided this study: How does the mBolden Academic Model influence student success at Piedmont City Middle School? Furthermore, this study has answered the following…

Using generalized additive (mixed) models to analyze single case designs.

PubMed

Shadish, William R; Zuur, Alain F; Sullivan, Kristynn J

2014-04-01

This article shows how to apply generalized additive models and generalized additive mixed models to single-case design data. These models excel at detecting the functional form between two variables (often called trend), that is, whether trend exists, and if it does, what its shape is (e.g., linear and nonlinear). In many respects, however, these models are also an ideal vehicle for analyzing single-case designs because they can consider level, trend, variability, overlap, immediacy of effect, and phase consistency that single-case design researchers examine when interpreting a functional relation. We show how these models can be implemented in a wide variety of ways to test whether treatment is effective, whether cases differ from each other, whether treatment effects vary over cases, and whether trend varies over cases. We illustrate diagnostic statistics and graphs, and we discuss overdispersion of data in detail, with examples of quasibinomial models for overdispersed data, including how to compute dispersion and quasi-AIC fit indices in generalized additive models. We show how generalized additive mixed models can be used to estimate autoregressive models and random effects and discuss the limitations of the mixed models compared to generalized additive models. We provide extensive annotated syntax for doing all these analyses in the free computer program R. Copyright © 2013 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Model Checking Failed Conjectures in Theorem Proving: A Case Study

NASA Technical Reports Server (NTRS)

Pike, Lee; Miner, Paul; Torres-Pomales, Wilfredo

2004-01-01

Interactive mechanical theorem proving can provide high assurance of correct design, but it can also be a slow iterative process. Much time is spent determining why a proof of a conjecture is not forthcoming. In some cases, the conjecture is false and in others, the attempted proof is insufficient. In this case study, we use the SAL family of model checkers to generate a concrete counterexample to an unproven conjecture specified in the mechanical theorem prover, PVS. The focus of our case study is the ROBUS Interactive Consistency Protocol. We combine the use of a mechanical theorem prover and a model checker to expose a subtle flaw in the protocol that occurs under a particular scenario of faults and processor states. Uncovering the flaw allows us to mend the protocol and complete its general verification in PVS.

The Aggregation of Single-Case Results Using Hierarchical Linear Models

ERIC Educational Resources Information Center

Van den Noortgate, Wim; Onghena, Patrick

2007-01-01

To investigate the generalizability of the results of single-case experimental studies, evaluating the effect of one or more treatments, in applied research various simultaneous and sequential replication strategies are used. We discuss one approach for aggregating the results for single-cases: the use of hierarchical linear models. This approach…

Option pricing, stochastic volatility, singular dynamics and constrained path integrals

NASA Astrophysics Data System (ADS)

Contreras, Mauricio; Hojman, Sergio A.

2014-01-01

Stochastic volatility models have been widely studied and used in the financial world. The Heston model (Heston, 1993) [7] is one of the best known models to deal with this issue. These stochastic volatility models are characterized by the fact that they explicitly depend on a correlation parameter ρ which relates the two Brownian motions that drive the stochastic dynamics associated to the volatility and the underlying asset. Solutions to the Heston model in the context of option pricing, using a path integral approach, are found in Lemmens et al. (2008) [21] while in Baaquie (2007,1997) [12,13] propagators for different stochastic volatility models are constructed. In all previous cases, the propagator is not defined for extreme cases ρ=±1. It is therefore necessary to obtain a solution for these extreme cases and also to understand the origin of the divergence of the propagator. In this paper we study in detail a general class of stochastic volatility models for extreme values ρ=±1 and show that in these two cases, the associated classical dynamics corresponds to a system with second class constraints, which must be dealt with using Dirac’s method for constrained systems (Dirac, 1958,1967) [22,23] in order to properly obtain the propagator in the form of a Euclidean Hamiltonian path integral (Henneaux and Teitelboim, 1992) [25]. After integrating over momenta, one gets an Euclidean Lagrangian path integral without constraints, which in the case of the Heston model corresponds to a path integral of a repulsive radial harmonic oscillator. In all the cases studied, the price of the underlying asset is completely determined by one of the second class constraints in terms of volatility and plays no active role in the path integral.

QSPR modeling: graph connectivity indices versus line graph connectivity indices

PubMed

Basak; Nikolic; Trinajstic; Amic; Beslo

2000-07-01

Five QSPR models of alkanes were reinvestigated. Properties considered were molecular surface-dependent properties (boiling points and gas chromatographic retention indices) and molecular volume-dependent properties (molar volumes and molar refractions). The vertex- and edge-connectivity indices were used as structural parameters. In each studied case we computed connectivity indices of alkane trees and alkane line graphs and searched for the optimum exponent. Models based on indices with an optimum exponent and on the standard value of the exponent were compared. Thus, for each property we generated six QSPR models (four for alkane trees and two for the corresponding line graphs). In all studied cases QSPR models based on connectivity indices with optimum exponents have better statistical characteristics than the models based on connectivity indices with the standard value of the exponent. The comparison between models based on vertex- and edge-connectivity indices gave in two cases (molar volumes and molar refractions) better models based on edge-connectivity indices and in three cases (boiling points for octanes and nonanes and gas chromatographic retention indices) better models based on vertex-connectivity indices. Thus, it appears that the edge-connectivity index is more appropriate to be used in the structure-molecular volume properties modeling and the vertex-connectivity index in the structure-molecular surface properties modeling. The use of line graphs did not improve the predictive power of the connectivity indices. Only in one case (boiling points of nonanes) a better model was obtained with the use of line graphs.

Synthesis of Single-Case Experimental Data: A Comparison of Alternative Multilevel Approaches

ERIC Educational Resources Information Center

Ferron, John; Van den Noortgate, Wim; Beretvas, Tasha; Moeyaert, Mariola; Ugille, Maaike; Petit-Bois, Merlande; Baek, Eun Kyeng

2013-01-01

Single-case or single-subject experimental designs (SSED) are used to evaluate the effect of one or more treatments on a single case. Although SSED studies are growing in popularity, the results are in theory case-specific. One systematic and statistical approach for combining single-case data within and across studies is multilevel modeling. The…

Using Visual Analysis to Evaluate and Refine Multilevel Models of Single-Case Studies

ERIC Educational Resources Information Center

Baek, Eun Kyeng; Petit-Bois, Merlande; Van den Noortgate, Wim; Beretvas, S. Natasha; Ferron, John M.

2016-01-01

In special education, multilevel models of single-case research have been used as a method of estimating treatment effects over time and across individuals. Although multilevel models can accurately summarize the effect, it is known that if the model is misspecified, inferences about the effects can be biased. Concern with the potential for model…

Evolution of Forms of Representation in a Modelling Activity: A Case Study

ERIC Educational Resources Information Center

Garuti, Rossella; Dapueto, Carlo; Boero, Paolo

2003-01-01

The report describes a mathematical modelling activity of a natural phenomenon (transmission of hereditary characters in a codominance case) using the concept of model as a theoretical instrument. The chosen tool enables us to show how the construction of a link between reality and a model is related to the evolution of the graphical…

An integrated hypnotherapeutic model for the treatment of childhood sexual trauma: a case study.

PubMed

Fourie, Gerda; Guse, Tharina

2011-01-01

Sexual abuse appears to constitute a major risk factor for a variety of problems in adult life. The effects of abuse on adult living are not uniform therefore intervention strategies should be individualized to address unique symptom constellations. The purpose of this paper is to introduce an integrated Ericksonian and Ego state therapy approach, based on a strengths perspective for the treatment of survivors of childhood sexual abuse. The theoretical foundation for this model is described, followed by a case study. The case study demonstrates how application of this model enabled the client to resolve the experience of sexual abuse, as well as to enhance her sense of general psychological well-being.

Building a Better Applicant Pool--A Case Study of the Use of Predictive Modeling and Market Segmentation to Build and Enroll Better Pools of Students

ERIC Educational Resources Information Center

Herridge, Bart; Heil, Robert

2003-01-01

Predictive modeling has been a popular topic in higher education for the last few years. This case study shows an example of an effective use of modeling combined with market segmentation to strategically divide large, unmanageable prospect and inquiry pools and convert them into applicants, and eventually, enrolled students. (Contains 6 tables.)

Case Studies of Successful Schoolwide Enrichment Model-Reading (SEM-R) Classroom Implementations. Research Monograph Series. RM10204

ERIC Educational Resources Information Center

Reis, Sally M.; Little, Catherine A.; Fogarty, Elizabeth; Housand, Angela M.; Housand, Brian C.; Sweeny, Sheelah M.; Eckert, Rebecca D.; Muller, Lisa M.

2010-01-01

The purpose of this qualitative study was to examine the scaling up of the Schoolwide Enrichment Model in Reading (SEM-R) in 11 elementary and middle schools in geographically diverse sites across the country. Qualitative comparative analysis was used in this study, with multiple data sources compiled into 11 in-depth school case studies…

The UMO (University of Maine, Orono) Teacher Training Program: A Case Study and a Model.

ERIC Educational Resources Information Center

Miller, James R.; McNally, Harry

This case study presents a model of the University of Maine, Orono, pre-service program for preparing secondary social studies teachers. Focus is on the Foundations Component and the Methods Component, either of which can function independently of the other. Only brief mention is made of either the Exploratory Field Experience Component or the…

FLAME: A platform for high performance computing of complex systems, applied for three case studies

DOE PAGES

Kiran, Mariam; Bicak, Mesude; Maleki-Dizaji, Saeedeh; ...

2011-01-01

FLAME allows complex models to be automatically parallelised on High Performance Computing (HPC) grids enabling large number of agents to be simulated over short periods of time. Modellers are hindered by complexities of porting models on parallel platforms and time taken to run large simulations on a single machine, which FLAME overcomes. Three case studies from different disciplines were modelled using FLAME, and are presented along with their performance results on a grid.

CoopEUS Case Study: Tsunami Modelling and Early Warning Systems for Near Source Areas (Mediterranean, Juan de Fuca).

NASA Astrophysics Data System (ADS)

Beranzoli, Laura; Best, Mairi; Chierici, Francesco; Embriaco, Davide; Galbraith, Nan; Heeseman, Martin; Kelley, Deborah; Pirenne, Benoit; Scofield, Oscar; Weller, Robert

2015-04-01

There is a need for tsunami modeling and early warning systems for near-source areas. For example this is a common public safety threat in the Mediterranean and Juan de Fuca/NE Pacific Coast of N.A.; Regions covered by the EMSO, OOI, and ONC ocean observatories. Through the CoopEUS international cooperation project, a number of environmental research infrastructures have come together to coordinate efforts on environmental challenges; this tsunami case study tackles one such challenge. There is a mutual need of tsunami event field data and modeling to deepen our experience in testing methodology and developing real-time data processing. Tsunami field data are already available for past events, part of this use case compares these for compatibility, gap analysis, and model groundtruthing. It also reviews sensors needed and harmonizes instrument settings. Sensor metadata and registries are compared, harmonized, and aligned. Data policies and access are also compared and assessed for gap analysis. Modelling algorithms are compared and tested against archived and real-time data. This case study will then be extended to other related tsunami data and model sources globally with similar geographic and seismic scenarios.

One size does not fit all: Adapting mark-recapture and occupancy models for state uncertainty

USGS Publications Warehouse

Kendall, W.L.; Thomson, David L.; Cooch, Evan G.; Conroy, Michael J.

2009-01-01

Multistate capture?recapture models continue to be employed with greater frequency to test hypotheses about metapopulation dynamics and life history, and more recently disease dynamics. In recent years efforts have begun to adjust these models for cases where there is uncertainty about an animal?s state upon capture. These efforts can be categorized into models that permit misclassification between two states to occur in either direction or one direction, where state is certain for a subset of individuals or is always uncertain, and where estimation is based on one sampling occasion per period of interest or multiple sampling occasions per period. State uncertainty also arises in modeling patch occupancy dynamics. I consider several case studies involving bird and marine mammal studies that illustrate how misclassified states can arise, and outline model structures for properly utilizing the data that are produced. In each case misclassification occurs in only one direction (thus there is a subset of individuals or patches where state is known with certainty), and there are multiple sampling occasions per period of interest. For the cases involving capture?recapture data I allude to a general model structure that could include each example as a special case. However, this collection of cases also illustrates how difficult it is to develop a model structure that can be directly useful for answering every ecological question of interest and account for every type of data from the field.

A devolved model for public involvement in the field of mental health research: case study learning.

PubMed

Moule, Pam; Davies, Rosie

2016-12-01

Patient and public involvement in all aspects of research is espoused and there is a continued interest in understanding its wider impact. Existing investigations have identified both beneficial outcomes and remaining issues. This paper presents the impact of public involvement in one case study led by a mental health charity conducted as part of a larger research project. The case study used a devolved model of working, contracting with service user-led organizations to maximize the benefits of local knowledge on the implementation of personalized budgets, support recruitment and local user-led organizations. To understand the processes and impact of public involvement in a devolved model of working with user-led organizations. Multiple data collection methods were employed throughout 2012. These included interviews with the researchers (n = 10) and research partners (n = 5), observation of two case study meetings and the review of key case study documentation. Analysis was conducted in NVivo10 using a coding framework developed following a literature review. Five key themes emerged from the data; Devolved model, Nature of involvement, Enabling factors, Implementation challenges and Impact. While there were some challenges of implementing the devolved model it is clear that our findings add to the growing understanding of the positive benefits research partners can bring to complex research. A devolved model can support the involvement of user-led organizations in research if there is a clear understanding of the underpinning philosophy and support mechanisms are in place. © 2015 The Authors. Health Expectations Published by John Wiley & Sons Ltd.

The Vroom and Yetton Normative Leadership Model Applied to Public School Case Examples.

ERIC Educational Resources Information Center

Sample, John

This paper seeks to familiarize school administrators with the Vroom and Yetton Normative Leadership model by presenting its essential components and providing original case studies for its application to school settings. The five decision-making methods of the Vroom and Yetton model, including two "autocratic," two…

Integration of Technology into the Classroom: Case Studies.

ERIC Educational Resources Information Center

Johnson, D. LaMont, Ed.; Maddux, Cleborne D., Ed.; Liu, Leping, Ed.

This book contains the following case studies on the integration of technology in education: (1) "First Steps toward a Statistically Generated Information Technology Integration Model" (D. LaMont Johnson and Leping Liu); (2) "Case Studies: Are We Rejecting Rigor or Rediscovering Richness?" (Cleborne D. Maddux); (3)…

The Value of SysML Modeling During System Operations: A Case Study

NASA Technical Reports Server (NTRS)

Dutenhoffer, Chelsea; Tirona, Joseph

2013-01-01

System models are often touted as engineering tools that promote better understanding of systems, but these models are typically created during system design. The Ground Data System (GDS) team for the Dawn spacecraft took on a case study to see if benefits could be achieved by starting a model of a system already in operations. This paper focuses on the four steps the team undertook in modeling the Dawn GDS: defining a model structure, populating model elements, verifying that the model represented reality, and using the model to answer system-level questions and simplify day-to-day tasks. Throughout this paper the team outlines our thought processes and the system insights the model provided.

The value of SysML modeling during system operations: A case study

NASA Astrophysics Data System (ADS)

Dutenhoffer, C.; Tirona, J.

System models are often touted as engineering tools that promote better understanding of systems, but these models are typically created during system design. The Ground Data System (GDS) team for the Dawn spacecraft took on a case study to see if benefits could be achieved by starting a model of a system already in operations. This paper focuses on the four steps the team undertook in modeling the Dawn GDS: defining a model structure, populating model elements, verifying that the model represented reality, and using the model to answer system-level questions and simplify day-to-day tasks. Throughout this paper the team outlines our thought processes and the system insights the model provided.

The phase diagrams of the ± K model on the Bethe lattice

NASA Astrophysics Data System (ADS)

Albayrak, Erhan

2015-07-01

The biquadratic exchange interaction is randomized in a bimodal form with probabilities (p) and (1 - p) for the cases with K > 0 (attractive case) and K < 0 (repulsive case), respectively, and its effects on the phase diagrams of the spin-1 Blume-Emery-Griffiths model are studied on the Bethe lattice by using the recursion relations. It was found that the critical behaviors of the model change drastically.

Genetic programming based quantitative structure-retention relationships for the prediction of Kovats retention indices.

PubMed

Goel, Purva; Bapat, Sanket; Vyas, Renu; Tambe, Amruta; Tambe, Sanjeev S

2015-11-13

The development of quantitative structure-retention relationships (QSRR) aims at constructing an appropriate linear/nonlinear model for the prediction of the retention behavior (such as Kovats retention index) of a solute on a chromatographic column. Commonly, multi-linear regression and artificial neural networks are used in the QSRR development in the gas chromatography (GC). In this study, an artificial intelligence based data-driven modeling formalism, namely genetic programming (GP), has been introduced for the development of quantitative structure based models predicting Kovats retention indices (KRI). The novelty of the GP formalism is that given an example dataset, it searches and optimizes both the form (structure) and the parameters of an appropriate linear/nonlinear data-fitting model. Thus, it is not necessary to pre-specify the form of the data-fitting model in the GP-based modeling. These models are also less complex, simple to understand, and easy to deploy. The effectiveness of GP in constructing QSRRs has been demonstrated by developing models predicting KRIs of light hydrocarbons (case study-I) and adamantane derivatives (case study-II). In each case study, two-, three- and four-descriptor models have been developed using the KRI data available in the literature. The results of these studies clearly indicate that the GP-based models possess an excellent KRI prediction accuracy and generalization capability. Specifically, the best performing four-descriptor models in both the case studies have yielded high (>0.9) values of the coefficient of determination (R(2)) and low values of root mean squared error (RMSE) and mean absolute percent error (MAPE) for training, test and validation set data. The characteristic feature of this study is that it introduces a practical and an effective GP-based method for developing QSRRs in gas chromatography that can be gainfully utilized for developing other types of data-driven models in chromatography science. Copyright © 2015 Elsevier B.V. All rights reserved.

New Lives: Some Case Studies in Minamata.

ERIC Educational Resources Information Center

Tsurumi, Kazuko

Three case studies of young Japanese adults who fell ill with Minamata disease (a form of methyl-mercury poisoning) are presented and the adjustment of the individuals to the disease is analyzed in terms of a model of creativity. The model distinguishes three types of creativity: identificational (in which one identifies with old ideas and…

Innovating Education with an Educational Modeling Language: Two Case Studies

ERIC Educational Resources Information Center

Sloep, Peter B.; van Bruggen, Jan; Tattersall, Colin; Vogten, Hubert; Koper, Rob; Brouns, Francis; van Rosmalen, Peter

2006-01-01

The intent of this study was to investigate how to maximize the chances of success of an educational innovation--specifically one based on the implementation of the educational modeling language called EML. This language is both technically and organizationally demanding. Two different implementation cases were investigated, one situated in an…

Two case studies in river naturalization: planform migration and bank erosion control

NASA Astrophysics Data System (ADS)

Abad, J. D.; Guneralp, I.; Rhoads, B. L.; Garcia, M. H.

2005-05-01

A sound understanding of river planform evolution and bank erosion control, along with integration of expertise from several disciplines is required for the development of predictive models for river naturalization. Over the last few years, several methodologies have been presented for naturalization projects, from purely heuristic to more advanced methods. Since the time and space scales of concern in naturalization vary widely, there is a need for appropriate tools at a variety of time and space scales. This study presents two case studies at different scales. The first case study describes the prediction of river planform evolution for a remeandering project based on a simplified two-dimensional hydrodynamic model. The second case study describes the applicability of a Computational Fluid Dynamics (CFD) model for evaluating the effectiveness of bank-erosion control structures in individual meander bends. Understanding the hydrodynamic influence of control structures on flow through bends allows accurate prediction of depositional and erosional distribution patterns, resulting in better assessment on river planform stability, especially for the case of natural complex systems. The first case study introduces a mathematical model for evolution of meandering rivers that can be used in remeandering projects. In United States in particular, several rivers have been channelized in the past causing environmental and ecological problems. Following Newton's third law, "for every action, there is a reaction", naturalization techniques evolve as natural reactive solutions to channelization. This model (herein referred as RVR Meander) can be used as a stand-alone Windows application or as module in a Geographic Information System. The model was applied to the Poplar Creek re-meanderization project and used to evaluate re-meandering alternatives for an approximately 800-meter long reach of Poplar Creek that was straightened in 1938. The second case study describes a streambank protection project using bendway weirs. In the State of Illinois, bendway weirs constructed of rock have been installed at hundreds of sites, especially on small streams, to control streambank erosion. Bendway weirs are low hard structures installed in the concave bank of a meander bend. Design criteria for these weirs are approximate and have not been rigorously evaluated for overall effectiveness at low-, medium- and high flows. This initial step of the study attempted to describe the hydrodynamics around the weirs and the influence of the hydrodynamic patterns on sediment transport (near-field and far-field). To do that, a state-of-the-art three-dimensional CFD model was used to simulate flow through meander bends where 3D velocity measurements have been obtained to validate model predictions at low stages. Results indicate that the weirs produce highly complex patterns of flow around the weirs, which in some cases may actually increase erosional potential near the outer bank. These two case studies represent components of an emerging initiative to develop predictive tools for naturalization over a range of spatial and temporal scales

Climate variations and salmonellosis transmission in Adelaide, South Australia: a comparison between regression models

NASA Astrophysics Data System (ADS)

Zhang, Ying; Bi, Peng; Hiller, Janet

2008-01-01

This is the first study to identify appropriate regression models for the association between climate variation and salmonellosis transmission. A comparison between different regression models was conducted using surveillance data in Adelaide, South Australia. By using notified salmonellosis cases and climatic variables from the Adelaide metropolitan area over the period 1990-2003, four regression methods were examined: standard Poisson regression, autoregressive adjusted Poisson regression, multiple linear regression, and a seasonal autoregressive integrated moving average (SARIMA) model. Notified salmonellosis cases in 2004 were used to test the forecasting ability of the four models. Parameter estimation, goodness-of-fit and forecasting ability of the four regression models were compared. Temperatures occurring 2 weeks prior to cases were positively associated with cases of salmonellosis. Rainfall was also inversely related to the number of cases. The comparison of the goodness-of-fit and forecasting ability suggest that the SARIMA model is better than the other three regression models. Temperature and rainfall may be used as climatic predictors of salmonellosis cases in regions with climatic characteristics similar to those of Adelaide. The SARIMA model could, thus, be adopted to quantify the relationship between climate variations and salmonellosis transmission.

[Application of ARIMA model to predict number of malaria cases in China].

PubMed

Hui-Yu, H; Hua-Qin, S; Shun-Xian, Z; Lin, A I; Yan, L U; Yu-Chun, C; Shi-Zhu, L I; Xue-Jiao, T; Chun-Li, Y; Wei, H U; Jia-Xu, C

2017-08-15

Objective To study the application of autoregressive integrated moving average (ARIMA) model to predict the monthly reported malaria cases in China, so as to provide a reference for prevention and control of malaria. Methods SPSS 24.0 software was used to construct the ARIMA models based on the monthly reported malaria cases of the time series of 20062015 and 2011-2015, respectively. The data of malaria cases from January to December, 2016 were used as validation data to compare the accuracy of the two ARIMA models. Results The models of the monthly reported cases of malaria in China were ARIMA (2, 1, 1) (1, 1, 0) 12 and ARIMA (1, 0, 0) (1, 1, 0) 12 respectively. The comparison between the predictions of the two models and actual situation of malaria cases showed that the ARIMA model based on the data of 2011-2015 had a higher accuracy of forecasting than the model based on the data of 2006-2015 had. Conclusion The establishment and prediction of ARIMA model is a dynamic process, which needs to be adjusted unceasingly according to the accumulated data, and in addition, the major changes of epidemic characteristics of infectious diseases must be considered.

Teaching Mathematical Modelling for Earth Sciences via Case Studies

NASA Astrophysics Data System (ADS)

Yang, Xin-She

2010-05-01

Mathematical modelling is becoming crucially important for earth sciences because the modelling of complex systems such as geological, geophysical and environmental processes requires mathematical analysis, numerical methods and computer programming. However, a substantial fraction of earth science undergraduates and graduates may not have sufficient skills in mathematical modelling, which is due to either limited mathematical training or lack of appropriate mathematical textbooks for self-study. In this paper, we described a detailed case-study-based approach for teaching mathematical modelling. We illustrate how essential mathematical skills can be developed for students with limited training in secondary mathematics so that they are confident in dealing with real-world mathematical modelling at university level. We have chosen various topics such as Airy isostasy, greenhouse effect, sedimentation and Stokes' flow,free-air and Bouguer gravity, Brownian motion, rain-drop dynamics, impact cratering, heat conduction and cooling of the lithosphere as case studies; and we use these step-by-step case studies to teach exponentials, logarithms, spherical geometry, basic calculus, complex numbers, Fourier transforms, ordinary differential equations, vectors and matrix algebra, partial differential equations, geostatistics and basic numeric methods. Implications for teaching university mathematics for earth scientists for tomorrow's classroom will also be discussed. Refereces 1) D. L. Turcotte and G. Schubert, Geodynamics, 2nd Edition, Cambridge University Press, (2002). 2) X. S. Yang, Introductory Mathematics for Earth Scientists, Dunedin Academic Press, (2009).

Prediction model for the return to work of workers with injuries in Hong Kong.

PubMed

Xu, Yanwen; Chan, Chetwyn C H; Lo, Karen Hui Yu-Ling; Tang, Dan

2008-01-01

This study attempts to formulate a prediction model of return to work for a group of workers who have been suffering from chronic pain and physical injury while also being out of work in Hong Kong. The study used Case-based Reasoning (CBR) method, and compared the result with the statistical method of logistic regression model. The database of the algorithm of CBR was composed of 67 cases who were also used in the logistic regression model. The testing cases were 32 participants who had a similar background and characteristics to those in the database. The methods of setting constraints and Euclidean distance metric were used in CBR to search the closest cases to the trial case based on the matrix. The usefulness of the algorithm was tested on 32 new participants, and the accuracy of predicting return to work outcomes was 62.5%, which was no better than the 71.2% accuracy derived from the logistic regression model. The results of the study would enable us to have a better understanding of the CBR applied in the field of occupational rehabilitation by comparing with the conventional regression analysis. The findings would also shed light on the development of relevant interventions for the return-to-work process of these workers.

Crash data modeling with a generalized estimator.

PubMed

Ye, Zhirui; Xu, Yueru; Lord, Dominique

2018-08-01

The investigation of relationships between traffic crashes and relevant factors is important in traffic safety management. Various methods have been developed for modeling crash data. In real world scenarios, crash data often display the characteristics of over-dispersion. However, on occasions, some crash datasets have exhibited under-dispersion, especially in cases where the data are conditioned upon the mean. The commonly used models (such as the Poisson and the NB regression models) have associated limitations to cope with various degrees of dispersion. In light of this, a generalized event count (GEC) model, which can be generally used to handle over-, equi-, and under-dispersed data, is proposed in this study. This model was first applied to case studies using data from Toronto, characterized by over-dispersion, and then to crash data from railway-highway crossings in Korea, characterized with under-dispersion. The results from the GEC model were compared with those from the Negative binomial and the hyper-Poisson models. The cases studies show that the proposed model provides good performance for crash data characterized with over- and under-dispersion. Moreover, the proposed model simplifies the modeling process and the prediction of crash data. Copyright © 2018 Elsevier Ltd. All rights reserved.

The role of production and teamwork practices in construction safety: a cognitive model and an empirical case study.

PubMed

Mitropoulos, Panagiotis Takis; Cupido, Gerardo

2009-01-01

In construction, the challenge for researchers and practitioners is to develop work systems (production processes and teams) that can achieve high productivity and high safety at the same time. However, construction accident causation models ignore the role of work practices and teamwork. This study investigates the mechanisms by which production and teamwork practices affect the likelihood of accidents. The paper synthesizes a new model for construction safety based on the cognitive perspective (Fuller's Task-Demand-Capability Interface model, 2005) and then presents an exploratory case study. The case study investigates and compares the work practices of two residential framing crews: a 'High Reliability Crew' (HRC)--that is, a crew with exceptional productivity and safety over several years, and an average performing crew from the same company. The model explains how the production and teamwork practices generate the work situations that workers face (the task demands) and affect the workers ability to cope (capabilities). The case study indicates that the work practices of the HRC directly influence the task demands and match them with the applied capabilities. These practices were guided by the 'principle' of avoiding errors and rework and included work planning and preparation, work distribution, managing the production pressures, and quality and behavior monitoring. The Task Demand-Capability model links construction research to a cognitive model of accident causation and provides a new way to conceptualize safety as an emergent property of the production practices and teamwork processes. The empirical evidence indicates that the crews' work practices and team processes strongly affect the task demands, the applied capabilities, and the match between demands and capabilities. The proposed model and the exploratory case study will guide further discovery of work practices and teamwork processes that can increase both productivity and safety in construction operations. Such understanding will enable training of construction foremen and crews in these practices to systematically develop high reliability crews.

Development of an Evaporation Sub-model and Simulation of Multiple Droplet Impingement in Volume of Fluid Method

NASA Astrophysics Data System (ADS)

Potham, Sathya Prasad

Droplet collision and impingement on a substrate are widely observed phenomenon in many applications like spray injection of Internal Combustion Engines, spray cooling, spray painting and atomizers used in propulsion applications. Existing Lagrangian models do not provide a comprehensive picture of the outcome of these events and may involve model constants requiring experimental data for validation. Physics based models like Volume of Fluid (VOF) method involve no parametric tuning and are more accurate. The aim of this thesis is to extend the basic VOF method with an evaporation sub-model and implement in an open source Computational Fluid Dynamics (CFD) software, OpenFOAM. The new model is applied to numerically study the evaporation of spherical n-heptane droplets impinging on a hot wall at atmospheric pressure and a temperature above the Leidenfrost temperature. An additional vapor phase is introduced apart from the liquid and gas phases to understand the mixing and diffusion of vapor and gas phases. The evaporation model is validated quantitatively and qualitatively with fundamental problems having analytical solutions and published results. The effect of droplet number and arrangement on evaporation is studied by three cases with one (Case 1), two (Case 2) and four (Case 3) droplets impinging on hot wall in film boiling regime at a fixed temperature of wall and a constant non-dimensional distance between droplets. Droplet lift and spread, surface temperature, heat transfer, and evaporation rate are examined. It was observed that more liquid mass evaporated in Case 1 compared to the other cases. Droplet levitation begins early in Case 1 and very high levitation observed was partially due to contraction of its shape from elongated to a more circular form. Average surface temperature was also considerably reduced in Case 1 due to high droplet levitation.

The neglected tool in the Bayesian ecologist's shed: a case study testing informative priors' effect on model accuracy

PubMed Central

Morris, William K; Vesk, Peter A; McCarthy, Michael A; Bunyavejchewin, Sarayudh; Baker, Patrick J

2015-01-01

Despite benefits for precision, ecologists rarely use informative priors. One reason that ecologists may prefer vague priors is the perception that informative priors reduce accuracy. To date, no ecological study has empirically evaluated data-derived informative priors' effects on precision and accuracy. To determine the impacts of priors, we evaluated mortality models for tree species using data from a forest dynamics plot in Thailand. Half the models used vague priors, and the remaining half had informative priors. We found precision was greater when using informative priors, but effects on accuracy were more variable. In some cases, prior information improved accuracy, while in others, it was reduced. On average, models with informative priors were no more or less accurate than models without. Our analyses provide a detailed case study on the simultaneous effect of prior information on precision and accuracy and demonstrate that when priors are specified appropriately, they lead to greater precision without systematically reducing model accuracy. PMID:25628867

The neglected tool in the Bayesian ecologist's shed: a case study testing informative priors' effect on model accuracy.

PubMed

Morris, William K; Vesk, Peter A; McCarthy, Michael A; Bunyavejchewin, Sarayudh; Baker, Patrick J

2015-01-01

Despite benefits for precision, ecologists rarely use informative priors. One reason that ecologists may prefer vague priors is the perception that informative priors reduce accuracy. To date, no ecological study has empirically evaluated data-derived informative priors' effects on precision and accuracy. To determine the impacts of priors, we evaluated mortality models for tree species using data from a forest dynamics plot in Thailand. Half the models used vague priors, and the remaining half had informative priors. We found precision was greater when using informative priors, but effects on accuracy were more variable. In some cases, prior information improved accuracy, while in others, it was reduced. On average, models with informative priors were no more or less accurate than models without. Our analyses provide a detailed case study on the simultaneous effect of prior information on precision and accuracy and demonstrate that when priors are specified appropriately, they lead to greater precision without systematically reducing model accuracy.

Aquatic Trophic Productivity model: A decision support model for river restoration planning in the Methow River, Washington

USGS Publications Warehouse

Benjamin, Joseph R.; Bellmore, J. Ryan

2016-05-19

In this report, we outline the structure of a stream food-web model constructed to explore how alternative river restoration strategies may affect stream fish populations. We have termed this model the “Aquatic Trophic Productivity model” (ATP). We present the model structure, followed by three case study applications of the model to segments of the Methow River watershed in northern Washington. For two case studies (middle Methow River and lower Twisp River floodplain), we ran a series of simulations to explore how food-web dynamics respond to four distinctly different, but applied, strategies in the Methow River watershed: (1) reconnection of floodplain aquatic habitats, (2) riparian vegetation planting, (3) nutrient augmentation (that is, salmon carcass addition), and (4) enhancement of habitat suitability for fish. For the third case study, we conducted simulations to explore the potential fish and food-web response to habitat improvements conducted in 2012 at the Whitefish Island Side Channel, located in the middle Methow River.

Bridging the Performance Gap with Ergonomics: A Case Study

ERIC Educational Resources Information Center

Rethaber, James D.

2011-01-01

Faced with increased incidences of work-related strain and sprain injuries and OSHA-recordable injuries, the organization in this case study details how it resolved these performance-related issues. This case study also demonstrates the effectiveness of Thomas Gilbert's (1978) Behavior Engineering Model as a tool for analyzing, defining, and…

American Association of University Women: Branch Operations Data Modeling Case

ERIC Educational Resources Information Center

Harris, Ranida B.; Wedel, Thomas L.

2015-01-01

A nationally prominent woman's advocacy organization is featured in this case study. The scenario may be used as a teaching case, an assignment, or a project in systems analysis and design as well as database design classes. Students are required to document the system operations and requirements, apply logical data modeling concepts, and design…

Tuberculosis active case finding in Cambodia: a pragmatic, cost-effectiveness comparison of three implementation models.

PubMed

James, Richard; Khim, Keovathanak; Boudarene, Lydia; Yoong, Joanne; Phalla, Chea; Saint, Saly; Koeut, Pichenda; Mao, Tan Eang; Coker, Richard; Khan, Mishal Sameer

2017-08-22

Globally, almost 40% of tuberculosis (TB) patients remain undiagnosed, and those that are diagnosed often experience prolonged delays before initiating correct treatment, leading to ongoing transmission. While there is a push for active case finding (ACF) to improve early detection and treatment of TB, there is extremely limited evidence about the relative cost-effectiveness of different ACF implementation models. Cambodia presents a unique opportunity for addressing this gap in evidence as ACF has been implemented using different models, but no comparisons have been conducted. The objective of our study is to contribute to knowledge and methodology on comparing cost-effectiveness of alternative ACF implementation models from the health service perspective, using programmatic data, in order to inform national policy and practice. We retrospectively compared three distinct ACF implementation models - door to door symptom screening in urban slums, checking contacts of TB patients, and door to door symptom screening focusing on rural populations aged above 55 - in terms of the number of new bacteriologically-positive pulmonary TB cases diagnosed and the cost of implementation assuming activities are conducted by the national TB program of Cambodia. We calculated the cost per additional case detected using the alternative ACF models. Our analysis, which is the first of its kind for TB, revealed that the ACF model based on door to door screening in poor urban areas of Phnom Penh was the most cost-effective (249 USD per case detected, 737 cases diagnosed), followed by the model based on testing contacts of TB patients (308 USD per case detected, 807 cases diagnosed), and symptomatic screening of older rural populations (316 USD per case detected, 397 cases diagnosed). Our study provides new evidence on the relative effectiveness and economics of three implementation models for enhanced TB case finding, in line with calls for data from 'routine conditions' to be included in disease control program strategic planning. Such cost-effectiveness comparisons are essential to inform resource allocation decisions of national policy makers in resource constraint settings. We applied a novel, pragmatic methodological approach, which was designed to provide results that are directly relevant to policy makers, costing the interventions from Cambodia's national TB program's perspective and using case finding data from implementation activities, rather than experimental settings.

The Woodworker's Website: A Project Management Case Study

ERIC Educational Resources Information Center

Jance, Marsha

2014-01-01

A case study that focuses on building a website for a woodworking business is discussed. Project management and linear programming techniques can be used to determine the time required to complete the website project discussed in the case. This case can be assigned to students in an undergraduate or graduate decision modeling or management science…

Expert knowledge maps for knowledge management: a case study in Traditional Chinese Medicine research.

PubMed

Cui, Meng; Yang, Shuo; Yu, Tong; Yang, Ce; Gao, Yonghong; Zhu, Haiyan

2013-10-01

To design a model to capture information on the state and trends of knowledge creation, at both an individual and an organizational level, in order to enhance knowledge management. We designed a graph-theoretic knowledge model, the expert knowledge map (EKM), based on literature-based annotation. A case study in the domain of Traditional Chinese Medicine research was used to illustrate the usefulness of the model. The EKM successfully captured various aspects of knowledge and enhanced knowledge management within the case-study organization through the provision of knowledge graphs, expert graphs, and expert-knowledge biography. Our model could help to reveal the hot topics, trends, and products of the research done by an organization. It can potentially be used to facilitate knowledge learning, sharing and decision-making among researchers, academicians, students, and administrators of organizations.

Predictors of re-entry into the child protection system in Singapore: a cumulative ecological-transactional risk model.

PubMed

Li, Dongdong; Chu, Chi Meng; Ng, Wei Chern; Leong, Wai

2014-11-01

This study examines the risk factors of re-entry for 1,750 child protection cases in Singapore using a cumulative ecological-transactional risk model. Using administrative data, the present study found that the overall percentage of Child Protection Service (CPS) re-entry in Singapore is 10.5% based on 1,750 cases, with a range from 3.9% (within 1 year) to 16.5% (within 8 years after case closure). One quarter of the re-entry cases were observed to occur within 9 months from case closure. Seventeen risk factors, as identified from the extant literature, were tested for their utility to predict CPS re-entry in this study using a series of Cox regression analyses. A final list of seven risk factors (i.e., children's age at entry, case type, case closure result, duration of case, household income, family size, and mother's employment status) was used to create a cumulative risk score. The results supported the cumulative risk model in that higher risk score is related to higher risk of CPS re-entry. Understanding the prevalence of CPS re-entry and the risk factors associated with re-entry is the key to informing practice and policy in a culturally relevant way. The results from this study could then be used to facilitate critical case management decisions in order to enhance positive outcomes of families and children in Singapore's care system. Copyright © 2014 Elsevier Ltd. All rights reserved.

[The effectiveness of continuing care models in patients with chronic diseases: a systematic review].

PubMed

Chen, Hsiao-Mei; Han, Tung-Chen; Chen, Ching-Min

2014-04-01

Population aging has caused significant rises in the prevalence of chronic diseases and the utilization of healthcare services in Taiwan. The current healthcare delivery system is fragmented. Integrating medical services may increase the quality of healthcare, enhance patient and patient family satisfaction with healthcare services, and better contain healthcare costs. This article introduces two continuing care models: discharge planning and case management. Further, the effectiveness and essential components of these two models are analyzed using a systematic review method. Articles included in this systematic review were all original articles on discharge-planning or case-management interventions published between February 1999 and March 2013 in any of 6 electronic databases (Medline, PubMed, Cinahl Plus with full Text, ProQuest, Cochrane Library, CEPS and Center for Chinese Studies electronic databases). Of the 70 articles retrieved, only 7 were randomized controlled trial studies. Three types of continuity-of-care models were identified: discharge planning, case management, and a hybrid of these two. All three models used logical and systematic processes to conduct assessment, planning, implementation, coordination, follow-up, and evaluation activities. Both the discharge planning model and the case management model were positively associated with improved self-care knowledge, reduced length of stay, decreased medical costs, and better quality of life. This study cross-referenced all reviewed articles in terms of target clients, content, intervention schedules, measurements, and outcome indicators. Study results may be referenced in future implementations of continuity-care models and may provide a reference for future research.

RACORO continental boundary layer cloud investigations. Part I: Case study development and ensemble large-scale forcings

DOE PAGES

Vogelmann, Andrew M.; Fridlind, Ann M.; Toto, Tami; ...

2015-06-19

Observation-based modeling case studies of continental boundary layer clouds have been developed to study cloudy boundary layers, aerosol influences upon them, and their representation in cloud- and global-scale models. Three 60-hour case study periods span the temporal evolution of cumulus, stratiform, and drizzling boundary layer cloud systems, representing mixed and transitional states rather than idealized or canonical cases. Based on in-situ measurements from the RACORO field campaign and remote-sensing observations, the cases are designed with a modular configuration to simplify use in large-eddy simulations (LES) and single-column models. Aircraft measurements of aerosol number size distribution are fit to lognormal functionsmore » for concise representation in models. Values of the aerosol hygroscopicity parameter, κ, are derived from observations to be ~0.10, which are lower than the 0.3 typical over continents and suggestive of a large aerosol organic fraction. Ensemble large-scale forcing datasets are derived from the ARM variational analysis, ECMWF forecasts, and a multi-scale data assimilation system. The forcings are assessed through comparison of measured bulk atmospheric and cloud properties to those computed in 'trial' large-eddy simulations, where more efficient run times are enabled through modest reductions in grid resolution and domain size compared to the full-sized LES grid. Simulations capture many of the general features observed, but the state-of-the-art forcings were limited at representing details of cloud onset, and tight gradients and high-resolution transients of importance. Methods for improving the initial conditions and forcings are discussed. The cases developed are available to the general modeling community for studying continental boundary clouds.« less

RACORO Continental Boundary Layer Cloud Investigations: 1. Case Study Development and Ensemble Large-Scale Forcings

NASA Technical Reports Server (NTRS)

Vogelmann, Andrew M.; Fridlind, Ann M.; Toto, Tami; Endo, Satoshi; Lin, Wuyin; Wang, Jian; Feng, Sha; Zhang, Yunyan; Turner, David D.; Liu, Yangang;

RACORO continental boundary layer cloud investigations: 1. Case study development and ensemble large-scale forcings

NASA Astrophysics Data System (ADS)

Vogelmann, Andrew M.; Fridlind, Ann M.; Toto, Tami; Endo, Satoshi; Lin, Wuyin; Wang, Jian; Feng, Sha; Zhang, Yunyan; Turner, David D.; Liu, Yangang; Li, Zhijin; Xie, Shaocheng; Ackerman, Andrew S.; Zhang, Minghua; Khairoutdinov, Marat

2015-06-01

Observation-based modeling case studies of continental boundary layer clouds have been developed to study cloudy boundary layers, aerosol influences upon them, and their representation in cloud- and global-scale models. Three 60 h case study periods span the temporal evolution of cumulus, stratiform, and drizzling boundary layer cloud systems, representing mixed and transitional states rather than idealized or canonical cases. Based on in situ measurements from the Routine AAF (Atmospheric Radiation Measurement (ARM) Aerial Facility) CLOWD (Clouds with Low Optical Water Depth) Optical Radiative Observations (RACORO) field campaign and remote sensing observations, the cases are designed with a modular configuration to simplify use in large-eddy simulations (LES) and single-column models. Aircraft measurements of aerosol number size distribution are fit to lognormal functions for concise representation in models. Values of the aerosol hygroscopicity parameter, κ, are derived from observations to be 0.10, which are lower than the 0.3 typical over continents and suggestive of a large aerosol organic fraction. Ensemble large-scale forcing data sets are derived from the ARM variational analysis, European Centre for Medium-Range Weather Forecasts, and a multiscale data assimilation system. The forcings are assessed through comparison of measured bulk atmospheric and cloud properties to those computed in "trial" large-eddy simulations, where more efficient run times are enabled through modest reductions in grid resolution and domain size compared to the full-sized LES grid. Simulations capture many of the general features observed, but the state-of-the-art forcings were limited at representing details of cloud onset, and tight gradients and high-resolution transients of importance. Methods for improving the initial conditions and forcings are discussed. The cases developed are available to the general modeling community for studying continental boundary clouds.

The Three-Block Model of Universal Design for Learning Implementation in a High School

ERIC Educational Resources Information Center

Katz, Jennifer; Sugden, Ron

2013-01-01

The role of the school leader (principal) in supporting educational reform is explored through a case study of one high school implementing the Three Block Model of UDL (Katz, 2012a) in an effort to meet the needs of a diverse student population. This case study is a part of a much larger study exploring outcomes for students and teachers of…

Into the development of a model to assess beam shaping and polarization control effects on laser cutting

NASA Astrophysics Data System (ADS)

Rodrigues, Gonçalo C.; Duflou, Joost R.

2018-02-01

This paper offers an in-depth look into beam shaping and polarization control as two of the most promising techniques for improving industrial laser cutting of metal sheets. An assessment model is developed for the study of such effects. It is built upon several modifications to models as available in literature in order to evaluate the potential of a wide range of considered concepts. This includes different kinds of beam shaping (achieved by extra-cavity optical elements or asymmetric diode staking) and polarization control techniques (linear, cross, radial, azimuthal). A fully mathematical description and solution procedure are provided. Three case studies for direct diode lasers follow, containing both experimental data and parametric studies. In the first case study, linear polarization is analyzed for any given angle between the cutting direction and the electrical field. In the second case several polarization strategies are compared for similar cut conditions, evaluating, for example, the minimum number of spatial divisions of a segmented polarized laser beam to achieve a target performance. A novel strategy, based on a 12-division linear-to-radial polarization converter with an axis misalignment and capable of improving cutting efficiency with more than 60%, is proposed. The last case study reveals different insights in beam shaping techniques, with an example of a beam shape optimization path for a 30% improvement in cutting efficiency. The proposed techniques are not limited to this type of laser source, neither is the model dedicated to these specific case studies. Limitations of the model and opportunities are further discussed.

Three ADIPOR1 Polymorphisms and Cancer Risk: A Meta-Analysis of Case-Control Studies.

PubMed

Ye, Jiaxiang; Jiang, Li; Wu, Changliang; Liu, Aiqun; Mao, Sufei; Ge, Lianying

2015-01-01

Studies have come to conflicting conclusions about whether polymorphisms in the adiponectin receptor 1 gene (ADIPOR1) are associated with cancer risk. To help resolve this question, we meta-analyzed case-control studies in the literature. PubMed, EMBASE, Cochrane Library, the Chinese Biological Medical Database and the Chinese National Knowledge Infrastructure Database were systematically searched to identify all case-control studies published through February 2015 examining any ADIPOR1 polymorphisms and risk of any type of cancer. Pooled odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were calculated. A total of 13 case-control studies involving 5,750 cases and 6,762 controls were analyzed. Analysis of the entire study population revealed a significant association between rs1342387(G/A) and overall cancer risk using a homozygous model (OR 0.82, 95%CI 0.72 to 0.94), heterozygous model (OR 0.84, 95%CI 0.76 to 0.93), dominant model (OR 0.85, 95%CI 0.75 to 0.97) and allele contrast model (OR 0.88, 95%CI 0.80 to 0.97). However, subgroup analysis showed that this association was significant only for Asians in the case of colorectal cancer. No significant associations were found between rs12733285(C/T) or rs7539542(C/G) and cancer risk, either in analyses of the entire study population or in analyses of subgroups. Our meta-analysis suggests that the ADIPOR1 rs1342387(G/A) polymorphism, but not rs12733285(C/T) or rs7539542(C/G), may be associated with cancer risk, especially risk of colorectal cancer in Asians. Large, well-designed studies are needed to verify our findings.

Assessing Discriminative Performance at External Validation of Clinical Prediction Models

PubMed Central

Nieboer, Daan; van der Ploeg, Tjeerd; Steyerberg, Ewout W.

2016-01-01

Introduction External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting. Methods We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1) the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2) the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury. Results The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples) and heterogeneous in scenario 2 (in 17%-39% of simulated samples). Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2. Conclusion The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients. PMID:26881753

Assessing Discriminative Performance at External Validation of Clinical Prediction Models.

PubMed

Nieboer, Daan; van der Ploeg, Tjeerd; Steyerberg, Ewout W

2016-01-01

External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting. We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1) the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2) the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury. The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples) and heterogeneous in scenario 2 (in 17%-39% of simulated samples). Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2. The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients.

Towards a Neurodevelopmental Model of Clinical Case Formulation

PubMed Central

Solomon, Marjorie; Hessl, David; Chiu, Sufen; Olsen, Emily; Hendren, Robert

2009-01-01

Rapid advances in molecular genetics and neuroimaging over the last 10-20 years have been a catalyst for research in neurobiology, developmental psychopathology, and translational neuroscience. Methods of study in psychiatry, previously described as “slow maturing,” now are becoming sufficiently sophisticated to more effectively investigate the biology of higher mental processes. Despite these technological advances, the recognition that psychiatric disorders are disorders of neurodevelopment, and the importance of case formulation to clinical practice, a neurodevelopmental model of case formulation has not yet been articulated. The goals of this manuscript, which is organized as a clinical case conference, are to begin to articulate a neurodevelopmental model of case formulation, to illustrate its value, and finally to explore how clinical psychiatric practice might evolve in the future if this model were employed. PMID:19248925

Modeling vs. Coaching of Argumentation in a Case-Based Learning Environment.

ERIC Educational Resources Information Center

Li, Tiancheng; And Others

The major purposes of this study are: (1) to investigate and compare the effectiveness of two instructional strategies, modeling and coaching on helping students to articulate and support their decisions in a case-based learning environment; (2) to compare the effectiveness of modeling and coaching on helping students address essential criteria in…

Developing and Using a Logic Model for Evaluation and Assessment of University Student Affairs Programming: A Case Study

ERIC Educational Resources Information Center

Cooper, Jeff

2009-01-01

This dissertation addresses theory and practice of evaluation and assessment in university student affairs, by applying logic modeling/program theory to a case study. I intend to add knowledge to ongoing dialogue among evaluation scholars and practitioners on student affairs program planning and improvement as integral considerations that serve…

The Early Start Denver Model: A Case Study of an Innovative Practice

ERIC Educational Resources Information Center

Vismara, Laurie A.; Rogers, Sally J.

2008-01-01

Intervention was implemented with an infant identified at 9 months of age with a behavioral profile consistent with autistic spectrum disorder. The intervention approach, the Early Start Denver model, consisted of a 12-week, 1.5-hr-per-week individualized parent-child education program. Results of this case study demonstrated that the parent…

The Use of the Racial/Cultural Identity Development Model to Understand a Vietnamese American: A Research Case Study

ERIC Educational Resources Information Center

West-Olatunji, Cirecie A.; Frazier, Kimberly N.; Guy, Tanisha L.; Smith, Angie J.; Clay, Latasha; Breaux, Walter, III

2007-01-01

This article presents the sociohistorical experiences of Vietnamese Americans that contextualize the therapeutic relationship. Using a case study approach, researchers illustrate the use of the Racial/Cultural Identity Development model (D. W. Sue & D. Sue, 2003) in the analysis of an interview with a young, adult, Vietnamese immigrant.

Combined Application of Study Design and Case-Based Learning Comprehensive Model in Epidemiology Teaching

ERIC Educational Resources Information Center

Shi, Xiuquan; Zhou, Yanna; Wang, Haiyan; Wang, Tao; Nie, Chan; Shi, Shangpeng

2017-01-01

This paper aims to conduct the SD-CBL (study design with the case based learning, SD-CBL) in Epidemiology teaching and evaluate its effect. Students from five classes were recruited, and a combined comprehensive teaching model of SD-CBL was used in the "Injury Epidemiology" chapter, while other chapters in "Epidemiology"…

An Ethnographic Case Study of the Professional Development Model in a Successful Elementary School within a Suburban Southeast Texas School District

ERIC Educational Resources Information Center

Petrzelka, Valerie

2012-01-01

This ethnographic case study was designed to investigate a successful professional development model, perceived effective professional learning and process for determining professional development for teachers. With eighty years of research on professional development, limited research was available on the process for determining professional…

Applying the ASCA National Model to Elementary School Students Who Are Homeless: A Case Study

ERIC Educational Resources Information Center

Baggerly, Jennifer; Borkowski, Tammilyn

2004-01-01

This case study of an African American elementary school female who is homeless illustrates how ASCA's National Model meets the needs of students who are homeless. The needs of children who are homeless and the rationale for school counseling interventions--including assessment, classroom guidance, group play therapy, and consultation--are…

Impact of Telecentre Tools on Wellbeing and Community: A Case Study and Conceptual Model of the Malian Experience

ERIC Educational Resources Information Center

Glander-Dolo, S. Mackenzie

2010-01-01

This case study of Malian technology implementation questions the historic patron-client approach of international development planning and deployment of aid and assistance to least developed countries while addressing the added challenges that globalization brings. Using a systems lens and analogy, a conceptual model is built from a literature…

CIS Program Redesign Driven by IS2010 Model: A Case Study

ERIC Educational Resources Information Center

Surendran, Ken; Amer, Suhair; Schwieger, Dana

2012-01-01

The release of the IS2010 Model Curriculum has triggered review of existing Information Systems (IS) programs. It also provides an opportunity to replace low enrollment IS programs with flexible ones that focus on specific application domains. In this paper, the authors present a case study of their redesigned Computer Information Systems (CIS)…

Risk Prediction for Epithelial Ovarian Cancer in 11 United States–Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci

PubMed Central

Clyde, Merlise A.; Palmieri Weber, Rachel; Iversen, Edwin S.; Poole, Elizabeth M.; Doherty, Jennifer A.; Goodman, Marc T.; Ness, Roberta B.; Risch, Harvey A.; Rossing, Mary Anne; Terry, Kathryn L.; Wentzensen, Nicolas; Whittemore, Alice S.; Anton-Culver, Hoda; Bandera, Elisa V.; Berchuck, Andrew; Carney, Michael E.; Cramer, Daniel W.; Cunningham, Julie M.; Cushing-Haugen, Kara L.; Edwards, Robert P.; Fridley, Brooke L.; Goode, Ellen L.; Lurie, Galina; McGuire, Valerie; Modugno, Francesmary; Moysich, Kirsten B.; Olson, Sara H.; Pearce, Celeste Leigh; Pike, Malcolm C.; Rothstein, Joseph H.; Sellers, Thomas A.; Sieh, Weiva; Stram, Daniel; Thompson, Pamela J.; Vierkant, Robert A.; Wicklund, Kristine G.; Wu, Anna H.; Ziogas, Argyrios; Tworoger, Shelley S.; Schildkraut, Joellen M.

2016-01-01

Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted. PMID:27698005

Numerical Investigation of Flapwise-Torsional Vibration Model of a Smart Section Blade with Microtab

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

Li, Nailu; Balas, Mark J.; Yang, Hua

2015-01-01

This study presents a method to develop an aeroelastic model of a smart section blade equipped with microtab. The model is suitable for potential passive vibration control study of the blade section in classic flutter. Equations of the model are described by the nondimensional flapwise and torsional vibration modes coupled with the aerodynamic model based on the Theodorsen theory and aerodynamic effects of the microtab based on the wind tunnel experimental data. The aeroelastic model is validated using numerical data available in the literature and then utilized to analyze the microtab control capability on flutter instability case and divergence instabilitymore » case. The effectiveness of the microtab is investigated with the scenarios of different output controllers and actuation deployments for both instability cases. The numerical results show that the microtab can effectively suppress both vibration modes with the appropriate choice of the output feedback controller.« less

Statistical Analysis of Q-matrix Based Diagnostic Classification Models

PubMed Central

Chen, Yunxiao; Liu, Jingchen; Xu, Gongjun; Ying, Zhiliang

2014-01-01

Diagnostic classification models have recently gained prominence in educational assessment, psychiatric evaluation, and many other disciplines. Central to the model specification is the so-called Q-matrix that provides a qualitative specification of the item-attribute relationship. In this paper, we develop theories on the identifiability for the Q-matrix under the DINA and the DINO models. We further propose an estimation procedure for the Q-matrix through the regularized maximum likelihood. The applicability of this procedure is not limited to the DINA or the DINO model and it can be applied to essentially all Q-matrix based diagnostic classification models. Simulation studies are conducted to illustrate its performance. Furthermore, two case studies are presented. The first case is a data set on fraction subtraction (educational application) and the second case is a subsample of the National Epidemiological Survey on Alcohol and Related Conditions concerning the social anxiety disorder (psychiatric application). PMID:26294801

A comparison of economic evaluation models as applied to geothermal energy technology

NASA Technical Reports Server (NTRS)

Ziman, G. M.; Rosenberg, L. S.

1983-01-01

Several cost estimation and financial cash flow models have been applied to a series of geothermal case studies. In order to draw conclusions about relative performance and applicability of these models to geothermal projects, the consistency of results was assessed. The model outputs of principal interest in this study were net present value, internal rate of return, or levelized breakeven price. The models used were VENVAL, a venture analysis model; the Geothermal Probabilistic Cost Model (GPC Model); the Alternative Power Systems Economic Analysis Model (APSEAM); the Geothermal Loan Guarantee Cash Flow Model (GCFM); and the GEOCOST and GEOCITY geothermal models. The case studies to which the models were applied include a geothermal reservoir at Heber, CA; a geothermal eletric power plant to be located at the Heber site; an alcohol fuels production facility to be built at Raft River, ID; and a direct-use, district heating system in Susanville, CA.

Methodological Considerations for an Evolving Model of Institutional Research.

ERIC Educational Resources Information Center

Jones, Timothy B.; Essien-Barrett, Barbara; Gill, Peggy B.

A multi-case study was used in the self-study of three programs within an academic department of a mid-sized Southern university. Multi-case methodology as a form of self-study encourages a process of self-renewal and programmatic change as it defines an active stakeholder role. The participants in the three case studies were university faculty…

Evaluation of Cirrus Cloud Simulations using ARM Data-Development of Case Study Data Set

NASA Technical Reports Server (NTRS)

Starr, David OC.; Demoz, Belay; Wang, Yansen; Lin, Ruei-Fong; Lare, Andrew; Mace, Jay; Poellot, Michael; Sassen, Kenneth; Brown, Philip

2002-01-01

Cloud-resolving models (CRMs) are being increasingly used to develop parametric treatments of clouds and related processes for use in global climate models (GCMs). CRMs represent the integrated knowledge of the physical processes acting to determine cloud system lifecycle and are well matched to typical observational data in terms of physical parameters/measurables and scale-resolved physical processes. Thus, they are suitable for direct comparison to field observations for model validation and improvement. The goal of this project is to improve state-of-the-art CRMs used for studies of cirrus clouds and to establish a relative calibration with GCMs through comparisons among CRMs, single column model (SCM) versions of the GCMs, and observations. The objective is to compare and evaluate a variety of CRMs and SCMs, under the auspices of the GEWEX Cloud Systems Study (GCSS) Working Group on Cirrus Cloud Systems (WG2), using ARM data acquired at the Southern Great Plains (SGP) site. This poster will report on progress in developing a suitable WG2 case study data set based on the September 26, 1996 ARM IOP case - the Hurricane Nora outflow case. Progress is assessing cloud and other environmental conditions will be described. Results of preliminary simulations using a regional cloud system model (MM5) and a CRM will be discussed. Focal science questions for the model comparison are strongly based on results of the idealized GCSS WG2 cirrus cloud model comparison projects (Idealized Cirrus Cloud Model Comparison Project and Cirrus Parcel Model Comparison Project), which will also be briefly summarized.

Predicting What Will Happen When You Intervene.

PubMed

Cartwright, Nancy; Hardie, Jeremy

2017-01-01

This paper offers some rules of thumb that practicing social workers can use for case studies that aim to construct, albeit not fully and never entirely reliably, models designed to help predict what will happen if they intervene in specific ways to help this particular client, here and now. We call these 'ex ante case-specific causal models'. 'Ex ante' because they are for before-the-fact prediction of what the likely effects of proposed actions are. 'Case-specific' because we are not concerned with studies that provide evidence for some general conclusion but rather with using what general and local knowledge one can get to predict what will happen to a specific client in the real settings in which they live. 'Causal' because this kind of case study aims to trace out as best possible the web of causal processes that will be responsible for what happens. In this sense our case studies resemble post facto realist evaluations.

Automobile exhaust as a means of suicide: an experimental study with a proposed model.

PubMed

Morgen, C; Schramm, J; Kofoed, P; Steensberg, J; Theilade, P

1998-07-01

Experiments were conducted to investigate the concentration of carbon monoxide (CO) in a car cabin under suicide attempts with different vehicles and different start situations, and a mathematical model describing the concentration of CO in the cabin was constructed. Three cars were set up to donate the exhaust. The first vehicle didn't have any catalyst, the second one was equipped with a malfunctioning three-way catalyst, and the third car was equipped with a well-functioning three-way catalyst. The three different starting situations were cold, tepid and warm engine start, respectively. Measurements of the CO concentrations were made in both the cabin and in the exhaust pipe. Lethal concentrations were measured in the cabin using all three vehicles as the donor car, including the vehicle with the well-functioning catalyst. The model results in most cases gave a good prediction of the CO concentration in the cabin. Four case studies of cars used for suicides were described. In each case measurements of CO were made in both the cabin and the exhaust under different starting conditions, and the mathematical model was tested on these cases. In most cases the model predictions were good.

An axisymmetric non-hydrostatic model for double-diffusive water systems

NASA Astrophysics Data System (ADS)

Hilgersom, Koen; Zijlema, Marcel; van de Giesen, Nick

2018-02-01

The three-dimensional (3-D) modelling of water systems involving double-diffusive processes is challenging due to the large computation times required to solve the flow and transport of constituents. In 3-D systems that approach axisymmetry around a central location, computation times can be reduced by applying a 2-D axisymmetric model set-up. This article applies the Reynolds-averaged Navier-Stokes equations described in cylindrical coordinates and integrates them to guarantee mass and momentum conservation. The discretized equations are presented in a way that a Cartesian finite-volume model can be easily extended to the developed framework, which is demonstrated by the implementation into a non-hydrostatic free-surface flow model. This model employs temperature- and salinity-dependent densities, molecular diffusivities, and kinematic viscosity. One quantitative case study, based on an analytical solution derived for the radial expansion of a dense water layer, and two qualitative case studies demonstrate a good behaviour of the model for seepage inflows with contrasting salinities and temperatures. Four case studies with respect to double-diffusive processes in a stratified water body demonstrate that turbulent flows are not yet correctly modelled near the interfaces and that an advanced turbulence model is required.

Evaluating the cost effectiveness of environmental projects: Case studies in aerospace and defense

NASA Technical Reports Server (NTRS)

Shunk, James F.

1995-01-01

Using the replacement technology of high pressure waterjet decoating systems as an example, a simple methodology is presented for developing a cost effectiveness model. The model uses a four-step process to formulate an economic justification designed for presentation to decision makers as an assessment of the value of the replacement technology over conventional methods. Three case studies from major U.S. and international airlines are used to illustrate the methodology and resulting model. Tax and depreciation impacts are also presented as potential additions to the model.

Use of machine learning methods to reduce predictive error of groundwater models.

PubMed

Xu, Tianfang; Valocchi, Albert J; Choi, Jaesik; Amir, Eyal

2014-01-01

Quantitative analyses of groundwater flow and transport typically rely on a physically-based model, which is inherently subject to error. Errors in model structure, parameter and data lead to both random and systematic error even in the output of a calibrated model. We develop complementary data-driven models (DDMs) to reduce the predictive error of physically-based groundwater models. Two machine learning techniques, the instance-based weighting and support vector regression, are used to build the DDMs. This approach is illustrated using two real-world case studies of the Republican River Compact Administration model and the Spokane Valley-Rathdrum Prairie model. The two groundwater models have different hydrogeologic settings, parameterization, and calibration methods. In the first case study, cluster analysis is introduced for data preprocessing to make the DDMs more robust and computationally efficient. The DDMs reduce the root-mean-square error (RMSE) of the temporal, spatial, and spatiotemporal prediction of piezometric head of the groundwater model by 82%, 60%, and 48%, respectively. In the second case study, the DDMs reduce the RMSE of the temporal prediction of piezometric head of the groundwater model by 77%. It is further demonstrated that the effectiveness of the DDMs depends on the existence and extent of the structure in the error of the physically-based model. © 2013, National GroundWater Association.

Spatial distribution of psychotic disorders in an urban area of France: an ecological study.

PubMed

Pignon, Baptiste; Schürhoff, Franck; Baudin, Grégoire; Ferchiou, Aziz; Richard, Jean-Romain; Saba, Ghassen; Leboyer, Marion; Kirkbride, James B; Szöke, Andrei

2016-05-18

Previous analyses of neighbourhood variations of non-affective psychotic disorders (NAPD) have focused mainly on incidence. However, prevalence studies provide important insights on factors associated with disease evolution as well as for healthcare resource allocation. This study aimed to investigate the distribution of prevalent NAPD cases in an urban area in France. The number of cases in each neighbourhood was modelled as a function of potential confounders and ecological variables, namely: migrant density, economic deprivation and social fragmentation. This was modelled using statistical models of increasing complexity: frequentist models (using Poisson and negative binomial regressions), and several Bayesian models. For each model, assumptions validity were checked and compared as to how this fitted to the data, in order to test for possible spatial variation in prevalence. Data showed significant overdispersion (invalidating the Poisson regression model) and residual autocorrelation (suggesting the need to use Bayesian models). The best Bayesian model was Leroux's model (i.e. a model with both strong correlation between neighbouring areas and weaker correlation between areas further apart), with economic deprivation as an explanatory variable (OR = 1.13, 95% CI [1.02-1.25]). In comparison with frequentist methods, the Bayesian model showed a better fit. The number of cases showed non-random spatial distribution and was linked to economic deprivation.

Ride-sharing business model for sustainability in developing country: Case Study Nebengers, Indonesia

NASA Astrophysics Data System (ADS)

Asirin, Asirin; Azhari, Danang

2018-05-01

The growth of population and urban economy increased the need for humans’ mobility to support their activities. On the other hand, online Information and Communication Technology (ICT) is growing rapidly and more affordable. Within few years, there is some sharing economy business formed by using online platform. This condition brings through the emergence of ride-sharing business model using an online platform which can be beneficial to sustainability. This research aims to explore one of ridesharing business models which use the online platform and its impact on sustainability. This research used the procedure of case study method with a single case study of Nebengers. This research explores the case study with the scope of this research is limited by using several conceptual frameworks, they are sharing economy business model, four elements of a business model for sustainability (BMfS), Social Construction of Technology (SCoT), sustainable mobility and agency theory. Nebengers is a sharing economy business using online platform that historically can be explained using Social Construction of Technology (SCoT) Theory. There are conflicts between nebengers entrepreneur and the city government. Nebengers disrupts traditional and formal public transportation services which are managed by the government. However, nebengers also contributes to achieve the city government goal in developing sustainable mobility. The future challenge is how to arrange ride-sharing collaborative governance business model for sustainability in the cities in Indonesia.

Genetically modified crops and aquatic ecosystems: considerations for environmental risk assessment and non-target organism testing.

PubMed

Carstens, Keri; Anderson, Jennifer; Bachman, Pamela; De Schrijver, Adinda; Dively, Galen; Federici, Brian; Hamer, Mick; Gielkens, Marco; Jensen, Peter; Lamp, William; Rauschen, Stefan; Ridley, Geoff; Romeis, Jörg; Waggoner, Annabel

2012-08-01

Environmental risk assessments (ERA) support regulatory decisions for the commercial cultivation of genetically modified (GM) crops. The ERA for terrestrial agroecosystems is well-developed, whereas guidance for ERA of GM crops in aquatic ecosystems is not as well-defined. The purpose of this document is to demonstrate how comprehensive problem formulation can be used to develop a conceptual model and to identify potential exposure pathways, using Bacillus thuringiensis (Bt) maize as a case study. Within problem formulation, the insecticidal trait, the crop, the receiving environment, and protection goals were characterized, and a conceptual model was developed to identify routes through which aquatic organisms may be exposed to insecticidal proteins in maize tissue. Following a tiered approach for exposure assessment, worst-case exposures were estimated using standardized models, and factors mitigating exposure were described. Based on exposure estimates, shredders were identified as the functional group most likely to be exposed to insecticidal proteins. However, even using worst-case assumptions, the exposure of shredders to Bt maize was low and studies supporting the current risk assessments were deemed adequate. Determining if early tier toxicity studies are necessary to inform the risk assessment for a specific GM crop should be done on a case by case basis, and should be guided by thorough problem formulation and exposure assessment. The processes used to develop the Bt maize case study are intended to serve as a model for performing risk assessments on future traits and crops.

Estimation of the contribution of private providers in tuberculosis case notification and treatment outcome in Pakistan.

PubMed

Chughtai, A A; Qadeer, E; Khan, W; Hadi, H; Memon, I A

2013-03-01

To improve involvement of the private sector in the national tuberculosis (TB) programme in Pakistan various public-private mix projects were set up between 2004 and 2009. A retrospective analysis of data was made to study 6 different public-private mix models for TB control in Pakistan and estimate the contribution of the various private providers to TB case notification and treatment outcome. The number of TB cases notified through the private sector increased significantly from 77 cases in 2004 to 37,656 in 2009. Among the models, the nongovernmental organization model made the greatest contribution to case notification (58.3%), followed by the hospital-based model (18.9%). Treatment success was highest for the district-led model (94.1%) and lowest for the hospital-based model (74.2%). The private sector made an important contribution to the national data through the various public-private mix projects. Issues of sustainability and the lack of treatment supporters are discussed as reasons for lack of success of some projects.

Testing MODFLOW-LGR for simulating flow around buried Quaternary valleys - synthetic test cases

NASA Astrophysics Data System (ADS)

Vilhelmsen, T. N.; Christensen, S.

2009-12-01

In this study the Local Grid Refinement (LGR) method developed for MODFLOW-2005 (Mehl and Hill, 2005) is utilized to describe groundwater flow in areas containing buried Quaternary valley structures. The tests are conducted as comparative analysis between simulations run with a globally refined model, a locally refined model, and a globally coarse model, respectively. The models vary from simple one layer models to more complex ones with up to 25 model layers. The comparisons of accuracy are conducted within the locally refined area and focus on water budgets, simulated heads, and simulated particle traces. Simulations made with the globally refined model are used as reference (regarded as “true” values). As expected, for all test cases the application of local grid refinement resulted in more accurate results than when using the globally coarse model. A significant advantage of utilizing MODFLOW-LGR was that it allows increased numbers of model layers to better resolve complex geology within local areas. This resulted in more accurate simulations than when using either a globally coarse model grid or a locally refined model with lower geological resolution. Improved accuracy in the latter case could not be expected beforehand because difference in geological resolution between the coarse parent model and the refined child model contradicts the assumptions of the Darcy weighted interpolation used in MODFLOW-LGR. With respect to model runtimes, it was sometimes found that the runtime for the locally refined model is much longer than for the globally refined model. This was the case even when the closure criteria were relaxed compared to the globally refined model. These results are contradictory to those presented by Mehl and Hill (2005). Furthermore, in the complex cases it took some testing (model runs) to identify the closure criteria and the damping factor that secured convergence, accurate solutions, and reasonable runtimes. For our cases this is judged to be a serious disadvantage of applying MODFLOW-LGR. Another disadvantage in the studied cases was that the MODFLOW-LGR results proved to be somewhat dependent on the correction method used at the parent-child model interface. This indicates that when applying MODFLOW-LGR there is a need for thorough and case-specific considerations regarding choice of correction method. References: Mehl, S. and M. C. Hill (2005). "MODFLOW-2005, THE U.S. GEOLOGICAL SURVEY MODULAR GROUND-WATER MODEL - DOCUMENTATION OF SHARED NODE LOCAL GRID REFINEMENT (LGR) AND THE BOUNDARY FLOW AND HEAD (BFH) PACKAGE " U.S. Geological Survey Techniques and Methods 6-A12

Long-term Evaluation of Landuse Changes On Landscape Water Balance - A Case Study From North-east Germany

NASA Astrophysics Data System (ADS)

Wegehenkel, M.

In this paper, long-term effects of different afforestation scenarios on landscape wa- ter balance will be analyzed taking into account the results of a regional case study. This analysis is based on using a GIS-coupled simulation model for the the spatially distributed calculation of water balance.For this purpose, the modelling system THE- SEUS with a simple GIS-interface will be used. To take into account the special case of change in forest cover proportion, THESEUS was enhanced with a simple for- est growth model. In the regional case study, model runs will be performed using a detailed spatial data set from North-East Germany. This data set covers a mesoscale catchment located at the moraine landscape of North-East Germany. Based on this data set, the influence of the actual landuse and of different landuse change scenarios on water balance dynamics will be investigated taking into account the spatial distributed modelling results from THESEUS. The model was tested using different experimen- tal data sets from field plots as well as obsverded catchment discharge. Additionally to such convential validation techniques, remote sensing data were used to check the simulated regional distribution of water balance components like evapotranspiration in the catchment.

Forecasting landslide activations by means of GA-SAKe. An example of application to three case studies in Calabria (Southern Italy)

NASA Astrophysics Data System (ADS)

Iovine, Giulio G. R.; De Rango, Alessio; Gariano, Stefano L.; Terranova, Oreste G.

2016-04-01

GA-SAKe - the Genetic-Algorithm based release of the hydrological model SAKe (Self Adaptive Kernel) - allows to forecast the timing of activation of landslides [1, 2], based on dates of landslide activations and rainfall series. The model can be applied to either single or set of similar landslides in a homogeneous context. Calibration of the model is performed through Genetic-Algorithm, and provides families of optimal, discretized solutions (kernels) that maximize the fitness function. The mobility functions are obtained through convolution of the optimal kernels with rain series. The shape of the kernel, including its base time, is related to magnitude of the landslide and hydro-geological complexity of the slope. Once validated, the model can be applied to estimate the timing of future landslide activations in the same study area, by employing measured or forecasted rainfall. GA-SAKe is here employed to analyse the historical activations of three rock slides in Calabria (Southern Italy), threatening villages and main infrastructures. In particular: 1) the Acri-Serra di Buda case, developed within a Sackung, involving weathered crystalline and metamorphic rocks; for this case study, 6 dates of activation are available; 2) the San Fili-Uncino case, developed in clay and conglomerate overlaying gneiss and biotitic schist; for this case study, 7 dates of activation are available [2]; 3) the San Benedetto Ullano-San Rocco case, developed in weathered metamorphic rocks; for this case study, 3 dates of activation are available [1, 3, 4, 5]. The obtained results are quite promising, given the high performance of the model against slope movements characterized by numerous historical activations. Obtained results, in terms of shape and base time of the kernels, are compared by taking into account types and sizes of the considered case studies, and involved rock types. References [1] Terranova O.G., Iaquinta P., Gariano S.L., Greco R. & Iovine G. (2013) In: Landslide Science and Practice, Margottini, Canuti, Sassa (Eds.), Vol. 3, pp.73-79. [2] Terranova O.G., Gariano S.L., Iaquinta P. & Iovine G.G.R. (2015). Geosci. Model Dev., 8, 1955-1978. [3] Iovine G., Iaquinta P. & Terranova O. (2009). In Anderssen, Braddock & Newham (Eds.), Proc. 18th World IMACS Congr. and MODSIM09 Int. Congr. on Modelling and Simulation, pp. 2686-2693. [4] Iovine G., Lollino P., Gariano S.L. & Terranova O.G. (2010). NHESS, 10, 2341-2354. [5] Capparelli G., Iaquinta P., Iovine G., Terranova O.G. & Versace P. (2012). Natural Hazards, 61(1), pp.247-256.

Numerical study of turbulence-influence mechanism on arc characteristics in an air direct current circuit breaker

NASA Astrophysics Data System (ADS)

Wu, Mingliang; Yang, Fei; Rong, Mingzhe; Wu, Yi; Qi, Yang; Cui, Yufei; Liu, Zirui; Guo, Anxiang

2016-04-01

This paper focuses on the numerical investigation of arc characteristics in an air direct current circuit breaker (air DCCB). Using magneto-hydrodynamics (MHD) theory, 3D laminar model and turbulence model are constructed and calculated. The standard k-epsilon model is utilized to consider the turbulence effect in the arc chamber of the DCCB. Several important phenomena are found: the arc column in the turbulence-model case is more extensive, moves much more slowly than the counterpart in the laminar-model case, and shows stagnation at the entrance of the chamber, unlike in the laminar-model case. Moreover, the arc voltage in the turbulence-model case is much lower than in the laminar-model case. However, the results in the turbulence-model case show a much better agreement with the results of the breaking experiments under DC condition than in the laminar-model case, which is contradictory to the previous conclusions from the arc researches of both the low-voltage circuit breaker and the sulfur hexafluoride (SF6) nozzle. First, in the previous air-arc research of the low-voltage circuit breaker, it is assumed that the air plasma inside the chamber is in the state of laminar, and the laminar-model application gives quite satisfactory results compared with the experiments, while in this paper, the laminar-model application works badly. Second, the turbulence-model application in the arc research of the SF6-nozzle performs much better and gives higher arc voltage than the laminar-model application does, whereas in this paper, the turbulence-model application predicts lower arc voltage than the laminar-model application does. Based on the analysis of simulation results in detail, the mechanism of the above phenomena is revealed. The transport coefficients are strongly changed by turbulence, which will enhance the arc diffusion and make the arc volume much larger. Consequently, the arc appearance and the distribution of Lorentz force in the turbulence-model case substantially differ from the arc appearance and the distribution of Lorentz force in the laminar-model case. Thus, the moving process of the arc in the turbulence-model case is slowed down and slower than in the laminar-model case. Moreover, the more extensive arc column in the turbulence-model case reduces the total arc resistance, which results in a lower arc voltage, more consistent with the experimental results than the arc voltage in the laminar-model case. Therefore, the air plasma inside this air DCCB is believed to be in the turbulence state, and the turbulence model is more suitable than the laminar model for the arc simulation of this kind of air DCCB.

Numerical study of turbulence-influence mechanism on arc characteristics in an air direct current circuit breaker

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

Wu, Mingliang; Yang, Fei, E-mail: yfei2007@mail.xjtu.edu.cn; Rong, Mingzhe

This paper focuses on the numerical investigation of arc characteristics in an air direct current circuit breaker (air DCCB). Using magneto-hydrodynamics (MHD) theory, 3D laminar model and turbulence model are constructed and calculated. The standard k-epsilon model is utilized to consider the turbulence effect in the arc chamber of the DCCB. Several important phenomena are found: the arc column in the turbulence-model case is more extensive, moves much more slowly than the counterpart in the laminar-model case, and shows stagnation at the entrance of the chamber, unlike in the laminar-model case. Moreover, the arc voltage in the turbulence-model case ismore » much lower than in the laminar-model case. However, the results in the turbulence-model case show a much better agreement with the results of the breaking experiments under DC condition than in the laminar-model case, which is contradictory to the previous conclusions from the arc researches of both the low-voltage circuit breaker and the sulfur hexafluoride (SF6) nozzle. First, in the previous air-arc research of the low-voltage circuit breaker, it is assumed that the air plasma inside the chamber is in the state of laminar, and the laminar-model application gives quite satisfactory results compared with the experiments, while in this paper, the laminar-model application works badly. Second, the turbulence-model application in the arc research of the SF6-nozzle performs much better and gives higher arc voltage than the laminar-model application does, whereas in this paper, the turbulence-model application predicts lower arc voltage than the laminar-model application does. Based on the analysis of simulation results in detail, the mechanism of the above phenomena is revealed. The transport coefficients are strongly changed by turbulence, which will enhance the arc diffusion and make the arc volume much larger. Consequently, the arc appearance and the distribution of Lorentz force in the turbulence-model case substantially differ from the arc appearance and the distribution of Lorentz force in the laminar-model case. Thus, the moving process of the arc in the turbulence-model case is slowed down and slower than in the laminar-model case. Moreover, the more extensive arc column in the turbulence-model case reduces the total arc resistance, which results in a lower arc voltage, more consistent with the experimental results than the arc voltage in the laminar-model case. Therefore, the air plasma inside this air DCCB is believed to be in the turbulence state, and the turbulence model is more suitable than the laminar model for the arc simulation of this kind of air DCCB.« less

Unconditional or Conditional Logistic Regression Model for Age-Matched Case-Control Data?

PubMed

Kuo, Chia-Ling; Duan, Yinghui; Grady, James

2018-01-01

Matching on demographic variables is commonly used in case-control studies to adjust for confounding at the design stage. There is a presumption that matched data need to be analyzed by matched methods. Conditional logistic regression has become a standard for matched case-control data to tackle the sparse data problem. The sparse data problem, however, may not be a concern for loose-matching data when the matching between cases and controls is not unique, and one case can be matched to other controls without substantially changing the association. Data matched on a few demographic variables are clearly loose-matching data, and we hypothesize that unconditional logistic regression is a proper method to perform. To address the hypothesis, we compare unconditional and conditional logistic regression models by precision in estimates and hypothesis testing using simulated matched case-control data. Our results support our hypothesis; however, the unconditional model is not as robust as the conditional model to the matching distortion that the matching process not only makes cases and controls similar for matching variables but also for the exposure status. When the study design involves other complex features or the computational burden is high, matching in loose-matching data can be ignored for negligible loss in testing and estimation if the distributions of matching variables are not extremely different between cases and controls.

Applying cost accounting to operating room staffing in otolaryngology: time-driven activity-based costing and outpatient adenotonsillectomy.

PubMed

Balakrishnan, Karthik; Goico, Brian; Arjmand, Ellis M

2015-04-01

(1) To describe the application of a detailed cost-accounting method (time-driven activity-cased costing) to operating room personnel costs, avoiding the proxy use of hospital and provider charges. (2) To model potential cost efficiencies using different staffing models with the case study of outpatient adenotonsillectomy. Prospective cost analysis case study. Tertiary pediatric hospital. All otolaryngology providers and otolaryngology operating room staff at our institution. Time-driven activity-based costing demonstrated precise per-case and per-minute calculation of personnel costs. We identified several areas of unused personnel capacity in a basic staffing model. Per-case personnel costs decreased by 23.2% by allowing a surgeon to run 2 operating rooms, despite doubling all other staff. Further cost reductions up to a total of 26.4% were predicted with additional staffing rearrangements. Time-driven activity-based costing allows detailed understanding of not only personnel costs but also how personnel time is used. This in turn allows testing of alternative staffing models to decrease unused personnel capacity and increase efficiency. © American Academy of Otolaryngology—Head and Neck Surgery Foundation 2015.

Modelling of occupational respirable crystalline silica exposure for quantitative exposure assessment in community-based case-control studies.

PubMed

Peters, Susan; Vermeulen, Roel; Portengen, Lützen; Olsson, Ann; Kendzia, Benjamin; Vincent, Raymond; Savary, Barbara; Lavoué, Jérôme; Cavallo, Domenico; Cattaneo, Andrea; Mirabelli, Dario; Plato, Nils; Fevotte, Joelle; Pesch, Beate; Brüning, Thomas; Straif, Kurt; Kromhout, Hans

2011-11-01

We describe an empirical model for exposure to respirable crystalline silica (RCS) to create a quantitative job-exposure matrix (JEM) for community-based studies. Personal measurements of exposure to RCS from Europe and Canada were obtained for exposure modelling. A mixed-effects model was elaborated, with region/country and job titles as random effect terms. The fixed effect terms included year of measurement, measurement strategy (representative or worst-case), sampling duration (minutes) and a priori exposure intensity rating for each job from an independently developed JEM (none, low, high). 23,640 personal RCS exposure measurements, covering a time period from 1976 to 2009, were available for modelling. The model indicated an overall downward time trend in RCS exposure levels of -6% per year. Exposure levels were higher in the UK and Canada, and lower in Northern Europe and Germany. Worst-case sampling was associated with higher reported exposure levels and an increase in sampling duration was associated with lower reported exposure levels. Highest predicted RCS exposure levels in the reference year (1998) were for chimney bricklayers (geometric mean 0.11 mg m(-3)), monument carvers and other stone cutters and carvers (0.10 mg m(-3)). The resulting model enables us to predict time-, job-, and region/country-specific exposure levels of RCS. These predictions will be used in the SYNERGY study, an ongoing pooled multinational community-based case-control study on lung cancer.

Accounting for control mislabeling in case-control biomarker studies.

PubMed

Rantalainen, Mattias; Holmes, Chris C

2011-12-02

In biomarker discovery studies, uncertainty associated with case and control labels is often overlooked. By omitting to take into account label uncertainty, model parameters and the predictive risk can become biased, sometimes severely. The most common situation is when the control set contains an unknown number of undiagnosed, or future, cases. This has a marked impact in situations where the model needs to be well-calibrated, e.g., when the prediction performance of a biomarker panel is evaluated. Failing to account for class label uncertainty may lead to underestimation of classification performance and bias in parameter estimates. This can further impact on meta-analysis for combining evidence from multiple studies. Using a simulation study, we outline how conventional statistical models can be modified to address class label uncertainty leading to well-calibrated prediction performance estimates and reduced bias in meta-analysis. We focus on the problem of mislabeled control subjects in case-control studies, i.e., when some of the control subjects are undiagnosed cases, although the procedures we report are generic. The uncertainty in control status is a particular situation common in biomarker discovery studies in the context of genomic and molecular epidemiology, where control subjects are commonly sampled from the general population with an established expected disease incidence rate.

Ambient temperature and coronary heart disease mortality in Beijing, China: a time series study

PubMed Central

2012-01-01

Background Many studies have examined the association between ambient temperature and mortality. However, less evidence is available on the temperature effects on coronary heart disease (CHD) mortality, especially in China. In this study, we examined the relationship between ambient temperature and CHD mortality in Beijing, China during 2000 to 2011. In addition, we compared time series and time-stratified case-crossover models for the non-linear effects of temperature. Methods We examined the effects of temperature on CHD mortality using both time series and time-stratified case-crossover models. We also assessed the effects of temperature on CHD mortality by subgroups: gender (female and male) and age (age > =65 and age < 65). We used a distributed lag non-linear model to examine the non-linear effects of temperature on CHD mortality up to 15 lag days. We used Akaike information criterion to assess the model fit for the two designs. Results The time series models had a better model fit than time-stratified case-crossover models. Both designs showed that the relationships between temperature and group-specific CHD mortality were non-linear. Extreme cold and hot temperatures significantly increased the risk of CHD mortality. Hot effects were acute and short-term, while cold effects were delayed by two days and lasted for five days. The old people and women were more sensitive to extreme cold and hot temperatures than young and men. Conclusions This study suggests that time series models performed better than time-stratified case-crossover models according to the model fit, even though they produced similar non-linear effects of temperature on CHD mortality. In addition, our findings indicate that extreme cold and hot temperatures increase the risk of CHD mortality in Beijing, China, particularly for women and old people. PMID:22909034

Developing a Model and Applications for Probabilities of Student Success: A Case Study of Predictive Analytics

ERIC Educational Resources Information Center

Calvert, Carol Elaine

2014-01-01

This case study relates to distance learning students on open access courses. It demonstrates the use of predictive analytics to generate a model of the probabilities of success and retention at different points, or milestones, in a student journey. A core set of explanatory variables has been established and their varying relative importance at…

Training Post-9/11 Police Officers with a Counter-Terrorism Reality-Based Training Model: A Case Study

ERIC Educational Resources Information Center

Biddle, Christopher J.

2013-01-01

The purpose of this qualitative holistic multiple-case study was to identify the optimal theoretical approach for a Counter-Terrorism Reality-Based Training (CTRBT) model to train post-9/11 police officers to perform effectively in their counter-terrorism assignments. Post-9/11 police officers assigned to counter-terrorism duties are not trained…

Explaining Variance and Identifying Predictors of Children's Communication via a Multilevel Model of Single-Case Design Research: Brief Report

ERIC Educational Resources Information Center

Ottley, Jennifer Riggie; Ferron, John M.; Hanline, Mary Frances

2016-01-01

The purpose of this study was to explain the variability in data collected from a single-case design study and to identify predictors of communicative outcomes for children with developmental delays or disabilities (n = 4). Using SAS® University Edition, we fit multilevel models with time nested within children. Children's level of baseline…

A Case Study: The Implementation of a Problem-Solving Model with a Student with Reading Difficulties in Turkey

ERIC Educational Resources Information Center

Ozmen, E. Ruya; Doganay-Bilgi, Arzu

2016-01-01

The purpose of this case study was to improve the reading accuracy and reading comprehension of a 10-year-old fourth-grade female student with reading difficulties. For that purpose, the problem- solving model was implemented in four stages. These stages included problem identification, problem analysis, intervention, and evaluation. During the…

Online Education: Analysis of Interaction and Knowledge Building Patterns among Foreign Language Teachers

ERIC Educational Resources Information Center

Celentin, Paola

2007-01-01

In this article we discuss findings from a case-study related to the distance education of teachers of Italian as a second/foreign language. This case-study has examined interactions among teachers during their discussions in a web-forum exploiting the model of content analysis proposed in the "Practical Inquiry Model" by Garrison, Anderson, and…

The Rural Health Care Delivery System in the Dingxian Experiment: A Case Study of Educational Transfer in Republican China.

ERIC Educational Resources Information Center

Lee, Wai-man; Lo, L. Nai-kwai

1988-01-01

Discusses dependency theory in comparative education studies. Examines U.S. educational transfer to China during the Republican period as it functioned through the public health delivery model of the Dingxian Experiment. Notes that resistance to dependency in this case could serve as a model for avoiding the technological misfitting of programs.…

Application of Cognitive Apprenticeship Model to a Graduate Course in Performance Systems Analysis: A Case Study

ERIC Educational Resources Information Center

Darabi, A. Aubteen

2005-01-01

This article reports a case study describing how the principles of a cognitive apprenticeship (CA) model developed by Collins, Brown, and Holum (1991) were applied to a graduate course on performance systems analysis (PSA), and the differences this application made in student performance and evaluation of the course compared to the previous…

Marginal Structural Models for Case-Cohort Study Designs to Estimate the Association of Antiretroviral Therapy Initiation With Incident AIDS or Death

PubMed Central

Cole, Stephen R.; Hudgens, Michael G.; Tien, Phyllis C.; Anastos, Kathryn; Kingsley, Lawrence; Chmiel, Joan S.; Jacobson, Lisa P.

2012-01-01

To estimate the association of antiretroviral therapy initiation with incident acquired immunodeficiency syndrome (AIDS) or death while accounting for time-varying confounding in a cost-efficient manner, the authors combined a case-cohort study design with inverse probability-weighted estimation of a marginal structural Cox proportional hazards model. A total of 950 adults who were positive for human immunodeficiency virus type 1 were followed in 2 US cohort studies between 1995 and 2007. In the full cohort, 211 AIDS cases or deaths occurred during 4,456 person-years. In an illustrative 20% random subcohort of 190 participants, 41 AIDS cases or deaths occurred during 861 person-years. Accounting for measured confounders and determinants of dropout by inverse probability weighting, the full cohort hazard ratio was 0.41 (95% confidence interval: 0.26, 0.65) and the case-cohort hazard ratio was 0.47 (95% confidence interval: 0.26, 0.83). Standard multivariable-adjusted hazard ratios were closer to the null, regardless of study design. The precision lost with the case-cohort design was modest given the cost savings. Results from Monte Carlo simulations demonstrated that the proposed approach yields approximately unbiased estimates of the hazard ratio with appropriate confidence interval coverage. Marginal structural model analysis of case-cohort study designs provides a cost-efficient design coupled with an accurate analytic method for research settings in which there is time-varying confounding. PMID:22302074

Modeling and design of challenge tests: Inflammatory and metabolic biomarker study examples.

PubMed

Gabrielsson, Johan; Hjorth, Stephan; Vogg, Barbara; Harlfinger, Stephanie; Gutierrez, Pablo Morentin; Peletier, Lambertus; Pehrson, Rikard; Davidsson, Pia

2015-01-25

Given the complexity of pharmacological challenge experiments, it is perhaps not surprising that design and analysis, and in turn interpretation and communication of results from a quantitative point of view, is often suboptimal. Here we report an inventory of common designs sampled from anti-inflammatory, respiratory and metabolic disease drug discovery studies, all of which are based on animal models of disease involving pharmacological and/or patho/physiological interaction challenges. The corresponding data are modeled and analyzed quantitatively, the merits of the respective approach discussed and inferences made with respect to future design improvements. Although our analysis is limited to these disease model examples, the challenge approach is generally applicable to the vast majority of pharmacological intervention studies. In the present five Case Studies results from pharmacodynamic effect models from different therapeutic areas were explored and analyzed according to five typical designs. Plasma exposures of test compounds were assayed by either liquid chromatography/mass spectrometry or ligand binding assays. To describe how drug intervention can regulate diverse processes, turnover models of test compound-challenger interaction, transduction processes, and biophase time courses were applied for biomarker response in eosinophil count, IL6 response, paw-swelling, TNFα response and glucose turnover in vivo. Case Study 1 shows results from intratracheal administration of Sephadex, which is a glucocorticoid-sensitive model of airway inflammation in rats. Eosinophils in bronchoalveolar fluid were obtained at different time points via destructive sampling and then regressed by the mixed-effects modeling. A biophase function of the Sephadex time course was inferred from the modeled eosinophil time courses. In Case Study 2, a mouse model showed that the time course of cytokine-induced IL1β challenge was altered with or without drug intervention. Anakinra reversed the IL1β induced cytokine IL6 response in a dose-dependent manner. This Case Study contained time courses of test compound (drug), challenger (IL1β) and cytokine response (IL6), which resulted in high parameter precision. Case Study 3 illustrates collagen-induced arthritis progression in the rat. Swelling scores (based on severity of hind paw swelling) were used to describe arthritis progression after the challenge and the inhibitory effect of two doses of an orally administered test compound. In Case Study 4, a cynomolgus monkey model for lipopolysaccharide LPS-induced TNFα synthesis and/or release was investigated. This model provides integrated information on pharmacokinetics and in vivo potency of the test compounds. Case Study 5 contains data from an oral glucose tolerance test in rats, where the challenger is the same as the pharmacodynamic response biomarker (glucose). It is therefore convenient to model the extra input of glucose simultaneously with baseline data and during intervention of a glucose-lowering compound at different dose levels. Typically time-series analyses of challenger- and biomarker-time data are necessary if an accurate and precise estimate of the pharmacodynamic properties of a test compound is sought. Erosion of data, resulting in the single-point assessment of drug action after a challenge test, should generally be avoided. This is particularly relevant for situations where one expects time-curve shifts, tolerance/rebound, impact of disease, or hormetic concentration-response relationships to occur. Copyright © 2014 Elsevier B.V. All rights reserved.

[Study on the automatic parameters identification of water pipe network model].

PubMed

Jia, Hai-Feng; Zhao, Qi-Feng

2010-01-01

Based on the problems analysis on development and application of water pipe network model, the model parameters automatic identification is regarded as a kernel bottleneck of model's application in water supply enterprise. The methodology of water pipe network model parameters automatic identification based on GIS and SCADA database is proposed. Then the kernel algorithm of model parameters automatic identification is studied, RSA (Regionalized Sensitivity Analysis) is used for automatic recognition of sensitive parameters, and MCS (Monte-Carlo Sampling) is used for automatic identification of parameters, the detail technical route based on RSA and MCS is presented. The module of water pipe network model parameters automatic identification is developed. At last, selected a typical water pipe network as a case, the case study on water pipe network model parameters automatic identification is conducted and the satisfied results are achieved.

Wisconsin District Case Study. A Report and Estimating Tool for K-12 School Districts

ERIC Educational Resources Information Center

Consortium for School Networking, 2004

2004-01-01

The Wisconsin case study school district is primarily urban and growing with 21,500 students on 40 campuses. This document contains case studies that are presented in the same format at the 2003 studies, but also have a focus on additional technologies beyond the base distributed computing model. These new technologies are voice/data integration,…

Evolving Curricular Models in Culinary Arts: An Instrumental Case Study of a Technical Field

ERIC Educational Resources Information Center

Cossio, Allison

2016-01-01

The purpose of this research study was to examine how chefs and other individuals in the food industry understood the field of culinary arts. This study used an instrumental case study with purposeful sampling of multiple cases. Through a series of open-ended interviews using snowball-sampling strategy that concluded with 45 participants sharing…

Causal Inference in Retrospective Studies.

ERIC Educational Resources Information Center

Holland, Paul W.; Rubin, Donald B.

1988-01-01

The problem of drawing causal inferences from retrospective case-controlled studies is considered. A model for causal inference in prospective studies is applied to retrospective studies. Limitations of case-controlled studies are formulated concerning relevant parameters that can be estimated in such studies. A coffee-drinking/myocardial…

Prognostic model for psychological outcomes in ambulatory surgery patients: A prospective study using a structural equation modeling framework.

PubMed

Mijderwijk, Hendrik-Jan; Stolker, Robert Jan; Duivenvoorden, Hugo J; Klimek, Markus; Steyerberg, Ewout W

2018-01-01

Surgical procedures are increasingly carried out in a day-case setting. Along with this increase, psychological outcomes have become prominent. The objective was to evaluate prospectively the prognostic effects of sociodemographic, medical, and psychological variables assessed before day-case surgery on psychological outcomes after surgery. The study was carried out between October 2010 and September 2011. We analyzed 398 mixed patients, from a randomized controlled trial, undergoing day-case surgery at a university medical center. Structural equation modeling was used to jointly study presurgical prognostic variables relating to sociodemographics (age, sex, nationality, marital status, having children, religion, educational level, employment), medical status (BMI, heart rate), and psychological status associated with anxiety (State-Trait Anxiety Inventory (STAI), Hospital Anxiety and Depression Scale (HADS-A)), fatigue (Multidimensional Fatigue Inventory (MFI)), aggression (State-Trait Anger Scale (STAS)), depressive moods (HADS-D), self-esteem, and self-efficacy. We studied psychological outcomes on day 7 after surgery, including anxiety, fatigue, depressive moods, and aggression regulation. The final prognostic model comprised the following variables: anxiety (STAI, HADS-A), fatigue (MFI), depression (HADS-D), aggression (STAS), self-efficacy, sex, and having children. The corresponding psychological variables as assessed at baseline were prominent (i.e. standardized regression coefficients ≥ 0.20), with STAI-Trait score being the strongest predictor overall. STAI-State (adjusted R2 = 0.44), STAI-Trait (0.66), HADS-A (0.45) and STAS-Trait (0.54) were best predicted. We provide a prognostic model that adequately predicts multiple postoperative outcomes in day-case surgery. Consequently, this enables timely identification of vulnerable patients who may require additional medical or psychological preventive treatment or-in a worst-case scenario-could be unselected for day-case surgery.

The contribution of case study design to supporting research on Clubhouse psychosocial rehabilitation.

PubMed

Raeburn, Toby; Schmied, Virginia; Hungerford, Catherine; Cleary, Michelle

2015-10-01

Psychosocial Clubhouses provide recovery-focused psychosocial rehabilitation to people with serious mental illness at over 300 sites in more than 30 countries worldwide. To deliver the services involved, Clubhouses employ a complex mix of theory, programs and relationships, with this complexity presenting a number of challenges to those undertaking Clubhouse research. This paper provides an overview of the usefulness of case study designs for Clubhouse researchers; and suggests ways in which the evaluation of Clubhouse models can be facilitated. The paper begins by providing a brief explanation of the Clubhouse model of psychosocial rehabilitation, and the need for ongoing evaluation of the services delivered. This explanation is followed by an introduction to case study design, with consideration given to the way in which case studies have been used in past Clubhouse research. It is posited that case study design provides a methodological framework that supports the analysis of either quantitative, qualitative or a mixture of both types of data to investigate complex phenomena in their everyday contexts, and thereby support the development of theory. As such, case study approaches to research are well suited to the Clubhouse environment. The paper concludes with recommendations for future Clubhouse researchers who choose to employ a case study design. While the quality of case study research that explores Clubhouses has been variable in the past, if applied in a diligent manner, case study design has a valuable contribution to make in future Clubhouse research.

The West. Grade Five (Unit V). Resource Unit. Project Social Studies.

ERIC Educational Resources Information Center

Minnesota Univ., Minneapolis. Project Social Studies Curriculum Center.

This resource unit for 5th graders includes three case studies and a sub-unit on the West as a region. Three sequent occupance case studies which are suggestive, rather than prescriptive, comprise the first part of the unit. Teachers may decide to select only one for an in-depth study or may decide to design a case study modeled after this…

Correlation analysis of air pollutant index levels and dengue cases across five different zones in Selangor, Malaysia.

PubMed

Thiruchelvam, Loshini; Dass, Sarat C; Zaki, Rafdzah; Yahya, Abqariyah; Asirvadam, Vijanth S

2018-05-07

This study investigated the potential relationship between dengue cases and air quality - as measured by the Air Pollution Index (API) for five zones in the state of Selangor, Malaysia. Dengue case patterns can be learned using prediction models based on feedback (lagged terms). However, the question whether air quality affects dengue cases is still not thoroughly investigated based on such feedback models. This work developed dengue prediction models using the autoregressive integrated moving average (ARIMA) and ARIMA with an exogeneous variable (ARIMAX) time series methodologies with API as the exogeneous variable. The Box Jenkins approach based on maximum likelihood was used for analysis as it gives effective model estimates and prediction. Three stages of model comparison were carried out for each zone: first with ARIMA models without API, then ARIMAX models with API data from the API station for that zone and finally, ARIMAX models with API data from the zone and spatially neighbouring zones. Bayesian Information Criterion (BIC) gives goodness-of-fit versus parsimony comparisons between all elicited models. Our study found that ARIMA models, with the lowest BIC value, outperformed the rest in all five zones. The BIC values for the zone of Kuala Selangor were -800.66, -796.22, and -790.5229, respectively, for ARIMA only, ARIMAX with single API component and ARIMAX with API components from its zone and spatially neighbouring zones. Therefore, we concluded that API levels, either temporally for each zone or spatio- temporally based on neighbouring zones, do not have a significant effect on dengue cases.

HSPF Modeling for Compliance and Enforcement: An Urban Case Study

NASA Astrophysics Data System (ADS)

Marshalonis, D.

2017-12-01

Stormwater runoff is one of the most significant challenges to water quality facing surface waters globally. In the United States, the Environmental Protection Agency (EPA) regulates stormwater flows through its National Pollutant Discharge Elimination System (NPDES) program permits. When egregious violations occur, EPA may develop its case and prove those violations through the legal dispute process. However, evidence in stormwater-related cases is ephemeral, difficult to collect due to unpredictable weather dynamics, and there are usually no witnesses. The work presented here illustrates an approach EPA takes for certain wet weather cases: introduce results from hydrologic and hydraulic models as evidence to meet legal burden of proof standards. The challenges and opportunities of using models in stormwater discharge modeling are highlighted.

Calibration and verification of models of organic carbon removal kinetics in Aerated Submerged Fixed-Bed Biofilm Reactors (ASFBBR): a case study of wastewater from an oil-refinery.

PubMed

Trojanowicz, Karol; Wójcik, Włodzimierz

2011-01-01

The article presents a case-study on the calibration and verification of mathematical models of organic carbon removal kinetics in biofilm. The chosen Harremöes and Wanner & Reichert models were calibrated with a set of model parameters obtained both during dedicated studies conducted at pilot- and lab-scales for petrochemical wastewater conditions and from the literature. Next, the models were successfully verified through studies carried out utilizing a pilot ASFBBR type bioreactor installed in an oil-refinery wastewater treatment plant. During verification the pilot biofilm reactor worked under varying surface organic loading rates (SOL), dissolved oxygen concentrations and temperatures. The verification proved that the models can be applied in practice to petrochemical wastewater treatment engineering for e.g. biofilm bioreactor dimensioning.

An analytical study of the dual mass mechanical system stability

NASA Astrophysics Data System (ADS)

Nikolov, Svetoslav; Sinapov, Petko; Kralov, Ivan; Ignatov, Ignat

2011-12-01

In this paper an autonomous, nonlinear model of five ordinary differential equations modeling the motion of a dual mass mechanical system with universal joint is studied. The model is investigated qualitatively. On the base of the stability analysis performed, we obtain that the system is: i) in an equilibrium state, or ii) in a structurally unstable behavior when equilibrium states disappear. In case (i) the system is in a normal technical condition and in case (ii) hard break-downs take place.

Homeland Security Collaboration: Catch Phrase or Preeminent Organizational Construct?

DTIC Science & Technology

2009-09-01

collaborative effort? C. RESEARCH METHODOLOGY This research project utilized a modified case study methodology. The traditional case study method ...discussing the research method , offering smart practices and culminate with findings and recommendations. Chapter II Homeland Security Collaboration...41 Centers for Regional Excellence, “Building Models.” 16 Chapter III Research Methodology:  Modified Case Study Method is

Individualization of Instruction: High School Chemistry - A Case Study.

ERIC Educational Resources Information Center

Altieri, Donald; Becht, Paul

This publication contains information on the individualization of instruction in high school chemistry in the form of a case study. The subject of the case study is the P. K. Yonge Laboratory School of the University of Florida, Gainesville. The instructional model, however, was also field-tested in 18 schools during 1971-72 and 1972-73. The…

Airpower Projection in the Anti-Access/Area Denial Environment: Dispersed Operations

DTIC Science & Technology

2015-02-01

Raptor Case Study.....................................................................6 Risks to Dispersed Operations...project airpower, this paper breaks down a case study of the Rapid Raptor concept. The risks with executing a dispersed model are analyzed and mitigation...will force leaders to look at alternative ways to project power. Alternative Option: Rapid Raptor Case Study The ability to defend forward operating

The Use of Business Case Studies in Business German Classes.

ERIC Educational Resources Information Center

Schutte, Lilith

The use of business case studies, defined as sophisticated models that present practical business problems and theoretical guidelines that can be used to solve the problems, is discussed. It is suggested that the main advantages of case studies are that they are usually more interesting to read than theoretical materials and they encourage student…

Lessons for Co-Innovation in Agricultural Innovation Systems: A Multiple Case Study Analysis and a Conceptual Model

ERIC Educational Resources Information Center

Fielke, Simon J.; Botha, Neels; Reid, Janet; Gray, David; Blackett, Paula; Park, Nicola; Williams, Tracy

2018-01-01

Purpose: This paper highlights important lessons for co-innovation drawn from three ex-post case study innovation projects implemented within three sub-sectors of the primary industry sector in New Zealand. Design/methodology/approach: The characteristics that fostered co-innovation in each innovation project case study were identified from…

DAMS: A Model to Assess Domino Effects by Using Agent-Based Modeling and Simulation.

PubMed

Zhang, Laobing; Landucci, Gabriele; Reniers, Genserik; Khakzad, Nima; Zhou, Jianfeng

2017-12-19

Historical data analysis shows that escalation accidents, so-called domino effects, have an important role in disastrous accidents in the chemical and process industries. In this study, an agent-based modeling and simulation approach is proposed to study the propagation of domino effects in the chemical and process industries. Different from the analytical or Monte Carlo simulation approaches, which normally study the domino effect at probabilistic network levels, the agent-based modeling technique explains the domino effects from a bottom-up perspective. In this approach, the installations involved in a domino effect are modeled as agents whereas the interactions among the installations (e.g., by means of heat radiation) are modeled via the basic rules of the agents. Application of the developed model to several case studies demonstrates the ability of the model not only in modeling higher-level domino effects and synergistic effects but also in accounting for temporal dependencies. The model can readily be applied to large-scale complicated cases. © 2017 Society for Risk Analysis.

Associative visual agnosia: a case study.

PubMed

Charnallet, A; Carbonnel, S; David, D; Moreaud, O

2008-01-01

We report a case of massive associative visual agnosia. In the light of current theories of identification and semantic knowledge organization, a deficit involving both levels of structural description system and visual semantics must be assumed to explain the case. We suggest, in line with a previous case study, an alternative account in the framework of (non abstractive) episodic models of memory.

Use of observational and model-derived fields and regime model output statistics in mesoscale forecasting

NASA Technical Reports Server (NTRS)

Forbes, G. S.; Pielke, R. A.

1985-01-01

Various empirical and statistical weather-forecasting studies which utilize stratification by weather regime are described. Objective classification was used to determine weather regime in some studies. In other cases the weather pattern was determined on the basis of a parameter representing the physical and dynamical processes relevant to the anticipated mesoscale phenomena, such as low level moisture convergence and convective precipitation, or the Froude number and the occurrence of cold-air damming. For mesoscale phenomena already in existence, new forecasting techniques were developed. The use of cloud models in operational forecasting is discussed. Models to calculate the spatial scales of forcings and resultant response for mesoscale systems are presented. The use of these models to represent the climatologically most prevalent systems, and to perform case-by-case simulations is reviewed. Operational implementation of mesoscale data into weather forecasts, using both actual simulation output and method-output statistics is discussed.

A new framework to enhance the interpretation of external validation studies of clinical prediction models.

PubMed

Debray, Thomas P A; Vergouwe, Yvonne; Koffijberg, Hendrik; Nieboer, Daan; Steyerberg, Ewout W; Moons, Karel G M

2015-03-01

It is widely acknowledged that the performance of diagnostic and prognostic prediction models should be assessed in external validation studies with independent data from "different but related" samples as compared with that of the development sample. We developed a framework of methodological steps and statistical methods for analyzing and enhancing the interpretation of results from external validation studies of prediction models. We propose to quantify the degree of relatedness between development and validation samples on a scale ranging from reproducibility to transportability by evaluating their corresponding case-mix differences. We subsequently assess the models' performance in the validation sample and interpret the performance in view of the case-mix differences. Finally, we may adjust the model to the validation setting. We illustrate this three-step framework with a prediction model for diagnosing deep venous thrombosis using three validation samples with varying case mix. While one external validation sample merely assessed the model's reproducibility, two other samples rather assessed model transportability. The performance in all validation samples was adequate, and the model did not require extensive updating to correct for miscalibration or poor fit to the validation settings. The proposed framework enhances the interpretation of findings at external validation of prediction models. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Emergent Theorisations in Modelling the Teaching of Two Science Teachers

NASA Astrophysics Data System (ADS)

Monteiro, Rute; Carrillo, José; Aguaded, Santiago

2008-05-01

The main goal of this study is to understand the teacher’s thoughts and action when he/she is immersed in the activity of teaching. To do so, it describes the procedures used to model two teachers’ practice with respect to the topic of Plant Diversity. Starting from a consideration of the theoretical constructs of script, routine and improvisation, this modelling basically corresponds to a microanalysis of the teacher’s beliefs, goals and knowledge, as highlighted in the classroom activity. From the process of modelling certain theorisations emerge, corresponding to abstractions gained from concrete cases. They allow us to foreground strong relationships between the beliefs and actions, and the knowledge and objectives of the teacher in action. Envisaged as conjectures rather than generalisations, these abstractions could possibly be extended to other cases, and tested out with new case studies, questioning their formulation or perhaps demonstrating that the limits of their applicability do not go beyond the original cases.

Antigravity in F( R) and Brans-Dicke theories

NASA Astrophysics Data System (ADS)

Oikonomou, V. K.; Karagiannakis, N.

2014-12-01

We study antigravity in F( R)-theory originating scalar-tensor theories and also in Brans-Dicke models without cosmological constant. For the F( R) theory case, we obtain the Jordan frame antigravity scalar-tensor theory by using a variant of the Lagrange multipliers method and we numerically study the time dependent effective gravitational constant. As we shall demonstrate in detail by using some viable F( R) models, although the initial F( R) models have no antigravity, their scalar-tensor counterpart theories might or not have antigravity, a fact mainly depending on the parameter that characterizes antigravity. Similar results hold true in the Brans-Dicke model, which we also studied numerically. In addition, regarding the Brans-Dicke model we also found some analytic cosmological solutions. Since antigravity is an unwanted feature in gravitational theories, our findings suggest that in the case of F( R) theories, antigravity does not occur in the real world described by the F( R) theory, but might occur in the Jordan frame scalar-tensor counterpart of the F( R) theory, and this happens under certain circumstances. The central goal of our study is to present all different cases in which antigravity might occur in modified gravity models.

Ensemble modelling and structured decision-making to support Emergency Disease Management.

PubMed

Webb, Colleen T; Ferrari, Matthew; Lindström, Tom; Carpenter, Tim; Dürr, Salome; Garner, Graeme; Jewell, Chris; Stevenson, Mark; Ward, Michael P; Werkman, Marleen; Backer, Jantien; Tildesley, Michael

2017-03-01

Epidemiological models in animal health are commonly used as decision-support tools to understand the impact of various control actions on infection spread in susceptible populations. Different models contain different assumptions and parameterizations, and policy decisions might be improved by considering outputs from multiple models. However, a transparent decision-support framework to integrate outputs from multiple models is nascent in epidemiology. Ensemble modelling and structured decision-making integrate the outputs of multiple models, compare policy actions and support policy decision-making. We briefly review the epidemiological application of ensemble modelling and structured decision-making and illustrate the potential of these methods using foot and mouth disease (FMD) models. In case study one, we apply structured decision-making to compare five possible control actions across three FMD models and show which control actions and outbreak costs are robustly supported and which are impacted by model uncertainty. In case study two, we develop a methodology for weighting the outputs of different models and show how different weighting schemes may impact the choice of control action. Using these case studies, we broadly illustrate the potential of ensemble modelling and structured decision-making in epidemiology to provide better information for decision-making and outline necessary development of these methods for their further application. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Artificial neural network model to distinguish follicular adenoma from follicular carcinoma on fine needle aspiration of thyroid.

PubMed

Savala, Rajiv; Dey, Pranab; Gupta, Nalini

2018-03-01

To distinguish follicular adenoma (FA) and follicular carcinoma (FC) of thyroid in fine needle aspiration cytology (FNAC) is a challenging problem. In this article, we attempted to build an artificial neural network (ANN) model from the cytological and morphometric features of the FNAC smears of thyroid to distinguish FA from FC. The cytological features and morphometric analysis were done on the FNAC smears of histology proven cases of FA (26) and FC (31). The cytological features were analysed semi-quantitatively by two independent observers (RS and PD). These data were used to make an ANN model to differentiate FA versus FC on FNAC material. The performance of this ANN model was assessed by analysing the confusion matrix and receiving operator curve. There were 39 cases in training set, 9 cases each in validation and test sets. In the test group, ANN model successfully distinguished all cases (9/9) of FA and FC. The area under receiver operating curve was 1. The present ANN model is efficient to diagnose follicular adenoma and carcinoma cases on cytology smears without any error. In future, this ANN model will be able to diagnose follicular adenoma and carcinoma cases on thyroid aspirate. This study has immense potential in future. This is an open ended ANN model and more parameters and more cases can be included to make the model much stronger. © 2017 Wiley Periodicals, Inc.

Measuring case-mix complexity of tertiary care hospitals using DRGs.

PubMed

Park, Hayoung; Shin, Youngsoo

2004-02-01

The objectives of the study were to develop a model that measures and evaluates case-mix complexity of tertiary care hospitals, and to examine the characteristics of such a model. Physician panels defined three classes of case complexity and assigned disease categories represented by Adjacent Diagnosis Related Groups (ADRGs) to one of three case complexity classes. Three types of scores, indicating proportions of inpatients in each case complexity class standardized by the proportions at the national level, were defined to measure the case-mix complexity of a hospital. Discharge information for about 10% of inpatient episodes at 85 hospitals with bed size larger than 400 and their input structure and research and education activity were used to evaluate the case-mix complexity model. Results show its power to predict hospitals with the expected functions of tertiary care hospitals, i.e. resource intensive care, expensive input structure, and high levels of research and education activities.

Implementing Generalized Additive Models to Estimate the Expected Value of Sample Information in a Microsimulation Model: Results of Three Case Studies.

PubMed

Rabideau, Dustin J; Pei, Pamela P; Walensky, Rochelle P; Zheng, Amy; Parker, Robert A

2018-02-01

The expected value of sample information (EVSI) can help prioritize research but its application is hampered by computational infeasibility, especially for complex models. We investigated an approach by Strong and colleagues to estimate EVSI by applying generalized additive models (GAM) to results generated from a probabilistic sensitivity analysis (PSA). For 3 potential HIV prevention and treatment strategies, we estimated life expectancy and lifetime costs using the Cost-effectiveness of Preventing AIDS Complications (CEPAC) model, a complex patient-level microsimulation model of HIV progression. We fitted a GAM-a flexible regression model that estimates the functional form as part of the model fitting process-to the incremental net monetary benefits obtained from the CEPAC PSA. For each case study, we calculated the expected value of partial perfect information (EVPPI) using both the conventional nested Monte Carlo approach and the GAM approach. EVSI was calculated using the GAM approach. For all 3 case studies, the GAM approach consistently gave similar estimates of EVPPI compared with the conventional approach. The EVSI behaved as expected: it increased and converged to EVPPI for larger sample sizes. For each case study, generating the PSA results for the GAM approach required 3 to 4 days on a shared cluster, after which EVPPI and EVSI across a range of sample sizes were evaluated in minutes. The conventional approach required approximately 5 weeks for the EVPPI calculation alone. Estimating EVSI using the GAM approach with results from a PSA dramatically reduced the time required to conduct a computationally intense project, which would otherwise have been impractical. Using the GAM approach, we can efficiently provide policy makers with EVSI estimates, even for complex patient-level microsimulation models.

Lung and stomach cancer associations with groundwater radon in North Carolina, USA

PubMed Central

Messier, Kyle P; Serre, Marc L

2017-01-01

Abstract Background: The risk of indoor air radon for lung cancer is well studied, but the risks of groundwater radon for both lung and stomach cancer are much less studied, and with mixed results. Methods: Geomasked and geocoded stomach and lung cancer cases in North Carolina from 1999 to 2009 were obtained from the North Carolina Central Cancer Registry. Models for the association with groundwater radon and multiple confounders were implemented at two scales: (i) an ecological model estimating cancer incidence rates at the census tract level; and (ii) a case-only logistic model estimating the odds that individual cancer cases are members of local cancer clusters. Results: For the lung cancer incidence rate model, groundwater radon is associated with an incidence rate ratio of 1.03 [95% confidence interval (CI) = 1.01, 1.06] for every 100 Bq/l increase in census tract averaged concentration. For the cluster membership models, groundwater radon exposure results in an odds ratio for lung cancer of 1.13 (95% CI = 1.04, 1.23) and for stomach cancer of 1.24 (95% CI = 1.03, 1.49), which means groundwater radon, after controlling for multiple confounders and spatial auto-correlation, increases the odds that lung and stomach cancer cases are members of their respective cancer clusters. Conclusion: Our study provides epidemiological evidence of a positive association between groundwater radon exposure and lung cancer incidence rates. The cluster membership model results find groundwater radon increases the odds that both lung and stomach cancer cases occur within their respective cancer clusters. The results corroborate previous biokinetic and mortality studies that groundwater radon is associated with increased risk for lung and stomach cancer. PMID:27639278

Lung and stomach cancer associations with groundwater radon in North Carolina, USA.

PubMed

Messier, Kyle P; Serre, Marc L

2017-04-01

The risk of indoor air radon for lung cancer is well studied, but the risks of groundwater radon for both lung and stomach cancer are much less studied, and with mixed results. Geomasked and geocoded stomach and lung cancer cases in North Carolina from 1999 to 2009 were obtained from the North Carolina Central Cancer Registry. Models for the association with groundwater radon and multiple confounders were implemented at two scales: (i) an ecological model estimating cancer incidence rates at the census tract level; and (ii) a case-only logistic model estimating the odds that individual cancer cases are members of local cancer clusters. For the lung cancer incidence rate model, groundwater radon is associated with an incidence rate ratio of 1.03 [95% confidence interval (CI) = 1.01, 1.06] for every 100 Bq/l increase in census tract averaged concentration. For the cluster membership models, groundwater radon exposure results in an odds ratio for lung cancer of 1.13 (95% CI = 1.04, 1.23) and for stomach cancer of 1.24 (95% CI = 1.03, 1.49), which means groundwater radon, after controlling for multiple confounders and spatial auto-correlation, increases the odds that lung and stomach cancer cases are members of their respective cancer clusters. Our study provides epidemiological evidence of a positive association between groundwater radon exposure and lung cancer incidence rates. The cluster membership model results find groundwater radon increases the odds that both lung and stomach cancer cases occur within their respective cancer clusters. The results corroborate previous biokinetic and mortality studies that groundwater radon is associated with increased risk for lung and stomach cancer. © The Author 2016; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association

The Misspecification of the Covariance Structures in Multilevel Models for Single-Case Data: A Monte Carlo Simulation Study

ERIC Educational Resources Information Center

Moeyaert, Mariola; Ugille, Maaike; Ferron, John M.; Beretvas, S. Natasha; Van den Noortgate, Wim

2016-01-01

The impact of misspecifying covariance matrices at the second and third levels of the three-level model is evaluated. Results indicate that ignoring existing covariance has no effect on the treatment effect estimate. In addition, the between-case variance estimates are unbiased when covariance is either modeled or ignored. If the research interest…

Hierarchical Bayesian Modeling of Fluid-Induced Seismicity

NASA Astrophysics Data System (ADS)

Broccardo, M.; Mignan, A.; Wiemer, S.; Stojadinovic, B.; Giardini, D.

2017-11-01

In this study, we present a Bayesian hierarchical framework to model fluid-induced seismicity. The framework is based on a nonhomogeneous Poisson process with a fluid-induced seismicity rate proportional to the rate of injected fluid. The fluid-induced seismicity rate model depends upon a set of physically meaningful parameters and has been validated for six fluid-induced case studies. In line with the vision of hierarchical Bayesian modeling, the rate parameters are considered as random variables. We develop both the Bayesian inference and updating rules, which are used to develop a probabilistic forecasting model. We tested the Basel 2006 fluid-induced seismic case study to prove that the hierarchical Bayesian model offers a suitable framework to coherently encode both epistemic uncertainty and aleatory variability. Moreover, it provides a robust and consistent short-term seismic forecasting model suitable for online risk quantification and mitigation.

Re-reading "Little Hans": Freud's case study and the question of competing paradigms in psychoanalysis.

PubMed

Midgley, Nicholas

2006-01-01

Psychoanalysts have long recognized the complex interaction between clinical data and formal psychoanalytic theories. While clinical data are often used to provide "evidence" for psychoanalytic paradigms, the theoretical model used by the analyst also structures what can and cannot be seen in the data. This delicate interaction between theory and clinical data can be seen in the history of interpretations of Freud's "Analysis of a Phobia in a Five-Year-Old Boy" ("Little Hans"). Freud's himself revised his reading of the case in 1926, after which a number of psychoanalysts--including Melanie Klein, Jacques Lacan, and John Bowlby--reinterpreted the case in the light of their particular models of the mind. These analysts each found "evidence" for their theoretical model within this classic case study, and in doing so they illuminated aspects of the case that had previously been obscured, while also revealing a great deal about the shifting preoccupations of psychoanalysis as a field.

Enhancing Students' Transitions to College and Careers: A Case Study of Distributed Leadership Practice in Supporting a High School Career Academy Model

ERIC Educational Resources Information Center

Malin, Joel R.; Hackmann, Donald G.

2017-01-01

Creating effective pathways for students to transition from high school to college or career is immensely important and, although challenging, some have developed promising approaches. This case study examined how formal and informal leaders in an urban high school and district collaborated to implement a college and career academy model,…

Court-Led Educational Reforms in Political Third Rails: Lessons from the Litigation over Ultra-Religious Jewish Schools in Israel

ERIC Educational Resources Information Center

Perry-Hazan, Lotem

2015-01-01

This paper offers a model for evaluating the strengths and weaknesses of judicial involvement in educational reforms. It uses the model to analyze two case studies of court-led educational reforms in the third rail of Israeli politics--the curricula and the admission policies of ultra-Othodox (Haredi) schools. These case studies are located at the…

Learning to Mean in Spanish Writing: A Case Study of a Genre-Based Pedagogy for Standards-Based Writing Instruction

ERIC Educational Resources Information Center

Troyan, Francis J.

2016-01-01

This case study reports the results of a genre-based approach, which was used to explicitly teach the touristic landmark description to fourth-grade students of Spanish as a foreign language. The instructional model and unit of instruction were informed by the pedagogies of the Sydney School of Linguistics and an instructional model for…

A systematic review and qualitative analysis to inform the development of a new emergency department-based geriatric case management model.

PubMed

Sinha, Samir K; Bessman, Edward S; Flomenbaum, Neal; Leff, Bruce

2011-06-01

We inform the future development of a new geriatric emergency management practice model. We perform a systematic review of the existing evidence for emergency department (ED)-based case management models designed to improve the health, social, and health service utilization outcomes for noninstitutionalized older patients within the context of an index ED visit. This was a systematic review of English-language articles indexed in MEDLINE and CINAHL (1966 to 2010), describing ED-based case management models for older adults. Bibliographies of the retrieved articles were reviewed to identify additional references. A systematic qualitative case study analytic approach was used to identify the core operational components and outcome measures of the described clinical interventions. The authors of the included studies were also invited to verify our interpretations of their work. The determined patterns of component adherence were then used to postulate the relative importance and effect of the presence or absence of a particular component in influencing the overall effectiveness of their respective interventions. Eighteen of 352 studies (reported in 20 articles) met study criteria. Qualitative analyses identified 28 outcome measures and 8 distinct model characteristic components that included having an evidence-based practice model, nursing clinical involvement or leadership, high-risk screening processes, focused geriatric assessments, the initiation of care and disposition planning in the ED, interprofessional and capacity-building work practices, post-ED discharge follow-up with patients, and evaluation and monitoring processes. Of the 15 positive study results, 6 had all 8 characteristic components and 9 were found to be lacking at least 1 component. Two studies with positive results lacked 2 characteristic components and none lacked more than 2 components. Of the 3 studies with negative results demonstrating no positive effects based on any outcome tested, one lacked 2, one lacked 3, and one lacked 4 of the 8 model components. Successful models of ED-based case management models for older adults share certain key characteristics. This study builds on the emerging literature in this area and leverages the differences in these models and their associated outcomes to support the development of an evidence-based normative and effective geriatric emergency management practice model designed to address the special care needs and thereby improve the health and health service utilization outcomes of older patients. Copyright © 2010 American College of Emergency Physicians. Published by Mosby, Inc. All rights reserved.

Building a 3D faulted a priori model for stratigraphic inversion: Illustration of a new methodology applied on a North Sea field case study

NASA Astrophysics Data System (ADS)

Rainaud, Jean-François; Clochard, Vincent; Delépine, Nicolas; Crabié, Thomas; Poudret, Mathieu; Perrin, Michel; Klein, Emmanuel

2018-07-01

Accurate reservoir characterization is needed all along the development of an oil and gas field study. It helps building 3D numerical reservoir simulation models for estimating the original oil and gas volumes in place and for simulating fluid flow behaviors. At a later stage of the field development, reservoir characterization can also help deciding which recovery techniques need to be used for fluids extraction. In complex media, such as faulted reservoirs, flow behavior predictions within volumes close to faults can be a very challenging issue. During the development plan, it is necessary to determine which types of communication exist between faults or which potential barriers exist for fluid flows. The solving of these issues rests on accurate fault characterization. In most cases, faults are not preserved along reservoir characterization workflows. The memory of the interpreted faults from seismic is not kept during seismic inversion and further interpretation of the result. The goal of our study is at first to integrate a 3D fault network as a priori information into a model-based stratigraphic inversion procedure. Secondly, we apply our methodology on a well-known oil and gas case study over a typical North Sea field (UK Northern North Sea) in order to demonstrate its added value for determining reservoir properties. More precisely, the a priori model is composed of several geological units populated by physical attributes, they are extrapolated from well log data following the deposition mode, but usually a priori model building methods respect neither the 3D fault geometry nor the stratification dips on the fault sides. We address this difficulty by applying an efficient flattening method for each stratigraphic unit in our workflow. Even before seismic inversion, the obtained stratigraphic model has been directly used to model synthetic seismic on our case study. Comparisons between synthetic seismic obtained from our 3D fault network model give much lower residuals than with a "basic" stratigraphic model. Finally, we apply our model-based inversion considering both faulted and non-faulted a priori models. By comparing the rock impedances results obtain in the two cases, we can see a better delineation of the Brent-reservoir compartments by using the 3D faulted a priori model built with our method.

A variable turbulent Prandtl and Schmidt number model study for scramjet applications

NASA Astrophysics Data System (ADS)

Keistler, Patrick

A turbulence model that allows for the calculation of the variable turbulent Prandtl (Prt) and Schmidt (Sct) numbers as part of the solution is presented. The model also accounts for the interactions between turbulence and chemistry by modeling the corresponding terms. Four equations are added to the baseline k-zeta turbulence model: two equations for enthalpy variance and its dissipation rate to calculate the turbulent diffusivity, and two equations for the concentrations variance and its dissipation rate to calculate the turbulent diffusion coefficient. The underlying turbulence model already accounts for compressibility effects. The variable Prt /Sct turbulence model is validated and tuned by simulating a wide variety of experiments. Included in the experiments are two-dimensional, axisymmetric, and three-dimensional mixing and combustion cases. The combustion cases involved either hydrogen and air, or hydrogen, ethylene, and air. Two chemical kinetic models are employed for each of these situations. For the hydrogen and air cases, a seven species/seven reaction model where the reaction rates are temperature dependent and a nine species/nineteen reaction model where the reaction rates are dependent on both pressure and temperature are used. For the cases involving ethylene, a 15 species/44 reaction reduced model that is both pressure and temperature dependent is used, along with a 22 species/18 global reaction reduced model that makes use of the quasi-steady-state approximation. In general, fair to good agreement is indicated for all simulated experiments. The turbulence/chemistry interaction terms are found to have a significant impact on flame location for the two-dimensional combustion case, with excellent experimental agreement when the terms are included. In most cases, the hydrogen chemical mechanisms behave nearly identically, but for one case, the pressure dependent model would not auto-ignite at the same conditions as the experiment and the other chemical model. The model was artificially ignited in that case. For the cases involving ethylene combustion, the chemical model has a profound impact on the flame size, shape, and ignition location. However, without quantitative experimental data, it is difficult to determine which one is more suitable for this particular application.

A hybrid Bayesian hierarchical model combining cohort and case-control studies for meta-analysis of diagnostic tests: Accounting for partial verification bias.

PubMed

Ma, Xiaoye; Chen, Yong; Cole, Stephen R; Chu, Haitao

2016-12-01

To account for between-study heterogeneity in meta-analysis of diagnostic accuracy studies, bivariate random effects models have been recommended to jointly model the sensitivities and specificities. As study design and population vary, the definition of disease status or severity could differ across studies. Consequently, sensitivity and specificity may be correlated with disease prevalence. To account for this dependence, a trivariate random effects model had been proposed. However, the proposed approach can only include cohort studies with information estimating study-specific disease prevalence. In addition, some diagnostic accuracy studies only select a subset of samples to be verified by the reference test. It is known that ignoring unverified subjects may lead to partial verification bias in the estimation of prevalence, sensitivities, and specificities in a single study. However, the impact of this bias on a meta-analysis has not been investigated. In this paper, we propose a novel hybrid Bayesian hierarchical model combining cohort and case-control studies and correcting partial verification bias at the same time. We investigate the performance of the proposed methods through a set of simulation studies. Two case studies on assessing the diagnostic accuracy of gadolinium-enhanced magnetic resonance imaging in detecting lymph node metastases and of adrenal fluorine-18 fluorodeoxyglucose positron emission tomography in characterizing adrenal masses are presented. © The Author(s) 2014.

A Hybrid Bayesian Hierarchical Model Combining Cohort and Case-control Studies for Meta-analysis of Diagnostic Tests: Accounting for Partial Verification Bias

PubMed Central

Ma, Xiaoye; Chen, Yong; Cole, Stephen R.; Chu, Haitao

2014-01-01

To account for between-study heterogeneity in meta-analysis of diagnostic accuracy studies, bivariate random effects models have been recommended to jointly model the sensitivities and specificities. As study design and population vary, the definition of disease status or severity could differ across studies. Consequently, sensitivity and specificity may be correlated with disease prevalence. To account for this dependence, a trivariate random effects model had been proposed. However, the proposed approach can only include cohort studies with information estimating study-specific disease prevalence. In addition, some diagnostic accuracy studies only select a subset of samples to be verified by the reference test. It is known that ignoring unverified subjects may lead to partial verification bias in the estimation of prevalence, sensitivities and specificities in a single study. However, the impact of this bias on a meta-analysis has not been investigated. In this paper, we propose a novel hybrid Bayesian hierarchical model combining cohort and case-control studies and correcting partial verification bias at the same time. We investigate the performance of the proposed methods through a set of simulation studies. Two case studies on assessing the diagnostic accuracy of gadolinium-enhanced magnetic resonance imaging in detecting lymph node metastases and of adrenal fluorine-18 fluorodeoxyglucose positron emission tomography in characterizing adrenal masses are presented. PMID:24862512

Landslide susceptibility modeling applying machine learning methods: A case study from Longju in the Three Gorges Reservoir area, China

NASA Astrophysics Data System (ADS)

Zhou, Chao; Yin, Kunlong; Cao, Ying; Ahmed, Bayes; Li, Yuanyao; Catani, Filippo; Pourghasemi, Hamid Reza

2018-03-01

Landslide is a common natural hazard and responsible for extensive damage and losses in mountainous areas. In this study, Longju in the Three Gorges Reservoir area in China was taken as a case study for landslide susceptibility assessment in order to develop effective risk prevention and mitigation strategies. To begin, 202 landslides were identified, including 95 colluvial landslides and 107 rockfalls. Twelve landslide causal factor maps were prepared initially, and the relationship between these factors and each landslide type was analyzed using the information value model. Later, the unimportant factors were selected and eliminated using the information gain ratio technique. The landslide locations were randomly divided into two groups: 70% for training and 30% for verifying. Two machine learning models: the support vector machine (SVM) and artificial neural network (ANN), and a multivariate statistical model: the logistic regression (LR), were applied for landslide susceptibility modeling (LSM) for each type. The LSM index maps, obtained from combining the assessment results of the two landslide types, were classified into five levels. The performance of the LSMs was evaluated using the receiver operating characteristics curve and Friedman test. Results show that the elimination of noise-generating factors and the separated modeling of each landslide type have significantly increased the prediction accuracy. The machine learning models outperformed the multivariate statistical model and SVM model was found ideal for the case study area.

Estimating multivariate response surface model with data outliers, case study in enhancing surface layer properties of an aircraft aluminium alloy

NASA Astrophysics Data System (ADS)

Widodo, Edy; Kariyam

2017-03-01

To determine the input variable settings that create the optimal compromise in response variable used Response Surface Methodology (RSM). There are three primary steps in the RSM problem, namely data collection, modelling, and optimization. In this study focused on the establishment of response surface models, using the assumption that the data produced is correct. Usually the response surface model parameters are estimated by OLS. However, this method is highly sensitive to outliers. Outliers can generate substantial residual and often affect the estimator models. Estimator models produced can be biased and could lead to errors in the determination of the optimal point of fact, that the main purpose of RSM is not reached. Meanwhile, in real life, the collected data often contain some response variable and a set of independent variables. Treat each response separately and apply a single response procedures can result in the wrong interpretation. So we need a development model for the multi-response case. Therefore, it takes a multivariate model of the response surface that is resistant to outliers. As an alternative, in this study discussed on M-estimation as a parameter estimator in multivariate response surface models containing outliers. As an illustration presented a case study on the experimental results to the enhancement of the surface layer of aluminium alloy air by shot peening.

Variables affecting the financial viability of your practice: a case study.

PubMed

Binderman, J

2001-01-01

Utilizing the discussion of variables affecting practice financial viability, a case study is considered. The case study reveals the relative impact multiple variables have upon the bottom line, including: practice capacity, percentage of capitation, and fee-for-service in the practice, as well as patient visit rates and patient churning. This article presents basic financial information through a case study model, utilizing a series of worksheets that can be adapted to any practice situation to encourage improved financial viability.

Test-Case Generation using an Explicit State Model Checker Final Report

NASA Technical Reports Server (NTRS)

Heimdahl, Mats P. E.; Gao, Jimin

2003-01-01

In the project 'Test-Case Generation using an Explicit State Model Checker' we have extended an existing tools infrastructure for formal modeling to export Java code so that we can use the NASA Ames tool Java Pathfinder (JPF) for test case generation. We have completed a translator from our source language RSML(exp -e) to Java and conducted initial studies of how JPF can be used as a testing tool. In this final report, we provide a detailed description of the translation approach as implemented in our tools.

Molecular markers of carcinogenesis for risk stratification of individuals with colorectal polyps: a case-control study.

PubMed

Gupta, Samir; Sun, Han; Yi, Sang; Storm, Joy; Xiao, Guanghua; Balasubramanian, Bijal A; Zhang, Song; Ashfaq, Raheela; Rockey, Don C

2014-10-01

Risk stratification using number, size, and histology of colorectal adenomas is currently suboptimal for identifying patients at increased risk for future colorectal cancer. We hypothesized that molecular markers of carcinogenesis in adenomas, measured via immunohistochemistry, may help identify high-risk patients. To test this hypothesis, we conducted a retrospective, 1:1 matched case-control study (n = 216; 46% female) in which cases were patients with colorectal cancer and synchronous adenoma and controls were patients with adenoma but no colorectal cancer at baseline or within 5 years of follow-up. In phase I of analyses, we compared expression of molecular markers of carcinogenesis in case and control adenomas, blind to case status. In phase II of analyses, patients were randomly divided into independent training and validation groups to develop a model for predicting case status. We found that seven markers [p53, p21, Cox-2, β-catenin (BCAT), DNA-dependent protein kinase (DNApkcs), survivin, and O6-methylguanine-DNA methyltransferase (MGMT)] were significantly associated with case status on unadjusted analyses, as well as analyses adjusted for age and advanced adenoma status (P < 0.01 for at least one marker component). When applied to the validation set, a predictive model using these seven markers showed substantial accuracy for identifying cases [area under the receiver operation characteristic curve (AUC), 0.83; 95% confidence interval (CI), 0.74-0.92]. A parsimonious model using three markers performed similarly to the seven-marker model (AUC, 0.84). In summary, we found that molecular markers of carcinogenesis distinguished adenomas from patients with and without colorectal cancer. Furthermore, we speculate that prospective studies using molecular markers to identify individuals with polyps at risk for future neoplasia are warranted. ©2014 American Association for Cancer Research.

Hybrid-Wing-Body Vehicle Composite Fuselage Analysis and Case Study

NASA Technical Reports Server (NTRS)

Mukhopadhyay, Vivek

2014-01-01

Recent progress in the structural analysis of a Hybrid Wing-Body (HWB) fuselage concept is presented with the objective of structural weight reduction under a set of critical design loads. This pressurized efficient HWB fuselage design is presently being investigated by the NASA Environmentally Responsible Aviation (ERA) project in collaboration with the Boeing Company, Huntington Beach. The Pultruded Rod-Stiffened Efficient Unitized Structure (PRSEUS) composite concept, developed at the Boeing Company, is approximately modeled for an analytical study and finite element analysis. Stiffened plate linear theories are employed for a parametric case study. Maximum deflection and stress levels are obtained with appropriate assumptions for a set of feasible stiffened panel configurations. An analytical parametric case study is presented to examine the effects of discrete stiffener spacing and skin thickness on structural weight, deflection and stress. A finite-element model (FEM) of an integrated fuselage section with bulkhead is developed for an independent assessment. Stress analysis and scenario based case studies are conducted for design improvement. The FEM model specific weight of the improved fuselage concept is computed and compared to previous studies, in order to assess the relative weight/strength advantages of this advanced composite airframe technology

JPL Thermal Design Modeling Philosophy and NASA-STD-7009 Standard for Models and Simulations - A Case Study

NASA Technical Reports Server (NTRS)

Avila, Arturo

2011-01-01

The Standard JPL thermal engineering practice prescribes worst-case methodologies for design. In this process, environmental and key uncertain thermal parameters (e.g., thermal blanket performance, interface conductance, optical properties) are stacked in a worst case fashion to yield the most hot- or cold-biased temperature. Thus, these simulations would represent the upper and lower bounds. This, effectively, represents JPL thermal design margin philosophy. Uncertainty in the margins and the absolute temperatures is usually estimated by sensitivity analyses and/or by comparing the worst-case results with "expected" results. Applicability of the analytical model for specific design purposes along with any temperature requirement violations are documented in peer and project design review material. In 2008, NASA released NASA-STD-7009, Standard for Models and Simulations. The scope of this standard covers the development and maintenance of models, the operation of simulations, the analysis of the results, training, recommended practices, the assessment of the Modeling and Simulation (M&S) credibility, and the reporting of the M&S results. The Mars Exploration Rover (MER) project thermal control system M&S activity was chosen as a case study determining whether JPL practice is in line with the standard and to identify areas of non-compliance. This paper summarizes the results and makes recommendations regarding the application of this standard to JPL thermal M&S practices.

Stochastic model search with binary outcomes for genome-wide association studies.

PubMed

Russu, Alberto; Malovini, Alberto; Puca, Annibale A; Bellazzi, Riccardo

2012-06-01

The spread of case-control genome-wide association studies (GWASs) has stimulated the development of new variable selection methods and predictive models. We introduce a novel Bayesian model search algorithm, Binary Outcome Stochastic Search (BOSS), which addresses the model selection problem when the number of predictors far exceeds the number of binary responses. Our method is based on a latent variable model that links the observed outcomes to the underlying genetic variables. A Markov Chain Monte Carlo approach is used for model search and to evaluate the posterior probability of each predictor. BOSS is compared with three established methods (stepwise regression, logistic lasso, and elastic net) in a simulated benchmark. Two real case studies are also investigated: a GWAS on the genetic bases of longevity, and the type 2 diabetes study from the Wellcome Trust Case Control Consortium. Simulations show that BOSS achieves higher precisions than the reference methods while preserving good recall rates. In both experimental studies, BOSS successfully detects genetic polymorphisms previously reported to be associated with the analyzed phenotypes. BOSS outperforms the other methods in terms of F-measure on simulated data. In the two real studies, BOSS successfully detects biologically relevant features, some of which are missed by univariate analysis and the three reference techniques. The proposed algorithm is an advance in the methodology for model selection with a large number of features. Our simulated and experimental results showed that BOSS proves effective in detecting relevant markers while providing a parsimonious model.

The Effect of a Case-Based Reasoning Instructional Model on Korean High School Students' Awareness in Climate Change Unit

ERIC Educational Resources Information Center

Jeong, Jinwoo; Kim, Hyoungbum; Chae, Dong-hyun; Kim, Eunjeong

2014-01-01

The purpose of this study is to investigate the effects of the case-based reasoning instructional model on learning about climate change unit. Results suggest that students showed interest because it allowed them to find the solution to the problem and solve the problem for themselves by analogy from other cases such as crossword puzzles in an…

Screening of pollution control and clean-up materials for river chemical spills using the multiple case-based reasoning method with a difference-driven revision strategy.

PubMed

Liu, Rentao; Jiang, Jiping; Guo, Liang; Shi, Bin; Liu, Jie; Du, Zhaolin; Wang, Peng

2016-06-01

In-depth filtering of emergency disposal technology (EDT) and materials has been required in the process of environmental pollution emergency disposal. However, an urgent problem that must be solved is how to quickly and accurately select the most appropriate materials for treating a pollution event from the existing spill control and clean-up materials (SCCM). To meet this need, the following objectives were addressed in this study. First, the material base and a case base for environment pollution emergency disposal were established to build a foundation and provide material for SCCM screening. Second, the multiple case-based reasoning model method with a difference-driven revision strategy (DDRS-MCBR) was applied to improve the original dual case-based reasoning model method system, and screening and decision-making was performed for SCCM using this model. Third, an actual environmental pollution accident from 2012 was used as a case study to verify the material base, case base, and screening model. The results demonstrated that the DDRS-MCBR method was fast, efficient, and practical. The DDRS-MCBR method changes the passive situation in which the choice of SCCM screening depends only on the subjective experience of the decision maker and offers a new approach to screening SCCM.

Time-series-based hybrid mathematical modelling method adapted to forecast automotive and medical waste generation: Case study of Lithuania.

PubMed

Karpušenkaitė, Aistė; Ruzgas, Tomas; Denafas, Gintaras

2018-05-01

The aim of the study was to create a hybrid forecasting method that could produce higher accuracy forecasts than previously used 'pure' time series methods. Mentioned methods were already tested with total automotive waste, hazardous automotive waste, and total medical waste generation, but demonstrated at least a 6% error rate in different cases and efforts were made to decrease it even more. Newly developed hybrid models used a random start generation method to incorporate different time-series advantages and it helped to increase the accuracy of forecasts by 3%-4% in hazardous automotive waste and total medical waste generation cases; the new model did not increase the accuracy of total automotive waste generation forecasts. Developed models' abilities to forecast short- and mid-term forecasts were tested using prediction horizon.

Associative Visual Agnosia: A Case Study

PubMed Central

Charnallet, A.; Carbonnel, S.; David, D.; Moreaud, O.

2008-01-01

We report a case of massive associative visual agnosia. In the light of current theories of identification and semantic knowledge organization, a deficit involving both levels of structural description system and visual semantics must be assumed to explain the case. We suggest, in line with a previous case study [1], an alternative account in the framework of (non abstractive) episodic models of memory [4]. PMID:18413915

A retrospective likelihood approach for efficient integration of multiple omics factors in case-control association studies.

PubMed

Balliu, Brunilda; Tsonaka, Roula; Boehringer, Stefan; Houwing-Duistermaat, Jeanine

2015-03-01

Integrative omics, the joint analysis of outcome and multiple types of omics data, such as genomics, epigenomics, and transcriptomics data, constitute a promising approach for powerful and biologically relevant association studies. These studies often employ a case-control design, and often include nonomics covariates, such as age and gender, that may modify the underlying omics risk factors. An open question is how to best integrate multiple omics and nonomics information to maximize statistical power in case-control studies that ascertain individuals based on the phenotype. Recent work on integrative omics have used prospective approaches, modeling case-control status conditional on omics, and nonomics risk factors. Compared to univariate approaches, jointly analyzing multiple risk factors with a prospective approach increases power in nonascertained cohorts. However, these prospective approaches often lose power in case-control studies. In this article, we propose a novel statistical method for integrating multiple omics and nonomics factors in case-control association studies. Our method is based on a retrospective likelihood function that models the joint distribution of omics and nonomics factors conditional on case-control status. The new method provides accurate control of Type I error rate and has increased efficiency over prospective approaches in both simulated and real data. © 2015 Wiley Periodicals, Inc.

Model-Selection Theory: The Need for a More Nuanced Picture of Use-Novelty and Double-Counting.

PubMed

Steele, Katie; Werndl, Charlotte

2018-06-01

This article argues that common intuitions regarding (a) the specialness of 'use-novel' data for confirmation and (b) that this specialness implies the 'no-double-counting rule', which says that data used in 'constructing' (calibrating) a model cannot also play a role in confirming the model's predictions, are too crude. The intuitions in question are pertinent in all the sciences, but we appeal to a climate science case study to illustrate what is at stake. Our strategy is to analyse the intuitive claims in light of prominent accounts of confirmation of model predictions. We show that on the Bayesian account of confirmation, and also on the standard classical hypothesis-testing account, claims (a) and (b) are not generally true; but for some select cases, it is possible to distinguish data used for calibration from use-novel data, where only the latter confirm. The more specialized classical model-selection methods, on the other hand, uphold a nuanced version of claim (a), but this comes apart from (b), which must be rejected in favour of a more refined account of the relationship between calibration and confirmation. Thus, depending on the framework of confirmation, either the scope or the simplicity of the intuitive position must be revised. 1   Introduction 2   A Climate Case Study 3   The Bayesian Method vis-à-vis Intuitions 4   Classical Tests vis-à-vis Intuitions 5   Classical Model-Selection Methods vis-à-vis Intuitions    5.1   Introducing classical model-selection methods    5.2   Two cases 6   Re-examining Our Case Study 7   Conclusion .

Numerical modelling for quantitative environmental risk assessment for the disposal of drill cuttings and mud

NASA Astrophysics Data System (ADS)

Wahab, Mohd Amirul Faiz Abdul; Shaufi Sokiman, Mohamad; Parsberg Jakobsen, Kim

2017-10-01

To investigate the fate of drilling waste and their impacts towards surrounding environment, numerical models were generated using an environmental software; MIKE by DHI. These numerical models were used to study the transportation of suspended drill waste plumes in the water column and its deposition on seabed in South China Sea (SCS). A random disposal site with the model area of 50 km × 25 km was selected near the Madalene Shoal in SCS and the ambient currents as well as other meteorological conditions were simulated in details at the proposed location. This paper was focusing on sensitivity study of different drill waste particle characteristics on impacts towards marine receiving environment. The drilling scenarios were obtained and adapted from the oil producer well at offshore Sabah (Case 1) and data from actual exploration drilling case at Pumbaa location (PL 469) in the Norwegian Sea (Case 2). The two cases were compared to study the effect of different drilling particle characteristics and their behavior in marine receiving environment after discharged. Using the Hydrodynamic and Sediment Transport models simulated in MIKE by DHI, the variation of currents and the behavior of the drilling waste particles can be analyzed and evaluated in terms of multiple degree zones of impacts.

Cylindrically symmetric cosmological model of the universe in modified gravity

NASA Astrophysics Data System (ADS)

Mishra, B.; Vadrevu, Samhita

2017-02-01

In this paper, we have constructed the cosmological models of the universe in a cylindrically symmetric space time in two classes of f(R,T) gravity (Harko et al. in Phys. Rev. D 84:024020, 2011). We have discussed two cases: one in the linear form and the other in the quadratic form of R. The matter is considered to be in the form of perfect fluid. It is observed that in the first case, the pressure and energy density remain the same, which reduces to a Zeldovich fluid. In the second case we have studied the quadratic function of f(R,T) gravity in the form f(R)=λ(R+R2) and f(T)=λ T. In the second case the pressure is in the negative domain and the energy density is in the positive domain, which confirms that the equation of state parameter is negative. The physical properties of the constructed models are studied.

The effects of video modeling in teaching functional living skills to persons with ASD: A meta-analysis of single-case studies.

PubMed

Hong, Ee Rea; Ganz, Jennifer B; Mason, Rose; Morin, Kristi; Davis, John L; Ninci, Jennifer; Neely, Leslie C; Boles, Margot B; Gilliland, Whitney D

2016-10-01

Many individuals with autism spectrum disorders (ASD) show deficits in functional living skills, leading to low independence, limited community involvement, and poor quality of life. With development of mobile devices, utilizing video modeling has become more feasible for educators to promote functional living skills of individuals with ASD. This article aims to review the single-case experimental literature and aggregate results across studies involving the use of video modeling to improve functional living skills of individuals with ASD. The authors extracted data from single-case experimental studies and evaluated them using the Tau-U effect size measure. Effects were also differentiated by categories of potential moderators and other variables, including age of participants, concomitant diagnoses, types of video modeling, and outcome measures. Results indicate that video modeling interventions are overall moderately effective with this population and dependent measures. While significant differences were not found between categories of moderators and other variables, effects were found to be at least moderate for most of them. It is apparent that more single-case experiments are needed in this area, particularly with preschool and secondary-school aged participants, participants with ASD-only and those with high-functioning ASD, and for video modeling interventions addressing community access skills. Copyright © 2016 Elsevier Ltd. All rights reserved.

Statistical distribution of the vacuum energy density in racetrack Kähler uplift models in string theory

NASA Astrophysics Data System (ADS)

Sumitomo, Yoske; Tye, S.-H. Henry; Wong, Sam S. C.

2013-07-01

We study a racetrack model in the presence of the leading α'-correction in flux compactification in Type IIB string theory, for the purpose of getting conceivable de-Sitter vacua in the large compactified volume approximation. Unlike the Kähler Uplift model studied previously, the α'-correction is more controllable for the meta-stable de-Sitter vacua in the racetrack case since the constraint on the compactified volume size is very much relaxed. We find that the vacuum energy density Λ for de-Sitter vacua approaches zero exponentially as the volume grows. We also analyze properties of the probability distribution of Λ in this class of models. As in other cases studied earlier, the probability distribution again peaks sharply at Λ = 0. We also study the Racetrack Kähler Uplift model in the Swiss-Cheese type model.

Three Cases of Adolescent Childbearing Decision-Making: The Importance of Ambivalence

ERIC Educational Resources Information Center

Bender, Soley S.

2008-01-01

Limited information is available about the childbearing decision-making experience by the pregnant adolescent. The purpose of this case study was to explore this experience with three pregnant teenagers. The study is based on nine qualitative interviews. Within-case descriptions applying the theoretical model of decision-making regarding unwanted…

Mixed Model Association with Family-Biased Case-Control Ascertainment.

PubMed

Hayeck, Tristan J; Loh, Po-Ru; Pollack, Samuela; Gusev, Alexander; Patterson, Nick; Zaitlen, Noah A; Price, Alkes L

2017-01-05

Mixed models have become the tool of choice for genetic association studies; however, standard mixed model methods may be poorly calibrated or underpowered under family sampling bias and/or case-control ascertainment. Previously, we introduced a liability threshold-based mixed model association statistic (LTMLM) to address case-control ascertainment in unrelated samples. Here, we consider family-biased case-control ascertainment, where case and control subjects are ascertained non-randomly with respect to family relatedness. Previous work has shown that this type of ascertainment can severely bias heritability estimates; we show here that it also impacts mixed model association statistics. We introduce a family-based association statistic (LT-Fam) that is robust to this problem. Similar to LTMLM, LT-Fam is computed from posterior mean liabilities (PML) under a liability threshold model; however, LT-Fam uses published narrow-sense heritability estimates to avoid the problem of biased heritability estimation, enabling correct calibration. In simulations with family-biased case-control ascertainment, LT-Fam was correctly calibrated (average χ 2 = 1.00-1.02 for null SNPs), whereas the Armitage trend test (ATT), standard mixed model association (MLM), and case-control retrospective association test (CARAT) were mis-calibrated (e.g., average χ 2 = 0.50-1.22 for MLM, 0.89-2.65 for CARAT). LT-Fam also attained higher power than other methods in some settings. In 1,259 type 2 diabetes-affected case subjects and 5,765 control subjects from the CARe cohort, downsampled to induce family-biased ascertainment, LT-Fam was correctly calibrated whereas ATT, MLM, and CARAT were again mis-calibrated. Our results highlight the importance of modeling family sampling bias in case-control datasets with related samples. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Effect of Turbulence Models on Two Massively-Separated Benchmark Flow Cases

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.

2003-01-01

Two massively-separated flow cases (the 2-D hill and the 3-D Ahmed body) were computed with several different turbulence models in the Reynolds-averaged Navier-Stokes code CFL3D as part of participation in a turbulence modeling workshop held in Poitiers, France in October, 2002. Overall, results were disappointing, but were consistent with results from other RANS codes and other turbulence models at the workshop. For the 2-D hill case, those turbulence models that predicted separation location accurately ended up yielding a too-long separation extent downstream. The one model that predicted a shorter separation extent in better agreement with LES data did so only by coincidence: its prediction of earlier reattachment was due to a too-late prediction of the separation location. For the Ahmed body, two slant angles were computed, and CFD performed fairly well for one of the cases (the larger slant angle). Both turbulence models tested in this case were very similar to each other. For the smaller slant angle, CFD predicted massive separation, whereas the experiment showed reattachment about half-way down the center of the face. These test cases serve as reminders that state- of-the-art CFD is currently not a reliable predictor of massively-separated flow physics, and that further validation studies in this area would be beneficial.

Challenges for Cloud Modeling in the Context of Aerosol–Cloud–Precipitation Interactions

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

Lebo, Zachary J.; Shipway, Ben J.; Fan, Jiwen

The International Cloud Modeling Workshop (CMW) has been a longstanding tradition in the cloud microphysics modeling community and is typically held the week prior to the International Conference on Clouds and Precipitation (ICCP). For the Ninth CMW, more than 40 participants from 10 countries convened at the Met Office in Exeter, United Kingdom. The workshop included 4 detailed case studies (described in more detail below) rooted in recent field campaigns. The overarching objective of these cases was to utilize new observations to better understand inter-model differences and model deficiencies, explore new modeling techniques, and gain physical insight into the behaviormore » of clouds. As was the case at the Eighth CMW, there was a general theme of understanding the role of aerosol impacts in the context of cloud-precipitation interactions. However, an additional objective was the focal point of several cases at the most recent workshop: microphysical-dynamical interactions. Many of the cases focused less on idealized small-domain simulations (as was the general focus of previous workshops) and more on large-scale nested configurations examining effects at various scales.« less

Quantitative analysis of multiple biokinetic models using a dynamic water phantom: A feasibility study

PubMed Central

Chiang, Fu-Tsai; Li, Pei-Jung; Chung, Shih-Ping; Pan, Lung-Fa; Pan, Lung-Kwang

2016-01-01

ABSTRACT This study analyzed multiple biokinetic models using a dynamic water phantom. The phantom was custom-made with acrylic materials to model metabolic mechanisms in the human body. It had 4 spherical chambers of different sizes, connected by 8 ditches to form a complex and adjustable water loop. One infusion and drain pole connected the chambers to an auxiliary silicon-based hose, respectively. The radio-active compound solution (TC-99m-MDP labeled) formed a sealed and static water loop inside the phantom. As clean feed water was infused to replace the original solution, the system mimicked metabolic mechanisms for data acquisition. Five cases with different water loop settings were tested and analyzed, with case settings changed by controlling valve poles located in the ditches. The phantom could also be changed from model A to model B by transferring its vertical configuration. The phantom was surveyed with a clinical gamma camera to determine the time-dependent intensity of every chamber. The recorded counts per pixel in each chamber were analyzed and normalized to compare with theoretical estimations from the MATLAB program. Every preset case was represented by uniquely defined, time-dependent, simultaneous differential equations, and a corresponding MATLAB program optimized the solutions by comparing theoretical calculations and practical measurements. A dimensionless agreement (AT) index was recommended to evaluate the comparison in each case. ATs varied from 5.6 to 48.7 over the 5 cases, indicating that this work presented an acceptable feasibility study. PMID:27286096

Evaluating uncertainty in environmental life-cycle assessment. A case study comparing two insulation options for a Dutch one-family dwelling.

PubMed

Huijbregts, Mark A J; Gilijamse, Wim; Ragas, Ad M J; Reijnders, Lucas

2003-06-01

The evaluation of uncertainty is relatively new in environmental life-cycle assessment (LCA). It provides useful information to assess the reliability of LCA-based decisions and to guide future research toward reducing uncertainty. Most uncertainty studies in LCA quantify only one type of uncertainty, i.e., uncertainty due to input data (parameter uncertainty). However, LCA outcomes can also be uncertain due to normative choices (scenario uncertainty) and the mathematical models involved (model uncertainty). The present paper outlines a new methodology that quantifies parameter, scenario, and model uncertainty simultaneously in environmental life-cycle assessment. The procedure is illustrated in a case study that compares two insulation options for a Dutch one-family dwelling. Parameter uncertainty was quantified by means of Monte Carlo simulation. Scenario and model uncertainty were quantified by resampling different decision scenarios and model formulations, respectively. Although scenario and model uncertainty were not quantified comprehensively, the results indicate that both types of uncertainty influence the case study outcomes. This stresses the importance of quantifying parameter, scenario, and model uncertainty simultaneously. The two insulation options studied were found to have significantly different impact scores for global warming, stratospheric ozone depletion, and eutrophication. The thickest insulation option has the lowest impact on global warming and eutrophication, and the highest impact on stratospheric ozone depletion.

Vibration modelling and verifications for whole aero-engine

NASA Astrophysics Data System (ADS)

Chen, G.

2015-08-01

In this study, a new rotor-ball-bearing-casing coupling dynamic model for a practical aero-engine is established. In the coupling system, the rotor and casing systems are modelled using the finite element method, support systems are modelled as lumped parameter models, nonlinear factors of ball bearings and faults are included, and four types of supports and connection models are defined to model the complex rotor-support-casing coupling system of the aero-engine. A new numerical integral method that combines the Newmark-β method and the improved Newmark-β method (Zhai method) is used to obtain the system responses. Finally, the new model is verified in three ways: (1) modal experiment based on rotor-ball bearing rig, (2) modal experiment based on rotor-ball-bearing-casing rig, and (3) fault simulations for a certain type of missile turbofan aero-engine vibration. The results show that the proposed model can not only simulate the natural vibration characteristics of the whole aero-engine but also effectively perform nonlinear dynamic simulations of a whole aero-engine with faults.

Use cases and DEMO: aligning functional features of ICT-infrastructure to business processes.

PubMed

Maij, E; Toussaint, P J; Kalshoven, M; Poerschke, M; Zwetsloot-Schonk, J H M

2002-11-12

The proper alignment of functional features of the ICT-infrastructure to business processes is a major challenge in health care organisations. This alignment takes into account that the organisational structure not only shapes the ICT-infrastructure, but that the inverse also holds. To solve the alignment problem, relevant features of the ICT-infrastructure should be derived from the organisational structure and the influence of this envisaged ICT to the work practices should be pointed out. The objective of our study was to develop a method to solve this alignment problem. In a previous study we demonstrated the appropriateness of the business process modelling methodology Dynamic Essential Modelling of Organizations (DEMO). A proven and widely used modelling language for expressing functional features is Unified Modelling Language (UML). In the context of a specific case study at the University Medical Centre Utrecht in the Netherlands we investigated if the combined use of DEMO and UML could solve the alignment problem. The study demonstrated that the DEMO models were suited as a starting point in deriving system functionality by using the use case concept of UML. Further, the case study demonstrated that in using this approach for the alignment problem, insight is gained into the mutual influence of ICT-infrastructure and organisation structure: (a) specification of independent, re-usable components-as a set of related functionalities-is realised, and (b) a helpful representation of the current and future work practice is provided for in relation to the envisaged ICT support.

IMACS 󈨟: Proceedings of the IMACS World Congress on Computation and Applied Mathematics (13th) Held in Dublin, Ireland on July 22-26, 1991. Volume 4. Modelling and Simulation for Electrical, Electronic and Semiconductor Devices, Computation for Management Systems, Applications of Modelling and Simulation, Environmental Systems Simulation, Software Forum, Poster Sessions

DTIC Science & Technology

1991-07-01

synchronous machine case study . IEEE T rons. on For the ease nd -nq -2, four time scales trust be used And the A.C, Vol. 36. nul 3, March 1989. damnper... studied . A spot welded(Csse 3) * ss s i* r 0. or a line welded( Case 4) reinforcement plate is attached on the colliding surface of box beams arnd their...phased armature, is given on Figure 1. analytical field calculation in the machine magnetic structure. Il - MAGNETIC STRUCTURE MODELLING: In the case

Systems-Oriented Workplace Learning Experiences for Early Learners: Three Models.

PubMed

O'Brien, Bridget C; Bachhuber, Melissa R; Teherani, Arianne; Iker, Theresa M; Batt, Joanne; O'Sullivan, Patricia S

2017-05-01

Early workplace learning experiences may be effective for learning systems-based practice. This study explores systems-oriented workplace learning experiences (SOWLEs) for early learners to suggest a framework for their development. The authors used a two-phase qualitative case study design. In Phase 1 (spring 2014), they prepared case write-ups based on transcribed interviews from 10 SOWLE leaders at the authors' institution and, through comparative analysis of cases, identified three SOWLE models. In Phase 2 (summer 2014), studying seven 8-week SOWLE pilots, the authors used interview and observational data collected from the seven participating medical students, two pharmacy students, and site leaders to construct case write-ups of each pilot and to verify and elaborate the models. In Model 1, students performed specific patient care activities that addressed a system gap. Some site leaders helped students connect the activities to larger systems problems and potential improvements. In Model 2, students participated in predetermined systems improvement (SI) projects, gaining experience in the improvement process. Site leaders had experience in SI and often had significant roles in the projects. In Model 3, students worked with key stakeholders to develop a project and conduct a small test of change. They experienced most elements of an improvement cycle. Site leaders often had experience with SI and knew how to guide and support students' learning. Each model could offer systems-oriented learning opportunities provided that key elements are in place including site leaders facile in SI concepts and able to guide students in SOWLE activities.

Joint models for longitudinal and time-to-event data: a review of reporting quality with a view to meta-analysis.

PubMed

Sudell, Maria; Kolamunnage-Dona, Ruwanthi; Tudur-Smith, Catrin

2016-12-05

Joint models for longitudinal and time-to-event data are commonly used to simultaneously analyse correlated data in single study cases. Synthesis of evidence from multiple studies using meta-analysis is a natural next step but its feasibility depends heavily on the standard of reporting of joint models in the medical literature. During this review we aim to assess the current standard of reporting of joint models applied in the literature, and to determine whether current reporting standards would allow or hinder future aggregate data meta-analyses of model results. We undertook a literature review of non-methodological studies that involved joint modelling of longitudinal and time-to-event medical data. Study characteristics were extracted and an assessment of whether separate meta-analyses for longitudinal, time-to-event and association parameters were possible was made. The 65 studies identified used a wide range of joint modelling methods in a selection of software. Identified studies concerned a variety of disease areas. The majority of studies reported adequate information to conduct a meta-analysis (67.7% for longitudinal parameter aggregate data meta-analysis, 69.2% for time-to-event parameter aggregate data meta-analysis, 76.9% for association parameter aggregate data meta-analysis). In some cases model structure was difficult to ascertain from the published reports. Whilst extraction of sufficient information to permit meta-analyses was possible in a majority of cases, the standard of reporting of joint models should be maintained and improved. Recommendations for future practice include clear statement of model structure, of values of estimated parameters, of software used and of statistical methods applied.

Modeling of Stiffness and Strength of Bone at Nanoscale.

PubMed

Abueidda, Diab W; Sabet, Fereshteh A; Jasiuk, Iwona M

2017-05-01

Two distinct geometrical models of bone at the nanoscale (collagen fibril and mineral platelets) are analyzed computationally. In the first model (model I), minerals are periodically distributed in a staggered manner in a collagen matrix while in the second model (model II), minerals form continuous layers outside the collagen fibril. Elastic modulus and strength of bone at the nanoscale, represented by these two models under longitudinal tensile loading, are studied using a finite element (FE) software abaqus. The analysis employs a traction-separation law (cohesive surface modeling) at various interfaces in the models to account for interfacial delaminations. Plane stress, plane strain, and axisymmetric versions of the two models are considered. Model II is found to have a higher stiffness than model I for all cases. For strength, the two models alternate the superiority of performance depending on the inputs and assumptions used. For model II, the axisymmetric case gives higher results than the plane stress and plane strain cases while an opposite trend is observed for model I. For axisymmetric case, model II shows greater strength and stiffness compared to model I. The collagen-mineral arrangement of bone at nanoscale forms a basic building block of bone. Thus, knowledge of its mechanical properties is of high scientific and clinical interests.

Learning Gene Expression Through Modelling and Argumentation. A Case Study Exploring the Connections Between the Worlds of Knowledge

NASA Astrophysics Data System (ADS)

Puig, Blanca; Ageitos, Noa; Jiménez-Aleixandre, María Pilar

2017-12-01

There is emerging interest on the interactions between modelling and argumentation in specific contexts, such as genetics learning. It has been suggested that modelling might help students understand and argue on genetics. We propose modelling gene expression as a way to learn molecular genetics and diseases with a genetic component. The study is framed in Tiberghien's (2000) two worlds of knowledge, the world of "theories & models" and the world of "objects & events", adding a third component, the world of representations. We seek to examine how modelling and argumentation interact and connect the three worlds of knowledge while modelling gene expression. It is a case study of 10th graders learning about diseases with a genetic component. The research questions are as follows: (1) What argumentative and modelling operations do students enact in the process of modelling gene expression? Specifically, which operations allow connecting the three worlds of knowledge? (2) What are the interactions between modelling and argumentation in modelling gene expression? To what extent do these interactions help students connect the three worlds of knowledge and modelling gene expression? The argumentative operation of using evidence helps students to relate the three worlds of knowledge, enacted in all the connections. It seems to be a relationship among the number of interactions between modelling and argumentation, the connections between world of knowledge and students' capacity to develop a more sophisticated representation. Despite this is a case study, this approach of analysis reveals potentialities for a deeper understanding of learning genetics though scientific practices.

Enhancing Infant Mental Health Using a Capacity-Building Model: A Case Study of a Process Evaluation of the "Ready, Steady, Grow" Initiative

ERIC Educational Resources Information Center

O'Farrelly, Christine; Guerin, Suzanne; Victory, Gerard

2017-01-01

Infant mental health (IMH) is best promoted through a continuum of services underpinned by strong service capacity. However, service providers often lack fundamental IMH knowledge and skills. Using the Ready, Steady, Grow (RSG) initiative as a case study of a capacity-building model (P., Hawe, L., King, M., Noort, C., Jordens, & B., Llyod,…

A Case Analysis of a Model Program for the Leadership Development of Women Faculty and Staff Seeking to Advance Their Careers in Higher Education

ERIC Educational Resources Information Center

Calizo, Lee Scherer Hawthorne

2011-01-01

The purpose of this case study was to explore a model of leadership development for women faculty and staff in higher education. This study is significant because it explored the only identified campus-based program open to both faculty and staff. The campus-based Women's Institute for Leadership Development (WILD) program at the University of…

Appendix 2: Risk-based framework and risk case studies. Risk Assessment for two bird species in northern Wisconsin.

Treesearch

Megan M. Friggens; Stephen N. Matthews

2012-01-01

Species distribution models for 147 bird species have been derived using climate, elevation, and distribution of current tree species as potential predictors (Matthews et al. 2011). In this case study, a risk matrix was developed for two bird species (fig. A2-5), with projected change in bird habitat (the x axis) based on models of changing suitable habitat resulting...

Evaluation of Cirrus Cloud Simulations Using ARM Data - Development of a Case Study Data Set

NASA Technical Reports Server (NTRS)

O'C.Starr, David; Demoz, Belay; Lare, Andrew; Poellot, Michael; Sassen, Kenneth; Heymsfield, Andrew; Brown, Philip; Mace, Jay; Einaudi, Franco (Technical Monitor)

2001-01-01

Cloud-resolving models (CRMs) provide an effective linkage in terms of parameters and scales between observations and the parametric treatments of clouds in global climate models (GCMs). They also represent the best understanding of the physical processes acting to determine cloud system lifecycle. The goal of this project is to improve state-of-the-art CRMs used for studies of cirrus clouds and to establish a relative calibration with GCMs through comparisons among CRMs, single column model (SCM) versions of the GCMs, and observations. This project will compare and evaluate a variety of CRMs and SCMs, under the auspices of the GEWEX Cloud Systems Study (GCSS) Working Group on Cirrus Cloud Systems (WG2), using ARM data acquired at the Southern Great Plains (SGP) site. This poster will report on progress in developing a suitable WG2 case study data set based on the September 26, 1996 ARM IOP case - the Hurricane Nora outflow case. The environmental data (input) will be described as well as the wealth of validating cloud observations. We plan to also show results of preliminary simulations. The science questions to be addressed derive significantly from results of the GCSS WG2 cloud model comparison projects, which will be briefly summarized.

Novel Uses of In Vitro Data to Develop Quantitative Biological Activity Relationship Models for in Vivo Carcinogenicity Prediction.

PubMed

Pradeep, Prachi; Povinelli, Richard J; Merrill, Stephen J; Bozdag, Serdar; Sem, Daniel S

2015-04-01

The availability of large in vitro datasets enables better insight into the mode of action of chemicals and better identification of potential mechanism(s) of toxicity. Several studies have shown that not all in vitro assays can contribute as equal predictors of in vivo carcinogenicity for development of hybrid Quantitative Structure Activity Relationship (QSAR) models. We propose two novel approaches for the use of mechanistically relevant in vitro assay data in the identification of relevant biological descriptors and development of Quantitative Biological Activity Relationship (QBAR) models for carcinogenicity prediction. We demonstrate that in vitro assay data can be used to develop QBAR models for in vivo carcinogenicity prediction via two case studies corroborated with firm scientific rationale. The case studies demonstrate the similarities between QBAR and QSAR modeling in: (i) the selection of relevant descriptors to be used in the machine learning algorithm, and (ii) the development of a computational model that maps chemical or biological descriptors to a toxic endpoint. The results of both the case studies show: (i) improved accuracy and sensitivity which is especially desirable under regulatory requirements, and (ii) overall adherence with the OECD/REACH guidelines. Such mechanism based models can be used along with QSAR models for prediction of mechanistically complex toxic endpoints. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Cognitive problem solving patterns of medical students correlate with success in diagnostic case solutions.

PubMed

Kiesewetter, Jan; Ebersbach, René; Görlitz, Anja; Holzer, Matthias; Fischer, Martin R; Schmidmaier, Ralf

2013-01-01

Problem-solving in terms of clinical reasoning is regarded as a key competence of medical doctors. Little is known about the general cognitive actions underlying the strategies of problem-solving among medical students. In this study, a theory-based model was used and adapted in order to investigate the cognitive actions in which medical students are engaged when dealing with a case and how patterns of these actions are related to the correct solution. Twenty-three medical students worked on three cases on clinical nephrology using the think-aloud method. The transcribed recordings were coded using a theory-based model consisting of eight different cognitive actions. The coded data was analysed using time sequences in a graphical representation software. Furthermore the relationship between the coded data and accuracy of diagnosis was investigated with inferential statistical methods. The observation of all main actions in a case elaboration, including evaluation, representation and integration, was considered a complete model and was found in the majority of cases (56%). This pattern significantly related to the accuracy of the case solution (φ = 0.55; p<.001). Extent of prior knowledge was neither related to the complete model nor to the correct solution. The proposed model is suitable to empirically verify the cognitive actions of problem-solving of medical students. The cognitive actions evaluation, representation and integration are crucial for the complete model and therefore for the accuracy of the solution. The educational implication which may be drawn from this study is to foster students reasoning by focusing on higher level reasoning.

Performance measurement and modeling of component applications in a high performance computing environment : a case study.

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

Armstrong, Robert C.; Ray, Jaideep; Malony, A.

2003-11-01

We present a case study of performance measurement and modeling of a CCA (Common Component Architecture) component-based application in a high performance computing environment. We explore issues peculiar to component-based HPC applications and propose a performance measurement infrastructure for HPC based loosely on recent work done for Grid environments. A prototypical implementation of the infrastructure is used to collect data for a three components in a scientific application and construct performance models for two of them. Both computational and message-passing performance are addressed.

Research impact in the community-based health sciences: an analysis of 162 case studies from the 2014 UK Research Excellence Framework.

PubMed

Greenhalgh, Trisha; Fahy, Nick

2015-09-21

The 2014 UK Research Excellence Framework (REF2014) generated a unique database of impact case studies, each describing a body of research and impact beyond academia. We sought to explore the nature and mechanism of impact in a sample of these. The study design was manual content analysis of a large sample of impact case studies (producing mainly quantitative data), plus in-depth interpretive analysis of a smaller sub-sample (for qualitative detail), thereby generating both breadth and depth. For all 162 impact case studies submitted to sub-panel A2 in REF2014, we extracted data on study design(s), stated impacts and audiences, mechanisms of impact, and efforts to achieve impact. We analysed four case studies (selected as exemplars of the range of approaches to impact) in depth, including contacting the authors for their narratives of impact efforts. Most impact case studies described quantitative research (most commonly, trials) and depicted a direct, linear link between research and impact. Research was said to have influenced a guideline in 122 case studies, changed policy in 88, changed practice in 84, improved morbidity in 44 and reduced mortality in 25. Qualitative and participatory research designs were rare, and only one case study described a co-production model of impact. Eighty-two case studies described strong and ongoing linkages with policymakers, but only 38 described targeted knowledge translation activities. In 40 case studies, no active efforts to achieve impact were described. Models of good implementation practice were characterised by an ethical commitment by researchers, strong institutional support and a proactive, interdisciplinary approach to impact activities. REF2014 both inspired and documented significant efforts by UK researchers to achieve impact. But in contrast with the published evidence on research impact (which depicts much as occurring indirectly through non-linear mechanisms), this sub-panel seems to have captured mainly direct and relatively short-term impacts one step removed from patient outcomes. Limited impacts on morbidity and mortality, and researchers' relatively low emphasis on the processes and interactions through which indirect impacts may occur, are concerns. These findings have implications for multi-stakeholder research collaborations such as UK National Institute for Health Research Collaborations for Leadership in Applied Health Research and Care, which are built on non-linear models of impact.

Increasing operating room productivity by duration categories and a newsvendor model.

PubMed

Lehtonen, Juha-Matti; Torkki, Paulus; Peltokorpi, Antti; Moilanen, Teemu

2013-01-01

Previous studies approach surgery scheduling mainly from the mathematical modeling perspective which is often hard to apply in a practical environment. The aim of this study is to develop a practical scheduling system that considers the advantages of both surgery categorization and newsvendor model to surgery scheduling. The research was carried out in a Finnish orthopaedic specialist centre that performs only joint replacement surgery. Four surgery categorization scenarios were defined and their productivity analyzed by simulation and newsvendor model. Detailed analyses of surgery durations and the use of more accurate case categories and their combinations in scheduling improved OR productivity 11.3 percent when compared to the base case. Planning to have one OR team to work longer led to remarkable decrease in scheduling inefficiency. In surgical services, productivity and cost-efficiency can be improved by utilizing historical data in case scheduling and by increasing flexibility in personnel management. The study increases the understanding of practical scheduling methods used to improve efficiency in surgical services.

Modeling the Dynamic Interrelations between Mobility, Utility, and Land Asking Price

NASA Astrophysics Data System (ADS)

Hidayat, E.; Rudiarto, I.; Siegert, F.; Vries, W. D.

2018-02-01

Limited and insufficient information about the dynamic interrelation among mobility, utility, and land price is the main reason to conduct this research. Several studies, with several approaches, and several variables have been conducted so far in order to model the land price. However, most of these models appear to generate primarily static land prices. Thus, a research is required to compare, design, and validate different models which calculate and/or compare the inter-relational changes of mobility, utility, and land price. The applied method is a combination of analysis of literature review, expert interview, and statistical analysis. The result is newly improved mathematical model which have been validated and is suitable for the case study location. This improved model consists of 12 appropriate variables. This model can be implemented in the Salatiga city as the case study location in order to arrange better land use planning to mitigate the uncontrolled urban growth.

Are transnational tobacco companies' market access strategies linked to economic development models? A case study of South Korea.

PubMed

Lee, Sungkyu; Holden, Chris; Lee, Kelley

2013-01-01

Transnational tobacco companies (TTCs) have used varied strategies to access previously closed markets. Using TTCs' efforts to enter the South Korean market from the late 1980s as a case study, this article asks whether there are common patterns in these strategies that relate to the broader economic development models adopted by targeted countries. An analytical review of the existing literature on TTCs' efforts to access emerging markets was conducted to develop hypotheses relating TTCs' strategies to countries' economic development models. A case study of Korea was then undertaken based on analysis of internal tobacco industry documents. Findings were consistent with the hypothesis that TTCs' strategies in Korea were linked to Korea's export-oriented economic development model and its hostile attitude towards foreign investment. A fuller understanding of TTCs' strategies for expansion globally can be derived by locating them within the economic development models of specific countries or regions. Of foremost importance is the need for governments to carefully balance economic and public health policies when considering liberalisation.

Are transnational tobacco companies’ market access strategies linked to economic development models? A case study of South Korea

PubMed Central

Lee, Sungkyu; Holden, Chris; Lee, Kelley

2013-01-01

Transnational tobacco companies (TTCs) have used varied strategies to access previously closed markets. Using TTCs’ efforts to enter the South Korean market from the late 1980s as a case study, this article asks whether there are common patterns in these strategies that relate to the broader economic development models adopted by targeted countries. An analytical review of the existing literature on TTCs’ efforts to access emerging markets was conducted to develop hypotheses relating TTCs’ strategies to countries’ economic development models. A case study of Korea was then undertaken based on analysis of internal tobacco industry documents. Findings were consistent with the hypothesis that TTCs’ strategies in Korea were linked to Korea’s export-oriented economic development model and its hostile attitude toward foreign investment. A fuller understanding of TTCs’ strategies for expansion globally can be derived by locating them within the economic development models of specific countries or regions. Of foremost importance is the need for governments to carefully balance economic and public health policies when considering liberalisation. PMID:23327486

Software for Brain Network Simulations: A Comparative Study

PubMed Central

Tikidji-Hamburyan, Ruben A.; Narayana, Vikram; Bozkus, Zeki; El-Ghazawi, Tarek A.

2017-01-01

Numerical simulations of brain networks are a critical part of our efforts in understanding brain functions under pathological and normal conditions. For several decades, the community has developed many software packages and simulators to accelerate research in computational neuroscience. In this article, we select the three most popular simulators, as determined by the number of models in the ModelDB database, such as NEURON, GENESIS, and BRIAN, and perform an independent evaluation of these simulators. In addition, we study NEST, one of the lead simulators of the Human Brain Project. First, we study them based on one of the most important characteristics, the range of supported models. Our investigation reveals that brain network simulators may be biased toward supporting a specific set of models. However, all simulators tend to expand the supported range of models by providing a universal environment for the computational study of individual neurons and brain networks. Next, our investigations on the characteristics of computational architecture and efficiency indicate that all simulators compile the most computationally intensive procedures into binary code, with the aim of maximizing their computational performance. However, not all simulators provide the simplest method for module development and/or guarantee efficient binary code. Third, a study of their amenability for high-performance computing reveals that NEST can almost transparently map an existing model on a cluster or multicore computer, while NEURON requires code modification if the model developed for a single computer has to be mapped on a computational cluster. Interestingly, parallelization is the weakest characteristic of BRIAN, which provides no support for cluster computations and limited support for multicore computers. Fourth, we identify the level of user support and frequency of usage for all simulators. Finally, we carry out an evaluation using two case studies: a large network with simplified neural and synaptic models and a small network with detailed models. These two case studies allow us to avoid any bias toward a particular software package. The results indicate that BRIAN provides the most concise language for both cases considered. Furthermore, as expected, NEST mostly favors large network models, while NEURON is better suited for detailed models. Overall, the case studies reinforce our general observation that simulators have a bias in the computational performance toward specific types of the brain network models. PMID:28775687

Correcting for batch effects in case-control microbiome studies

PubMed Central

Gibbons, Sean M.; Duvallet, Claire

2018-01-01

High-throughput data generation platforms, like mass-spectrometry, microarrays, and second-generation sequencing are susceptible to batch effects due to run-to-run variation in reagents, equipment, protocols, or personnel. Currently, batch correction methods are not commonly applied to microbiome sequencing datasets. In this paper, we compare different batch-correction methods applied to microbiome case-control studies. We introduce a model-free normalization procedure where features (i.e. bacterial taxa) in case samples are converted to percentiles of the equivalent features in control samples within a study prior to pooling data across studies. We look at how this percentile-normalization method compares to traditional meta-analysis methods for combining independent p-values and to limma and ComBat, widely used batch-correction models developed for RNA microarray data. Overall, we show that percentile-normalization is a simple, non-parametric approach for correcting batch effects and improving sensitivity in case-control meta-analyses. PMID:29684016

Thermodynamics of Biological Processes

PubMed Central

Garcia, Hernan G.; Kondev, Jane; Orme, Nigel; Theriot, Julie A.; Phillips, Rob

2012-01-01

There is a long and rich tradition of using ideas from both equilibrium thermodynamics and its microscopic partner theory of equilibrium statistical mechanics. In this chapter, we provide some background on the origins of the seemingly unreasonable effectiveness of ideas from both thermodynamics and statistical mechanics in biology. After making a description of these foundational issues, we turn to a series of case studies primarily focused on binding that are intended to illustrate the broad biological reach of equilibrium thinking in biology. These case studies include ligand-gated ion channels, thermodynamic models of transcription, and recent applications to the problem of bacterial chemotaxis. As part of the description of these case studies, we explore a number of different uses of the famed Monod–Wyman–Changeux (MWC) model as a generic tool for providing a mathematical characterization of two-state systems. These case studies should provide a template for tailoring equilibrium ideas to other problems of biological interest. PMID:21333788

Bayesian adjustment for measurement error in continuous exposures in an individually matched case-control study.

PubMed

Espino-Hernandez, Gabriela; Gustafson, Paul; Burstyn, Igor

2011-05-14

In epidemiological studies explanatory variables are frequently subject to measurement error. The aim of this paper is to develop a Bayesian method to correct for measurement error in multiple continuous exposures in individually matched case-control studies. This is a topic that has not been widely investigated. The new method is illustrated using data from an individually matched case-control study of the association between thyroid hormone levels during pregnancy and exposure to perfluorinated acids. The objective of the motivating study was to examine the risk of maternal hypothyroxinemia due to exposure to three perfluorinated acids measured on a continuous scale. Results from the proposed method are compared with those obtained from a naive analysis. Using a Bayesian approach, the developed method considers a classical measurement error model for the exposures, as well as the conditional logistic regression likelihood as the disease model, together with a random-effect exposure model. Proper and diffuse prior distributions are assigned, and results from a quality control experiment are used to estimate the perfluorinated acids' measurement error variability. As a result, posterior distributions and 95% credible intervals of the odds ratios are computed. A sensitivity analysis of method's performance in this particular application with different measurement error variability was performed. The proposed Bayesian method to correct for measurement error is feasible and can be implemented using statistical software. For the study on perfluorinated acids, a comparison of the inferences which are corrected for measurement error to those which ignore it indicates that little adjustment is manifested for the level of measurement error actually exhibited in the exposures. Nevertheless, a sensitivity analysis shows that more substantial adjustments arise if larger measurement errors are assumed. In individually matched case-control studies, the use of conditional logistic regression likelihood as a disease model in the presence of measurement error in multiple continuous exposures can be justified by having a random-effect exposure model. The proposed method can be successfully implemented in WinBUGS to correct individually matched case-control studies for several mismeasured continuous exposures under a classical measurement error model.

Developing Army Leaders through Increased Rigor in Professional Military Training and Education

DTIC Science & Technology

2017-06-09

leadership. Research Methodology An applied, exploratory, qualitative research methodology via a structured and focused case study comparison was...research methodology via a structured and focused case study comparison. Finally, it will discuss how the methodology will be conducted to make...development models; it serves as the base data for case study comparison. 48 Research Methodology and Data Analysis A qualitative research

Modeling Prosecutors' Charging Decisions in Domestic Violence Cases

ERIC Educational Resources Information Center

Worrall, John L.; Ross, Jay W.; McCord, Eric S.

2006-01-01

Relatively little research explaining prosecutors' charging decisions in criminal cases is available. Even less has focused on charging decisions in domestic violence cases. Past studies have also relied on restrictive definitions of domestic violence, notably cases with male offenders and female victims, and they have not considered prosecutors'…

Exploring Biomolecular Recognition by Modeling and Simulation

NASA Astrophysics Data System (ADS)

Wade, Rebecca

2007-12-01

Biomolecular recognition is complex. The balance between the different molecular properties that contribute to molecular recognition, such as shape, electrostatics, dynamics and entropy, varies from case to case. This, along with the extent of experimental characterization, influences the choice of appropriate computational approaches to study biomolecular interactions. I will present computational studies in which we aim to make concerted use of bioinformatics, biochemical network modeling and molecular simulation techniques to study protein-protein and protein-small molecule interactions and to facilitate computer-aided drug design.

Northeast Artificial Intelligence Consortium (NAIC). Volume 15. Strategies for Coupling Symbolic and Numerical Computation in Knowledge Base Systems

DTIC Science & Technology

1990-12-01

Implementation of Coupled System 18 15.4. CASE STUDIES & IMPLEMENTATION EXAMPLES 24 15.4.1. The Case Studies of Coupled System 24 15.4.2. Example: Coupled System...occurs during specific phases of the problem-solving process. By decomposing the coupling process into its component layers we effectively study the nature...by the qualitative model, appropriate mathematical model is invoked. 5) The results are verified. If successful, stop. Else go to (2) and use an

Testing the effectiveness of family therapeutic assessment: a case study using a time-series design.

PubMed

Smith, Justin D; Wolf, Nicole J; Handler, Leonard; Nash, Michael R

2009-11-01

We describe a family Therapeutic Assessment (TA) case study employing 2 assessors, 2 assessment rooms, and a video link. In the study, we employed a daily measures time-series design with a pretreatment baseline and follow-up period to examine the family TA treatment model. In addition to being an illustrative addition to a number of clinical reports suggesting the efficacy of family TA, this study is the first to apply a case-based time-series design to test whether family TA leads to clinical improvement and also illustrates when that improvement occurs. Results support the trajectory of change proposed by Finn (2007), the TA model's creator, who posits that benefits continue beyond the formal treatment itself.

75 FR 74024 - Notice of Submission for OMB Review

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-30

... purpose of the Study of School Turnaround is to document over time the intervention models, approaches... with school principals, district administrators and state officials; site visits to case study schools... study team will conduct in-depth case studies over three years, and two sets of 10 ``special topics...

Life cycle assessment based environmental impact estimation model for pre-stressed concrete beam bridge in the early design phase

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

Kim, Kyong Ju, E-mail: kjkim@cau.ac.kr; Yun, Won Gun, E-mail: ogun78@naver.com; Cho, Namho, E-mail: nhc51@cau.ac.kr

The late rise in global concern for environmental issues such as global warming and air pollution is accentuating the need for environmental assessments in the construction industry. Promptly evaluating the environmental loads of the various design alternatives during the early stages of a construction project and adopting the most environmentally sustainable candidate is therefore of large importance. Yet, research on the early evaluation of a construction project's environmental load in order to aid the decision making process is hitherto lacking. In light of this dilemma, this study proposes a model for estimating the environmental load by employing only the mostmore » basic information accessible during the early design phases of a project for the pre-stressed concrete (PSC) beam bridge, the most common bridge structure. Firstly, a life cycle assessment (LCA) was conducted on the data from 99 bridges by integrating the bills of quantities (BOQ) with a life cycle inventory (LCI) database. The processed data was then utilized to construct a case based reasoning (CBR) model for estimating the environmental load. The accuracy of the estimation model was then validated using five test cases; the model's mean absolute error rates (MAER) for the total environmental load was calculated as 7.09%. Such test results were shown to be superior compared to those obtained from a multiple-regression based model and a slab area base-unit analysis model. Henceforth application of this model during the early stages of a project is expected to highly complement environmentally friendly designs and construction by facilitating the swift evaluation of the environmental load from multiple standpoints. - Highlights: • This study is to develop the model of assessing the environmental impacts on LCA. • Bills of quantity from completed designs of PSC Beam were linked with the LCI DB. • Previous cases were used to estimate the environmental load of new case by CBR model. • CBR model produces more accurate estimations (7.09%) than other conventional models. • This study supports decision making process in the early stage of a new construction case.« less

The Effect of Instruction through Mathematical Modelling on Modelling Skills of Prospective Elementary Mathematics Teachers

ERIC Educational Resources Information Center

Ciltas, Alper; Isik, Ahmet

2013-01-01

The aim of this study was to examine the modelling skills of prospective elementary mathematics teachers who were studying the mathematical modelling method. The research study group was composed of 35 prospective teachers. The exploratory case analysis method was used in the study. The data were obtained via semi-structured interviews and a…

Collaborative Assessment: Middle School Case Study

ERIC Educational Resources Information Center

Parkison, Paul T.

2014-01-01

Utilizing a participant observer research model, a case study of the efficacy of a collaborative assessment methodology within a middle school social studies class was conducted. A review of existing research revealed that students' perceptions of assessment, evaluation, and accountability influence their intrinsic motivation to learn. A…

Models of Shelter Management Training and Delivery Systems.

DTIC Science & Technology

1980-05-31

case study can be pre- sented orally, in writing, through a dramatization, or on film. Advantages: the case can be designed to focus on a problem or...develop a good, complex case study ; it may not be possible to use a case with more than one group (Ax & Kohls, 1977; Bauman, 1977; U.S. Civil Service...Although public information on self-protection continued to be distributed, the shelter program remained incomplete (e.g., an AIR study in 1966 noted that

Identification and calibration of the structural model of historical masonry building damaged during the 2016 Italian earthquakes: The case study of Palazzo del Podestà in Montelupone

NASA Astrophysics Data System (ADS)

Catinari, Federico; Pierdicca, Alessio; Clementi, Francesco; Lenci, Stefano

2017-11-01

The results of an ambient-vibration based investigation conducted on the "Palazzo del Podesta" in Montelupone (Italy) is presented. The case study was damaged during the 20I6 Italian earthquakes that stroke the central part of the Italy. The assessment procedure includes full-scale ambient vibration testing, modal identification from ambient vibration responses, finite element modeling and dynamic-based identification of the uncertain structural parameters of the model. A very good match between theoretical and experimental modal parameters was reached and the model updating has been performed identifying some structural parameters.

Models of community care for severe mental illness: a review of research on case management.

PubMed

Mueser, K T; Bond, G R; Drake, R E; Resnick, S G

1998-01-01

We describe different models of community care for persons with severe mental illness and review the research literature on case management, including the results of 75 studies. Most research has been conducted on the assertive community treatment (ACT) or intensive case management (ICM) models. Controlled research on ACT and ICM indicates that these models reduce time in the hospital and improve housing stability, especially among patients who are high service users. ACT and ICM appear to have moderate effects on improving symptomatology and quality of life. Most studies suggest little effect of ACT and ICM on social functioning, arrests and time spent in jail, or vocational functioning. Studies on reducing or withdrawing ACT or ICM services suggest some deterioration in gains. Research on other models of community care is inconclusive. We discuss the implications of the findings in terms of the need for specialization of ACT or ICM teams to address social and vocational functioning and substance abuse. We suggest directions for future research on models of community care, including evaluating implementation fidelity, exploring patient predictors of improvement, and evaluating the role of the helping alliance in mediating outcome.

Literacy in Motion: A Case Study of a Shape-Shifting Kindergartener

ERIC Educational Resources Information Center

Siegel, Marjorie; Kontovourki, Stavroula; Schmier, Stephanie; Enriquez, Grace

2008-01-01

This article presents a case study of a kindergarten girl from a Bangladeshi immigrant family who demonstrates her multiliteracies as she negotiates the multiple demands of the mandated literacy curriculum. The case is drawn from a year-long ethnographic inquiry of the literacy practices and cultural models in a balanced literacy curriculum where…

Comparison of organs' shapes with geometric and Zernike 3D moments.

PubMed

Broggio, D; Moignier, A; Ben Brahim, K; Gardumi, A; Grandgirard, N; Pierrat, N; Chea, M; Derreumaux, S; Desbrée, A; Boisserie, G; Aubert, B; Mazeron, J-J; Franck, D

2013-09-01

The morphological similarity of organs is studied with feature vectors based on geometric and Zernike 3D moments. It is particularly investigated if outliers and average models can be identified. For this purpose, the relative proximity to the mean feature vector is defined, principal coordinate and clustering analyses are also performed. To study the consistency and usefulness of this approach, 17 livers and 76 hearts voxel models from several sources are considered. In the liver case, models with similar morphological feature are identified. For the limited amount of studied cases, the liver of the ICRP male voxel model is identified as a better surrogate than the female one. For hearts, the clustering analysis shows that three heart shapes represent about 80% of the morphological variations. The relative proximity and clustering analysis rather consistently identify outliers and average models. For the two cases, identification of outliers and surrogate of average models is rather robust. However, deeper classification of morphological feature is subject to caution and can only be performed after cross analysis of at least two kinds of feature vectors. Finally, the Zernike moments contain all the information needed to re-construct the studied objects and thus appear as a promising tool to derive statistical organ shapes. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

LBQ2D, Extending the Line Broadened Quasilinear Model to TAE-EP Interaction

NASA Astrophysics Data System (ADS)

Ghantous, Katy; Gorelenkov, Nikolai; Berk, Herbert

2012-10-01

The line broadened quasilinear model was proposed and tested on the one dimensional electrostatic case of the bump on tailfootnotetextH.L Berk, B. Breizman and J. Fitzpatrick, Nucl. Fusion, 35:1661, 1995 to study the wave particle interaction. In conventional quasilinear theory, the sea of overlapping modes evolve with time as the particle distribution function self consistently undergo diffusion in phase space. The line broadened quasilinear model is an extension to the conventional theory in a way that allows treatment of isolated modes as well as overlapping modes by broadening the resonant line in phase space. This makes it possible to treat the evolution of modes self consistently from onset to saturation in either case. We describe here the model denoted by LBQ2D which is an extension of the proposed one dimensional line broadened quasilinear model to the case of TAEs interacting with energetic particles in two dimensional phase space, energy as well as canonical angular momentum. We study the saturation of isolated modes in various regimes and present the analytical derivation and numerical results. Finally, we present, using ITER parameters, the case where multiple modes overlap and describe the techniques used for the numerical treatment.

Stability Analysis Susceptible, Exposed, Infected, Recovered (SEIR) Model for Spread Model for Spread of Dengue Fever in Medan

NASA Astrophysics Data System (ADS)

Side, Syafruddin; Molliq Rangkuti, Yulita; Gerhana Pane, Dian; Setia Sinaga, Marlina

2018-01-01

Dengue fever is endemic disease which spread through vector, Aedes Aegypty. This disease is found more than 100 countries, such as, United State, Africa as well Asia, especially in country that have tropic climate. Mathematical modeling in this paper, discusses the speed of the spread of dengue fever. The model adopting divided over four classes, such as Susceptible (S), Exposed (E), Infected (I) and Recovered (R). SEIR model further analyzed to detect the re-breeding value based on the number reported case by dengue in Medan city. Analysis of the stability of the system in this study is asymptotically stable indicating a case of endemic and unstable that show cases the endemic cases. Simulation on the mathematical model of SEIR showed that require a very long time to produce infected humans will be free of dengue virus infection. This happens because of dengue virus infection that occurs continuously between human and vector populations.

Dependability analysis of parallel systems using a simulation-based approach. M.S. Thesis

NASA Technical Reports Server (NTRS)

Sawyer, Darren Charles

1994-01-01

The analysis of dependability in large, complex, parallel systems executing real applications or workloads is examined in this thesis. To effectively demonstrate the wide range of dependability problems that can be analyzed through simulation, the analysis of three case studies is presented. For each case, the organization of the simulation model used is outlined, and the results from simulated fault injection experiments are explained, showing the usefulness of this method in dependability modeling of large parallel systems. The simulation models are constructed using DEPEND and C++. Where possible, methods to increase dependability are derived from the experimental results. Another interesting facet of all three cases is the presence of some kind of workload of application executing in the simulation while faults are injected. This provides a completely new dimension to this type of study, not possible to model accurately with analytical approaches.

Developing a Time Series Predictive Model for Dengue in Zhongshan, China Based on Weather and Guangzhou Dengue Surveillance Data.

PubMed

Zhang, Yingtao; Wang, Tao; Liu, Kangkang; Xia, Yao; Lu, Yi; Jing, Qinlong; Yang, Zhicong; Hu, Wenbiao; Lu, Jiahai

2016-02-01

Dengue is a re-emerging infectious disease of humans, rapidly growing from endemic areas to dengue-free regions due to favorable conditions. In recent decades, Guangzhou has again suffered from several big outbreaks of dengue; as have its neighboring cities. This study aims to examine the impact of dengue epidemics in Guangzhou, China, and to develop a predictive model for Zhongshan based on local weather conditions and Guangzhou dengue surveillance information. We obtained weekly dengue case data from 1st January, 2005 to 31st December, 2014 for Guangzhou and Zhongshan city from the Chinese National Disease Surveillance Reporting System. Meteorological data was collected from the Zhongshan Weather Bureau and demographic data was collected from the Zhongshan Statistical Bureau. A negative binomial regression model with a log link function was used to analyze the relationship between weekly dengue cases in Guangzhou and Zhongshan, controlling for meteorological factors. Cross-correlation functions were applied to identify the time lags of the effect of each weather factor on weekly dengue cases. Models were validated using receiver operating characteristic (ROC) curves and k-fold cross-validation. Our results showed that weekly dengue cases in Zhongshan were significantly associated with dengue cases in Guangzhou after the treatment of a 5 weeks prior moving average (Relative Risk (RR) = 2.016, 95% Confidence Interval (CI): 1.845-2.203), controlling for weather factors including minimum temperature, relative humidity, and rainfall. ROC curve analysis indicated our forecasting model performed well at different prediction thresholds, with 0.969 area under the receiver operating characteristic curve (AUC) for a threshold of 3 cases per week, 0.957 AUC for a threshold of 2 cases per week, and 0.938 AUC for a threshold of 1 case per week. Models established during k-fold cross-validation also had considerable AUC (average 0.938-0.967). The sensitivity and specificity obtained from k-fold cross-validation was 78.83% and 92.48% respectively, with a forecasting threshold of 3 cases per week; 91.17% and 91.39%, with a threshold of 2 cases; and 85.16% and 87.25% with a threshold of 1 case. The out-of-sample prediction for the epidemics in 2014 also showed satisfactory performance. Our study findings suggest that the occurrence of dengue outbreaks in Guangzhou could impact dengue outbreaks in Zhongshan under suitable weather conditions. Future studies should focus on developing integrated early warning systems for dengue transmission including local weather and human movement.

Simulation model calibration and validation : phase II : development of implementation handbook and short course.

DOT National Transportation Integrated Search

2006-01-01

A previous study developed a procedure for microscopic simulation model calibration and validation and evaluated the procedure via two relatively simple case studies using three microscopic simulation models. Results showed that default parameters we...

The minipig as an animal model to study Mycobacterium tuberculosis infection and natural transmission

USDA-ARS?s Scientific Manuscript database

Infants and children with tuberculosis (TB) account for more than 20% of cases in endemic countries. Current animal models study TB during adulthood but animal models for adolescent and infant TB are scarce. Here we propose that minipigs can be used as an animal model to study adult, adolescent and ...

Exchangeability in the case-crossover design

PubMed Central

Mittleman, Murray A; Mostofsky, Elizabeth

2014-01-01

In cohort and case-control studies, confounding that arises as a result of differences in the distribution of determinants of the outcome between exposure groups leading to non-exchangeability are addressed by restriction, matching or with statistical models. In case-only studies, this issue is addressed by comparing each individual with his/herself. Although case-only designs use self-matching and only include individuals who develop the outcome of interest, issues of non-exchangeability are identical to those that arise in traditional case-control and cohort studies. In this review, we describe one type of case-only design, the case-crossover design, and discuss how the concept of exchangeability can be used to understand issues of confounding, carryover effects, period effects and selection bias in case-crossover studies. PMID:24756878

MBA: Is the Traditional Model Doomed?

ERIC Educational Resources Information Center

Lataif, Louis E.; And Others

1992-01-01

Presents 13 commentaries on a previously published case study about the value of a Master's of Business Administration to employers today. Critiques center on the case study method, theory-practice gap, and value of practical experience and include international perspectives. (SK)

The Role of Prostatitis in Prostate Cancer: Meta-Analysis

PubMed Central

Yunxia, Zhang; Zhu, Hong; Liu, Junjiang; Pumill, Chris

2013-01-01

Objective Use systematic review methods to quantify the association between prostatitis and prostate cancer, under both fixed and random effects model. Evidence Acquisition Case control studies of prostate cancer with information on prostatitis history. All studies published between 1990-2012, were collected to calculate a pooled odds ratio. Selection criteria: the selection criteria are as follows: human case control studies; published from May 1990 to July 2012; containing number of prostatitis, and prostate cancer cases. Evidence Synthesis In total, 20 case control studies were included. A significant association between prostatitis and prostate cancer was found, under both fixed effect model (pooled OR=1.50, 95%CI: 1.39-1.62), and random effects model (OR=1.64, 95%CI: 1.36-1.98). Personal interview based case control studies showed a high level of association (fixed effect model: pooled OR=1.59, 95%CI: 1.47-1.73, random effects model: pooled OR= 1.87, 95%CI: 1.52-2.29), compared with clinical based studies (fixed effect model: pooled OR=1.05, 95%CI: 0.86-1.28, random effects model: pooled OR= 0.98, 95%CI: 0.67-1.45). Additionally, pooled ORs, were calculated for each decade. In a fixed effect model: 1990’s: OR=1.58, 95% CI: 1.35-1.84; 2000’s: OR=1.59, 95% CI: 1.40-1.79; 2010’s: OR=1.37, 95% CI: 1.22-1.56. In a random effects model: 1990’s: OR=1.98, 95% CI: 1.08-3.62; 2000’s: OR=1.64, 95% CI: 1.23-2.19; 2010’s: OR=1.34, 95% CI: 1.03-1.73. Finally a meta-analysis stratified by each country was conducted. In fixed effect models, U.S: pooled OR =1.45, 95%CI: 1.34-1.57; China: pooled OR =4.67, 95%CI: 3.08-7.07; Cuba: pooled OR =1.43, 95%CI: 1.00-2.04; Italy: pooled OR =0.61, 95%CI: 0.13-2.90. In random effects model, U.S: pooled OR=1.50, 95%CI: 1.25-1.80; China: pooled OR =4.67, 95%CI: 3.08-7.07; Cuba: pooled OR =1.43, 95%CI: 1.00-2.04; Italy: pooled OR =0.61, 95%CI: 0.13-2.90.CONCLUSIONS: the present meta-analysis provides the statistical evidence that the association between prostatitis and prostate cancer is significant. PMID:24391995

Summary of Data from the Sixth AIAA CFD Drag Prediction Workshop: CRM Cases 2 to 5

NASA Technical Reports Server (NTRS)

Tinoco, Edward N.; Brodersen, Olaf P.; Keye, Stefan; Laflin, Kelly R.; Feltrop, Edward; Vassberg, John C.; Mani, Mori; Rider, Ben; Wahls, Richard A.; Morrison, Joseph H.;

Desktop Techniques for Analyzing Surface-Ground Water Interactions. The Reelfoot Lake Case Study

DTIC Science & Technology

1988-05-01

Reelfoot Lake Case Study DTlCSELECTE JUN 13 M Research Document No. 28 May 1988 Approved for Public Release. Distribution Unlimited. 86 , l~ g DESKTOP...TECHNIQUES FOR ANALYZING SURFACE-GROUND WATER INTERACTIONS The Reelfoot Lake Case Study Prepared by Dennis B. McLaughlin ’ Ia Prepared for The...Engineers became involved in a study of Reelfoot Lake , a large natural lake in northwestern Tennessee. Although modeling studies of the lake and its

A Socioecological Model of Rape Survivors' Decisions to Aid in Case Prosecution

ERIC Educational Resources Information Center

Anders, Mary C.; Christopher, F. Scott

2011-01-01

The purpose of our study was to identify factors underlying rape survivors' post-assault prosecution decisions by testing a decision model that included the complex relations between the multiple social ecological systems within which rape survivors are embedded. We coded 440 police rape cases for characteristics of the assault and characteristics…

Prestige-Oriented Market Entry Strategy: The Case of Australian Universities

ERIC Educational Resources Information Center

Tayar, Mark; Jack, Robert

2013-01-01

Through an exploratory case study of four Australian universities this article finds that foreign market entry strategies are shaped by prestige-seeking motivations and a culture of risk aversion. From the market selection, entry mode and higher education literature, a conceptual model, embedded with four propositions, is presented. The model sees…

Spatial distribution of the risk of dengue fever in southeast Brazil, 2006-2007

PubMed Central

2011-01-01

Background Many factors have been associated with circulation of the dengue fever virus and vector, although the dynamics of transmission are not yet fully understood. The aim of this work is to estimate the spatial distribution of the risk of dengue fever in an area of continuous dengue occurrence. Methods This is a spatial population-based case-control study that analyzed 538 cases and 727 controls in one district of the municipality of Campinas, São Paulo, Brazil, from 2006-2007, considering socio-demographic, ecological, case severity, and household infestation variables. Information was collected by in-home interviews and inspection of living conditions in and around the homes studied. Cases were classified as mild or severe according to clinical data, and they were compared with controls through a multinomial logistic model. A generalized additive model was used in order to include space in a non-parametric fashion with cubic smoothing splines. Results Variables associated with increased incidence of all dengue cases in the multiple binomial regression model were: higher larval density (odds ratio (OR) = 2.3 (95%CI: 2.0-2.7)), reports of mosquito bites during the day (OR = 1.8 (95%CI: 1.4-2.4)), the practice of water storage at home (OR = 2.5 (95%CI: 1.4, 4.3)), low frequency of garbage collection (OR = 2.6 (95%CI: 1.6-4.5)) and lack of basic sanitation (OR = 2.9 (95%CI: 1.8-4.9)). Staying at home during the day was protective against the disease (OR = 0.5 (95%CI: 0.3-0.6)). When cases were analyzed by categories (mild and severe) in the multinomial model, age and number of breeding sites more than 10 were significant only for the occurrence of severe cases (OR = 0.97, (95%CI: 0.96-0.99) and OR = 2.1 (95%CI: 1.2-3.5), respectively. Spatial distribution of risks of mild and severe dengue fever differed from each other in the 2006/2007 epidemic, in the study area. Conclusions Age and presence of more than 10 breeding sites were significant only for severe cases. Other predictors of mild and severe cases were similar in the multiple models. The analyses of multinomial models and spatial distribution maps of dengue fever probabilities suggest an area-specific epidemic with varying clinical and demographic characteristics. PMID:21599980

The cost of different types of lameness in dairy cows calculated by dynamic programming.

PubMed

Cha, E; Hertl, J A; Bar, D; Gröhn, Y T

2010-10-01

Traditionally, studies which placed a monetary value on the effect of lameness have calculated the costs at the herd level and rarely have they been specific to different types of lameness. These costs which have been calculated from former studies are not particularly useful for farmers in making economically optimal decisions depending on individual cow characteristics. The objective of this study was to calculate the cost of different types of lameness at the individual cow level and thereby identify the optimal management decision for each of three representative lameness diagnoses. This model would provide a more informed decision making process in lameness management for maximal economic profitability. We made modifications to an existing dynamic optimization and simulation model, studying the effects of various factors (incidence of lameness, milk loss, pregnancy rate and treatment cost) on the cost of different types of lameness. The average cost per case (US$) of sole ulcer, digital dermatitis and foot rot were 216.07, 132.96 and 120.70, respectively. It was recommended that 97.3% of foot rot cases, 95.5% of digital dermatitis cases and 92.3% of sole ulcer cases be treated. The main contributor to the total cost per case of sole ulcer was milk loss (38%), treatment cost for digital dermatitis (42%) and the effect of decreased fertility for foot rot (50%). This model affords versatility as it allows for parameters such as production costs, economic values and disease frequencies to be altered. Therefore, cost estimates are the direct outcome of the farm specific parameters entered into the model. Thus, this model can provide farmers economically optimal guidelines specific to their individual cows suffering from different types of lameness. Copyright © 2010 Elsevier B.V. All rights reserved.

Quantitative analysis of factors that affect oil pipeline network accident based on Bayesian networks: A case study in China

NASA Astrophysics Data System (ADS)

Zhang, Chao; Qin, Ting Xin; Huang, Shuai; Wu, Jian Song; Meng, Xin Yan

2018-06-01

Some factors can affect the consequences of oil pipeline accident and their effects should be analyzed to improve emergency preparation and emergency response. Although there are some qualitative analysis models of risk factors' effects, the quantitative analysis model still should be researched. In this study, we introduce a Bayesian network (BN) model of risk factors' effects analysis in an oil pipeline accident case that happened in China. The incident evolution diagram is built to identify the risk factors. And the BN model is built based on the deployment rule for factor nodes in BN and the expert knowledge by Dempster-Shafer evidence theory. Then the probabilities of incident consequences and risk factors' effects can be calculated. The most likely consequences given by this model are consilient with the case. Meanwhile, the quantitative estimations of risk factors' effects may provide a theoretical basis to take optimal risk treatment measures for oil pipeline management, which can be used in emergency preparation and emergency response.

A Conceptual Model for Leadership Transition

ERIC Educational Resources Information Center

Manderscheid, Steven V.; Ardichvili, Alexandre

2008-01-01

The purpose of this study was to develop a model of leadership transition based on an integrative review of literature. The article establishes a compelling case for focusing on leadership transitions as an area for study and leadership development practitioner intervention. The proposed model in this study identifies important success factors…

Application of the Analog Method to Modelling Heat Waves: A Case Study with Power Transformers

DTIC Science & Technology

2017-04-21

UNCLASSIFIED Massachusetts Institute of Technology Lincoln Laboratory APPLICATION OF THE ANALOG METHOD TO MODELLING HEAT WAVES: A CASE STUDY WITH...18 2 Calibration and validation statistics with the use of five atmospheric vari- ables to construct analogue diagnostics for JJA of transformer T2...electrical grid as a series of nodes (transformers) and edges (transmission lines) so that basic mathematical anal- ysis can be performed. The mathematics

Parameterisation of Orographic Cloud Dynamics in a GCM

DTIC Science & Technology

2007-01-01

makes use of both satellite observations of a case study, and a simulation in which the Unified Model is nudged to- wards ERA-40 assimilated winds...this parameterisation makes use of both satellite observations of a case study, and a simulation in which the Unified Model is nudged towards ERA-40...by ANSI Std Z39-18 et al. (1999), predicted the temperature perturbations in the lower stratosphere which can influence polar stratospheric clouds

Cirrus cloud development in a mobile upper tropospheric trough: The November 26th FIRE cirrus case study

NASA Technical Reports Server (NTRS)

Mace, Gerald G.; Ackerman, Thomas P.

1993-01-01

The period from 18 UTC 26 Nov. 1991 to roughly 23 UTC 26 Nov. 1991 is one of the study periods of the FIRE (First International Satellite Cloud Climatology Regional Experiment) 2 field campaign. The middle and upper tropospheric cloud data that was collected during this time allowed FIRE scientists to learn a great deal about the detailed structure, microphysics, and radiative characteristics of the mid latitude cirrus that occurred during that time. Modeling studies that range from the microphysical to the mesoscale are now underway attempting to piece the detailed knowledge of this cloud system into a coherent picture of the atmospheric processes important to cirrus cloud development and maintenance. An important component of the modeling work, either as an input parameter in the case of cloud-scale models, or as output in the case of meso and larger scale models, is the large scale forcing of the cloud system. By forcing we mean the synoptic scale vertical motions and moisture budget that initially send air parcels ascending and supply the water vapor to allow condensation during ascent. Defining this forcing from the synoptic scale to the cloud scale is one of the stated scientific objectives of the FIRE program. From the standpoint of model validation, it is also necessary that the vertical motions and large scale moisture budget of the case studies be derived from observations. It is considered important that the models used to simulate the observed cloud fields begin with the correct dynamics and that the dynamics be in the right place for the right reasons.

A general description of detachment for multidimensional modelling of biofilms.

PubMed

Xavier, Joao de Bivar; Picioreanu, Cristian; van Loosdrecht, Mark C M

2005-09-20

A general method for describing biomass detachment in multidimensional biofilm modelling is introduced. Biomass losses from processes acting on the entire surface of the biofilm, such as erosion, are modelled using a continuous detachment speed function F(det). Discrete detachment events, i.e. sloughing, are implicitly derived from simulations. The method is flexible to allow F(det) to take several forms, including expressions dependent on any state variables such as the local biofilm density. This methodology for biomass detachment was integrated with multidimensional (2D and 3D) particle-based multispecies biofilm models by using a novel application of the level set method. Application of the method is illustrated by trends in the dynamics of biofilms structure and activity derived from simulations performed on a simple model considering uniform biomass (case study I) and a model discriminating biomass composition in heterotrophic active mass, extracellular polymeric substances (EPS) and inert mass (case study II). Results from case study I demonstrate the effect of applied detachment forces as a fundamental factor influencing steady-state biofilm activity and structure. Trends from experimental observations reported in literature were correctly described. For example, simulation results indicated that biomass sloughing is reduced when erosion forces are increased. Case study II illustrates the application of the detachment methodology to systems with non-uniform biomass composition. Simulations carried out at different bulk concentrations of substrate show changes in biofilm structure (in terms of shape, density and spatial distribution of biomass components) and activity (in terms of oxygen and substrate consumption) as a consequence of either oxygen-limited or substrate-limited growth. (c) 2005 Wiley Periodicals, Inc.

A combined disease management and process modeling approach for assessing and improving care processes: a fall management case-study.

PubMed

Askari, Marjan; Westerhof, Richard; Eslami, Saied; Medlock, Stephanie; de Rooij, Sophia E; Abu-Hanna, Ameen

2013-10-01

To propose a combined disease management and process modeling approach for evaluating and improving care processes, and demonstrate its usability and usefulness in a real-world fall management case study. We identified essential disease management related concepts and mapped them into explicit questions meant to expose areas for improvement in the respective care processes. We applied the disease management oriented questions to a process model of a comprehensive real world fall prevention and treatment program covering primary and secondary care. We relied on interviews and observations to complete the process models, which were captured in UML activity diagrams. A preliminary evaluation of the usability of our approach by gauging the experience of the modeler and an external validator was conducted, and the usefulness of the method was evaluated by gathering feedback from stakeholders at an invitational conference of 75 attendees. The process model of the fall management program was organized around the clinical tasks of case finding, risk profiling, decision making, coordination and interventions. Applying the disease management questions to the process models exposed weaknesses in the process including: absence of program ownership, under-detection of falls in primary care, and lack of efficient communication among stakeholders due to missing awareness about other stakeholders' workflow. The modelers experienced the approach as usable and the attendees of the invitational conference found the analysis results to be valid. The proposed disease management view of process modeling was usable and useful for systematically identifying areas of improvement in a fall management program. Although specifically applied to fall management, we believe our case study is characteristic of various disease management settings, suggesting the wider applicability of the approach. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Developing Emotion-Based Case Formulations: A Research-Informed Method.

PubMed

Pascual-Leone, Antonio; Kramer, Ueli

2017-01-01

New research-informed methods for case conceptualization that cut across traditional therapy approaches are increasingly popular. This paper presents a trans-theoretical approach to case formulation based on the research observations of emotion. The sequential model of emotional processing (Pascual-Leone & Greenberg, 2007) is a process research model that provides concrete markers for therapists to observe the emerging emotional development of their clients. We illustrate how this model can be used by clinicians to track change and provides a 'clinical map,' by which therapist may orient themselves in-session and plan treatment interventions. Emotional processing offers as a trans-theoretical framework for therapists who wish to conduct emotion-based case formulations. First, we present criteria for why this research model translates well into practice. Second, two contrasting case studies are presented to demonstrate the method. The model bridges research with practice by using client emotion as an axis of integration. Key Practitioner Message Process research on emotion can offer a template for therapists to make case formulations while using a range of treatment approaches. The sequential model of emotional processing provides a 'process map' of concrete markers for therapists to (1) observe the emerging emotional development of their clients, and (2) help therapists develop a treatment plan. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Comparison of the binary logistic and skewed logistic (Scobit) models of injury severity in motor vehicle collisions.

PubMed

Tay, Richard

2016-03-01

The binary logistic model has been extensively used to analyze traffic collision and injury data where the outcome of interest has two categories. However, the assumption of a symmetric distribution may not be a desirable property in some cases, especially when there is a significant imbalance in the two categories of outcome. This study compares the standard binary logistic model with the skewed logistic model in two cases in which the symmetry assumption is violated in one but not the other case. The differences in the estimates, and thus the marginal effects obtained, are significant when the assumption of symmetry is violated. Copyright © 2015 Elsevier Ltd. All rights reserved.

Model-Selection Theory: The Need for a More Nuanced Picture of Use-Novelty and Double-Counting

PubMed Central

Steele, Katie; Werndl, Charlotte

2018-01-01

Abstract This article argues that common intuitions regarding (a) the specialness of ‘use-novel’ data for confirmation and (b) that this specialness implies the ‘no-double-counting rule’, which says that data used in ‘constructing’ (calibrating) a model cannot also play a role in confirming the model’s predictions, are too crude. The intuitions in question are pertinent in all the sciences, but we appeal to a climate science case study to illustrate what is at stake. Our strategy is to analyse the intuitive claims in light of prominent accounts of confirmation of model predictions. We show that on the Bayesian account of confirmation, and also on the standard classical hypothesis-testing account, claims (a) and (b) are not generally true; but for some select cases, it is possible to distinguish data used for calibration from use-novel data, where only the latter confirm. The more specialized classical model-selection methods, on the other hand, uphold a nuanced version of claim (a), but this comes apart from (b), which must be rejected in favour of a more refined account of the relationship between calibration and confirmation. Thus, depending on the framework of confirmation, either the scope or the simplicity of the intuitive position must be revised. 1 Introduction2 A Climate Case Study3 The Bayesian Method vis-à-vis Intuitions4 Classical Tests vis-à-vis Intuitions5 Classical Model-Selection Methods vis-à-vis Intuitions  5.1 Introducing classical model-selection methods  5.2 Two cases6 Re-examining Our Case Study7 Conclusion PMID:29780170

Network-based regularization for matched case-control analysis of high-dimensional DNA methylation data.

PubMed

Sun, Hokeun; Wang, Shuang

2013-05-30

The matched case-control designs are commonly used to control for potential confounding factors in genetic epidemiology studies especially epigenetic studies with DNA methylation. Compared with unmatched case-control studies with high-dimensional genomic or epigenetic data, there have been few variable selection methods for matched sets. In an earlier paper, we proposed the penalized logistic regression model for the analysis of unmatched DNA methylation data using a network-based penalty. However, for popularly applied matched designs in epigenetic studies that compare DNA methylation between tumor and adjacent non-tumor tissues or between pre-treatment and post-treatment conditions, applying ordinary logistic regression ignoring matching is known to bring serious bias in estimation. In this paper, we developed a penalized conditional logistic model using the network-based penalty that encourages a grouping effect of (1) linked Cytosine-phosphate-Guanine (CpG) sites within a gene or (2) linked genes within a genetic pathway for analysis of matched DNA methylation data. In our simulation studies, we demonstrated the superiority of using conditional logistic model over unconditional logistic model in high-dimensional variable selection problems for matched case-control data. We further investigated the benefits of utilizing biological group or graph information for matched case-control data. We applied the proposed method to a genome-wide DNA methylation study on hepatocellular carcinoma (HCC) where we investigated the DNA methylation levels of tumor and adjacent non-tumor tissues from HCC patients by using the Illumina Infinium HumanMethylation27 Beadchip. Several new CpG sites and genes known to be related to HCC were identified but were missed by the standard method in the original paper. Copyright © 2012 John Wiley & Sons, Ltd.

Evaluation of integration methods for hybrid simulation of complex structural systems through collapse

NASA Astrophysics Data System (ADS)

Del Carpio R., Maikol; Hashemi, M. Javad; Mosqueda, Gilberto

2017-10-01

This study examines the performance of integration methods for hybrid simulation of large and complex structural systems in the context of structural collapse due to seismic excitations. The target application is not necessarily for real-time testing, but rather for models that involve large-scale physical sub-structures and highly nonlinear numerical models. Four case studies are presented and discussed. In the first case study, the accuracy of integration schemes including two widely used methods, namely, modified version of the implicit Newmark with fixed-number of iteration (iterative) and the operator-splitting (non-iterative) is examined through pure numerical simulations. The second case study presents the results of 10 hybrid simulations repeated with the two aforementioned integration methods considering various time steps and fixed-number of iterations for the iterative integration method. The physical sub-structure in these tests consists of a single-degree-of-freedom (SDOF) cantilever column with replaceable steel coupons that provides repeatable highlynonlinear behavior including fracture-type strength and stiffness degradations. In case study three, the implicit Newmark with fixed-number of iterations is applied for hybrid simulations of a 1:2 scale steel moment frame that includes a relatively complex nonlinear numerical substructure. Lastly, a more complex numerical substructure is considered by constructing a nonlinear computational model of a moment frame coupled to a hybrid model of a 1:2 scale steel gravity frame. The last two case studies are conducted on the same porotype structure and the selection of time steps and fixed number of iterations are closely examined in pre-test simulations. The generated unbalance forces is used as an index to track the equilibrium error and predict the accuracy and stability of the simulations.

The Relationships Between Modelling and Argumentation from the Perspective of the Model of Modelling Diagram

NASA Astrophysics Data System (ADS)

Cardoso Mendonça, Paula Cristina; Justi, Rosária

2013-09-01

Some studies related to the nature of scientific knowledge demonstrate that modelling is an inherently argumentative process. This study aims at discussing the relationship between modelling and argumentation by analysing data collected during the modelling-based teaching of ionic bonding and intermolecular interactions. The teaching activities were planned from the transposition of the main modelling stages that constitute the 'Model of Modelling Diagram' so that students could experience each of such stages. All the lessons were video recorded and their transcriptions supported the elaboration of case studies for each group of students. From the analysis of the case studies, we identified argumentative situations when students performed all of the modelling stages. Our data show that the argumentative situations were related to sense making, articulating and persuasion purposes, and were closely related to the generation of explanations in the modelling processes. They also show that representations are important resources for argumentation. Our results are consistent with some of those already reported in the literature regarding the relationship between modelling and argumentation, but are also divergent when they show that argumentation is not only related to the model evaluation phase.

Bayesian dynamic modeling of time series of dengue disease case counts.

PubMed

Martínez-Bello, Daniel Adyro; López-Quílez, Antonio; Torres-Prieto, Alexander

2017-07-01

The aim of this study is to model the association between weekly time series of dengue case counts and meteorological variables, in a high-incidence city of Colombia, applying Bayesian hierarchical dynamic generalized linear models over the period January 2008 to August 2015. Additionally, we evaluate the model's short-term performance for predicting dengue cases. The methodology shows dynamic Poisson log link models including constant or time-varying coefficients for the meteorological variables. Calendar effects were modeled using constant or first- or second-order random walk time-varying coefficients. The meteorological variables were modeled using constant coefficients and first-order random walk time-varying coefficients. We applied Markov Chain Monte Carlo simulations for parameter estimation, and deviance information criterion statistic (DIC) for model selection. We assessed the short-term predictive performance of the selected final model, at several time points within the study period using the mean absolute percentage error. The results showed the best model including first-order random walk time-varying coefficients for calendar trend and first-order random walk time-varying coefficients for the meteorological variables. Besides the computational challenges, interpreting the results implies a complete analysis of the time series of dengue with respect to the parameter estimates of the meteorological effects. We found small values of the mean absolute percentage errors at one or two weeks out-of-sample predictions for most prediction points, associated with low volatility periods in the dengue counts. We discuss the advantages and limitations of the dynamic Poisson models for studying the association between time series of dengue disease and meteorological variables. The key conclusion of the study is that dynamic Poisson models account for the dynamic nature of the variables involved in the modeling of time series of dengue disease, producing useful models for decision-making in public health.

A comparative study of mixture cure models with covariate

NASA Astrophysics Data System (ADS)

Leng, Oh Yit; Khalid, Zarina Mohd

2017-05-01

In survival analysis, the survival time is assumed to follow a non-negative distribution, such as the exponential, Weibull, and log-normal distributions. In some cases, the survival time is influenced by some observed factors. The absence of these observed factors may cause an inaccurate estimation in the survival function. Therefore, a survival model which incorporates the influences of observed factors is more appropriate to be used in such cases. These observed factors are included in the survival model as covariates. Besides that, there are cases where a group of individuals who are cured, that is, not experiencing the event of interest. Ignoring the cure fraction may lead to overestimate in estimating the survival function. Thus, a mixture cure model is more suitable to be employed in modelling survival data with the presence of a cure fraction. In this study, three mixture cure survival models are used to analyse survival data with a covariate and a cure fraction. The first model includes covariate in the parameterization of the susceptible individuals survival function, the second model allows the cure fraction to depend on covariate, and the third model incorporates covariate in both cure fraction and survival function of susceptible individuals. This study aims to compare the performance of these models via a simulation approach. Therefore, in this study, survival data with varying sample sizes and cure fractions are simulated and the survival time is assumed to follow the Weibull distribution. The simulated data are then modelled using the three mixture cure survival models. The results show that the three mixture cure models are more appropriate to be used in modelling survival data with the presence of cure fraction and an observed factor.

Hybrid supply chain model for material requirement planning under financial constraints: A case study

NASA Astrophysics Data System (ADS)

Curci, Vita; Dassisti, Michele; Josefa, Mula Bru; Manuel, Díaz Madroñero

2014-10-01

Supply chain model (SCM) are potentially capable to integrate different aspects in supporting decision making for enterprise management tasks. The aim of the paper is to propose an hybrid mathematical programming model for optimization of production requirements resources planning. The preliminary model was conceived bottom-up from a real industrial case analysed oriented to maximize cash flow. Despite the intense computational effort required to converge to a solution, optimisation done brought good result in solving the objective function.

Diagramming Transactive Building Business Cases: Using Principles of e3 Value to Document Valuation Studies

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

Hammerstrom, Donald J.; Makhmalbaf, Atefe; Marinovici, Maria C.

Energy management in buildings is becoming more transactive. Pacific Northwest National Laboratory and the U.S. Department of Energy Building Technologies Office recently defined innovative use cases wherein market-like mechanisms are used to manage energy within buildings, between buildings, and between buildings and third-party entities, such as power utilities. A next step toward defining a set of transactive use cases in the buildings domain is to carefully diagram the corresponding business cases to capture details of transactions among all stakeholders and their economic value propositions. The principles of e3-value diagramming are applied in this report toward creating business value diagrams. Thesemore » principles are extended to be consistent with Universal Modeling Language use-case diagrams. Example diagrams are presented for a subset of buildings-domain use cases that were introduced in an earlier Pacific Northwest National Laboratory report. The diagrams are intended to clearly represent an understanding of the transactions through which individual entities accumulate value in their respective use cases, and the diagrams should therefore support economic valuation studies. The report reviews some of the foundational principles of e3 value and includes authors’ insights concerning the formulation of these diagrams using Universal Modeling Language as a more systematic modeling approach.« less

Physics of Materials.

ERIC Educational Resources Information Center

Archenhold, W. F.; And Others

1987-01-01

Describes a new high school physics option in Great Britain which uses the model of a technological approach to the study of materials. Discusses the components of the program, including the development of a student book for independent learning and six case studies. Provides a case study about turbine blades. (TW)

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

Xiao, Heng; Gustafson, William I.; Wang, Hailong

Subgrid-scale interactions between turbulence and radiation are potentially important for accurately reproducing marine low clouds in climate models. To better understand the impact of these interactions, the Weather Research and Forecasting (WRF) model is configured for large eddy simulation (LES) to study the stratocumulus-to-trade cumulus (Sc-to-Cu) transition. Using the GEWEX Atmospheric System Studies (GASS) composite Lagrangian transition case and the Atlantic Trade Wind Experiment (ATEX) case, it is shown that the lack of subgrid-scale turbulence-radiation interaction, as is the case in current generation climate models, accelerates the Sc-to-Cu transition. Our analysis suggests that in cloud-topped boundary layers subgrid-scale turbulence-radiation interactionsmore » contribute to stronger production of temperature variance, which in turn leads to stronger buoyancy production of turbulent kinetic energy and helps to maintain the Sc cover.« less

Spatial Prediction of Coxiella burnetii Outbreak Exposure via Notified Case Counts in a Dose-Response Model.

PubMed

Brooke, Russell J; Kretzschmar, Mirjam E E; Hackert, Volker; Hoebe, Christian J P A; Teunis, Peter F M; Waller, Lance A

2017-01-01

We develop a novel approach to study an outbreak of Q fever in 2009 in the Netherlands by combining a human dose-response model with geostatistics prediction to relate probability of infection and associated probability of illness to an effective dose of Coxiella burnetii. The spatial distribution of the 220 notified cases in the at-risk population are translated into a smooth spatial field of dose. Based on these symptomatic cases, the dose-response model predicts a median of 611 asymptomatic infections (95% range: 410, 1,084) for the 220 reported symptomatic cases in the at-risk population; 2.78 (95% range: 1.86, 4.93) asymptomatic infections for each reported case. The low attack rates observed during the outbreak range from (Equation is included in full-text article.)to (Equation is included in full-text article.). The estimated peak levels of exposure extend to the north-east from the point source with an increasing proportion of asymptomatic infections further from the source. Our work combines established methodology from model-based geostatistics and dose-response modeling allowing for a novel approach to study outbreaks. Unobserved infections and the spatially varying effective dose can be predicted using the flexible framework without assuming any underlying spatial structure of the outbreak process. Such predictions are important for targeting interventions during an outbreak, estimating future disease burden, and determining acceptable risk levels.

Using a contextualized sensemaking model for interaction design: A case study of tumor contouring.

PubMed

Aselmaa, Anet; van Herk, Marcel; Laprie, Anne; Nestle, Ursula; Götz, Irina; Wiedenmann, Nicole; Schimek-Jasch, Tanja; Picaud, Francois; Syrykh, Charlotte; Cagetti, Leonel V; Jolnerovski, Maria; Song, Yu; Goossens, Richard H M

2017-01-01

Sensemaking theories help designers understand the cognitive processes of a user when he/she performs a complicated task. This paper introduces a two-step approach of incorporating sensemaking support within the design of health information systems by: (1) modeling the sensemaking process of physicians while performing a task, and (2) identifying software interaction design requirements that support sensemaking based on this model. The two-step approach is presented based on a case study of the tumor contouring clinical task for radiotherapy planning. In the first step of the approach, a contextualized sensemaking model was developed to describe the sensemaking process based on the goal, the workflow and the context of the task. In the second step, based on a research software prototype, an experiment was conducted where three contouring tasks were performed by eight physicians respectively. Four types of navigation interactions and five types of interaction sequence patterns were identified by analyzing the gathered interaction log data from those twenty-four cases. Further in-depth study on each of the navigation interactions and interaction sequence patterns in relation to the contextualized sensemaking model revealed five main areas for design improvements to increase sensemaking support. Outcomes of the case study indicate that the proposed two-step approach was beneficial for gaining a deeper understanding of the sensemaking process during the task, as well as for identifying design requirements for better sensemaking support. Copyright © 2016. Published by Elsevier Inc.

NFKB1 -94insertion/deletion ATTG polymorphism and cancer risk: Evidence from 50 case-control studies.

PubMed

Fu, Wen; Zhuo, Zhen-Jian; Chen, Yung-Chang; Zhu, Jinhong; Zhao, Zhang; Jia, Wei; Hu, Jin-Hua; Fu, Kai; Zhu, Shi-Bo; He, Jing; Liu, Guo-Chang

2017-02-07

Nuclear factor-kappa B1 (NF-κB1) is a pleiotropic transcription factor and key contributor to tumorigenesis in many types of cancer. Numerous studies have addressed the association of a functional insertion (I)/deletion (D) polymorphism (-94ins/delATTG, rs28362491) in the promoter region of NFKB1 gene with the risk of various types of cancer; however, their conclusions have been inconsistent. We therefore conducted a meta-analysis to reevaluate this association. PubMed, EMBASE, China National Knowledge infrastructure (CNKI), and WANFANG databases were searched through July 2016 to retrieve relevant studies. After careful assessment, 50 case-control studies, comprising 18,299 cases and 23,484 controls were selected. Crude odds ratios (ORs) and 95% confidence intervals (CIs) were used to determine the strength of the association. The NFKB1 -94ins/delATTG polymorphism was associated with a decreased risk of overall cancer in the homozygote model (DD vs. II): OR = 0.75, 95% CI = 0.64-0.87); heterozygote model (ID vs. II): OR = 0.91, 95% CI = 0.83-0.99; recessive model (DD vs. ID/II): OR = 0.81, 95% CI = 0.71-0.91; dominant model (ID/DD vs. II): OR = 0.86, 95% CI = 0.78-0.95; and allele contrast model (D vs. I): OR = 0.88, 95% CI = 0.81-0.95). Subgroup and stratified analyses revealed decreased risks for lung cancer, nasopharyngeal carcinoma, prostate cancer, ovarian cancer, and oral squamous cell carcinoma, and this association held true also for Asians (especially Chinese subjects) in hospital-based studies, and in studies with quality scores less than nine. Well-designed, large-scale case-control studies are needed to confirm these results.

Research misconduct oversight: defining case costs.

PubMed

Gammon, Elizabeth; Franzini, Luisa

2013-01-01

This study uses a sequential mixed method study design to define cost elements of research misconduct among faculty at academic medical centers. Using time driven activity based costing, the model estimates a per case cost for 17 cases of research misconduct reported by the Office of Research Integrity for the period of 2000-2005. Per case cost of research misconduct was found to range from $116,160 to $2,192,620. Research misconduct cost drivers are identified.

Optimizing clinical and organizational practice in cancer survivor transitions between specialized oncology and primary care teams: a realist evaluation of multiple case studies.

PubMed

Tremblay, Dominique; Prady, Catherine; Bilodeau, Karine; Touati, Nassera; Chouinard, Maud-Christine; Fortin, Martin; Gaboury, Isabelle; Rodrigue, Jean; L'Italien, Marie-France

2017-12-16

Cancer is now viewed as a chronic disease, presenting challenges to follow-up and survivorship care. Models to shift from haphazard, suboptimal and fragmented episodes of care to an integrated cancer care continuum must be developed, tested and implemented. Numerous studies demonstrate improved care when follow-up is assured by both oncology and primary care providers rather than either group alone. However, there is little data on the roles assumed by specialized oncology teams and primary care providers and the extent to which they work together. This study aims to develop, pilot test and measure outcomes of an innovative risk-based coordinated cancer care model for patients transitioning from specialized oncology teams to primary care providers. This multiple case study using a sequential mixed-methods design rests on a theory-driven realist evaluation approach to understand how transitions might be improved. The cases are two health regions in Quebec, Canada, defined by their geographic territory. Each case includes a Cancer Centre and three Family Medicine Groups selected based on differences in their determining characteristics. Qualitative data will be collected from document review (scientific journal, grey literature, local documentation), semi-directed interviews with key informants, and observation of care coordination practices. Qualitative data will be supplemented with a survey to measure the outcome of the coordinated model among providers (scope of practice, collaboration, relational coordination, leadership) and patients diagnosed with breast, colorectal or prostate cancer (access to care, patient-centredness, communication, self-care, survivorship profile, quality of life). Results from descriptive and regression analyses will be triangulated with thematic analysis of qualitative data. Qualitative, quantitative, and mixed methods data will be interpreted within and across cases in order to identify context-mechanism associations that explain outcomes. The study will provide empirical data on a risk-based coordinated model of cancer care to guide actions at different levels in the health system. This in-depth multiple case study using a realist approach considers both the need for context-specific intervention research and the imperative to address research gaps regarding coordinated models of cancer care.

System Dynamic Model for the Accumulation of Renewable Electricity using Power-to-Gas and Power-to-Liquid Concepts

NASA Astrophysics Data System (ADS)

Blumberga, Andra; Timma, Lelde; Blumberga, Dagnija

2015-12-01

When the renewable energy is used, the challenge is match the supply of intermittent energy with the demand for energy therefore the energy storage solutions should be used. This paper is dedicated to hydrogen accumulation from wind sources. The case study investigates the conceptual system that uses intermitted renewable energy resources to produce hydrogen (power-to-gas concept) and fuel (power-to-liquid concept). For this specific case study hydrogen is produced from surplus electricity generated by wind power plant trough electrolysis process and fuel is obtained by upgrading biogas to biomethane using hydrogen. System dynamic model is created for this conceptual system. The developed system dynamics model has been used to simulate 2 different scenarios. The results show that in both scenarios the point at which the all electricity needs of Latvia are covered is obtained. Moreover, the methodology of system dynamics used in this paper is white-box model that allows to apply the developed model to other case studies and/or to modify model based on the newest data. The developed model can be used for both scientific research and policy makers to better understand the dynamic relation within the system and the response of system to changes in both internal and external factors.

Time Series Analysis of Onchocerciasis Data from Mexico: A Trend towards Elimination

PubMed Central

Pérez-Rodríguez, Miguel A.; Adeleke, Monsuru A.; Orozco-Algarra, María E.; Arrendondo-Jiménez, Juan I.; Guo, Xianwu

2013-01-01

Background In Latin America, there are 13 geographically isolated endemic foci distributed among Mexico, Guatemala, Colombia, Venezuela, Brazil and Ecuador. The communities of the three endemic foci found within Mexico have been receiving ivermectin treatment since 1989. In this study, we predicted the trend of occurrence of cases in Mexico by applying time series analysis to monthly onchocerciasis data reported by the Mexican Secretariat of Health between 1988 and 2011 using the software R. Results A total of 15,584 cases were reported in Mexico from 1988 to 2011. The data of onchocerciasis cases are mainly from the main endemic foci of Chiapas and Oaxaca. The last case in Oaxaca was reported in 1998, but new cases were reported in the Chiapas foci up to 2011. Time series analysis performed for the foci in Mexico showed a decreasing trend of the disease over time. The best-fitted models with the smallest Akaike Information Criterion (AIC) were Auto-Regressive Integrated Moving Average (ARIMA) models, which were used to predict the tendency of onchocerciasis cases for two years ahead. According to the ARIMA models predictions, the cases in very low number (below 1) are expected for the disease between 2012 and 2013 in Chiapas, the last endemic region in Mexico. Conclusion The endemic regions of Mexico evolved from high onchocerciasis-endemic states to the interruption of transmission due to the strategies followed by the MSH, based on treatment with ivermectin. The extremely low level of expected cases as predicted by ARIMA models for the next two years suggest that the onchocerciasis is being eliminated in Mexico. To our knowledge, it is the first study utilizing time series for predicting case dynamics of onchocerciasis, which could be used as a benchmark during monitoring and post-treatment surveillance. PMID:23459370

Use and interpretation of logistic regression in habitat-selection studies

USGS Publications Warehouse

Keating, Kim A.; Cherry, Steve

2004-01-01

 Logistic regression is an important tool for wildlife habitat-selection studies, but the method frequently has been misapplied due to an inadequate understanding of the logistic model, its interpretation, and the influence of sampling design. To promote better use of this method, we review its application and interpretation under 3 sampling designs: random, case-control, and use-availability. Logistic regression is appropriate for habitat use-nonuse studies employing random sampling and can be used to directly model the conditional probability of use in such cases. Logistic regression also is appropriate for studies employing case-control sampling designs, but careful attention is required to interpret results correctly. Unless bias can be estimated or probability of use is small for all habitats, results of case-control studies should be interpreted as odds ratios, rather than probability of use or relative probability of use. When data are gathered under a use-availability design, logistic regression can be used to estimate approximate odds ratios if probability of use is small, at least on average. More generally, however, logistic regression is inappropriate for modeling habitat selection in use-availability studies. In particular, using logistic regression to fit the exponential model of Manly et al. (2002:100) does not guarantee maximum-likelihood estimates, valid probabilities, or valid likelihoods. We show that the resource selection function (RSF) commonly used for the exponential model is proportional to a logistic discriminant function. Thus, it may be used to rank habitats with respect to probability of use and to identify important habitat characteristics or their surrogates, but it is not guaranteed to be proportional to probability of use. Other problems associated with the exponential model also are discussed. We describe an alternative model based on Lancaster and Imbens (1996) that offers a method for estimating conditional probability of use in use-availability studies. Although promising, this model fails to converge to a unique solution in some important situations. Further work is needed to obtain a robust method that is broadly applicable to use-availability studies.

Addressing trend-related changes within cumulative effects studies in water resources planning

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

Canter, L.W., E-mail: envimptr@aol.com; Chawla, M.K.; Swor, C.T.

2014-01-15

Summarized herein are 28 case studies wherein trend-related causative physical, social, or institutional changes were connected to consequential changes in runoff, water quality, and riparian and aquatic ecological features. The reviewed cases were systematically evaluated relative to their identified environmental effects; usage of analytical frameworks, and appropriate models, methods, and technologies; and the attention given to mitigation and/or management of the resultant causative and consequential changes. These changes also represent important considerations in project design and operation, and in cumulative effects studies associated therewith. The cases were grouped into five categories: institutional changes associated with legislation and policies (seven cases);more » physical changes from land use changes in urbanizing watersheds (eight cases); physical changes from land use changes and development projects in watersheds (four cases); physical, institutional, and social changes from land use and related policy changes in river basins (three cases); and multiple changes within a comprehensive study of land use and policy changes in the Willamette River Basin in Oregon (six cases). A tabulation of 110 models, methods and technologies used in the studies is also presented. General observations from this review were that the features were unique for each case; the consequential changes were logically based on the causative changes; the analytical frameworks provided relevant structures for the studies, and the identified methods and technologies were pertinent for addressing both the causative and consequential changes. One key lesson was that the cases provide useful, “real-world” illustrations of the importance of addressing trend-related changes in cumulative effects studies within water resources planning. Accordingly, they could be used as an “initial tool kit” for addressing trend-related changes.« less

Three-dimensional surgical modelling with an open-source software protocol: study of precision and reproducibility in mandibular reconstruction with the fibula free flap.

PubMed

Ganry, L; Quilichini, J; Bandini, C M; Leyder, P; Hersant, B; Meningaud, J P

2017-08-01

Very few surgical teams currently use totally independent and free solutions to perform three-dimensional (3D) surgical modelling for osseous free flaps in reconstructive surgery. This study assessed the precision and technical reproducibility of a 3D surgical modelling protocol using free open-source software in mandibular reconstruction with fibula free flaps and surgical guides. Precision was assessed through comparisons of the 3D surgical guide to the sterilized 3D-printed guide, determining accuracy to the millimetre level. Reproducibility was assessed in three surgical cases by volumetric comparison to the millimetre level. For the 3D surgical modelling, a difference of less than 0.1mm was observed. Almost no deformations (<0.2mm) were observed post-autoclave sterilization of the 3D-printed surgical guides. In the three surgical cases, the average precision of fibula free flap modelling was between 0.1mm and 0.4mm, and the average precision of the complete reconstructed mandible was less than 1mm. The open-source software protocol demonstrated high accuracy without complications. However, the precision of the surgical case depends on the surgeon's 3D surgical modelling. Therefore, surgeons need training on the use of this protocol before applying it to surgical cases; this constitutes a limitation. Further studies should address the transfer of expertise. Copyright © 2017 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

Teachers' and Researchers' Beliefs of Learning and the use of Learning Progressions

NASA Astrophysics Data System (ADS)

Clapp, Francis Neely

In the last decade, science education reform in the United States has emphasized the exploration of cognitive learning pathways, which are theories on how a person learns a particular science subject matter. These theories are based, in part, by Piagetian developmental theory. One such model, called Learning Progressions (LP), has become prominent within science education reform. Science education researchers design LPs which in turn are used by science educators to sequence their curricula. The new national science standards released in April 2013 (Next Generation Science Standards) are, in part, grounded in the LP model. Understanding how teachers apply and use LPs, therefore, is valuable because professional development programs are likely to use this model, given the federal attention LP have received in science education reform. I sought to identify the beliefs and discourse that both LP developers and intended LP implementers have around student learning, teaching, and learning progressions. However, studies measuring beliefs or perspectives of LP-focused projects are absent in published works. A qualitative research is therefore warranted to explore this rather uncharted research area. Research questions were examined through the use of an instrumental case study. A case study approach was selected over other methodologies, as the research problem is, in part, bound within a clearly identifiable case (a professional development experience centering on a single LP model). One of the broadest definitions of a case study is noted by Becker (1968), who stated that goals of case studies are "to arrive at a comprehensive understanding of the groups under study" and to develop "general theoretical statements about regularities in social structure and process." (p.233). Based on Merriam (1985) the general consensus in the case study literature is that the assumptions underlying this method are common to naturalistic inquiry with research conducted primarily in the field with little control of variables. Beyond this similarity, different researchers have varying definitions to case studies. Merriam's (1985) provided a summary of the delineations and varying types of case studies. Merriam divided the various case study methods by their functions, with a marked divide between theory building and non-theory building methods. Non-theory building case studies are generally descriptive, and interpretive methods that apply theory to a case or context allow researchers to better understand the phenomena observed (Lijphart, 1971; Merriam, 1985). Conversely, theory building case studies focus on hypothesis generation, theory confirming, theory informing, or theory refuting (Lijphart, 1971; Merriam, 1985). Though there are many definitions and methods labeled as 'case studies,' for the purpose of this study, Yin's (1981) definition of a case study will be used. Yin (1981) defined a case study as a method to examine "(a) a contemporary phenomenon in its real-life context, especially when (b) the boundaries between phenomenon and context are not clearly evident" (p. 59). My study seeks to apply theory and study phenomena in their context, as I will examine teachers' practice in context of their respective classrooms. This study focuses on the lived experiences of both teacher and research stakeholders within the study. Specifically, I interviewed teachers who participated in a year-long teacher-in-residence (TiR) program. In addition, researchers/content experts who conceptualized the LP were also interviewed. Because the TiR experience was a form of professional development, I propose to study the impact that it had on participants' perceptions of the LP and any teacher-reported changes in their respective classrooms. However, because beliefs influence the language that we use to describe phenomena (such as learning and teaching), it is informative to also describe patterns in how LP developers explain learning and teaching. Subsequently, the results of this study will inform literature on both science teacher professional development and LPs theory to practice.

Coupled heat transfer model and experiment study of semitransparent barrier materials in aerothermal environment

NASA Astrophysics Data System (ADS)

Wang, Da-Lin; Qi, Hong

Semi-transparent materials (such as IR optical windows) are widely used for heat protection or transfer, temperature and image measurement, and safety in energy , space, military, and information technology applications. They are used, for instance, ceramic coatings for thermal barriers of spacecrafts or gas turbine blades, and thermal image observation under extreme or some dangerous environments. In this paper, the coupled conduction and radiation heat transfer model is established to describe temperature distribution of semitransparent thermal barrier medium within the aerothermal environment. In order to investigate this numerical model, one semi-transparent sample with black coating was considered, and photothermal properties were measured. At last, Finite Volume Method (FVM) was used to solve the coupled model, and the temperature responses from the sample surfaces were obtained. In addition, experiment study was also taken into account. In the present experiment, aerodynamic heat flux was simulated by one electrical heater, and two experiment cases were designed in terms of the duration of aerodynamic heating. One case is that the heater irradiates one surface of the sample continually until the other surface temperature up to constant, and the other case is that the heater works only 130 s. The surface temperature responses of these two cases were recorded. Finally, FVM model of the coupling conduction-radiation heat transfer was validated based on the experiment study with relative error less than 5%.

Primary care physicians’ perspectives on facilitating older patients’ access to community support services

PubMed Central

Ploeg, Jenny; Denton, Margaret; Hutchison, Brian; McAiney, Carrie; Moore, Ainsley; Brazil, Kevin; Tindale, Joseph; Lam, Annie

2017-01-01

Abstract Objective To understand how family physicians facilitate older patients’ access to community support services (CSSs) and to identify similarities and differences across primary health care (PHC) models. Design Qualitative, multiple-case study design using semistructured interviews. Setting Four models of PHC delivery, specifically 2 family health teams (FHTs), 4 non-FHTs family health organizations, 4 fee-for-service practices, and 2 community health centres in urban Ontario. Participants Purposeful sampling of 23 family physicians in solo and small and large group practices within the 4 models of PHC. Methods A multiple-case study approach was used. Semistructured interviews were conducted and data were analyzed using within- and cross-case analysis. Case study tactics to ensure study rigour included memos and an audit trail, investigator triangulation, and the use of multiple, rather than single, case studies. Main findings Three main themes were identified: consulting and communicating with the health care team to create linkages; linking patients and families to CSSs; and relying on out-of-date resources and ineffective search strategies for information on CSSs. All participants worked with their team members; however, those in FHTs and community health centres generally had a broader range of health care providers available to assist them. Physicians relied on home-care case managers to help make linkages to CSSs. Physicians recommended the development of an easily searchable, online database containing available CSSs. Conclusion This study shows the importance of interprofessional teamwork in primary care settings to facilitate linkages of older patients to CSSs. The study also provides insight into the strategies physicians use to link older persons to CSSs and their recommendations for change. This understanding can be used to develop resources and approaches to better support physicians in making appropriate linkages to CSSs. PMID:28115458

Maximum likelihood estimation for Cox's regression model under nested case-control sampling.

PubMed

Scheike, Thomas H; Juul, Anders

2004-04-01

Nested case-control sampling is designed to reduce the costs of large cohort studies. It is important to estimate the parameters of interest as efficiently as possible. We present a new maximum likelihood estimator (MLE) for nested case-control sampling in the context of Cox's proportional hazards model. The MLE is computed by the EM-algorithm, which is easy to implement in the proportional hazards setting. Standard errors are estimated by a numerical profile likelihood approach based on EM aided differentiation. The work was motivated by a nested case-control study that hypothesized that insulin-like growth factor I was associated with ischemic heart disease. The study was based on a population of 3784 Danes and 231 cases of ischemic heart disease where controls were matched on age and gender. We illustrate the use of the MLE for these data and show how the maximum likelihood framework can be used to obtain information additional to the relative risk estimates of covariates.

Comparing colon cancer outcomes: The impact of low hospital case volume and case-mix adjustment.

PubMed

Fischer, C; Lingsma, H F; van Leersum, N; Tollenaar, R A E M; Wouters, M W; Steyerberg, E W

2015-08-01

When comparing performance across hospitals it is essential to consider the noise caused by low hospital case volume and to perform adequate case-mix adjustment. We aimed to quantify the role of noise and case-mix adjustment on standardized postoperative mortality and anastomotic leakage (AL) rates. We studied 13,120 patients who underwent colon cancer resection in 85 Dutch hospitals. We addressed differences between hospitals in postoperative mortality and AL, using fixed (ignoring noise) and random effects (incorporating noise) logistic regression models with general and additional, disease specific, case-mix adjustment. Adding disease specific variables improved the performance of the case-mix adjustment models for postoperative mortality (c-statistic increased from 0.77 to 0.81). The overall variation in standardized mortality ratios was similar, but some individual hospitals changed considerably. For the standardized AL rates the performance of the adjustment models was poor (c-statistic 0.59 and 0.60) and overall variation was small. Most of the observed variation between hospitals was actually noise. Noise had a larger effect on hospital performance than extended case-mix adjustment, although some individual hospital outcome rates were affected by more detailed case-mix adjustment. To compare outcomes between hospitals it is crucial to consider noise due to low hospital case volume with a random effects model. Copyright © 2015 Elsevier Ltd. All rights reserved.

A hybrid model for combining case-control and cohort studies in systematic reviews of diagnostic tests

PubMed Central

Chen, Yong; Liu, Yulun; Ning, Jing; Cormier, Janice; Chu, Haitao

2014-01-01

Systematic reviews of diagnostic tests often involve a mixture of case-control and cohort studies. The standard methods for evaluating diagnostic accuracy only focus on sensitivity and specificity and ignore the information on disease prevalence contained in cohort studies. Consequently, such methods cannot provide estimates of measures related to disease prevalence, such as population averaged or overall positive and negative predictive values, which reflect the clinical utility of a diagnostic test. In this paper, we propose a hybrid approach that jointly models the disease prevalence along with the diagnostic test sensitivity and specificity in cohort studies, and the sensitivity and specificity in case-control studies. In order to overcome the potential computational difficulties in the standard full likelihood inference of the proposed hybrid model, we propose an alternative inference procedure based on the composite likelihood. Such composite likelihood based inference does not suffer computational problems and maintains high relative efficiency. In addition, it is more robust to model mis-specifications compared to the standard full likelihood inference. We apply our approach to a review of the performance of contemporary diagnostic imaging modalities for detecting metastases in patients with melanoma. PMID:25897179

Integrating urban recharge uncertainty into standard groundwater modeling practice: A case study on water main break predictions for the Barton Springs segment of the Edwards Aquifer, Austin, Texas

NASA Astrophysics Data System (ADS)

Sinner, K.; Teasley, R. L.

2016-12-01

Groundwater models serve as integral tools for understanding flow processes and informing stakeholders and policy makers in management decisions. Historically, these models tended towards a deterministic nature, relying on historical data to predict and inform future decisions based on model outputs. This research works towards developing a stochastic method of modeling recharge inputs from pipe main break predictions in an existing groundwater model, which subsequently generates desired outputs incorporating future uncertainty rather than deterministic data. The case study for this research is the Barton Springs segment of the Edwards Aquifer near Austin, Texas. Researchers and water resource professionals have modeled the Edwards Aquifer for decades due to its high water quality, fragile ecosystem, and stakeholder interest. The original case study and model that this research is built upon was developed as a co-design problem with regional stakeholders and the model outcomes are generated specifically for communication with policy makers and managers. Recently, research in the Barton Springs segment demonstrated a significant contribution of urban, or anthropogenic, recharge to the aquifer, particularly during dry period, using deterministic data sets. Due to social and ecological importance of urban water loss to recharge, this study develops an evaluation method to help predicted pipe breaks and their related recharge contribution within the Barton Springs segment of the Edwards Aquifer. To benefit groundwater management decision processes, the performance measures captured in the model results, such as springflow, head levels, storage, and others, were determined by previous work in elicitation of problem framing to determine stakeholder interests and concerns. The results of the previous deterministic model and the stochastic model are compared to determine gains to stakeholder knowledge through the additional modeling

Exploring the Use of Multiple Analogical Models when Teaching and Learning Chemical Equilibrium

ERIC Educational Resources Information Center

Harrison, Allan G.; De Jong, Onno

2005-01-01

This study describes the multiple analogical models used to introduce and teach Grade 12 chemical equilibrium. We examine the teacher's reasons for using models, explain each model's development during the lessons, and analyze the understandings students derived from the models. A case study approach was used and the data were drawn from the…

Three dimensional modeling and dynamic analysis of four-wheel-steering vehicles

NASA Astrophysics Data System (ADS)

Hu, Haiyan; Han, Qiang

2003-02-01

The paper presents a nonlinear dynamic model of 9 degrees of freedom for four-wheel-steering vehicles. Compared with those in previous studies, this model includes the pitch and roll of the vehicle body, the motion of 4 wheels in the accelerating or braking process, the nonlinear coupling of vehicle body and unsprung part, as well as the air drag and wind effect. As a result, the model can be used for the analysis of various maneuvers of the four-wheel-steering vehicles. In addition, the previous models can be considered as a special case of this model. The paper gives some case studies for the dynamic performance of a four-wheel-steering vehicle under step input and saw-tooth input of steering angle applied on the front wheels, respectively.

Modeling and projection of dengue fever cases in Guangzhou based on variation of weather factors.

PubMed

Li, Chenlu; Wang, Xiaofeng; Wu, Xiaoxu; Liu, Jianing; Ji, Duoying; Du, Juan

2017-12-15

Dengue fever is one of the most serious vector-borne infectious diseases, especially in Guangzhou, China. Dengue viruses and their vectors Aedes albopictus are sensitive to climate change primarily in relation to weather factors. Previous research has mainly focused on identifying the relationship between climate factors and dengue cases, or developing dengue case models with some non-climate factors. However, there has been little research addressing the modeling and projection of dengue cases only from the perspective of climate change. This study considered this topic using long time series data (1998-2014). First, sensitive weather factors were identified through meta-analysis that included literature review screening, lagged analysis, and collinear analysis. Then, key factors that included monthly average temperature at a lag of two months, and monthly average relative humidity and monthly average precipitation at lags of three months were determined. Second, time series Poisson analysis was used with the generalized additive model approach to develop a dengue model based on key weather factors for January 1998 to December 2012. Data from January 2013 to July 2014 were used to validate that the model was reliable and reasonable. Finally, future weather data (January 2020 to December 2070) were input into the model to project the occurrence of dengue cases under different climate scenarios (RCP 2.6 and RCP 8.5). Longer time series analysis and scientifically selected weather variables were used to develop a dengue model to ensure reliability. The projections suggested that seasonal disease control (especially in summer and fall) and mitigation of greenhouse gas emissions could help reduce the incidence of dengue fever. The results of this study hope to provide a scientifically theoretical basis for the prevention and control of dengue fever in Guangzhou. Copyright © 2017 Elsevier B.V. All rights reserved.

Effects of climatological parameters in modeling and forecasting seasonal influenza transmission in Abidjan, Cote d'Ivoire.

PubMed

N'gattia, A K; Coulibaly, D; Nzussouo, N Talla; Kadjo, H A; Chérif, D; Traoré, Y; Kouakou, B K; Kouassi, P D; Ekra, K D; Dagnan, N S; Williams, T; Tiembré, I

2016-09-13

In temperate regions, influenza epidemics occur in the winter and correlate with certain climatological parameters. In African tropical regions, the effects of climatological parameters on influenza epidemics are not well defined. This study aims to identify and model the effects of climatological parameters on seasonal influenza activity in Abidjan, Cote d'Ivoire. We studied the effects of weekly rainfall, humidity, and temperature on laboratory-confirmed influenza cases in Abidjan from 2007 to 2010. We used the Box-Jenkins method with the autoregressive integrated moving average (ARIMA) process to create models using data from 2007-2010 and to assess the predictive value of best model on data from 2011 to 2012. The weekly number of influenza cases showed significant cross-correlation with certain prior weeks for both rainfall, and relative humidity. The best fitting multivariate model (ARIMAX (2,0,0) _RF) included the number of influenza cases during 1-week and 2-weeks prior, and the rainfall during the current week and 5-weeks prior. The performance of this model showed an increase of >3 % for Akaike Information Criterion (AIC) and 2.5 % for Bayesian Information Criterion (BIC) compared to the reference univariate ARIMA (2,0,0). The prediction of the weekly number of influenza cases during 2011-2012 with the best fitting multivariate model (ARIMAX (2,0,0) _RF), showed that the observed values were within the 95 % confidence interval of the predicted values during 97 of 104 weeks. Including rainfall increases the performances of fitted and predicted models. The timing of influenza in Abidjan can be partially explained by rainfall influence, in a setting with little change in temperature throughout the year. These findings can help clinicians to anticipate influenza cases during the rainy season by implementing preventive measures.

Center for the Built Environment: Research on Building Envelope Systems

Science.gov Websites

Studies Facade and Perimeter Zone Field Study Facades and Thermal Comfort Facade Symposium Mixed-Mode Research Adaptive Comfort Model Mixed-Mode Case Studies Operable Windows and Thermal Comfort Occupant thermal preferences in naturally ventilated as sealed buildings? Case Study Research of Mixed-Mode Office

FAST Model Calibration and Validation of the OC5-DeepCwind Floating Offshore Wind System Against Wave Tank Test Data

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

Wendt, Fabian F; Robertson, Amy N; Jonkman, Jason

During the course of the Offshore Code Comparison Collaboration, Continued, with Correlation (OC5) project, which focused on the validation of numerical methods through comparison against tank test data, the authors created a numerical FAST model of the 1:50-scale DeepCwind semisubmersible system that was tested at the Maritime Research Institute Netherlands ocean basin in 2013. This paper discusses several model calibration studies that were conducted to identify model adjustments that improve the agreement between the numerical simulations and the experimental test data. These calibration studies cover wind-field-specific parameters (coherence, turbulence), hydrodynamic and aerodynamic modeling approaches, as well as rotor model (blade-pitchmore » and blade-mass imbalances) and tower model (structural tower damping coefficient) adjustments. These calibration studies were conducted based on relatively simple calibration load cases (wave only/wind only). The agreement between the final FAST model and experimental measurements is then assessed based on more-complex combined wind and wave validation cases.« less

Comparison of time series models for predicting campylobacteriosis risk in New Zealand.

PubMed

Al-Sakkaf, A; Jones, G

2014-05-01

Predicting campylobacteriosis cases is a matter of considerable concern in New Zealand, after the number of the notified cases was the highest among the developed countries in 2006. Thus, there is a need to develop a model or a tool to predict accurately the number of campylobacteriosis cases as the Microbial Risk Assessment Model used to predict the number of campylobacteriosis cases failed to predict accurately the number of actual cases. We explore the appropriateness of classical time series modelling approaches for predicting campylobacteriosis. Finding the most appropriate time series model for New Zealand data has additional practical considerations given a possible structural change, that is, a specific and sudden change in response to the implemented interventions. A univariate methodological approach was used to predict monthly disease cases using New Zealand surveillance data of campylobacteriosis incidence from 1998 to 2009. The data from the years 1998 to 2008 were used to model the time series with the year 2009 held out of the data set for model validation. The best two models were then fitted to the full 1998-2009 data and used to predict for each month of 2010. The Holt-Winters (multiplicative) and ARIMA (additive) intervention models were considered the best models for predicting campylobacteriosis in New Zealand. It was noticed that the prediction by an additive ARIMA with intervention was slightly better than the prediction by a Holt-Winter multiplicative method for the annual total in year 2010, the former predicting only 23 cases less than the actual reported cases. It is confirmed that classical time series techniques such as ARIMA with intervention and Holt-Winters can provide a good prediction performance for campylobacteriosis risk in New Zealand. The results reported by this study are useful to the New Zealand Health and Safety Authority's efforts in addressing the problem of the campylobacteriosis epidemic. © 2013 Blackwell Verlag GmbH.

Multiple commodities in statistical microeconomics: Model and market

NASA Astrophysics Data System (ADS)

Baaquie, Belal E.; Yu, Miao; Du, Xin

2016-11-01

A statistical generalization of microeconomics has been made in Baaquie (2013). In Baaquie et al. (2015), the market behavior of single commodities was analyzed and it was shown that market data provides strong support for the statistical microeconomic description of commodity prices. The case of multiple commodities is studied and a parsimonious generalization of the single commodity model is made for the multiple commodities case. Market data shows that the generalization can accurately model the simultaneous correlation functions of up to four commodities. To accurately model five or more commodities, further terms have to be included in the model. This study shows that the statistical microeconomics approach is a comprehensive and complete formulation of microeconomics, and which is independent to the mainstream formulation of microeconomics.

An Analysis of 19 International Case Studies of Stress Prevention Through Work Reorganization Using the Demand/Control Model

ERIC Educational Resources Information Center

Karasek, Robert A.

2004-01-01

Nineteen international case studies of workplace stress prevention initiatives are analyzed. The focus of these cases, which span a variety of workplaces and locations, is on preventing stress through work reorganization rather than remedial approaches for stress relief. It is found that the majority of the occupations represented in the case…

A Case Study of Principal Leadership in an Effective Inclusive School

ERIC Educational Resources Information Center

Hoppey, David; McLeskey, James

2013-01-01

This investigation examined the role of the principal in school change during the current era of high-stakes accountability. Qualitative methods were used to conduct a case study of one principal who had a record of success in leading school change efforts and developing a model inclusive program in his school. The results of the case study…

Case Study: Teaching Nature of Science through Scientific Models--The Geocentric vs. Heliocentric Cosmology

ERIC Educational Resources Information Center

Price, Matthew; Rogers, Michael

2016-01-01

In the nonmajor science classroom, case studies--when used as learning tools--should help students build the necessary framework to understand the nature of science. For most students, the nonmajor science course (in this case, Astronomy 101) may be the last time that they interact with science in a formal learning setting. A National Science…

Optimized model tuning in medical systems.

PubMed

Kléma, Jirí; Kubalík, Jirí; Lhotská, Lenka

2005-12-01

In medical systems it is often advantageous to utilize specific problem situations (cases) in addition to or instead of a general model. Decisions are then based on relevant past cases retrieved from a case memory. The reliability of such decisions depends directly on the ability to identify cases of practical relevance to the current situation. This paper discusses issues of automated tuning in order to obtain a proper definition of mutual case similarity in a specific medical domain. The main focus is on a reasonably time-consuming optimization of the parameters that determine case retrieval and further utilization in decision making/ prediction. The two case studies - mortality prediction after cardiological intervention, and resource allocation at a spa - document that the optimization process is influenced by various characteristics of the problem domain.

Using radiative transfer models to study the atmospheric water vapor content and to eliminate telluric lines from high-resolution optical spectra

NASA Astrophysics Data System (ADS)

Gardini, A.; Maíz Apellániz, J.; Pérez, E.; Quesada, J. A.; Funke, B.

2013-05-01

The Radiative Transfer Model (RTM) and the retrieval algorithm, incorporated in the SCIATRAN 2.2 software package developed at the Institute of Remote Sensing/Institute of Enviromental Physics of Bremen University (Germany), allows to simulate, among other things, radiance/irradiance spectra in the 2400--24 000 Å range. In this work we present applications of RTM to two case studies. In the first case the RTM was used to simulate direct solar irradiance spectra, with different water vapor amounts, for the study of the water vapor content in the atmosphere above Sierra Nevada Observatory. Simulated spectra were compared with those measured with a spectrometer operating in the 8000--10 000 Å range. In the second case the RTM was used to generate telluric model spectra to subtract the atmospheric contribution and correct high-resolution stellar spectra from atmospheric water vapor and oxygen lines. The results of both studies are discussed.

The short-term effects of air pollutants on respiratory disease mortality in Wuhan, China: comparison of time-series and case-crossover analyses.

PubMed

Ren, Meng; Li, Na; Wang, Zhan; Liu, Yisi; Chen, Xi; Chu, Yuanyuan; Li, Xiangyu; Zhu, Zhongmin; Tian, Liqiao; Xiang, Hao

2017-01-13

Few studies have compared different methods when exploring the short-term effects of air pollutants on respiratory disease mortality in Wuhan, China. This study assesses the association between air pollutants and respiratory disease mortality with both time-series and time-stratified-case-crossover designs. The generalized additive model (GAM) and the conditional logistic regression model were used to assess the short-term effects of air pollutants on respiratory disease mortality. Stratified analyses were performed by age, sex, and diseases. A 10 μg/m 3 increment in SO 2 level was associated with an increase in relative risk for all respiratory disease mortality of 2.4% and 1.9% in the case-crossover and time-series analyses in single pollutant models, respectively. Strong evidence of an association between NO 2 and daily respiratory disease mortality among men or people older than 65 years was found in the case-crossover study. There was a positive association between air pollutants and respiratory disease mortality in Wuhan, China. Both time-series and case-crossover analyses consistently reveal the association between three air pollutants and respiratory disease mortality. The estimates of association between air pollution and respiratory disease mortality from the case-crossover analysis displayed greater variation than that from the time-series analysis.

The short-term effects of air pollutants on respiratory disease mortality in Wuhan, China: comparison of time-series and case-crossover analyses

NASA Astrophysics Data System (ADS)

Ren, Meng; Li, Na; Wang, Zhan; Liu, Yisi; Chen, Xi; Chu, Yuanyuan; Li, Xiangyu; Zhu, Zhongmin; Tian, Liqiao; Xiang, Hao

2017-01-01

Few studies have compared different methods when exploring the short-term effects of air pollutants on respiratory disease mortality in Wuhan, China. This study assesses the association between air pollutants and respiratory disease mortality with both time-series and time-stratified-case-crossover designs. The generalized additive model (GAM) and the conditional logistic regression model were used to assess the short-term effects of air pollutants on respiratory disease mortality. Stratified analyses were performed by age, sex, and diseases. A 10 μg/m3 increment in SO2 level was associated with an increase in relative risk for all respiratory disease mortality of 2.4% and 1.9% in the case-crossover and time-series analyses in single pollutant models, respectively. Strong evidence of an association between NO2 and daily respiratory disease mortality among men or people older than 65 years was found in the case-crossover study. There was a positive association between air pollutants and respiratory disease mortality in Wuhan, China. Both time-series and case-crossover analyses consistently reveal the association between three air pollutants and respiratory disease mortality. The estimates of association between air pollution and respiratory disease mortality from the case-crossover analysis displayed greater variation than that from the time-series analysis.

Ethics: A Bridge for Studying the Social Contexts of Professional Communication.

ERIC Educational Resources Information Center

Speck, Bruce W.

1989-01-01

Describes a method for helping students evaluate ethical issues in a systematic way, based on Lawrence Kohlberg's stages of moral development. Recommends the case-study approach for creating social constructs in which students face ethical dilemmas, and outlines a case-study ethics unit using Kohlberg's model. (MM)

On the importance of methods in hydrological modelling. Perspectives from a case study

NASA Astrophysics Data System (ADS)

Fenicia, Fabrizio; Kavetski, Dmitri

2017-04-01

The hydrological community generally appreciates that developing any non-trivial hydrological model requires a multitude of modelling choices. These choices may range from a (seemingly) straightforward application of mass conservation, to the (often) guesswork-like selection of constitutive functions, parameter values, etc. The application of a model itself requires a myriad of methodological choices - the selection of numerical solvers, objective functions for model calibration, validation approaches, performance metrics, etc. Not unreasonably, hydrologists embarking on ever ambitious projects prioritize hydrological insight over the morass of methodological choices. Perhaps to emphasize "ideas" over "methods", some journals have even reduced the fontsize of the methodology sections of its articles. However, the very nature of modelling is that seemingly routine methodological choices can significantly affect the conclusions of case studies and investigations - making it dangerous to skimp over methodological details in an enthusiastic rush towards the next great hydrological idea. This talk shares modelling insights from a hydrological study of a 300 km2 catchment in Luxembourg, where the diversity of hydrograph dynamics observed at 10 locations begs the question of whether external forcings or internal catchment properties act as dominant controls on streamflow generation. The hydrological insights are fascinating (at least to us), but in this talk we emphasize the impact of modelling methodology on case study conclusions and recommendations. How did we construct our prior set of hydrological model hypotheses? What numerical solver was implemented and why was an objective function based on Bayesian theory deployed? And what would have happened had we omitted model cross-validation, or not used a systematic hypothesis testing approach?

Project Photofly: New 3d Modeling Online Web Service (case Studies and Assessments)

NASA Astrophysics Data System (ADS)

Abate, D.; Furini, G.; Migliori, S.; Pierattini, S.

2011-09-01

During summer 2010, Autodesk has released a still ongoing project called Project Photofly, freely downloadable from AutodeskLab web site until August 1 2011. Project Photofly based on computer-vision and photogrammetric principles, exploiting the power of cloud computing, is a web service able to convert collections of photographs into 3D models. Aim of our research was to evaluate the Project Photofly, through different case studies, for 3D modeling of cultural heritage monuments and objects, mostly to identify for which goals and objects it is suitable. The automatic approach will be mainly analyzed.

SAM International Case Studies: DPV Analysis in Mexico

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

McCall, James D

Presentation demonstrates the use of the System Advisor Model (SAM) in international analyses, specifically Mexico. Two analyses are discussed with relation to SAM modelling efforts: 1) Customer impacts from changes to net metering and billing agreements and 2) Potential benefits of PV for Mexican solar customers, the Mexican Treasury, and the environment. Along with the SAM analyses, integration of the International Utility Rate Database (I-URDB) with SAM and future international SAM work are discussed. Presentation was created for the International Solar Energy Society's (ISES) webinar titled 'International use of the NREL System Advisor Model (SAM) with case studies'.

Model-free methods to study membrane environmental probes: a comparison of the spectral phasor and generalized polarization approaches

PubMed Central

Malacrida, Leonel; Gratton, Enrico; Jameson, David M

2016-01-01

In this note, we present a discussion of the advantages and scope of model-free analysis methods applied to the popular solvatochromic probe LAURDAN, which is widely used as an environmental probe to study dynamics and structure in membranes. In particular, we compare and contrast the generalized polarization approach with the spectral phasor approach. To illustrate our points we utilize several model membrane systems containing pure lipid phases and, in some cases, cholesterol or surfactants. We demonstrate that the spectral phasor method offers definitive advantages in the case of complex systems. PMID:27182438

Redesigning models of patient care delivery and organisation: building collegial generosity in response to workplace challenges.

PubMed

Chiarella, E Mary

2007-04-01

This case study describes the New South Wales Nursing and Midwifery Office (NaMO) Models of Care Project, a project designed to identify, encourage and disseminate innovations in nursing care organisation and delivery. The project is a 4-year action research project, using a range of interactive engagements including workshops, seminars, questionnaires and websites to achieve the goals. This case study briefly describes the main stimuli for review and redesign of models of care identified through analysis of the clinicians' presentations, and explores the range of responses to the workplace challenges.

A case study of cost-efficient staffing under annualized hours.

PubMed

van der Veen, Egbert; Hans, Erwin W; Veltman, Bart; Berrevoets, Leo M; Berden, Hubert J J M

2015-09-01

We propose a mathematical programming formulation that incorporates annualized hours and shows to be very flexible with regard to modeling various contract types. The objective of our model is to minimize salary cost, thereby covering workforce demand, and using annualized hours. Our model is able to address various business questions regarding tactical workforce planning problems, e.g., with regard to annualized hours, subcontracting, and vacation planning. In a case study for a Dutch hospital two of these business questions are addressed, and we demonstrate that applying annualized hours potentially saves up to 5.2% in personnel wages annually.

Empirical validation of an agent-based model of wood markets in Switzerland

PubMed Central

Hilty, Lorenz M.; Lemm, Renato; Thees, Oliver

2018-01-01

We present an agent-based model of wood markets and show our efforts to validate this model using empirical data from different sources, including interviews, workshops, experiments, and official statistics. Own surveys closed gaps where data was not available. Our approach to model validation used a variety of techniques, including the replication of historical production amounts, prices, and survey results, as well as a historical case study of a large sawmill entering the market and becoming insolvent only a few years later. Validating the model using this case provided additional insights, showing how the model can be used to simulate scenarios of resource availability and resource allocation. We conclude that the outcome of the rigorous validation qualifies the model to simulate scenarios concerning resource availability and allocation in our study region. PMID:29351300

Diagnosis of Insidious Data Disasters

NASA Astrophysics Data System (ADS)

Lundquist, J. D.; Wayand, N. E.; Massmann, A.; Clark, M. P.; Lott, F.; Cristea, N. C.

2014-12-01

Measurements and modeling have gone hand-in-hand since hydrology began as a science. In most early work, the same person took the measurements and developed the model, and iterated between them until all information collectively made sense. Over time, research has become more specialized, and now many people use a model developed by someone else, compare model simulations to data collected by another someone else, pronounce success and proceed with research if the two match, and face a black hole of uncertainty if they don't match. In many cases, the model is calibrated to achieve a match. In perhaps many more cases, the work is shelved; the apparent failure swept under the rug. We present two case studies of apparent modeling failure, wherein all efforts at model calibration failed, where traditional data quality-control measures detected no problems, and where only extreme stubbornness and repetitive iteration between modeling and observations led to discovery of the root of the problem. These two cases are by no means a complete sampling of data disasters that have occurred, or that may occur in the future, and are probably more likely to be outliers that will [hopefully] never occur again. The point is to exemplify that such odd cases do occur, and that while the specific-oddity varies widely, odd cases are likely much more common than we are aware of. To quote from Arthur Conan Doyle's Sherlock Holmes: "when you have eliminated the impossible, whatever remains, however improbable, must be the truth." The first case presents an issue with the water balance in the snow-fed Tuolumne River, Sierra Nevada, California, combined with modeling using the Distributed Hydrology Soil Vegetation Model (DHSVM, Wigmosta et al. 1994), and the second case presents an issue with the energy balance at Snoqualmie Pass, Washington, combined with modeling using the Structure for Understanding Multiple Modeling Alternatives (SUMMA, Clark et al., submitted). The figure presents the fundamental problems: In the Tuolumne (case 1), streamflow in one year was off by a factor of two; at Snoqualmie (case 2), nighttime surface temperatures were biased by about 10°C. The reasons for and solutions to these problems will be presented, and they're not what you might guess first.

A Disability Studies Framework for Policy Activism in Postsecondary Education

ERIC Educational Resources Information Center

Gabel, Susan L.

2010-01-01

This article uses disability studies and the social model of disability as theoretical foundations for policy activism in postsecondary education. The social model is discussed and a model for policy activism is described. A case study of how disability studies and policy activism can be applied is provided utilizing the "3C Project to Provide…

a Study of the Reconstruction of Accidents and Crime Scenes Through Computational Experiments

NASA Astrophysics Data System (ADS)

Park, S. J.; Chae, S. W.; Kim, S. H.; Yang, K. M.; Chung, H. S.

Recently, with an increase in the number of studies of the safety of both pedestrians and passengers, computer software, such as MADYMO, Pam-crash, and LS-dyna, has been providing human models for computer simulation. Although such programs have been applied to make machines beneficial for humans, studies that analyze the reconstruction of accidents or crime scenes are rare. Therefore, through computational experiments, the present study presents reconstructions of two questionable accidents. In the first case, a car fell off the road and the driver was separated from it. The accident investigator was very confused because some circumstantial evidence suggested the possibility that the driver was murdered. In the second case, a woman died in her house and the police suspected foul play with her boyfriend as a suspect. These two cases were reconstructed using the human model in MADYMO software. The first case was eventually confirmed as a traffic accident in which the driver bounced out of the car when the car fell off, and the second case was proved to be suicide rather than homicide.

How to include the variability of TMS responses in simulations: a speech mapping case study

NASA Astrophysics Data System (ADS)

De Geeter, N.; Lioumis, P.; Laakso, A.; Crevecoeur, G.; Dupré, L.

2016-11-01

When delivered over a specific cortical site, TMS can temporarily disrupt the ongoing process in that area. This allows mapping of speech-related areas for preoperative evaluation purposes. We numerically explore the observed variability of TMS responses during a speech mapping experiment performed with a neuronavigation system. We selected four cases with very small perturbations in coil position and orientation. In one case (E) a naming error occurred, while in the other cases (NEA, B, C) the subject appointed the images as smoothly as without TMS. A realistic anisotropic head model was constructed of the subject from T1-weighted and diffusion-weighted MRI. The induced electric field distributions were computed, associated to the coil parameters retrieved from the neuronavigation system. Finally, the membrane potentials along relevant white matter fibre tracts, extracted from DTI-based tractography, were computed using a compartmental cable equation. While only minor differences could be noticed between the induced electric field distributions of the four cases, computing the corresponding membrane potentials revealed different subsets of tracts were activated. A single tract was activated for all coil positions. Another tract was only triggered for case E. NEA induced action potentials in 13 tracts, while NEB stimulated 11 tracts and NEC one. The calculated results are certainly sensitive to the coil specifications, demonstrating the observed variability in this study. However, even though a tract connecting Broca’s with Wernicke’s area is only triggered for the error case, further research is needed on other study cases and on refining the neural model with synapses and network connections. Case- and subject-specific modelling that includes both electromagnetic fields and neuronal activity enables demonstration of the variability in TMS experiments and can capture the interaction with complex neural networks.

Integration of the predictions of two models with dose measurements in a case study of children exposed to the emissions of a lead smelter

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

Bonnard, R.; McKone, T.E.

2009-03-01

The predictions of two source-to-dose models are systematically evaluated with observed data collected in a village polluted by a currently operating secondary lead smelter. Both models were built up from several sub-models linked together and run using Monte-Carlo simulation, to calculate the distribution children's blood lead levels attributable to the emissions from the facility. The first model system is composed of the CalTOX model linked to a recoded version of the IEUBK model. This system provides the distribution of the media-specific lead concentrations (air, soil, fruit, vegetables and blood) in the whole area investigated. The second model consists of amore » statistical model to estimate the lead deposition on the ground, a modified version of the model HHRAP and the same recoded version of the IEUBK model. This system provides an estimate of the concentration of exposure of specific individuals living in the study area. The predictions of the first model system were improved in terms of accuracy and precision by performing a sensitivity analysis and using field data to correct the default value provided for the leaf wet density. However, in this case study, the first model system tends to overestimate the exposure due to exposed vegetables. The second model was tested for nine children with contrasting exposure conditions. It managed to capture the blood levels for eight of them. In the last case, the exposure of the child by pathways not considered in the model may explain the failure of the model. The interest of this integrated model is to provide outputs with lower variance than the first model system, but at the moment further tests are necessary to conclude about its accuracy.« less

Case studies of seasonal rainfall forecasts for Hong Kong and its vicinity using a regional climate model

Treesearch

David Hui; Karen Shum; Ji Chen; Shyh-Chin Chen; Jack Ritchie; John Roads

2007-01-01

Seasonal climate forecasts are one of the most promising tools for providing early warnings for natural hazards such as floods and droughts. Using two case studies, this paper documents the skill of a regional climate model in the seasonal forecasting of below normal rainfall in southern China during the rainy seasons of July–August–September 2003 and April–...

Learning to Construct Meaning from Text: A Case Study of the Relationship between a Tutor and an English Learner within a Response to Intervention Setting

ERIC Educational Resources Information Center

Jaeger, Elizabeth L.

2015-01-01

This case study describes the ways in which Sam, an English learner with weak comprehension, grew as a reader, student, and friend during his fourth grade year. Using the Interactive Model of Reading (Dis)ability and the RAND model of comprehension as a frame, Sam's experience in a Tier 2/3 tutorial program is examined. Over time, Sam (1) engaged…

Improving rational thermal comfort prediction by using subpopulation characteristics: A case study at Hermitage Amsterdam

PubMed Central

Kramer, Rick; Schellen, Lisje; Schellen, Henk; Kingma, Boris

2017-01-01

ABSTRACT This study aims to improve the prediction accuracy of the rational standard thermal comfort model, known as the Predicted Mean Vote (PMV) model, by (1) calibrating one of its input variables “metabolic rate,” and (2) extending it by explicitly incorporating the variable running mean outdoor temperature (RMOT) that relates to adaptive thermal comfort. The analysis was performed with survey data (n = 1121) and climate measurements of the indoor and outdoor environment from a one year-long case study undertaken at Hermitage Amsterdam museum in the Netherlands. The PMVs were calculated for 35 survey days using (1) an a priori assumed metabolic rate, (2) a calibrated metabolic rate found by fitting the PMVs to the thermal sensation votes (TSVs) of each respondent using an optimization routine, and (3) extending the PMV model by including the RMOT. The results show that the calibrated metabolic rate is estimated to be 1.5 Met for this case study that was predominantly visited by elderly females. However, significant differences in metabolic rates have been revealed between adults and elderly showing the importance of differentiating between subpopulations. Hence, the standard tabular values, which only differentiate between various activities, may be oversimplified for many cases. Moreover, extending the PMV model with the RMOT substantially improves the thermal sensation prediction, but thermal sensation toward extreme cool and warm sensations remains partly underestimated. PMID:28680934

Improving rational thermal comfort prediction by using subpopulation characteristics: A case study at Hermitage Amsterdam.

PubMed

Kramer, Rick; Schellen, Lisje; Schellen, Henk; Kingma, Boris

2017-01-01

This study aims to improve the prediction accuracy of the rational standard thermal comfort model, known as the Predicted Mean Vote (PMV) model, by (1) calibrating one of its input variables "metabolic rate," and (2) extending it by explicitly incorporating the variable running mean outdoor temperature (RMOT) that relates to adaptive thermal comfort. The analysis was performed with survey data ( n = 1121) and climate measurements of the indoor and outdoor environment from a one year-long case study undertaken at Hermitage Amsterdam museum in the Netherlands. The PMVs were calculated for 35 survey days using (1) an a priori assumed metabolic rate, (2) a calibrated metabolic rate found by fitting the PMVs to the thermal sensation votes (TSVs) of each respondent using an optimization routine, and (3) extending the PMV model by including the RMOT. The results show that the calibrated metabolic rate is estimated to be 1.5 Met for this case study that was predominantly visited by elderly females. However, significant differences in metabolic rates have been revealed between adults and elderly showing the importance of differentiating between subpopulations. Hence, the standard tabular values, which only differentiate between various activities, may be oversimplified for many cases. Moreover, extending the PMV model with the RMOT substantially improves the thermal sensation prediction, but thermal sensation toward extreme cool and warm sensations remains partly underestimated.

Signal detection of adverse events with imperfect confirmation rates in vaccine safety studies using self-controlled case series design.

PubMed

Xu, Stanley; Newcomer, Sophia; Nelson, Jennifer; Qian, Lei; McClure, David; Pan, Yi; Zeng, Chan; Glanz, Jason

2014-05-01

The Vaccine Safety Datalink project captures electronic health record data including vaccinations and medically attended adverse events on 8.8 million enrollees annually from participating managed care organizations in the United States. While the automated vaccination data are generally of high quality, a presumptive adverse event based on diagnosis codes in automated health care data may not be true (misclassification). Consequently, analyses using automated health care data can generate false positive results, where an association between the vaccine and outcome is incorrectly identified, as well as false negative findings, where a true association or signal is missed. We developed novel conditional Poisson regression models and fixed effects models that accommodate misclassification of adverse event outcome for self-controlled case series design. We conducted simulation studies to evaluate their performance in signal detection in vaccine safety hypotheses generating (screening) studies. We also reanalyzed four previously identified signals in a recent vaccine safety study using the newly proposed models. Our simulation studies demonstrated that (i) outcome misclassification resulted in both false positive and false negative signals in screening studies; (ii) the newly proposed models reduced both the rates of false positive and false negative signals. In reanalyses of four previously identified signals using the novel statistical models, the incidence rate ratio estimates and statistical significances were similar to those using conventional models and including only medical record review confirmed cases. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The CAST Initiative in Guam: A Model of Effective Teachers Teaching Teachers

ERIC Educational Resources Information Center

Zuercher, Deborah K.; Kessler, Cristy; Yoshioka, Jon

2011-01-01

The CAST (content area specialized training) model of professional development enables sustainable teacher leadership and is responsive to the need for culturally relevant educational practices. The purpose of this paper is to share the background, methods, findings and recommendations of a case study on the CAST initiative in Guam. The case study…

Catholic School Faculty Meetings: A Case Study Linking Catholic Identity, School Improvement, and Teacher Engagement

ERIC Educational Resources Information Center

Hagan, Daryl C.; Houchens, Gary

2016-01-01

While research on faculty meetings is limited, existing literature suggests that meetings could be an arena where schools can address their most pressing challenges (Brandenburg, 2008; Michel, 2011; Riehl, 1998). Building on Macey and Schneider's (2008) Model of Employee Engagement and McGrath's Model of Group Effectiveness (1964), this case study…

Three-Level Analysis of Single-Case Experimental Data: Empirical Validation

ERIC Educational Resources Information Center

Moeyaert, Mariola; Ugille, Maaike; Ferron, John M.; Beretvas, S. Natasha; Van den Noortgate, Wim

2014-01-01

One approach for combining single-case data involves use of multilevel modeling. In this article, the authors use a Monte Carlo simulation study to inform applied researchers under which realistic conditions the three-level model is appropriate. The authors vary the value of the immediate treatment effect and the treatment's effect on the time…

Productivity of "Collisions Generate Heat" for Reconciling an Energy Model with Mechanistic Reasoning: A Case Study

ERIC Educational Resources Information Center

Scherr, Rachel E.; Robertson, Amy D.

2015-01-01

We observe teachers in professional development courses about energy constructing mechanistic accounts of energy transformations. We analyze a case in which teachers investigating adiabatic compression develop a model of the transformation of kinetic energy to thermal energy. Among their ideas is the idea that thermal energy is generated as a…

The influence of tie strength on evolutionary games on networks: An empirical investigation

NASA Astrophysics Data System (ADS)

Buesser, Pierre; Peña, Jorge; Pestelacci, Enea; Tomassini, Marco

2011-11-01

Extending previous work on unweighted networks, we present here a systematic numerical investigation of standard evolutionary games on weighted networks. In the absence of any reliable model for generating weighted social networks, we attribute weights to links in a few ways supported by empirical data ranging from totally uncorrelated to weighted bipartite networks. The results of the extensive simulation work on standard complex network models show that, except in a case that does not seem to be common in social networks, taking the tie strength into account does not change in a radical manner the long-run steady-state behavior of the studied games. Besides model networks, we also included a real-life case drawn from a coauthorship network. In this case also, taking the weights into account only changes the results slightly with respect to the raw unweighted graph, although to draw more reliable conclusions on real social networks many more cases should be studied as these weighted networks become available.

On the pursuit of a nuclear development capability: The case of the Cuban nuclear program

NASA Astrophysics Data System (ADS)

Benjamin-Alvarado, Jonathan Calvert

1998-09-01

While there have been many excellent descriptive accounts of modernization schemes in developing states, energy development studies based on prevalent modernization theory have been rare. Moreover, heretofore there have been very few analyses of efforts to develop a nuclear energy capability by developing states. Rarely have these analyses employed social science research methodologies. The purpose of this study was to develop a general analytical framework, based on such a methodology to analyze nuclear energy development and to utilize this framework for the study of the specific case of Cuba's decision to develop nuclear energy. The analytical framework developed focuses on a qualitative tracing of the process of Cuban policy objectives and implementation to develop a nuclear energy capability, and analyzes the policy in response to three models of modernization offered to explain the trajectory of policy development. These different approaches are the politically motivated modernization model, the economic and technological modernization model and the economic and energy security model. Each model provides distinct and functionally differentiated expectations for the path of development toward this objective. Each model provides expected behaviors to external stimuli that would result in specific policy responses. In the study, Cuba's nuclear policy responses to stimuli from domestic constraints and intensities, institutional development, and external influences are analyzed. The analysis revealed that in pursuing the nuclear energy capability, Cuba primarily responded by filtering most of the stimuli through the twin objectives of economic rationality and technological advancement. Based upon the Cuban policy responses to the domestic and international stimuli, the study concluded that the economic and technological modernization model of nuclear energy development offered a more complete explanation of the trajectory of policy development than either the politically-motivated or economic and energy security models. The findings of this case pose some interesting questions for the general study of energy programs in developing states. By applying the analytical framework employed in this study to a number of other cases, perhaps the understanding of energy development schemes may be expanded through future research.

The cost and management of different types of clinical mastitis in dairy cows estimated by dynamic programming.

PubMed

Cha, E; Bar, D; Hertl, J A; Tauer, L W; Bennett, G; González, R N; Schukken, Y H; Welcome, F L; Gröhn, Y T

2011-09-01

The objective of this study was to estimate the cost of 3 different types of clinical mastitis (CM) (caused by gram-positive bacteria, gram-negative bacteria, and other organisms) at the individual cow level and thereby identify the economically optimal management decision for each type of mastitis. We made modifications to an existing dynamic optimization and simulation model, studying the effects of various factors (incidence of CM, milk loss, pregnancy rate, and treatment cost) on the cost of different types of CM. The average costs per case (US$) of gram-positive, gram-negative, and other CM were $133.73, $211.03, and $95.31, respectively. This model provided a more informed decision-making process in CM management for optimal economic profitability and determined that 93.1% of gram-positive CM cases, 93.1% of gram-negative CM cases, and 94.6% of other CM cases should be treated. The main contributor to the total cost per case was treatment cost for gram-positive CM (51.5% of the total cost per case), milk loss for gram-negative CM (72.4%), and treatment cost for other CM (49.2%). The model affords versatility as it allows for parameters such as production costs, economic values, and disease frequencies to be altered. Therefore, cost estimates are the direct outcome of the farm-specific parameters entered into the model. Thus, this model can provide farmers economically optimal guidelines specific to their individual cows suffering from different types of CM. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Geothermal Case Studies

DOE Data Explorer

Young, Katherine

2014-09-30

database.) In fiscal year 2015, NREL is working with universities to populate additional case studies on OpenEI. The goal is to provide a large enough dataset to start conducting analyses of exploration programs to identify correlations between successful exploration plans for areas with similar geologic occurrence models.

Using causal loop diagrams for the initialization of stakeholder engagement in soil salinity management in agricultural watersheds in developing countries: a case study in the Rechna Doab watershed, Pakistan.

PubMed

Inam, Azhar; Adamowski, Jan; Halbe, Johannes; Prasher, Shiv

2015-04-01

Over the course of the last twenty years, participatory modeling has increasingly been advocated as an integral component of integrated, adaptive, and collaborative water resources management. However, issues of high cost, time, and expertise are significant hurdles to the widespread adoption of participatory modeling in many developing countries. In this study, a step-wise method to initialize the involvement of key stakeholders in the development of qualitative system dynamics models (i.e. causal loop diagrams) is presented. The proposed approach is designed to overcome the challenges of low expertise, time and financial resources that have hampered previous participatory modeling efforts in developing countries. The methodological framework was applied in a case study of soil salinity management in the Rechna Doab region of Pakistan, with a focus on the application of qualitative modeling through stakeholder-built causal loop diagrams to address soil salinity problems in the basin. Individual causal loop diagrams were developed by key stakeholder groups, following which an overall group causal loop diagram of the entire system was built based on the individual causal loop diagrams to form a holistic qualitative model of the whole system. The case study demonstrates the usefulness of the proposed approach, based on using causal loop diagrams in initiating stakeholder involvement in the participatory model building process. In addition, the results point to social-economic aspects of soil salinity that have not been considered by other modeling studies to date. Copyright © 2015 Elsevier Ltd. All rights reserved.

[Study on the ARIMA model application to predict echinococcosis cases in China].

PubMed

En-Li, Tan; Zheng-Feng, Wang; Wen-Ce, Zhou; Shi-Zhu, Li; Yan, Lu; Lin, Ai; Yu-Chun, Cai; Xue-Jiao, Teng; Shun-Xian, Zhang; Zhi-Sheng, Dang; Chun-Li, Yang; Jia-Xu, Chen; Wei, Hu; Xiao-Nong, Zhou; Li-Guang, Tian

2018-02-26

To predict the monthly reported echinococcosis cases in China with the autoregressive integrated moving average (ARIMA) model, so as to provide a reference for prevention and control of echinococcosis. SPSS 24.0 software was used to construct the ARIMA models based on the monthly reported echinococcosis cases of time series from 2007 to 2015 and 2007 to 2014, respectively, and the accuracies of the two ARIMA models were compared. The model based on the data of the monthly reported cases of echinococcosis in China from 2007 to 2015 was ARIMA (1, 0, 0) (1, 1, 0) 12 , the relative error among reported cases and predicted cases was -13.97%, AR (1) = 0.367 ( t = 3.816, P < 0.001), SAR (1) = -0.328 ( t = -3.361, P = 0.001), and Ljung-Box Q = 14.119 ( df = 16, P = 0.590) . The model based on the data of the monthly reported cases of echinococcosis in China from 2007 to 2014 was ARIMA (1, 0, 0) (1, 0, 1) 12 , the relative error among reported cases and predicted cases was 0.56%, AR (1) = 0.413 ( t = 4.244, P < 0.001), SAR (1) = 0.809 ( t = 9.584, P < 0.001), SMA (1) = 0.356 ( t = 2.278, P = 0.025), and Ljung-Box Q = 18.924 ( df = 15, P = 0.217). The different time series may have different ARIMA models as for the same infectious diseases. It is needed to be further verified that the more data are accumulated, the shorter time of predication is, and the smaller the average of the relative error is. The establishment and prediction of an ARIMA model is a dynamic process that needs to be adjusted and optimized continuously according to the accumulated data, meantime, we should give full consideration to the intensity of the work related to infectious diseases reported (such as disease census and special investigation).

External Validation of a Case-Mix Adjustment Model for the Standardized Reporting of 30-Day Stroke Mortality Rates in China.

PubMed

Yu, Ping; Pan, Yuesong; Wang, Yongjun; Wang, Xianwei; Liu, Liping; Ji, Ruijun; Meng, Xia; Jing, Jing; Tong, Xu; Guo, Li; Wang, Yilong

2016-01-01

A case-mix adjustment model has been developed and externally validated, demonstrating promise. However, the model has not been thoroughly tested among populations in China. In our study, we evaluated the performance of the model in Chinese patients with acute stroke. The case-mix adjustment model A includes items on age, presence of atrial fibrillation on admission, National Institutes of Health Stroke Severity Scale (NIHSS) score on admission, and stroke type. Model B is similar to Model A but includes only the consciousness component of the NIHSS score. Both model A and B were evaluated to predict 30-day mortality rates in 13,948 patients with acute stroke from the China National Stroke Registry. The discrimination of the models was quantified by c-statistic. Calibration was assessed using Pearson's correlation coefficient. The c-statistic of model A in our external validation cohort was 0.80 (95% confidence interval, 0.79-0.82), and the c-statistic of model B was 0.82 (95% confidence interval, 0.81-0.84). Excellent calibration was reported in the two models with Pearson's correlation coefficient (0.892 for model A, p<0.001; 0.927 for model B, p = 0.008). The case-mix adjustment model could be used to effectively predict 30-day mortality rates in Chinese patients with acute stroke.

Modelling the influence of climate on malaria occurrence in Chimoio Municipality, Mozambique.

PubMed

Ferrão, João Luís; Mendes, Jorge M; Painho, Marco

2017-05-25

Mozambique was recently ranked fifth in the African continent for the number of cases of malaria. In Chimoio municipality cases of malaria are increasing annually, contrary to the decreasing trend in Africa. As malaria transmission is influenced to a large extent by climatic conditions, modelling this relationship can provide useful insights for designing precision health measures for malaria control. There is a scarcity of information on the association between climatic variability and malaria transmission risk in Mozambique in general, and in Chimoio in particular. Therefore, the aim of this study is to model the association between climatic variables and malaria cases on a weekly basis, to help policy makers find adequate measures for malaria control and eradication. Time series analysis was conducted using data on weekly climatic variables and weekly malaria cases (counts) in Chimoio municipality, from 2006 to 2014. All data were analysed using SPSS-20, R 3.3.2 and BioEstat 5.0. Cross-correlation analysis, linear processes, namely ARIMA models and regression modelling, were used to develop the final model. Between 2006 and 2014, 490,561 cases of malaria were recorded in Chimoio. Both malaria and climatic data exhibit weekly and yearly systematic fluctuations. Cross-correlation analysis showed that mean temperature and precipitation present significantly lagged correlations with malaria cases. An ARIMA model (2,1,0) (2,1,1) 52 , and a regression model for a Box-Cox transformed number of malaria cases with lags 1, 2 and 3 of weekly malaria cases and lags 6 and 7 of weekly mean temperature and lags 12 of precipitation were fitted. Although, both produced similar widths for prediction intervals, the last was able to anticipate malaria outbreak more accurately. The Chimoio climate seems ideal for malaria occurrence. Malaria occurrence peaks during January to March in Chimoio. As the lag effect between climatic events and malaria occurrence is important for the prediction of malaria cases, this can be used for designing public precision health measures. The model can be used for planning specific measures for Chimoio municipality. Prospective and multidisciplinary research involving researchers from different fields is welcomed to improve the effect of climatic factors and other factors in malaria cases.

Improving the FLORIS wind plant model for compatibility with gradient-based optimization

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

Thomas, Jared J.; Gebraad, Pieter MO; Ning, Andrew

The FLORIS (FLOw Redirection and Induction in Steady-state) model, a parametric wind turbine wake model that predicts steady-state wake characteristics based on wind turbine position and yaw angle, was developed for optimization of control settings and turbine locations. This article provides details on changes made to the FLORIS model to make the model more suitable for gradient-based optimization. Changes to the FLORIS model were made to remove discontinuities and add curvature to regions of non-physical zero gradient. Exact gradients for the FLORIS model were obtained using algorithmic differentiation. A set of three case studies demonstrate that using exact gradients withmore » gradient-based optimization reduces the number of function calls by several orders of magnitude. The case studies also show that adding curvature improves convergence behavior, allowing gradient-based optimization algorithms used with the FLORIS model to more reliably find better solutions to wind farm optimization problems.« less

The Role of Integrated Modelling and Assessment for Decision-Making: Lessons from Water Allocation Issues in Australia

NASA Astrophysics Data System (ADS)

Jakeman, A. J.; Guillaume, J. H. A.; El Sawah, S.; Hamilton, S.

2014-12-01

Integrated modelling and assessment (IMA) is best regarded as a process that can support environmental decision-making when issues are strongly contested and uncertainties pervasive. To be most useful, the process must be multi-dimensional and phased. Principally, it must be tailored to the problem context to encompass diverse issues of concern, management settings and stakeholders. This in turn requires the integration of multiple processes and components of natural and human systems and their corresponding spatial and temporal scales. Modellers therefore need to be able to integrate multiple disciplines, methods, models, tools and data, and many sources and types of uncertainty. These dimensions are incorporated into iteration between the various phases of the IMA process, including scoping, problem framing and formulation, assessing options and communicating findings. Two case studies in Australia are employed to share the lessons of how integration can be achieved in these IMA phases using a mix of stakeholder participation processes and modelling tools. One case study aims to improve the relevance of modelling by incorporating stakeholder's views of irrigated viticulture and water management decision making. It used a novel methodology with the acronym ICTAM, consisting of Interviews to elicit mental models, Cognitive maps to represent and analyse individual and group mental models, Time-sequence diagrams to chronologically structure the decision making process, an All-encompassing conceptual model, and computational Models of stakeholder decision making. The second case uses a hydro-economic river network model to examine basin-wide impacts of water allocation cuts and adoption of farm innovations. The knowledge exchange approach used in each case was designed to integrate data and knowledge bearing in mind the contextual dimensions of the problem at hand, and the specific contributions that environmental modelling was thought to be able to make.

Study of conformally flat polytropes with tilted congruence

NASA Astrophysics Data System (ADS)

Sharif, M.; Sadiq, Sobia

This paper is aimed to study the modeling of spherically symmetric spacetime in the presence of anisotropic dissipative fluid configuration. This is accomplished for an observer moving relative to matter content using two cases of polytropic equation-of-state under conformally flat condition. We formulate the corresponding generalized Tolman-Oppenheimer-Volkoff equation, mass equation, as well as energy conditions for both cases. The conformally flat condition is imposed to find an expression for anisotropy which helps to study spherically symmetric polytropes. Finally, Tolman mass is used to analyze stability of the resulting models.

Unsolved homicides in Sweden: A population-based study of 264 homicides.

PubMed

Sturup, Joakim; Karlberg, Daniel; Kristiansson, Marianne

2015-12-01

The clearance rates for homicides have decreased internationally. This retrospective population-based study of all Swedish homicide incidents between 2007 and 2009 (n=264) aims to investigate factors associated with solvability in homicides. Victims were identified in an autopsy registry and offenders in a criminal-conviction registry. Autopsy reports, police files, court verdicts and criminal records were systematically collected and linked. The clearance rate was 86.4% (n=228), and almost three quarters of cases (71.9%) were solved within the first week. Nine factors were significantly associated with the case status; however, only four factors remained significant in the multivariate logistic-regression model. Cases were more likely to be solved if there was an eyewitness and if the victim was intoxicated with alcohol. Moreover, cases were less likely to be solved if the victim had a criminal record in the past five years and was killed by a firearm. In the final model, a Cox proportional-hazards model, where time to arrest was taken into account, only alcohol intoxication were positively and firearms negatively significantly associated with clearance status. The study concludes that cases involving these factors should be granted extra, intensive and lasting resources. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The Pediatric Home Care/Expenditure Classification Model (P/ECM): A Home Care Case-Mix Model for Children Facing Special Health Care Challenges.

PubMed

Phillips, Charles D

2015-01-01

Case-mix classification and payment systems help assure that persons with similar needs receive similar amounts of care resources, which is a major equity concern for consumers, providers, and programs. Although health service programs for adults regularly use case-mix payment systems, programs providing health services to children and youth rarely use such models. This research utilized Medicaid home care expenditures and assessment data on 2,578 children receiving home care in one large state in the USA. Using classification and regression tree analyses, a case-mix model for long-term pediatric home care was developed. The Pediatric Home Care/Expenditure Classification Model (P/ECM) grouped children and youth in the study sample into 24 groups, explaining 41% of the variance in annual home care expenditures. The P/ECM creates the possibility of a more equitable, and potentially more effective, allocation of home care resources among children and youth facing serious health care challenges.

The Pediatric Home Care/Expenditure Classification Model (P/ECM): A Home Care Case-Mix Model for Children Facing Special Health Care Challenges

PubMed Central

Phillips, Charles D.

2015-01-01

Case-mix classification and payment systems help assure that persons with similar needs receive similar amounts of care resources, which is a major equity concern for consumers, providers, and programs. Although health service programs for adults regularly use case-mix payment systems, programs providing health services to children and youth rarely use such models. This research utilized Medicaid home care expenditures and assessment data on 2,578 children receiving home care in one large state in the USA. Using classification and regression tree analyses, a case-mix model for long-term pediatric home care was developed. The Pediatric Home Care/Expenditure Classification Model (P/ECM) grouped children and youth in the study sample into 24 groups, explaining 41% of the variance in annual home care expenditures. The P/ECM creates the possibility of a more equitable, and potentially more effective, allocation of home care resources among children and youth facing serious health care challenges. PMID:26740744

EXAMINING TATOOINE: ATMOSPHERIC MODELS OF NEPTUNE-LIKE CIRCUMBINARY PLANETS

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

May, E. M.; Rauscher, E.

2016-08-01

Circumbinary planets experience a time-varying irradiation pattern as they orbit their two host stars. In this work, we present the first detailed study of the atmospheric effects of this irradiation pattern on known and hypothetical gaseous circumbinary planets. Using both a one-dimensional energy balance model (EBM) and a three-dimensional general circulation model (GCM), we look at the temperature differences between circumbinary planets and their equivalent single-star cases in order to determine the nature of the atmospheres of these planets. We find that for circumbinary planets on stable orbits around their host stars, temperature differences are on average no more thanmore » 1.0% in the most extreme cases. Based on detailed modeling with the GCM, we find that these temperature differences are not large enough to excite circulation differences between the two cases. We conclude that gaseous circumbinary planets can be treated as their equivalent single-star case in future atmospheric modeling efforts.« less

Beta-2 adrenergic receptor (ADRB2) gene polymorphisms and the risk of asthma: a meta-analysis of case-control studies.

PubMed

Liang, Si-Qiao; Chen, Xiao-Li; Deng, Jing-Min; Wei, Xuan; Gong, Chen; Chen, Zhang-Rong; Wang, Zhi-Bo

2014-01-01

A number of studies have assessed the relationship between beta-2 adrenergic receptor (ADRB2) gene polymorphisms and asthma risk. However, the results are inconsistent. A meta-analysis that focused on the association between asthma and all ADRB2 polymorphisms with at least three case-control studies was thus performed. A literature search of the PubMed, Embase, Web of Science, CNKI, and Wangfang databases was conducted. Odds ratios with 95% confidence intervals were used to assess the strength of associations. Arg16Gly, Gln27Glu, Thr164Ile, and Arg19Cys single nucleotide polymorphisms (SNPs) were identified in 46 case-control studies. The results showed that not all of the SNPs were associated with asthma in the overall population. Significant associations were found for the Arg16Gly polymorphism in the South American population via dominant model comparison (OR = 1.754, 95% CI = 1.179-2.609, I2 = 16.9%, studies  = 2, case  = 314, control  = 237) in an analysis stratified by ethnicity. For the Gln27Glu polymorphism, a protective association was found in children via recessive model comparison (OR = 0.566, 95% CI = 0.417-0.769, I2 = 0.0%, studies  = 11, case  = 1693, control  =  502) and homozygote genotype comparison (OR = 0.610, 95% CI = 0.434-0.856, I2 = 0.0%, studies  = 11, case  = 1693, control  = 1502), and in adults via dominant model comparison (OR = 0.864, 95% CI = 0.768-0.971, I2 = 46.9%, n = 18, case  = 3160, control  = 3433). None of the ADRB2 gene polymorphisms were reproducibly associated with a risk of asthma across ethnic groups in the general population.

3D printed renal cancer models derived from MRI data: application in pre-surgical planning.

PubMed

Wake, Nicole; Rude, Temitope; Kang, Stella K; Stifelman, Michael D; Borin, James F; Sodickson, Daniel K; Huang, William C; Chandarana, Hersh

2017-05-01

To determine whether patient-specific 3D printed renal tumor models change pre-operative planning decisions made by urological surgeons in preparation for complex renal mass surgical procedures. From our ongoing IRB approved study on renal neoplasms, ten renal mass cases were retrospectively selected based on Nephrometry Score greater than 5 (range 6-10). A 3D post-contrast fat-suppressed gradient-echo T1-weighted sequence was used to generate 3D printed models. The cases were evaluated by three experienced urologic oncology surgeons in a randomized fashion using (1) imaging data on PACS alone and (2) 3D printed model in addition to the imaging data. A questionnaire regarding surgical approach and planning was administered. The presumed pre-operative approaches with and without the model were compared. Any change between the presumed approaches and the actual surgical intervention was recorded. There was a change in planned approach with the 3D printed model for all ten cases with the largest impact seen regarding decisions on transperitoneal or retroperitoneal approach and clamping, with changes seen in 30%-50% of cases. Mean parenchymal volume loss for the operated kidney was 21.4%. Volume losses >20% were associated with increased ischemia times and surgeons tended to report a different approach with the use of the 3D model compared to that with imaging alone in these cases. The 3D printed models helped increase confidence regarding the chosen operative procedure in all cases. Pre-operative physical 3D models created from MRI data may influence surgical planning for complex kidney cancer.

The impact of case specificity and generalisable skills on clinical performance: a correlated traits-correlated methods approach.

PubMed

Wimmers, Paul F; Fung, Cha-Chi

2008-06-01

The finding of case or content specificity in medical problem solving moved the focus of research away from generalisable skills towards the importance of content knowledge. However, controversy about the content dependency of clinical performance and the generalisability of skills remains. This study aimed to explore the relative impact of both perspectives (case specificity and generalisable skills) on different components (history taking, physical examination, communication) of clinical performance within and across cases. Data from a clinical performance examination (CPX) taken by 350 Year 3 students were used in a correlated traits-correlated methods (CTCM) approach using confirmatory factor analysis, whereby 'traits' refers to generalisable skills and 'methods' to individual cases. The baseline CTCM model was analysed and compared with four nested models using structural equation modelling techniques. The CPX consisted of three skills components and five cases. Comparison of the four different models with the least-restricted baseline CTCM model revealed that a model with uncorrelated generalisable skills factors and correlated case-specific knowledge factors represented the data best. The generalisable processes found in history taking, physical examination and communication were responsible for half the explained variance, in comparison with the variance related to case specificity. Conclusions Pure knowledge-based and pure skill-based perspectives on clinical performance both seem too one-dimensional and new evidence supports the idea that a substantial amount of variance contributes to both aspects of performance. It could be concluded that generalisable skills and specialised knowledge go hand in hand: both are essential aspects of clinical performance.

Small traveling clusters in attractive and repulsive Hamiltonian mean-field models.

PubMed

Barré, Julien; Yamaguchi, Yoshiyuki Y

2009-03-01

Long-lasting small traveling clusters are studied in the Hamiltonian mean-field model by comparing between attractive and repulsive interactions. Nonlinear Landau damping theory predicts that a Gaussian momentum distribution on a spatially homogeneous background permits the existence of traveling clusters in the repulsive case, as in plasma systems, but not in the attractive case. Nevertheless, extending the analysis to a two-parameter family of momentum distributions of Fermi-Dirac type, we theoretically predict the existence of traveling clusters in the attractive case; these findings are confirmed by direct N -body numerical simulations. The parameter region with the traveling clusters is much reduced in the attractive case with respect to the repulsive case.

A comparison between conventional and LANDSAT based hydrologic modeling: The Four Mile Run case study

NASA Technical Reports Server (NTRS)

Ragan, R. M.; Jackson, T. J.; Fitch, W. N.; Shubinski, R. P.

1976-01-01

Models designed to support the hydrologic studies associated with urban water resources planning require input parameters that are defined in terms of land cover. Estimating the land cover is a difficult and expensive task when drainage areas larger than a few sq. km are involved. Conventional and LANDSAT based methods for estimating the land cover based input parameters required by hydrologic planning models were compared in a case study of the 50.5 sq. km (19.5 sq. mi) Four Mile Run Watershed in Virginia. Results of the study indicate that the LANDSAT based approach is highly cost effective for planning model studies. The conventional approach to define inputs was based on 1:3600 aerial photos, required 110 man-days and a total cost of $14,000. The LANDSAT based approach required 6.9 man-days and cost $2,350. The conventional and LANDSAT based models gave similar results relative to discharges and estimated annual damages expected from no flood control, channelization, and detention storage alternatives.

SPOTting Model Parameters Using a Ready-Made Python Package

NASA Astrophysics Data System (ADS)

Houska, Tobias; Kraft, Philipp; Chamorro-Chavez, Alejandro; Breuer, Lutz

2017-04-01

The choice for specific parameter estimation methods is often more dependent on its availability than its performance. We developed SPOTPY (Statistical Parameter Optimization Tool), an open source python package containing a comprehensive set of methods typically used to calibrate, analyze and optimize parameters for a wide range of ecological models. SPOTPY currently contains eight widely used algorithms, 11 objective functions, and can sample from eight parameter distributions. SPOTPY has a model-independent structure and can be run in parallel from the workstation to large computation clusters using the Message Passing Interface (MPI). We tested SPOTPY in five different case studies to parameterize the Rosenbrock, Griewank and Ackley functions, a one-dimensional physically based soil moisture routine, where we searched for parameters of the van Genuchten-Mualem function and a calibration of a biogeochemistry model with different objective functions. The case studies reveal that the implemented SPOTPY methods can be used for any model with just a minimal amount of code for maximal power of parameter optimization. They further show the benefit of having one package at hand that includes number of well performing parameter search methods, since not every case study can be solved sufficiently with every algorithm or every objective function.

SPOTting Model Parameters Using a Ready-Made Python Package.

PubMed

Houska, Tobias; Kraft, Philipp; Chamorro-Chavez, Alejandro; Breuer, Lutz

2015-01-01

The choice for specific parameter estimation methods is often more dependent on its availability than its performance. We developed SPOTPY (Statistical Parameter Optimization Tool), an open source python package containing a comprehensive set of methods typically used to calibrate, analyze and optimize parameters for a wide range of ecological models. SPOTPY currently contains eight widely used algorithms, 11 objective functions, and can sample from eight parameter distributions. SPOTPY has a model-independent structure and can be run in parallel from the workstation to large computation clusters using the Message Passing Interface (MPI). We tested SPOTPY in five different case studies to parameterize the Rosenbrock, Griewank and Ackley functions, a one-dimensional physically based soil moisture routine, where we searched for parameters of the van Genuchten-Mualem function and a calibration of a biogeochemistry model with different objective functions. The case studies reveal that the implemented SPOTPY methods can be used for any model with just a minimal amount of code for maximal power of parameter optimization. They further show the benefit of having one package at hand that includes number of well performing parameter search methods, since not every case study can be solved sufficiently with every algorithm or every objective function.

SPOTting Model Parameters Using a Ready-Made Python Package

PubMed Central

Houska, Tobias; Kraft, Philipp; Chamorro-Chavez, Alejandro; Breuer, Lutz

2015-01-01

The choice for specific parameter estimation methods is often more dependent on its availability than its performance. We developed SPOTPY (Statistical Parameter Optimization Tool), an open source python package containing a comprehensive set of methods typically used to calibrate, analyze and optimize parameters for a wide range of ecological models. SPOTPY currently contains eight widely used algorithms, 11 objective functions, and can sample from eight parameter distributions. SPOTPY has a model-independent structure and can be run in parallel from the workstation to large computation clusters using the Message Passing Interface (MPI). We tested SPOTPY in five different case studies to parameterize the Rosenbrock, Griewank and Ackley functions, a one-dimensional physically based soil moisture routine, where we searched for parameters of the van Genuchten-Mualem function and a calibration of a biogeochemistry model with different objective functions. The case studies reveal that the implemented SPOTPY methods can be used for any model with just a minimal amount of code for maximal power of parameter optimization. They further show the benefit of having one package at hand that includes number of well performing parameter search methods, since not every case study can be solved sufficiently with every algorithm or every objective function. PMID:26680783

Nursing home case mix in Wisconsin. Findings and policy implications.

PubMed

Arling, G; Zimmerman, D; Updike, L

1989-02-01

Along with many other states, Wisconsin is considering a case mix approach to Medicaid nursing home reimbursement. To support this effort, a nursing home case mix model was developed from a representative sample of 410 Medicaid nursing home residents from 56 facilities in Wisconsin. The model classified residents into mutually exclusive groups that were homogeneous in their use of direct care resources, i.e., minutes of direct care time (weighted for nurse skill level) over a 7-day period. Groups were defined initially by intense, Special, or Routine nursing requirements. Within these nursing requirement categories, subgroups were formed by the presence/absence of behavioral problems and dependency in activities of daily living (ADL). Wisconsin's current Skilled/Intermediate Care (SNF/ICF) classification system was analyzed in light of the case mix model and found to be less effective in distinguishing residents by resource use. The case mix model accounted for 48% of the variance in resource use, whereas the SNF/ICF classification system explained 22%. Comparisons were drawn with nursing home case mix models in New York State (RUG-II) and Minnesota. Despite progress in the study of nursing home case mix and its application to reimbursement reform, methodologic and policy issues remain. These include the differing operational definitions for nursing requirements and ADL dependency, the inconsistency in findings concerning psychobehavioral problems, and the problem of promoting positive health and functional outcomes based on models that may be insensitive to change in resident conditions over time.

Particle Interactions Mediated by Dynamical Networks: Assessment of Macroscopic Descriptions

NASA Astrophysics Data System (ADS)

Barré, J.; Carrillo, J. A.; Degond, P.; Peurichard, D.; Zatorska, E.

2018-02-01

We provide a numerical study of the macroscopic model of Barré et al. (Multiscale Model Simul, 2017, to appear) derived from an agent-based model for a system of particles interacting through a dynamical network of links. Assuming that the network remodeling process is very fast, the macroscopic model takes the form of a single aggregation-diffusion equation for the density of particles. The theoretical study of the macroscopic model gives precise criteria for the phase transitions of the steady states, and in the one-dimensional case, we show numerically that the stationary solutions of the microscopic model undergo the same phase transitions and bifurcation types as the macroscopic model. In the two-dimensional case, we show that the numerical simulations of the macroscopic model are in excellent agreement with the predicted theoretical values. This study provides a partial validation of the formal derivation of the macroscopic model from a microscopic formulation and shows that the former is a consistent approximation of an underlying particle dynamics, making it a powerful tool for the modeling of dynamical networks at a large scale.

Particle Interactions Mediated by Dynamical Networks: Assessment of Macroscopic Descriptions.

PubMed

Barré, J; Carrillo, J A; Degond, P; Peurichard, D; Zatorska, E

2018-01-01

We provide a numerical study of the macroscopic model of Barré et al. (Multiscale Model Simul, 2017, to appear) derived from an agent-based model for a system of particles interacting through a dynamical network of links. Assuming that the network remodeling process is very fast, the macroscopic model takes the form of a single aggregation-diffusion equation for the density of particles. The theoretical study of the macroscopic model gives precise criteria for the phase transitions of the steady states, and in the one-dimensional case, we show numerically that the stationary solutions of the microscopic model undergo the same phase transitions and bifurcation types as the macroscopic model. In the two-dimensional case, we show that the numerical simulations of the macroscopic model are in excellent agreement with the predicted theoretical values. This study provides a partial validation of the formal derivation of the macroscopic model from a microscopic formulation and shows that the former is a consistent approximation of an underlying particle dynamics, making it a powerful tool for the modeling of dynamical networks at a large scale.

The Second Prototype of the Development of a Technological Pedagogical Content Knowledge Based Instructional Design Model: An Implementation Study in a Technology Integration Course

ERIC Educational Resources Information Center

Lee, Chia-Jung; Kim, ChanMin

2014-01-01

This study presents a refined technological pedagogical content knowledge (also known as TPACK) based instructional design model, which was revised using findings from the implementation study of a prior model. The refined model was applied in a technology integration course with 38 preservice teachers. A case study approach was used in this…

Reexamination of the State of the Art Cloud Modeling Shows Real Improvements

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

Muehlbauer, Andreas D.; Grabowski, Wojciech W.; Malinowski, S. P.

Following up on an almost thirty year long history of International Cloud Modeling Workshops, that started out with a meeting in Irsee, Germany in 1985, the 8th International Cloud Modeling Workshop was held in July 2012 in Warsaw, Poland. The workshop, hosted by the Institute of Geophysics at the University of Warsaw, was organized by Szymon Malinowski and his local team of students and co-chaired by Wojciech Grabowski (NCAR/MMM) and Andreas Muhlbauer (University of Washington). International Cloud Modeling Workshops have been held traditionally every four years typically during the week before the International Conference on Clouds and Precipitation (ICCP) .more » Rooted in the World Meteorological Organization’s (WMO) weather modification program, the core objectives of the Cloud Modeling Workshop have been centered at the numerical modeling of clouds, cloud microphysics, and the interactions between cloud microphysics and cloud dynamics. In particular, the goal of the workshop is to provide insight into the pertinent problems of today’s state-of-the-art of cloud modeling and to identify key deficiencies in the microphysical representation of clouds in numerical models and cloud parameterizations. In recent years, the workshop has increasingly shifted the focus toward modeling the interactions between aerosols and clouds and provided case studies to investigate both the effects of aerosols on clouds and precipitation as well as the impact of cloud and precipitation processes on aerosols. This time, about 60 (?) scientists from about 10 (?) different countries participated in the workshop and contributed with discussions, oral and poster presentations to the workshop’s plenary and breakout sessions. Several case leaders contributed to the workshop by setting up five observationally-based case studies covering a wide range of cloud types, namely, marine stratocumulus, mid-latitude squall lines, mid-latitude cirrus clouds, Arctic stratus and winter-time orographic clouds and precipitation. Interested readers are encouraged to visit the workshop website at http://www.atmos.washington.edu/~andreasm/workshop2012/ and browse through the list of case studies. The web page also provides a detailed list of participants and the workshop agenda. Aside from contributed oral and poster presentations during the workshop’s plenary sessions, parallel breakout sessions focused on presentations and discussions of the individual cases. A short summary and science highlights from each of the cases is presented below.« less

An analytic model for acoustic scattering from an impedance cylinder placed normal to an impedance plane

NASA Astrophysics Data System (ADS)

Swearingen, Michelle E.

2004-04-01

An analytic model, developed in cylindrical coordinates, is described for the scattering of a spherical wave off a semi-infinite reight cylinder placed normal to a ground surface. The motivation for the research is to have a model with which one can simulate scattering from a single tree and which can be used as a fundamental element in a model for estimating the attenuation in a forest comprised of multiple tree trunks. Comparisons are made to the plane wave case, the transparent cylinder case, and the rigid and soft ground cases as a method of theoretically verifying the model for the contemplated range of model parameters. Agreement is regarded as excellent for these benchmark cases. Model sensitivity to five parameters is also explored. An experiment was performed to study the scattering from a cylinder normal to a ground surface. The data from the experiment is analyzed with a transfer function method to yield frequency and impulse responses, and calculations based on the analytic model are compared to the experimental data. Thesis advisor: David C. Swanson Copies of this thesis written in English can be obtained from

D Modelling and Rapid Prototyping for Cardiovascular Surgical Planning - Two Case Studies

NASA Astrophysics Data System (ADS)

Nocerino, E.; Remondino, F.; Uccheddu, F.; Gallo, M.; Gerosa, G.

2016-06-01

In the last years, cardiovascular diagnosis, surgical planning and intervention have taken advantages from 3D modelling and rapid prototyping techniques. The starting data for the whole process is represented by medical imagery, in particular, but not exclusively, computed tomography (CT) or multi-slice CT (MCT) and magnetic resonance imaging (MRI). On the medical imagery, regions of interest, i.e. heart chambers, valves, aorta, coronary vessels, etc., are segmented and converted into 3D models, which can be finally converted in physical replicas through 3D printing procedure. In this work, an overview on modern approaches for automatic and semiautomatic segmentation of medical imagery for 3D surface model generation is provided. The issue of accuracy check of surface models is also addressed, together with the critical aspects of converting digital models into physical replicas through 3D printing techniques. A patient-specific 3D modelling and printing procedure (Figure 1), for surgical planning in case of complex heart diseases was developed. The procedure was applied to two case studies, for which MCT scans of the chest are available. In the article, a detailed description on the implemented patient-specific modelling procedure is provided, along with a general discussion on the potentiality and future developments of personalized 3D modelling and printing for surgical planning and surgeons practice.

Effect of temperature and precipitation on salmonellosis cases in South-East Queensland, Australia: an observational study

PubMed Central

Barnett, Adrian Gerard

2016-01-01

Objective Foodborne illnesses in Australia, including salmonellosis, are estimated to cost over $A1.25 billion annually. The weather has been identified as being influential on salmonellosis incidence, as cases increase during summer, however time series modelling of salmonellosis is challenging because outbreaks cause strong autocorrelation. This study assesses whether switching models is an improved method of estimating weather–salmonellosis associations. Design We analysed weather and salmonellosis in South-East Queensland between 2004 and 2013 using 2 common regression models and a switching model, each with 21-day lags for temperature and precipitation. Results The switching model best fit the data, as judged by its substantial improvement in deviance information criterion over the regression models, less autocorrelated residuals and control of seasonality. The switching model estimated a 5°C increase in mean temperature and 10 mm precipitation were associated with increases in salmonellosis cases of 45.4% (95% CrI 40.4%, 50.5%) and 24.1% (95% CrI 17.0%, 31.6%), respectively. Conclusions Switching models improve on traditional time series models in quantifying weather–salmonellosis associations. A better understanding of how temperature and precipitation influence salmonellosis may identify where interventions can be made to lower the health and economic costs of salmonellosis. PMID:26916693

Climatic Variables and Malaria Morbidity in Mutale Local Municipality, South Africa: A 19-Year Data Analysis.

PubMed

Adeola, Abiodun M; Botai, Joel O; Rautenbach, Hannes; Adisa, Omolola M; Ncongwane, Katlego P; Botai, Christina M; Adebayo-Ojo, Temitope C

2017-11-08

The north-eastern parts of South Africa, comprising the Limpopo Province, have recorded a sudden rise in the rate of malaria morbidity and mortality in the 2017 malaria season. The epidemiological profiles of malaria, as well as other vector-borne diseases, are strongly associated with climate and environmental conditions. A retrospective understanding of the relationship between climate and the occurrence of malaria may provide insight into the dynamics of the disease's transmission and its persistence in the north-eastern region. In this paper, the association between climatic variables and the occurrence of malaria was studied in the Mutale local municipality in South Africa over a period of 19-year. Time series analysis was conducted on monthly climatic variables and monthly malaria cases in the Mutale municipality for the period of 1998-2017. Spearman correlation analysis was performed and the Seasonal Autoregressive Integrated Moving Average (SARIMA) model was developed. Microsoft Excel was used for data cleaning, and statistical software R was used to analyse the data and develop the model. Results show that both climatic variables' and malaria cases' time series exhibited seasonal patterns, showing a number of peaks and fluctuations. Spearman correlation analysis indicated that monthly total rainfall, mean minimum temperature, mean maximum temperature, mean average temperature, and mean relative humidity were significantly and positively correlated with monthly malaria cases in the study area. Regression analysis showed that monthly total rainfall and monthly mean minimum temperature ( R ² = 0.65), at a two-month lagged effect, are the most significant climatic predictors of malaria transmission in Mutale local municipality. A SARIMA (2,1,2) (1,1,1) model fitted with only malaria cases has a prediction performance of about 51%, and the SARIMAX (2,1,2) (1,1,1) model with climatic variables as exogenous factors has a prediction performance of about 72% in malaria cases. The model gives a close comparison between the predicted and observed number of malaria cases, hence indicating that the model provides an acceptable fit to predict the number of malaria cases in the municipality. To sum up, the association between the climatic variables and malaria cases provides clues to better understand the dynamics of malaria transmission. The lagged effect detected in this study can help in adequate planning for malaria intervention.

A study of pilot modeling in multi-controller tasks

NASA Technical Reports Server (NTRS)

Whitbeck, R. F.; Knight, J. R.

1972-01-01

A modeling approach, which utilizes a matrix of transfer functions to describe the human pilot in multiple input, multiple output control situations, is studied. The approach used was to extend a well established scalar Wiener-Hopf minimization technique to the matrix case and then study, via a series of experiments, the data requirements when only finite record lengths are available. One of these experiments was a two-controller roll tracking experiment designed to force the pilot to use rudder in order to coordinate and reduce the effects of aileron yaw. One model was computed for the case where the signals used to generate the spectral matrix are error and bank angle while another model was computed for the case where error and yaw angle are the inputs. Several anomalies were observed to be present in the experimental data. These are defined by the descriptive terms roll up, break up, and roll down. Due to these algorithm induced anomalies, the frequency band over which reliable estimates of power spectra can be achieved is considerably less than predicted by the sampling theorem.

Identifiability of large-scale non-linear dynamic network models applied to the ADM1-case study.

PubMed

Nimmegeers, Philippe; Lauwers, Joost; Telen, Dries; Logist, Filip; Impe, Jan Van

2017-06-01

In this work, both the structural and practical identifiability of the Anaerobic Digestion Model no. 1 (ADM1) is investigated, which serves as a relevant case study of large non-linear dynamic network models. The structural identifiability is investigated using the probabilistic algorithm, adapted to deal with the specifics of the case study (i.e., a large-scale non-linear dynamic system of differential and algebraic equations). The practical identifiability is analyzed using a Monte Carlo parameter estimation procedure for a 'non-informative' and 'informative' experiment, which are heuristically designed. The model structure of ADM1 has been modified by replacing parameters by parameter combinations, to provide a generally locally structurally identifiable version of ADM1. This means that in an idealized theoretical situation, the parameters can be estimated accurately. Furthermore, the generally positive structural identifiability results can be explained from the large number of interconnections between the states in the network structure. This interconnectivity, however, is also observed in the parameter estimates, making uncorrelated parameter estimations in practice difficult. Copyright © 2017. Published by Elsevier Inc.

Modeling Tetanus Neonatorum case using the regression of negative binomial and zero-inflated negative binomial

NASA Astrophysics Data System (ADS)

Amaliana, Luthfatul; Sa'adah, Umu; Wayan Surya Wardhani, Ni

2017-12-01

Tetanus Neonatorum is an infectious disease that can be prevented by immunization. The number of Tetanus Neonatorum cases in East Java Province is the highest in Indonesia until 2015. Tetanus Neonatorum data contain over dispersion and big enough proportion of zero-inflation. Negative Binomial (NB) regression is an alternative method when over dispersion happens in Poisson regression. However, the data containing over dispersion and zero-inflation are more appropriately analyzed by using Zero-Inflated Negative Binomial (ZINB) regression. The purpose of this study are: (1) to model Tetanus Neonatorum cases in East Java Province with 71.05 percent proportion of zero-inflation by using NB and ZINB regression, (2) to obtain the best model. The result of this study indicates that ZINB is better than NB regression with smaller AIC.

Purpose, Processes, Partnerships, and Products: 4Ps to advance Participatory Socio-Environmental Modeling

NASA Astrophysics Data System (ADS)

Gray, S. G.; Voinov, A. A.; Jordan, R.; Paolisso, M.

2016-12-01

Model-based reasoning is a basic part of human understanding, decision-making, and communication. Including stakeholders in environmental model building and analysis is an increasingly popular approach to understanding environmental change since stakeholders often hold valuable knowledge about socio-environmental dynamics and since collaborative forms of modeling produce important boundary objects used to collectively reason about environmental problems. Although the number of participatory modeling (PM) case studies and the number of researchers adopting these approaches has grown in recent years, the lack of standardized reporting and limited reproducibility have prevented PM's establishment and advancement as a cohesive field of study. We suggest a four dimensional framework that includes reporting on dimensions of: (1) the Purpose for selecting a PM approach (the why); (2) the Process by which the public was involved in model building or evaluation (the how); (3) the Partnerships formed (the who); and (4) the Products that resulted from these efforts (the what). We highlight four case studies that use common PM software-based approaches (fuzzy cognitive mapping, agent-based modeling, system dynamics, and participatory geospatial modeling) to understand human-environment interactions and the consequences of environmental changes, including bushmeat hunting in Tanzania and Cameroon, agricultural production and deforestation in Zambia, and groundwater management in India. We demonstrate how standardizing communication about PM case studies can lead to innovation and new insights about model-based reasoning in support of environmental policy development. We suggest that our 4P framework and reporting approach provides a way for new hypotheses to be identified and tested in the growing field of PM.

Validity of using ad hoc methods to analyze secondary traits in case-control association studies.

PubMed

Yung, Godwin; Lin, Xihong

2016-12-01

Case-control association studies often collect from their subjects information on secondary phenotypes. Reusing the data and studying the association between genes and secondary phenotypes provide an attractive and cost-effective approach that can lead to discovery of new genetic associations. A number of approaches have been proposed, including simple and computationally efficient ad hoc methods that ignore ascertainment or stratify on case-control status. Justification for these approaches relies on the assumption of no covariates and the correct specification of the primary disease model as a logistic model. Both might not be true in practice, for example, in the presence of population stratification or the primary disease model following a probit model. In this paper, we investigate the validity of ad hoc methods in the presence of covariates and possible disease model misspecification. We show that in taking an ad hoc approach, it may be desirable to include covariates that affect the primary disease in the secondary phenotype model, even though these covariates are not necessarily associated with the secondary phenotype. We also show that when the disease is rare, ad hoc methods can lead to severely biased estimation and inference if the true disease model follows a probit model instead of a logistic model. Our results are justified theoretically and via simulations. Applied to real data analysis of genetic associations with cigarette smoking, ad hoc methods collectively identified as highly significant (P<10-5) single nucleotide polymorphisms from over 10 genes, genes that were identified in previous studies of smoking cessation. © 2016 WILEY PERIODICALS, INC.

Estimation of the cure rate in Iranian breast cancer patients.

PubMed

Rahimzadeh, Mitra; Baghestani, Ahmad Reza; Gohari, Mahmood Reza; Pourhoseingholi, Mohamad Amin

2014-01-01

Although the Cox's proportional hazard model is the popular approach for survival analysis to investigate significant risk factors of cancer patient survival, it is not appropriate in the case of log-term disease free survival. Recently, cure rate models have been introduced to distinguish between clinical determinants of cure and variables associated with the time to event of interest. The aim of this study was to use a cure rate model to determine the clinical associated factors for cure rates of patients with breast cancer (BC). This prospective cohort study covered 305 patients with BC, admitted at Shahid Faiazbakhsh Hospital, Tehran, during 2006 to 2008 and followed until April 2012. Cases of patient death were confirmed by telephone contact. For data analysis, a non-mixed cure rate model with Poisson distribution and negative binomial distribution were employed. All analyses were carried out using a developed Macro in WinBugs. Deviance information criteria (DIC) were employed to find the best model. The overall 1-year, 3-year and 5-year relative survival rates were 97%, 89% and 74%. Metastasis and stage of BC were the significant factors, but age was significant only in negative binomial model. The DIC also showed that the negative binomial model had a better fit. This study indicated that, metastasis and stage of BC were identified as the clinical criteria for cure rates. There are limited studies on BC survival which employed these cure rate models to identify the clinical factors associated with cure. These models are better than Cox, in the case of long-term survival.

An open source Bayesian Monte Carlo isotope mixing model with applications in Earth surface processes

NASA Astrophysics Data System (ADS)

Arendt, Carli A.; Aciego, Sarah M.; Hetland, Eric A.

2015-05-01

The implementation of isotopic tracers as constraints on source contributions has become increasingly relevant to understanding Earth surface processes. Interpretation of these isotopic tracers has become more accessible with the development of Bayesian Monte Carlo (BMC) mixing models, which allow uncertainty in mixing end-members and provide methodology for systems with multicomponent mixing. This study presents an open source multiple isotope BMC mixing model that is applicable to Earth surface environments with sources exhibiting distinct end-member isotopic signatures. Our model is first applied to new δ18O and δD measurements from the Athabasca Glacier, which showed expected seasonal melt evolution trends and vigorously assessed the statistical relevance of the resulting fraction estimations. To highlight the broad applicability of our model to a variety of Earth surface environments and relevant isotopic systems, we expand our model to two additional case studies: deriving melt sources from δ18O, δD, and 222Rn measurements of Greenland Ice Sheet bulk water samples and assessing nutrient sources from ɛNd and 87Sr/86Sr measurements of Hawaiian soil cores. The model produces results for the Greenland Ice Sheet and Hawaiian soil data sets that are consistent with the originally published fractional contribution estimates. The advantage of this method is that it quantifies the error induced by variability in the end-member compositions, unrealized by the models previously applied to the above case studies. Results from all three case studies demonstrate the broad applicability of this statistical BMC isotopic mixing model for estimating source contribution fractions in a variety of Earth surface systems.

Building more realistic reservoir optimization models using data mining - A case study of Shelbyville Reservoir

NASA Astrophysics Data System (ADS)

Hejazi, Mohamad I.; Cai, Ximing

2011-06-01

In this paper, we promote a novel approach to develop reservoir operation routines by learning from historical hydrologic information and reservoir operations. The proposed framework involves a knowledge discovery step to learn the real drivers of reservoir decision making and to subsequently build a more realistic (enhanced) model formulation using stochastic dynamic programming (SDP). The enhanced SDP model is compared to two classic SDP formulations using Lake Shelbyville, a reservoir on the Kaskaskia River in Illinois, as a case study. From a data mining procedure with monthly data, the past month's inflow ( Qt-1 ), current month's inflow ( Qt), past month's release ( Rt-1 ), and past month's Palmer drought severity index ( PDSIt-1 ) are identified as important state variables in the enhanced SDP model for Shelbyville Reservoir. When compared to a weekly enhanced SDP model of the same case study, a different set of state variables and constraints are extracted. Thus different time scales for the model require different information. We demonstrate that adding additional state variables improves the solution by shifting the Pareto front as expected while using new constraints and the correct objective function can significantly reduce the difference between derived policies and historical practices. The study indicates that the monthly enhanced SDP model resembles historical records more closely and yet provides lower expected average annual costs than either of the two classic formulations (25.4% and 4.5% reductions, respectively). The weekly enhanced SDP model is compared to the monthly enhanced SDP, and it shows that acquiring the correct temporal scale is crucial to model reservoir operation for particular objectives.

Comparison of different modelling approaches of drive train temperature for the purposes of wind turbine failure detection

NASA Astrophysics Data System (ADS)

Tautz-Weinert, J.; Watson, S. J.

2016-09-01

Effective condition monitoring techniques for wind turbines are needed to improve maintenance processes and reduce operational costs. Normal behaviour modelling of temperatures with information from other sensors can help to detect wear processes in drive trains. In a case study, modelling of bearing and generator temperatures is investigated with operational data from the SCADA systems of more than 100 turbines. The focus is here on automated training and testing on a farm level to enable an on-line system, which will detect failures without human interpretation. Modelling based on linear combinations, artificial neural networks, adaptive neuro-fuzzy inference systems, support vector machines and Gaussian process regression is compared. The selection of suitable modelling inputs is discussed with cross-correlation analyses and a sensitivity study, which reveals that the investigated modelling techniques react in different ways to an increased number of inputs. The case study highlights advantages of modelling with linear combinations and artificial neural networks in a feedforward configuration.

Evaluating risk factors for endemic human Salmonella Enteritidis infections with different phage types in Ontario, Canada using multinomial logistic regression and a case-case study approach

PubMed Central

2012-01-01

Background Identifying risk factors for Salmonella Enteritidis (SE) infections in Ontario will assist public health authorities to design effective control and prevention programs to reduce the burden of SE infections. Our research objective was to identify risk factors for acquiring SE infections with various phage types (PT) in Ontario, Canada. We hypothesized that certain PTs (e.g., PT8 and PT13a) have specific risk factors for infection. Methods Our study included endemic SE cases with various PTs whose isolates were submitted to the Public Health Laboratory-Toronto from January 20th to August 12th, 2011. Cases were interviewed using a standardized questionnaire that included questions pertaining to demographics, travel history, clinical symptoms, contact with animals, and food exposures. A multinomial logistic regression method using the Generalized Linear Latent and Mixed Model procedure and a case-case study design were used to identify risk factors for acquiring SE infections with various PTs in Ontario, Canada. In the multinomial logistic regression model, the outcome variable had three categories representing human infections caused by SE PT8, PT13a, and all other SE PTs (i.e., non-PT8/non-PT13a) as a referent category to which the other two categories were compared. Results In the multivariable model, SE PT8 was positively associated with contact with dogs (OR=2.17, 95% CI 1.01-4.68) and negatively associated with pepper consumption (OR=0.35, 95% CI 0.13-0.94), after adjusting for age categories and gender, and using exposure periods and health regions as random effects to account for clustering. Conclusions Our study findings offer interesting hypotheses about the role of phage type-specific risk factors. Multinomial logistic regression analysis and the case-case study approach are novel methodologies to evaluate associations among SE infections with different PTs and various risk factors. PMID:23057531

Groundwater Model Validation

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

Ahmed E. Hassan

2006-01-24

Models have an inherent uncertainty. The difficulty in fully characterizing the subsurface environment makes uncertainty an integral component of groundwater flow and transport models, which dictates the need for continuous monitoring and improvement. Building and sustaining confidence in closure decisions and monitoring networks based on models of subsurface conditions require developing confidence in the models through an iterative process. The definition of model validation is postulated as a confidence building and long-term iterative process (Hassan, 2004a). Model validation should be viewed as a process not an end result. Following Hassan (2004b), an approach is proposed for the validation process ofmore » stochastic groundwater models. The approach is briefly summarized herein and detailed analyses of acceptance criteria for stochastic realizations and of using validation data to reduce input parameter uncertainty are presented and applied to two case studies. During the validation process for stochastic models, a question arises as to the sufficiency of the number of acceptable model realizations (in terms of conformity with validation data). Using a hierarchical approach to make this determination is proposed. This approach is based on computing five measures or metrics and following a decision tree to determine if a sufficient number of realizations attain satisfactory scores regarding how they represent the field data used for calibration (old) and used for validation (new). The first two of these measures are applied to hypothetical scenarios using the first case study and assuming field data consistent with the model or significantly different from the model results. In both cases it is shown how the two measures would lead to the appropriate decision about the model performance. Standard statistical tests are used to evaluate these measures with the results indicating they are appropriate measures for evaluating model realizations. The use of validation data to constrain model input parameters is shown for the second case study using a Bayesian approach known as Markov Chain Monte Carlo. The approach shows a great potential to be helpful in the validation process and in incorporating prior knowledge with new field data to derive posterior distributions for both model input and output.« less

Patient-Specific Geometry Modeling and Mesh Generation for Simulating Obstructive Sleep Apnea Syndrome Cases by Maxillomandibular Advancement

PubMed Central

Ito, Yasushi; Cheng, Gary C.; Shih, Alan M.; Koomullil, Roy P.; Soni, Bharat K.; Sittitavornwong, Somsak; Waite, Peter D.

2011-01-01

The objective of this paper is the reconstruction of upper airway geometric models as hybrid meshes from clinically used Computed Tomography (CT) data sets in order to understand the dynamics and behaviors of the pre- and postoperative upper airway systems of Obstructive Sleep Apnea Syndrome (OSAS) patients by viscous Computational Fluid Dynamics (CFD) simulations. The selection criteria for OSAS cases studied are discussed because two reasonable pre- and postoperative upper airway models for CFD simulations may not be created for every case without a special protocol for CT scanning. The geometry extraction and manipulation methods are presented with technical barriers that must be overcome so that they can be used along with computational simulation software as a daily clinical evaluation tool. Eight cases are presented in this paper, and each case consists of pre- and postoperative configurations. The results of computational simulations of two cases are included in this paper as demonstration. PMID:21625395

Development of Airport Noise Mapping using Matlab Software (Case Study: Adi Soemarmo Airport - Boyolali, Indonesia)

NASA Astrophysics Data System (ADS)

Andarani, Pertiwi; Setiyo Huboyo, Haryono; Setyanti, Diny; Budiawan, Wiwik

2018-02-01

Noise is considered as one of the main environmental impact of Adi Soemarmo International Airport (ASIA), the second largest airport in Central Java Province, Indonesia. In order to manage the noise of airport, airport noise mapping is necessary. However, a model that requires simple input but still reliable was not available in ASIA. Therefore, the objective of this study are to develop model using Matlab software, to verify its reliability by measuring actual noise exposure, and to analyze the area of noise levels‥ The model was developed based on interpolation or extrapolation of identified Noise-Power-Distance (NPD) data. In accordance with Indonesian Government Ordinance No.40/2012, the noise metric used is WECPNL (Weighted Equivalent Continuous Perceived Noise Level). Based on this model simulation, there are residence area in the region of noise level II (1.912 km2) and III (1.16 km2) and 18 school buildings in the area of noise levels I, II, and III. These land-uses are actually prohibited unless noise insulation is equipped. The model using Matlab in the case of Adi Soemarmo International Airport is valid based on comparison of the field measurement (6 sampling points). However, it is important to validate the model again once the case study (the airport) is changed.

Enhancement of the Acquisition Process for a Combat System-A Case Study to Model the Workflow Processes for an Air Defense System Acquisition

DTIC Science & Technology

2009-12-01

Business Process Modeling BPMN Business Process Modeling Notation SoA Service-oriented Architecture UML Unified Modeling Language CSP...system developers. Supporting technologies include Business Process Modeling Notation ( BPMN ), Unified Modeling Language (UML), model-driven architecture

Psychosocial work environment and myocardial infarction: improving risk estimation by combining two complementary job stress models in the SHEEP Study

PubMed Central

Peter, R; Siegrist, J; Hallqvist, J; Reuterwall, C; Theorell, T

2002-01-01

Objectives: Associations between two alternative formulations of job stress derived from the effort-reward imbalance and the job strain model and first non-fatal acute myocardial infarction were studied. Whereas the job strain model concentrates on situational (extrinsic) characteristics the effort-reward imbalance model analyses distinct person (intrinsic) characteristics in addition to situational ones. In view of these conceptual differences the hypothesis was tested that combining information from the two models improves the risk estimation of acute myocardial infarction. Methods: 951 male and female myocardial infarction cases and 1147 referents aged 45–64 years of The Stockholm Heart Epidemiology (SHEEP) case-control study underwent a clinical examination. Information on job stress and health adverse behaviours was derived from standardised questionnaires. Results: Multivariate analysis showed moderately increased odds ratios for either model. Yet, with respect to the effort-reward imbalance model gender specific effects were found: in men the extrinsic component contributed to risk estimation, whereas this was the case with the intrinsic component in women. Controlling each job stress model for the other in order to test the independent effect of either approach did not show systematically increased odds ratios. An improved estimation of acute myocardial infarction risk resulted from combining information from the two models by defining groups characterised by simultaneous exposure to effort-reward imbalance and job strain (men: odds ratio 2.02 (95% confidence intervals (CI) 1.34 to 3.07); women odds ratio 2.19 (95% CI 1.11 to 4.28)). Conclusions: Findings show an improved risk estimation of acute myocardial infarction by combining information from the two job stress models under study. Moreover, gender specific effects of the two components of the effort-reward imbalance model were observed. PMID:11896138

Enhancement of Entrepreneurial Leadership: A Case Focusing on a Model of Successful Conflict Management Skills

ERIC Educational Resources Information Center

Leffel, Anita; Hallam, Cory; Darling, John

2012-01-01

The purpose of this paper is to present a case study focusing on a new technology start-up firm, founded by two graduate students, an engineer and a business major, who met during their university studies. The case is timely, in that only ten percent of new product introductions result in a profitable business. The causes of failure are numerous…

A Case Study of Troika Short-Term Study Abroad Program Model in Community Colleges

ERIC Educational Resources Information Center

Pickard, Jeremy L.

2010-01-01

This case study examined the phenomenon, through a basic interpretive approach, of 13 students who participated in a short-term study abroad program at a community college. Participants shared experiences from their programs that provided meaning to their lives and how that meaning has shaped their life socially, academically, professionally, and…

University Positioning and Changing Patterns of Doctoral Study: The Case of the University of Bath

ERIC Educational Resources Information Center

Jamieson, Ian; Naidoo, Rajani

2007-01-01

The study examines the changing nature of doctoral study in higher education in the context of significant global changes in higher education. From its origins with Humboldt, the trajectory of doctoral study is traced through the traditional Ph.D, the extended "American model", to the professional doctorate. A university case study…

A Case Study on Pre-Service Secondary School Mathematics Teachers' Cognitive-Metacognitive Behaviours in Mathematical Modelling Process

ERIC Educational Resources Information Center

Sagirli, Meryem Özturan

2016-01-01

The aim of the present study is to investigate pre-service secondary mathematics teachers' cognitive-metacognitive behaviours during the mathematical problem-solving process considering class level. The study, in which the case study methodology was employed, was carried out with eight pre-service mathematics teachers, enrolled at a university in…

Computer-Aided System Engineering and Analysis (CASE/A) Programmer's Manual, Version 5.0

NASA Technical Reports Server (NTRS)

Knox, J. C.

1996-01-01

The Computer Aided System Engineering and Analysis (CASE/A) Version 5.0 Programmer's Manual provides the programmer and user with information regarding the internal structure of the CASE/A 5.0 software system. CASE/A 5.0 is a trade study tool that provides modeling/simulation capabilities for analyzing environmental control and life support systems and active thermal control systems. CASE/A has been successfully used in studies such as the evaluation of carbon dioxide removal in the space station. CASE/A modeling provides a graphical and command-driven interface for the user. This interface allows the user to construct a model by placing equipment components in a graphical layout of the system hardware, then connect the components via flow streams and define their operating parameters. Once the equipment is placed, the simulation time and other control parameters can be set to run the simulation based on the model constructed. After completion of the simulation, graphical plots or text files can be obtained for evaluation of the simulation results over time. Additionally, users have the capability to control the simulation and extract information at various times in the simulation (e.g., control equipment operating parameters over the simulation time or extract plot data) by using "User Operations (OPS) Code." This OPS code is written in FORTRAN with a canned set of utility subroutines for performing common tasks. CASE/A version 5.0 software runs under the VAX VMS(Trademark) environment. It utilizes the Tektronics 4014(Trademark) graphics display system and the VTIOO(Trademark) text manipulation/display system.

Association between rs3087243 and rs231775 polymorphism within the cytotoxic T-lymphocyte antigen 4 gene and Graves' disease: a case/control study combined with meta-analyses

PubMed Central

Dai, Yu; Zeng, Tianshu; Xiao, Fei; Chen, Lulu; Kong, Wen

2017-01-01

We conducted a case/control study to assess the impact of SNP rs3087243 and rs231775 within the CTLA4 gene, on the susceptibility to Graves' disease (GD) in a Chinese Han dataset (271 cases and 298 controls). The frequency of G allele for rs3087243 and rs231775 was observed to be significantly higher in subjects with GD than in control subjects (p = 0.005 and p = 0.000, respectively). After logistic regression analysis, a significant association was detected between SNP rs3087243 and GD in the additive and recessive models. Similarly, association for the SNP rs231775 could also be detected in the additive model, dominant model and recessive model. A meta-analysis, including 27 published datasets along with the current dataset, was performed to further confirm the association. Consistent with our case/control results, rs3087243 and rs231775 showed a significant association with GD in all genetic models. Of note, ethnic stratification revealed that these two SNPs were associated with susceptibility to GD in populations of both Asian and European descent. In conclusion, our data support that the rs3087243 and rs231775 polymorphisms within the CTLA4 gene confer genetic susceptibility to GD. PMID:29299173

Generalisability of vaccine effectiveness estimates: an analysis of cases included in a postlicensure evaluation of 13-valent pneumococcal conjugate vaccine in the USA

PubMed Central

Link-Gelles, Ruth; Westreich, Daniel; Aiello, Allison E; Shang, Nong; Weber, David J; Rosen, Jennifer B; Motala, Tasneem; Mascola, Laurene; Eason, Jeffery; Scherzinger, Karen; Holtzman, Corinne; Reingold, Arthur L; Barnes, Meghan; Petit, Susan; Farley, Monica M; Harrison, Lee H; Zansky, Shelley; Thomas, Ann; Schaffner, William; McGee, Lesley; Whitney, Cynthia G; Moore, Matthew R

2017-01-01

Objectives External validity, or generalisability, is the measure of how well results from a study pertain to individuals in the target population. We assessed generalisability, with respect to socioeconomic status, of estimates from a matched case–control study of 13-valent pneumococcal conjugate vaccine effectiveness for the prevention of invasive pneumococcal disease in children in the USA. Design Matched case–control study. Setting Thirteen active surveillance sites for invasive pneumococcal disease in the USA. Participants Cases were identified from active surveillance and controls were age and zip code matched. Outcome measures Socioeconomic status was assessed at the individual level via parent interview (for enrolled individuals only) and birth certificate data (for both enrolled and unenrolled individuals) and at the neighbourhood level by geocoding to the census tract (for both enrolled and unenrolled individuals). Prediction models were used to determine if socioeconomic status was associated with enrolment. Results We enrolled 54.6% of 1211 eligible cases and found a trend toward enrolled cases being more affluent than unenrolled cases. Enrolled cases were slightly more likely to have private insurance at birth (p=0.08) and have mothers with at least some college education (p<0.01). Enrolled cases also tended to come from more affluent census tracts. Despite these differences, our best predictive model for enrolment yielded a concordance statistic of only 0.703, indicating mediocre predictive value. Variables retained in the final model were assessed for effect measure modification, and none were found to be significant modifiers of vaccine effectiveness. Conclusions We conclude that although enrolled cases are somewhat more affluent than unenrolled cases, our estimates are externally valid with respect to socioeconomic status. Our analysis provides evidence that this study design can yield valid estimates and the assessing generalisability of observational data is feasible, even when unenrolled individuals cannot be contacted. PMID:28851801

Slip-Size Distribution and Self-Organized Criticality in Block-Spring Models with Quenched Randomness

NASA Astrophysics Data System (ADS)

Sakaguchi, Hidetsugu; Kadowaki, Shuntaro

2017-07-01

We study slowly pulling block-spring models in random media. Second-order phase transitions exist in a model pulled by a constant force in the case of velocity-strengthening friction. If external forces are slowly increased, nearly critical states are self-organized. Slips of various sizes occur, and the probability distributions of slip size roughly obey power laws. The exponent is close to that in the quenched Edwards-Wilkinson model. Furthermore, the slip-size distributions are investigated in cases of Coulomb friction, velocity-weakening friction, and two-dimensional block-spring models.

Case management: a case study.

PubMed

Stanton, M P; Walizer, E M; Graham, J I; Keppel, L

2000-01-01

This article describes the implementation of a pilot case management program at Walter Reed Army Medical Center. I, it we discuss obvious pitfalls and problems implementing case management in a large multiservice center and the steps and processes implemented to expedite and move case management forward in its early stages. The insights shared may be useful for those implementing case management in a complex medical center situation. Other models used in similar situations are also reviewed.

A Case Study of the Implementation of Social Models of Teaching in E-Learning: "The Social Networks in Education", Online Course of the Inter-Orthodox Centre of the Church of Greece

ERIC Educational Resources Information Center

Komninou, Ioanna

2018-01-01

The development of e-learning has caused a growing interest in learning models that may have the best results. We believe that it is good practice to implement social learning models in the field of online education. In this case, the implementation of complex instruction in online training courses for teachers, on "Social Networks in…

Case-mix adjustment for diabetes indicators: a systematic review.

PubMed

Calsbeek, Hiske; Markhorst, Joekle G M; Voerman, Gerlienke E; Braspenning, Jozé C C

2016-02-01

Case-mix adjustment is generally considered indispensable for fair comparison of healthcare performance. Inaccurate results are also unfair to patients as they are ineffective for improving quality. However, little is known about what factors should be adjusted for. We reviewed case-mix factors included in adjustment models for key diabetes indicators, the rationale for their inclusion, and their impact on performance. Systematic review. This systematic review included studies published up to June 2013 addressing case-mix factors for 6 key diabetes indicators: 2 outcomes and 2 process indicators for glycated hemoglobin (A1C), low-density lipoprotein cholesterol, and blood pressure. Factors were categorized as demographic, diabetes-related, comorbidity, generic health, geographic, or care-seeking, and were evaluated on the rationale for inclusion in the adjustment models, as well as their impact on indicator scores and ranking. Thirteen studies were included, mainly addressing A1C value and measurement. Twenty-three different case-mix factors, mostly demographic and diabetes-related, were identified, and varied from 1 to 14 per adjustment model. Six studies provided selection motives for the inclusion of case-mix factors. Marital status and body mass index showed a significant impact on A1C value. For the other factors, either no or conflicting associations were reported, or too few studies (n ≤ 2) investigated this association. Scientific knowledge about the relative importance of case-mix factors for diabetes indicators is emerging, especially for demographic and diabetes-related factors and indicators on A1C, but is still limited. Because arbitrary adjustment potentially results in inaccurate quality information, meaningful stratification that demonstrates inequity in care might be a better guide, as it can be a driver for quality improvement.

Numerical Investigation of Flapwise-Torsional Vibration Model of a Smart Section Blade with Microtab

DOE PAGES

Li, Nailu; Balas, Mark J.; Yang, Hua; ...

2015-01-01

This paper presents a method to develop an aeroelastic model of a smart section blade equipped with microtab. The model is suitable for potential passive vibration control study of the blade section in classic flutter. Equations of the model are described by the nondimensional flapwise and torsional vibration modes coupled with the aerodynamic model based on the Theodorsen theory and aerodynamic effects of the microtab based on the wind tunnel experimental data. The aeroelastic model is validated using numerical data available in the literature and then utilized to analyze the microtab control capability on flutter instability case and divergence instabilitymore » case. The effectiveness of the microtab is investigated with the scenarios of different output controllers and actuation deployments for both instability cases. The numerical results show that the microtab can effectively suppress both vibration modes with the appropriate choice of the output feedback controller.« less

A Multi-Year Program Developing an Explicit Reflective Pedagogy for Teaching Pre-service Teachers the Nature of Science by Ostention

NASA Astrophysics Data System (ADS)

Smith, Mike U.; Scharmann, Lawrence

2008-02-01

This investigation delineates a multi-year action research agenda designed to develop an instructional model for teaching the nature of science (NOS) to preservice science teachers. Our past research strongly supports the use of explicit reflective instructional methods, which includes Thomas Kuhn’s notion of learning by ostention and treating science as a continuum (i.e., comparing fields of study to one another for relative placement as less to more scientific). Instruction based on conceptual change precepts, however, also exhibits promise. Thus, the investigators sought to ascertain the degree to which conceptual change took place among students (n = 15) participating in the NOS instructional model. Three case studies are presented to illustrate successful conceptual changes that took place as a result of the NOS instructional model. All three cases represent students who claim a very conservative Christian heritage and for whom evolution was not considered a legitimate scientific theory prior to participating in the NOS instructional model. All three case study individuals, along with their twelve classmates, placed evolution as most scientific when compared to intelligent design and a fictional field of study called “Umbrellaology.”

Applying a contingency model of strategic decision making to the implementation of smoking bans: a case study.

PubMed

Willemsen, M C; Meijer, A; Jannink, M

1999-08-01

A model of strategic decision making was applied to study the implementation of worksite smoking policy. This model assumes there is no best way of implementing smoking policies, but that 'the best way' depends on how decision making fits specific content and context factors. A case study at Wehkamp, a mail-order company, is presented to illustrate the usefulness of this model to understand how organizations implement smoking policies. Interview data were collected from representatives of Wehkamp, and pre- and post-ban survey data were collected from employees. After having failed to solve the smoking problem in a more democratic way, Wehkamp's top management choose a highly confrontational and decentralized decision-making approach to implement a complete smoking ban. This resulted in an effective smoking ban, but was to some extent at the cost of employees' satisfaction with the policy and with how the policy was implemented. The choice of implementation approach was contingent upon specific content and context factors, such as managers' perception of the problem, leadership style and legislation. More case studies from different types of companies are needed to better understand how organizational factors affect decision making about smoking bans and other health promotion innovations.

Impacts of Outer Continental Shelf (OCS) development on recreation and tourism. Volume 2. Final report and case studies

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

Not Available

The final report for the project is comprised of five volumes. The volume presents the study conclusions, summarizes the methodology used (more detail is found in Volume 3), discusses four case study applications of the model, and contains profiles of coastal communities in an Appendix.

Teacher and Administrator Views on School Principals' Accountability

ERIC Educational Resources Information Center

Argon, Turkan

2015-01-01

The current study aims to identify teacher and administrator views regarding primary school principals' accountability. The case study model, a qualitative research method, was adopted in the study using the holistic single-case design. The working group was composed of a total of 56 individuals, 42 teachers and 14 administrators (11 principals…

Academic Culture and Citizenship in Transitional Societies: Case Studies from China and Hungary

ERIC Educational Resources Information Center

Szelényi, Katalin; Rhoads, Robert A.

2013-01-01

Through organizational case studies conducted at Guangdong University of Foreign Studies in China and Central European University in Hungary, this paper examines academic culture and citizenship in societies transitioning from communist to market-driven social and economic structures. The article presents a new model of citizenship, representing…

An Application of an IDEFO Model to Improve the Process of Base Closure: A Case Study

DTIC Science & Technology

1993-12-01

Leave blank) 2. REPORT DATE 3. REPORT TYPE AND DATES COVERED December 1993 Master’s Thesis 4. TITLE AND SUBTITLE AN APLICATION OF AN IDEFO MODEL 5...Closure: A Case Study by Varanda K. Phillips December, 1993 Thesis Advisor: Kenneth J. Euske Approved for public release; distribution is unlimited. AY...10. SPONSOR ING/MONITORING AGENCY REPORT NUMBER 11. SUPPLEMENTARY NOTES The views expressed in this thesis are those of the author and do not reflect

Multi-Robot Search for a Moving Target: Integrating World Modeling, Task Assignment and Context

DTIC Science & Technology

2016-12-01

Case Study Our approach to coordination was initially motivated and developed in RoboCup soccer games. In fact, it has been first deployed on a team of...features a rather accurate model of the behavior and capabilities of the humanoid robot in the field. In the soccer case study , our goal is to...on experiments carried out with a team of humanoid robots in a soccer scenario and a team of mobile bases in an office environment. I. INTRODUCTION

Best Practices for Evaluating the Capability of Nondestructive Evaluation (NDE) and Structural Health Monitoring (SHM) Techniques for Damage Characterization (Post-Print)

DTIC Science & Technology

2016-02-10

a wide range of part, environmental and damage conditions. Best practices of using models are presented for both an eddy current NDE sizing and...to assess the reliability of NDE and SHM characterization capability. Best practices of using models are presented for both an eddy current NDE... EDDY CURRENT NDE CASE STUDY An eddy current crack sizing case study is presented to highlight examples of some of these complex characteristics of

Optimal insemination and replacement decisions to minimize the cost of pathogen-specific clinical mastitis in dairy cows.

PubMed

Cha, E; Kristensen, A R; Hertl, J A; Schukken, Y H; Tauer, L W; Welcome, F L; Gröhn, Y T

2014-01-01

Mastitis is a serious production-limiting disease, with effects on milk yield, milk quality, and conception rate, and an increase in the risk of mortality and culling. The objective of this study was 2-fold: (1) to develop an economic optimization model that incorporates all the different types of pathogens that cause clinical mastitis (CM) categorized into 8 classes of culture results, and account for whether the CM was a first, second, or third case in the current lactation and whether the cow had a previous case or cases of CM in the preceding lactation; and (2) to develop this decision model to be versatile enough to add additional pathogens, diseases, or other cow characteristics as more information becomes available without significant alterations to the basic structure of the model. The model provides economically optimal decisions depending on the individual characteristics of the cow and the specific pathogen causing CM. The net returns for the basic herd scenario (with all CM included) were $507/cow per year, where the incidence of CM (cases per 100 cow-years) was 35.6, of which 91.8% of cases were recommended for treatment under an optimal replacement policy. The cost per case of CM was $216.11. The CM cases comprised (incidences, %) Staphylococcus spp. (1.6), Staphylococcus aureus (1.8), Streptococcus spp. (6.9), Escherichia coli (8.1), Klebsiella spp. (2.2), other treated cases (e.g., Pseudomonas; 1.1), other not treated cases (e.g., Trueperella pyogenes; 1.2), and negative culture cases (12.7). The average cost per case, even under optimal decisions, was greatest for Klebsiella spp. ($477), followed by E. coli ($361), other treated cases ($297), and other not treated cases ($280). This was followed by the gram-positive pathogens; among these, the greatest cost per case was due to Staph. aureus ($266), followed by Streptococcus spp. ($174) and Staphylococcus spp. ($135); negative culture had the lowest cost ($115). The model recommended treatment for most CM cases (>85%); the range was 86.2% (Klebsiella spp.) to 98.5% (Staphylococcus spp.). In general, the optimal recommended time for replacement was up to 5 mo earlier for cows with CM compared with cows without CM. Furthermore, although the parameter estimates implemented in this model are applicable to the dairy farms in this study, the parameters may be altered to be specific to other dairy farms. Cow rankings and values based on disease status, pregnancy status, and milk production can be extracted; these provide guidance when determining which cows to keep or cull. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Relevance of the c-statistic when evaluating risk-adjustment models in surgery.

PubMed

Merkow, Ryan P; Hall, Bruce L; Cohen, Mark E; Dimick, Justin B; Wang, Edward; Chow, Warren B; Ko, Clifford Y; Bilimoria, Karl Y

2012-05-01

The measurement of hospital quality based on outcomes requires risk adjustment. The c-statistic is a popular tool used to judge model performance, but can be limited, particularly when evaluating specific operations in focused populations. Our objectives were to examine the interpretation and relevance of the c-statistic when used in models with increasingly similar case mix and to consider an alternative perspective on model calibration based on a graphical depiction of model fit. From the American College of Surgeons National Surgical Quality Improvement Program (2008-2009), patients were identified who underwent a general surgery procedure, and procedure groups were increasingly restricted: colorectal-all, colorectal-elective cases only, and colorectal-elective cancer cases only. Mortality and serious morbidity outcomes were evaluated using logistic regression-based risk adjustment, and model c-statistics and calibration curves were used to compare model performance. During the study period, 323,427 general, 47,605 colorectal-all, 39,860 colorectal-elective, and 21,680 colorectal cancer patients were studied. Mortality ranged from 1.0% in general surgery to 4.1% in the colorectal-all group, and serious morbidity ranged from 3.9% in general surgery to 12.4% in the colorectal-all procedural group. As case mix was restricted, c-statistics progressively declined from the general to the colorectal cancer surgery cohorts for both mortality and serious morbidity (mortality: 0.949 to 0.866; serious morbidity: 0.861 to 0.668). Calibration was evaluated graphically by examining predicted vs observed number of events over risk deciles. For both mortality and serious morbidity, there was no qualitative difference in calibration identified between the procedure groups. In the present study, we demonstrate how the c-statistic can become less informative and, in certain circumstances, can lead to incorrect model-based conclusions, as case mix is restricted and patients become more homogenous. Although it remains an important tool, caution is advised when the c-statistic is advanced as the sole measure of a model performance. Copyright © 2012 American College of Surgeons. All rights reserved.

Multiple imputation of missing data in nested case-control and case-cohort studies.

PubMed

Keogh, Ruth H; Seaman, Shaun R; Bartlett, Jonathan W; Wood, Angela M

2018-06-05

The nested case-control and case-cohort designs are two main approaches for carrying out a substudy within a prospective cohort. This article adapts multiple imputation (MI) methods for handling missing covariates in full-cohort studies for nested case-control and case-cohort studies. We consider data missing by design and data missing by chance. MI analyses that make use of full-cohort data and MI analyses based on substudy data only are described, alongside an intermediate approach in which the imputation uses full-cohort data but the analysis uses only the substudy. We describe adaptations to two imputation methods: the approximate method (MI-approx) of White and Royston () and the "substantive model compatible" (MI-SMC) method of Bartlett et al. (). We also apply the "MI matched set" approach of Seaman and Keogh () to nested case-control studies, which does not require any full-cohort information. The methods are investigated using simulation studies and all perform well when their assumptions hold. Substantial gains in efficiency can be made by imputing data missing by design using the full-cohort approach or by imputing data missing by chance in analyses using the substudy only. The intermediate approach brings greater gains in efficiency relative to the substudy approach and is more robust to imputation model misspecification than the full-cohort approach. The methods are illustrated using the ARIC Study cohort. Supplementary Materials provide R and Stata code. © 2018, The International Biometric Society.

Thermo-elastic-plastic analysis for elastic component under high temperature fatigue crack growth rate

NASA Astrophysics Data System (ADS)

Ali, Mohammed Ali Nasser

The research project presents a fundamental understanding of the fatigue crack growth mechanisms of AISI 420 martensitic stainless steel, based on the comparison analysis between the theoretical and numerical modelling, incorporating research findings under isothermal fatigue loading for solid cylindrical specimen and the theoretical modelling with the numerical simulation for tubular specimen when subjected to cyclic mechanical loading superimposed by cyclic thermal shock.The experimental part of this research programme studied the fatigue stress-life data for three types of surface conditions specimen and the isothermal stress-controlled fatigue testing at 300 °C - 600 °C temperature range. It is observed that the highest strength is obtained for the polished specimen, while the machined specimen shows lower strength, and the lowest strength is the notched specimen due to the high effect of the stress concentration. The material behaviour at room and high temperatures shows an initial hardening, followed by slow extension until fully plastic saturation then followed by crack initiation and growth eventually reaching the failure of the specimen, resulting from the dynamic strain ageing occurred from the transformation of austenitic microstructure to martensite and also, the nucleation of precipitation at grain boundaries and the incremental temperature increase the fatigue crack growth rate with stress intensity factor however, the crack growth rate at 600 °C test temperature is less than 500 °C because of the creep-fatigue taking place.The theoretical modelling presents the crack growth analysis and stress and strain intensity factor approaches analysed in two case studies based on the addition of thermo-elastic-plastic stresses to the experimental fatigue applied loading. Case study one estimates the thermal stresses superimposed sinusoidal cyclic mechanical stress results in solid cylinder under isothermal fatigue simulation. Case study two estimates the transient thermal stresses superimposed on cyclic mechanical loading results in hollow cylinder under thermal shock in heating case and down shock cooling case. The combination of stress and strain intensity factor theoretical calculations with the experimental output recorded data shows a similar behaviour with increasing temperature, and there is a fair correlation between the profiles at the beginning and then divergence with increasing the crack length. The transient influence of high temperature in case two, giving a very high thermal shock stress as a heating or cooling effects, shifting up the combined stress, when applied a cyclic mechanical load in fraction of seconds, and the reputations of these shocks, causing a fast failure under high thermal shock stress superimposed with mechanical loading.Finally, the numerical modelling analyses three cases studied were solved due to the types of loading and types of specimen geometry by using finite element models constructed through the ANSYS Workbench version 13.0. The first case is a low cyclic fatigue case for a solid cylinder specimen simulated by applying a cyclic mechanical loading. The second is an isothermal fatigue case for solid cylinder specimen simulated by supplying different constant temperatures on the outer surface with cyclic mechanical loading, where the two cases are similar to the experimental tests and the third case, is a thermo-mechanical fatigue for a hollow cylinder model by simulating a thermal up-shock generated due to transient heating on the outer surface of the model or down shock cooling on the inner surface with the cyclic mechanical loading. The results show a good agreement with the experimental data in terms of alternative stress and life in the first case. In case two results show the strain intensity factor is increases with increasing temperature similar to the theoretical solution due to the influence of the modulus of elasticity and the difference in life estimation with the experimental output record is related to the input data made of theoretical physical properties and the experimental stress-life data.

The operating room case-mix problem under uncertainty and nurses capacity constraints.

PubMed

Yahia, Zakaria; Eltawil, Amr B; Harraz, Nermine A

2016-12-01

Surgery is one of the key functions in hospitals; it generates significant revenue and admissions to hospitals. In this paper we address the decision of choosing a case-mix for a surgery department. The objective of this study is to generate an optimal case-mix plan of surgery patients with uncertain surgery operations, which includes uncertainty in surgery durations, length of stay, surgery demand and the availability of nurses. In order to obtain an optimal case-mix plan, a stochastic optimization model is proposed and the sample average approximation method is applied. The proposed model is used to determine the number of surgery cases to be weekly served, the amount of operating rooms' time dedicated to each specialty and the number of ward beds dedicated to each specialty. The optimal case-mix selection criterion is based upon a weighted score taking into account both the waiting list and the historical demand of each patient category. The score aims to maximizing the service level of the operating rooms by increasing the total number of surgery cases that could be served. A computational experiment is presented to demonstrate the performance of the proposed method. The results show that the stochastic model solution outperforms the expected value problem solution. Additional analysis is conducted to study the effect of varying the number of ORs and nurses capacity on the overall ORs' performance.

Power and sample size for multivariate logistic modeling of unmatched case-control studies.

PubMed

Gail, Mitchell H; Haneuse, Sebastien

2017-01-01

Sample size calculations are needed to design and assess the feasibility of case-control studies. Although such calculations are readily available for simple case-control designs and univariate analyses, there is limited theory and software for multivariate unconditional logistic analysis of case-control data. Here we outline the theory needed to detect scalar exposure effects or scalar interactions while controlling for other covariates in logistic regression. Both analytical and simulation methods are presented, together with links to the corresponding software.

Bias correction of risk estimates in vaccine safety studies with rare adverse events using a self-controlled case series design.

PubMed

Zeng, Chan; Newcomer, Sophia R; Glanz, Jason M; Shoup, Jo Ann; Daley, Matthew F; Hambidge, Simon J; Xu, Stanley

2013-12-15

The self-controlled case series (SCCS) method is often used to examine the temporal association between vaccination and adverse events using only data from patients who experienced such events. Conditional Poisson regression models are used to estimate incidence rate ratios, and these models perform well with large or medium-sized case samples. However, in some vaccine safety studies, the adverse events studied are rare and the maximum likelihood estimates may be biased. Several bias correction methods have been examined in case-control studies using conditional logistic regression, but none of these methods have been evaluated in studies using the SCCS design. In this study, we used simulations to evaluate 2 bias correction approaches-the Firth penalized maximum likelihood method and Cordeiro and McCullagh's bias reduction after maximum likelihood estimation-with small sample sizes in studies using the SCCS design. The simulations showed that the bias under the SCCS design with a small number of cases can be large and is also sensitive to a short risk period. The Firth correction method provides finite and less biased estimates than the maximum likelihood method and Cordeiro and McCullagh's method. However, limitations still exist when the risk period in the SCCS design is short relative to the entire observation period.

How Polish Children Switch from One Case to Another when Using Novel Nouns: Challenges for Models of Inflectional Morphology

ERIC Educational Resources Information Center

Krajewski, Grzegorz; Theakston, Anna L.; Lieven, Elena V. M.; Tomasello, Michael

2011-01-01

The two main models of children's acquisition of inflectional morphology--the Dual-Mechanism approach and the usage-based (schema-based) approach--have both been applied mainly to languages with fairly simple morphological systems. Here we report two studies of 2-3-year-old Polish children's ability to generalise across case-inflectional endings…

Therapeutic Assessment for Preadolescent Boys with Oppositional Defiant Disorder: A Replicated Single-Case Time-Series Design

ERIC Educational Resources Information Center

Smith, Justin D.; Handler, Leonard; Nash, Michael R.

2010-01-01

The Therapeutic Assessment (TA) model is a relatively new treatment approach that fuses assessment and psychotherapy. The study examines the efficacy of this model with preadolescent boys with oppositional defiant disorder and their families. A replicated single-case time-series design with daily measures is used to assess the effects of TA and to…

Evaluation of the feasibility of scale modeling to quantify wind and terrain effects on low-angle sound propagation

NASA Technical Reports Server (NTRS)

Anderson, G. S.; Hayden, R. E.; Thompson, A. R.; Madden, R.

1985-01-01

The feasibility of acoustical scale modeling techniques for modeling wind effects on long range, low frequency outdoor sound propagation was evaluated. Upwind and downwind propagation was studied in 1/100 scale for flat ground and simple hills with both rigid and finite ground impedance over a full scale frequency range from 20 to 500 Hz. Results are presented as 1/3-octave frequency spectra of differences in propagation loss between the case studied and a free-field condition. Selected sets of these results were compared with validated analytical models for propagation loss, when such models were available. When they were not, results were compared with predictions from approximate models developed. Comparisons were encouraging in many cases considering the approximations involved in both the physical modeling and analysis methods. Of particular importance was the favorable comparison between theory and experiment for propagation over soft ground.

The rising impact of mathematical modelling in epidemiology: antibiotic resistance research as a case study

PubMed Central

TEMIME, L.; HEJBLUM, G.; SETBON, M.; VALLERON, A. J.

2008-01-01

SUMMARY Mathematical modelling of infectious diseases has gradually become part of public health decision-making in recent years. However, the developing status of modelling in epidemiology and its relationship with other relevant scientific approaches have never been assessed quantitatively. Herein, using antibiotic resistance as a case study, 60 published models were analysed. Their interactions with other scientific fields are reported and their citation impact evaluated, as well as temporal trends. The yearly number of antibiotic resistance modelling publications increased significantly between 1990 and 2006. This rise cannot be explained by the surge of interest in resistance phenomena alone. Moreover, modelling articles are, on average, among the most frequently cited third of articles from the journal in which they were published. The results of this analysis, which might be applicable to other emerging public health problems, demonstrate the growing interest in mathematical modelling approaches to evaluate antibiotic resistance. PMID:17767792

Wind Field Extractions from SAR Sentinel-1 Images Using Electromagnetic Models

NASA Astrophysics Data System (ADS)

La, Tran Vu; Khenchaf, Ali; Comblet, Fabrice; Nahum, Carole

2016-08-01

Among available wind sources, i.e. measured data, numeric weather models, the retrieval of wind vectors from Synthetic Aperture Radar (SAR) data / images is particularly preferred due to a lot of SAR systems (available data in most meteorological conditions, revisit mode, high resolution, etc.). For this purpose, the retrieval of wind vectors is principally based on the empirical (EP) models, e.g. CMOD series in C-band. Little studies have been reported about the use of the electromagnetic (EM) models for wind vector retrieval, since it is quite complicated to invert. However, the EM models can be applied for most cases of polarization, frequency and wind regime. In order to evaluate the advantages and limits of the EM models for wind vector retrieval, we compare in this study estimated results by the EM and EP models for both cases of polarization (vertical-vertical, or VV-pol and horizontal- horizontal, or HH-pol).

[Case finding in early prevention networks - a heuristic for ambulatory care settings].

PubMed

Barth, Michael; Belzer, Florian

2016-06-01

One goal of early prevention is the support of families with small children up to three years who are exposed to psychosocial risks. The identification of these cases is often complex and not well-directed, especially in the ambulatory care setting. Development of a model of a feasible and empirical based strategy for case finding in ambulatory care. Based on the risk factors of postpartal depression, lack of maternal responsiveness, parental stress with regulation disorders and poverty a lexicographic and non-compensatory heuristic model with simple decision rules, will be constructed and empirically tested. Therefore the original data set from an evaluation of the pediatric documentary form on psychosocial issues of families with small children in well-child visits will be used and reanalyzed. The first diagnostic step in the non-compensatory and hierarchical classification process is the assessment of postpartal depression followed by maternal responsiveness, parental stress and poverty. The classification model identifies 89.0 % cases from the original study. Compared to the original study the decision process becomes clearer and more concise. The evidence-based and data-driven model exemplifies a strategy for the assessment of psychosocial risk factors in ambulatory care settings. It is based on four evidence-based risk factors and offers a quick and reliable classification. A further advantage of this model is that after a risk factor is identified the diagnostic procedure will be stopped and the counselling process can commence. For further validation of the model studies, in well suited early prevention networks are needed.

Understanding the role of individual consumer-provider relationships within assertive community treatment.

PubMed

Stanhope, Victoria; Matejkowski, Jason

2010-08-01

The widespread adoption of assertive community treatment has resulted in a shift from an individual model to a team model of case management. The shift has had implications for individual relationships between case managers and consumers, but still little is known about how these relationships develop in teams. This exploratory mixed methods study looked at how case managers and consumers negotiate individual relationships within a team model. Quantitative methods identified high and low service intensity relationships between consumers and case managers and qualitative methods explored and compared these relationships. Consumers in high service intensity relationships described a preference for certain case managers and the burden of working with multiple people. Case managers invested high service intensity relationships with special therapeutic value, articulated the challenges of coordinating care across the team, and utilized team limit setting techniques. In contrast, low service intensity relationships were more likely to reflect integration with the entire team. Findings suggest that teams need to consider how individual relationships enhance care for their consumers and how to nurture these relationships while maintaining the support necessary for case managers and consumers.

Simulated Radar Characteristics of LBA Convective Systems: Easterly and Westerly Regimes

NASA Technical Reports Server (NTRS)

Lang, Stephen E.; Tao, Wei-Kuo; Simpson, Joanne

2003-01-01

The 3D Goddard Cumulus Ensemble (GCE) model was used to simulate convection that occurred during the TRMM LBA field experiment in Brazil. Convection in this region can be categorized into two different regimes. Low-level easterly flow results in moderate to high CAPE and a drier environment. Convection is more intense like that seen over continents. Low-level westerly flow results in low CAPE and a moist environment. Convection is weaker and more widespread characteristic of oceanic or monsoon-like systems. The GCE model has been used to study both regimes n order to provide cloud datasets that are representative of both environments in support of TRMM rainfall and heating algorithm development. Two different cases are analyzed: Jan 26, 1999, an eastely regime case, and Feb 23, 1999, a westerly regime case. The Jan 26 case is an organized squall line, while the Feb 23 case is less organized with only transient lines. Radar signatures, including CFADs, from the two simulated cases are compared to each other and with observations. The microphysical processes simulated in the model are also compared between the two cases.

Examining of Model Eliciting Activities Developed by Mathematics Student Teachers

ERIC Educational Resources Information Center

Dede, Ayse Tekin; Hidiroglu, Çaglar Naci; Güzel, Esra Bukova

2017-01-01

The purpose of this study is to examine the model eliciting activities developed by the mathematics student teachers in the context of the principles of the model eliciting activities. The participants of the study conducted as a case study design were twenty one mathematics student teachers working on seven groups. The data collection tools were…

Intercomparison of the community multiscale air quality model and CALGRID using process analysis.

PubMed

O'Neill, Susan M; Lamb, Brian K

2005-08-01

This study was designed to examine the similarities and differences between two advanced photochemical air quality modeling systems: EPA Models-3/CMAQ and CALGRID/CALMET. Both modeling systems were applied to an ozone episode that occurred along the I-5 urban corridor in western Washington and Oregon during July 11-14, 1996. Both models employed the same modeling domain and used the same detailed gridded emission inventory. The CMAQ model was run using both the CB-IV and RADM2 chemical mechanisms, while CALGRID was used with the SAPRC-97 chemical mechanism. Outputfrom the Mesoscale Meteorological Model (MM5) employed with observational nudging was used in both models. The two modeling systems, representing three chemical mechanisms and two sets of meteorological inputs, were evaluated in terms of statistical performance measures for both 1- and 8-h average observed ozone concentrations. The results showed that the different versions of the systems were more similar than different, and all versions performed well in the Portland region and downwind of Seattle but performed poorly in the more rural region north of Seattle. Improving the meteorological input into the CALGRID/CALMET system with planetary boundary layer (PBL) parameters from the Models-3/CMAQ meteorology preprocessor (MCIP) improved the performance of the CALGRID/CALMET system. The 8-h ensemble case was often the best performer of all the cases indicating that the models perform better over longer analysis periods. The 1-h ensemble case, derived from all runs, was not necessarily an improvement over the five individual cases, but the standard deviation about the mean provided a measure of overall modeling uncertainty. Process analysis was applied to examine the contribution of the individual processes to the species conservation equation. The process analysis results indicated that the two modeling systems arrive at similar solutions by very different means. Transport rates are faster and exhibit greater fluctuations in the CMAQ cases than in the CALGRID cases, which lead to different placement of the urban ozone plumes. The CALGRID cases, which rely on the SAPRC97 chemical mechanism, exhibited a greater diurnal production/loss cycle of ozone concentrations per hour compared to either the RADM2 or CBIV chemical mechanisms in the CMAQ cases. These results demonstrate the need for specialized process field measurements to confirm whether we are modeling ozone with valid processes.

BASINs and WEPP Climate Assessment Tools (CAT): Case Study Guide to Potential Applications (Final Report)

EPA Science Inventory

EPA announced the release of the final report, BASINs and WEPP Climate Assessment Tools (CAT): Case Study Guide to Potential Applications. This report supports application of two recently developed water modeling tools, the Better Assessment Science Integrating point & ...

Comprehensive Stuttering Treatment or Adolescents: A Case Study

ERIC Educational Resources Information Center

Coleman, Craig E.

2018-01-01

Purpose: This article will focus on a hypothetical case study to highlight comprehensive assessment and treatment for adolescent children who stutter. Method: Assessment and treatment are laid out with a literature review utilizing the components of the International Classification of Functioning, Disability and Health model. Specific assessment…

Overshooting convection during TRO-pico: mesoscale modelling of two cases hydrating the lower stratosphere

NASA Astrophysics Data System (ADS)

Rivière, Emmanuel; Marécal, Virginie; Khaykin, Sergey; Amarouche, Nadir; Ghysels, Mélanie; Mappe-Fogaing, Irène; Behera, Abhinna; Held, Gerhard; França, Hermes

2016-04-01

One of the main aims of the TRO-pico project (2010-2015) was to study the variability of overshooting convection at the local scale to try to deduce a typical impact on the TTL water at the global scale. In this study, we've identified local maximum in the water vapour profiles gathered by the balloon-borne hygrometers Pico-SDLA and Flash above Bauru, Brazil (22.3 S) during the TRO-pico campaign. We tried to link them to overshooting cells in the surrounding of Bauru with a trajectory analysis. In this study we select a couple of cases of overshooting convection both sampled by the Bauru S-Band radar and by one of the balloon-borne instruments of the TRO-pico campaign in 2012 and 2013. The selected cases are the case of March 13, 2012 (hereafter M12), sounded by both hygrometers Pico-SDLA and FLASH, and the case of January 26, 2013 (hereafter J13), sounded by Pico-SDLA. For the M12 case, local water vapour enhancements at two different altitudes due to two different cells were reported, with local enhancement of about 0.65 ppmv. For the J26 case, the water enhancement was about 1 ppmv. The corresponding mesoscale simulations with the Brazilian Regional Atmospheric Modelling System (BRAMS) using 3 nested grids with horizontal resolution down to 800 m were carried out. Simulation results are compared to Bauru's radar echo tops and and water vapour in situ measurements. As for the M12 simulation, the model is doing a rather good job in reproducing several overshooting cells, both in severity and timing. Associated stratospheric water budget are computed for each cases.

Case management training needs to support vocational rehabilitation for case managers and general practitioners: a survey study

PubMed Central

2014-01-01

Background The use of the biopsychosocial model of health and case management for effective vocational rehabilitation (VR) has been confirmed for many health conditions. While Case and Condition Managers (CCMPs) use this approach in their everyday work, little is known about their views on training needs. A review of the training curriculum for General Practitioners’ (GPs) revealed little training in VR and the biopsychosocial model of care. This study aims to identify Case and Condition Managers and GPs perceptions of their training needs in relation to employability and VR. Methods 80 Case and Condition Managers and 304 GPs working in NHS Lanarkshire, providing a comparison group, were invited to participate in this study. A self-completion questionnaire was developed and circulated for online completion with a second round of hardcopy questionnaires distributed. Results In total 45 responses were obtained from CCMPs, 5 from occupational health nurses (62% response rate) and 60 from GPs (20% response rate). CCMPs and the nursing group expressed a need for training but to a lesser extent than GP’s. The GP responses demonstrated a need for high levels of training in case/condition management, the biopsychosocial model, legal and ethical issues associated with employment and VR, and management training. Conclusions This survey confirms a need for further training of CCMPs and that respondent GPs in one health board are not fully equipped to deal with patients employability and vocational needs. GPs also reported a lack of understanding about the role of Case and Condition managers. Training for these professional groups and others involved in multidisciplinary VR could improve competencies and mutual understanding among those advising patients on return-to-work. PMID:24884477

Training the Next Generation of Scientists: System Dynamics Modeling of Chagas Disease (American Trypanosomiasis) transmission.

NASA Astrophysics Data System (ADS)

Goff, P.; Hulse, A.; Harder, H. R.; Pierce, L. A.; Rizzo, D.; Hanley, J.; Orantes, L.; Stevens, L.; Justi, S.; Monroy, C.

2015-12-01

A computational simulation has been designed as an investigative case study by high school students to introduce system dynamics modeling into high school curriculum. This case study approach leads users through the forensics necessary to diagnose an unknown disease in a Central American village. This disease, Chagas, is endemic to 21 Latin American countries. The CDC estimates that of the 110 million people living in areas with the disease, 8 million are infected, with as many as 300,000 US cases. Chagas is caused by the protozoan parasite, Trypanosoma cruzi, and is spread via blood feeding insect (vectors), that feed on vertebrates and live in crevasses in the walls and roofs of adobe homes. One-third of the infected people will develop chronic Chagas who are asymptomatic for years before their heart or GI tract become enlarged resulting in death. The case study has three parts. Students play the role of WHO field investigators and work collaboratively to: 1) use genetics to identify the host(s) and vector of the disease 2) use a STELLA™ SIR (Susceptible, Infected, Recovered) system dynamics model to study Chagas at the village scale and 3) develop management strategies. The simulations identify mitigation strategies known as Ecohealth Interventions (e.g., home improvements using local materials) to help stakeholders test and compare multiple optima. High school students collaborated with researchers from the University of Vermont, Loyola University and Universidad de San Carlos, Guatemala, working in labs, interviewing researchers, and incorporating mulitple field data as part of a NSF-funded multiyear grant. The model displays stable equilibria of hosts, vectors, and disease-states. Sensitivity analyses show measures of household condition and presence of vertebrates were significant leverage points, supporting other findings by the University research team. The village-scale model explores multiple solutions to disease mitigation for the purpose of producing students who can think long-term, better understand feedbacks, and anticipate unexpected consequences associated with non-linear systems. This case study enables high school teachers to incorporate ongoing research, systems modeling, and engineering design, three core goals Next Generation Science Standards and STEM initiatives.