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Background: Early identification and treatment of chronic disease is associated with better clinical outcomes, lower costs, and reduced hospitalisation. Primary care is ideally placed to identify patients at risk of, or in the early stages of, chronic disease and to implement prevention and early intervention measures. This paper evaluates the implementation of a technological intervention called Future Health Today that integrates with general practice EMRs to (1) identify patients at-risk of, or with undiagnosed or untreated, chronic kidney disease (CKD), and (2) provide guideline concordant recommendations for patient care. The evaluation aimed to identify the barriers and facilitators to successful implementation. Methods: Future Health Today was implemented in 12 general practices in Victoria, Australia. Fifty-two interviews with 30 practice staff were undertaken between July 2020 and April 2021. Practice characteristics were collected directly from practices via survey. Data were analysed using inductive and deductive qualitative analysis strategies, using Clinical Performance - Feedback Intervention Theory (CP-FIT) for theoretical guidance. Results: Future Health Today was acceptable, user friendly and useful to general practice staff, and supported clinical performance improvement in the identification and management of chronic kidney disease. CP-FIT variables supporting use of FHT included the simplicity of design and delivery of actionable feedback via FHT, good fit within existing workflow, strong engagement with practices and positive attitudes toward FHT. Context variables provided the main barriers to use and were largely situated in the external context of practices (including pressures arising from the COVID-19 pandemic) and technical glitches impacting installation and early use. Participants primarily utilised the point of care prompt rather than the patient management dashboard due to its continued presence, and immediacy and relevance of the recommendations on the prompt, suggesting mechanisms of compatibility, complexity, actionability and credibility influenced use. Most practices continued using FHT after the evaluation phase was complete. Conclusions: This study demonstrates that FHT is a useful and acceptable software platform that provides direct support to general practice in identifying and managing patients with CKD. Further research is underway to explore the effectiveness of FHT, and to expand the conditions on the platform. [ABSTRACT FROM AUTHOR]

Thousands of people are reported lost in the wilderness in the United States every year and locating these missing individuals as rapidly as possible depends on coordinated search and rescue (SAR) operations. As time passes, the search area grows, survival rate decreases, and searchers are faced with an increasingly daunting task of searching large areas in a short amount of time. To optimize the search process, mathematical models of lost person behavior with respect to landscape can be used in conjunction with current SAR practices. In this paper, we introduce an agent-based model of lost person behavior which allows agents to move on known landscapes with behavior defined as independent realizations of a random variable. The behavior random variable selects from a distribution of six known lost person reorientation strategies to simulate the agent's trajectory. We systematically simulate a range of possible behavior distributions and find a best-fit behavioral profile for a hiker with the International Search and Rescue Incident Database. We validate these results with a leave-one-out analysis. This work represents the first time-discrete model of lost person dynamics validated with data from real SAR incidents and has the potential to improve current methods for wilderness SAR. [ABSTRACT FROM AUTHOR]

The article reviews the article "Moody's Mega Math Challenge Winning Paper: Making Sense of the 2010 Census," by A. Das Sarma and colleagues, which appeared in the "SIAM Undergraduate Research Online" (SIURO) 3 on August 4, 2010.

Background: Since spring 2013, periodic emergence of avian influenza A(H7N9) virus in China has heightened the concern for a possible pandemic outbreak among humans, though it is believed that the virus is not yet human-to-human transmittable. Till June 2017, A(H7N9) has resulted in 1533 laboratory-confirmed cases of human infections causing 592 deaths. The aim of this paper is to present disease burden estimates (measured by infection attack rates (IAR) and number of deaths) in the event of a possible pandemic outbreak caused by human-to-human transmission capability acquired by A(H7N9) virus. Even though such a pandemic will likely spread worldwide, our focus in this paper is to estimate the impact on the United States alone.Method: The method first uses a data clustering technique to divide 50 states in the U.S. into a small number of clusters. Thereafter, for a few selected states in each cluster, the method employs an agent-based (AB) model to simulate human A(H7N9) influenza pandemic outbreaks. The model uses demographic and epidemiological data. A few selected non-pharmaceutical intervention (NPI) measures are applied to mitigate the outbreaks. Disease burden for the U.S. is estimated by combining results from the clusters applying a method used in stratified sampling.Results: Two possible pandemic scenarios with R 0 = 1.5 and 1.8 are examined. Infection attack rates with 95% C.I. (Confidence Interval) for R 0 = 1.5 and 1.8 are estimated to be 18.78% (17.3-20.27) and 25.05% (23.11-26.99), respectively. The corresponding number of deaths (95% C.I.), per 100,000, are 7252.3 (6598.45-7907.33) and 9670.99 (8953.66-10,389.95).Conclusions: The results reflect a possible worst-case scenario where the outbreak extends over all states of the U.S. and antivirals and vaccines are not administered. Our disease burden estimations are also likely to be somewhat high due to the fact that only dense urban regions covering approximately 3% of the geographic area and 81% of the population are used for simulating sample outbreaks. Outcomes from these simulations are extrapolated over the remaining 19% of the population spread sparsely over 97% of the area. Furthermore, the full extent of possible NPIs, if deployed, could also have lowered the disease burden estimates. [ABSTRACT FROM AUTHOR]

Background: Over the past few decades, numerous forecasting methods have been proposed in the field of epidemic forecasting. Such methods can be classified into different categories such as deterministic vs. probabilistic, comparative methods vs. generative methods, and so on. In some of the more popular comparative methods, researchers compare observed epidemiological data from the early stages of an outbreak with the output of proposed models to forecast the future trend and prevalence of the pandemic. A significant problem in this area is the lack of standard well-defined evaluation measures to select the best algorithm among different ones, as well as for selecting the best possible configuration for a particular algorithm.Results: In this paper we present an evaluation framework which allows for combining different features, error measures, and ranking schema to evaluate forecasts. We describe the various epidemic features (Epi-features) included to characterize the output of forecasting methods and provide suitable error measures that could be used to evaluate the accuracy of the methods with respect to these Epi-features. We focus on long-term predictions rather than short-term forecasting and demonstrate the utility of the framework by evaluating six forecasting methods for predicting influenza in the United States. Our results demonstrate that different error measures lead to different rankings even for a single Epi-feature. Further, our experimental analyses show that no single method dominates the rest in predicting all Epi-features when evaluated across error measures. As an alternative, we provide various Consensus Ranking schema that summarize individual rankings, thus accounting for different error measures. Since each Epi-feature presents a different aspect of the epidemic, multiple methods need to be combined to provide a comprehensive forecast. Thus we call for a more nuanced approach while evaluating epidemic forecasts and we believe that a comprehensive evaluation framework, as presented in this paper, will add value to the computational epidemiology community. [ABSTRACT FROM AUTHOR]

Lung cancer, primarily non-small-cell lung cancer (NSCLC), is the leading cause of cancer deaths in the United States and worldwide. While early detection significantly improves five-year survival, there are no reliable diagnostic tools for early detection. Several exosomal microRNAs (miRs) are overexpressed in NSCLC, and have been suggested as potential biomarkers for early detection. The present paper develops a mathematical model for early stage of NSCLC with emphasis on the role of the three highest overexpressed miRs, namely miR-21, miR-205 and miR-155. Simulations of the model provide quantitative relationships between the tumor volume and the total mass of each of the above miRs in the tumor. Because of the positive correlation between these miRs in the tumor tissue and in the blood, the results of the paper may be viewed as a first step toward establishing a combination of miRs 21, 205, 155 and possibly other miRs as serum biomarkers for early detection of NSCLC. [ABSTRACT FROM AUTHOR]

The paper presents some optimization dynamic mathematical models of the military aggressive subordinating interactions of two States in favor of one of them, created on the base of the optimization dynamic mathematical model of a State earlier constructed by the Author. [ABSTRACT FROM AUTHOR]

Perinatal mental health problems, experienced by 15-20% of women, are a significant public health issue associated with adverse effects among childbearing women; yet only 20-25% receive adequate treatment. There has been a recent proliferation of intensive perinatal day treatment programs in the United States. To meet this need in the greater Philadelphia area, we introduce Mother Baby Connections (MBC), an innovative interdisciplinary, attachment-focused, intensive, outpatient perinatal mental health program recently launched at Drexel University. The purpose of this paper is to (1) present an overview of MBC, its theoretical framework for services, and its evidence-based components, highlighting the unique factors that differentiate this program from traditional outpatient treatment, and (2) present clinical outcome data utilizing scores from reliable and valid scales, including enrollment to discharge outcomes from 20 months of MBC operation. In sum, outcomes for 20 predominantly minority women with complete measures showed significant improvements in maternal depression symptom severity, maternal functioning, birth trauma symptoms, perceived stress, parenting stress, and emotional regulation. Effect sizes were medium to large (i.e., 0.42-2.00). We conclude that MBC is a viable model for tailored intensive outpatient treatment to foster maternal mental health and functioning during the perinatal period. [ABSTRACT FROM AUTHOR]

Visceral leishmaniasis (VL), one of the deadliest parasitic diseases in the world, causes more than 50,000 human deaths each year and afflicts millions of people throughout South America, East Africa, South Asia, and Mediterranean Region. In 2015 the World Health Organization classified VL as a neglected tropical disease (NTD), prompting concentrated study of the VL epidemic using mathematical and simulation models. This paper reviews literature related to prevalence and prevention control strategies. More than thirty current research works were reviewed and classified based on VL epidemic study methods, including modeling approaches, control strategies, and simulation techniques since 2013. A summarization of these technical methods, major findings, and contributions from existing works revealed that VL epidemic research efforts must improve in the areas of validating and verifying VL mathematical models with real-world epidemic data. In addition, more dynamic disease control strategies must be explored and advanced simulation techniques must be used to predict VL pandemics. [ABSTRACT FROM AUTHOR]

This paper proposes the use of two indicators of the predictability of the load series along with an accuracy value such as mean average percentage error as standard measures of load forecasting performance. Over the last 10 years, there has been a significant increase in load forecasting models proposed in engineering journals. Most of these models provide a description of the inner design of the model, the results from applying this model to a specific data base and the conclusions drawn from this application. However, a single accuracy value may not be sufficient to describe the performance of the model when applied to other data bases. The aim of this paper is to provide researchers with a tool that is able to assess the predictability of a load series and, therefore, contextualize the forecasting accuracy reported. Nine different data bases from the U.S. have been used; all of them include hourly load and temperature data. [ABSTRACT FROM PUBLISHER]

Abstract: Weak roof conditions in underground coal mines are a common occurrence and cause significant problems in delaying production. This work presents innovative way of using directional drilling method for roof support in weak sandstone conditions other than conventional method such as bolting, trussing, and cribbing methods. This paper presents a conceptual model of pipe umbrella roof support methods intended for employment in the underground coal mining environment over a single entry of a development section. The design methodology was evaluated by examining a case study of a western U.S. coal mine, and its specific geologic conditions. This work used extensive literature reviews and laboratory test results of the mine. Geotechnical laboratory testing was performed for a weak sandstone channel material that occurs in large extents at the mine for input into numerical models. 2D and 3D models in FLAC were developed. These models utilize beam elements embedded in the continuum model. Results from the modeling showed that bending moments vary in the embedded beams based on the pipe spacing and the diameter of the pipes. A design criterion for a pipe umbrella system was based on the developed bending moment due to undermining and the commonly used flexure formula for bending stress. A safety factor approach was used in this paper for the design of a pipe umbrella system. [Copyright &y& Elsevier]

Abstract: This paper analyzes the impact of voucher design on student sorting in the application and enrollment phases of parental choice. Much of the existing literature investigates the question of sorting where private schools can screen students. However, the publicly funded U.S. voucher programs require private schools to accept all students unless oversubscribed and to pick students randomly if oversubscribed. In the context of a theoretical model, this paper argues that this feature coupled with the absence of topping up of vouchers can preclude sorting by income in the application stage, although there is still sorting by ability. This design can avert sorting by ability in the enrollment stage, but revelation of new monetary costs can lead to sorting by income. Using a logit model and student level data from the Milwaukee voucher program for 1990–1994, this study finds robust evidence that this indeed has been the case in reality. [Copyright &y& Elsevier]

Crew costs are a significant portion of rail operating expenses, and so effective deployment of train crews is an important priority for freight railroads. This paper proposes an optimization model and develops an effective solution approach to assign crews to trains and decide when to deadhead crew members in double-ended crew districts in U.S. freight railways. To solve this model quickly, we develop several modeling and methodological enhancements including methods to reduce the problem size, strengthen the model, and generate good heuristic solutions. Computational testing and validation using 140 real-life problem instances demonstrate that our algorithm can find optimal and implementable solutions very quickly (typically within one minute), making it well-suited for practical use to provide real-time decision support to crew planners. [ABSTRACT FROM AUTHOR]

The paper presents the journey of the Pipistrel's Taurus G4, the World's first four-seat electric aeroplane and winner of the NASA Green Flight Challenge 2011, sponsored by Google, from idea to completion of competition. At the beginning, the race event and qualification requirements are presented. The selection of the aeroplane's configuration and sizing is discussed, and emphasis given to the unique twin-fuselage configuration. Next, the architecture of the electrical systems on board the aeroplane, including the large battery pack and propulsion elements is presented. In the second part of the paper, authors give an insight to the 40-hour flight test, the challenges encountered and the preparation to the race event itself. A non-linear mathematical performance model was developed to predict performance of the Taurus G4 during the two race events and used for flight planning and in-flight online performance optimisation. Instead of the conclusion, the results of the NASA Green Flight Challenge 2011 are presented and discussed, together with a comparison to other participating teams' results. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents an optimal control strategy suitable for investigating the mission performance of a spacecraft equipped with a NASAʼs Evolutionary Xenon Thruster. Using an accurate mathematical model of the propulsion system, based on both experimental data and a semi-empirical schematization of the power generation system, the minimum-time rendezvous problem with various celestial bodies is investigated through an indirect approach. Unlike a conventional approach, in which the thruster power is varied with continuity within a given range, here the solar electric propulsion system is described using a finite number of operation points, characterized by different pairs of thruster input power and propellant mass flow rate. The model includes the possibility of obtaining coasting phases along the spacecraft trajectory. The optimal control strategy is found for a three-dimensional problem in which the actual shape and relative orientation of the initial and final orbits are taken into account. The paper presents the simulation results for a number of minimum-time trajectories towards inner planets (Mercury, Venus, and Mars) and three Near Earth Asteroids (NEAs) of particular interest for the scientific community: 1998 KY-26, 99942 Apophis, and 2007 VK-184. [Copyright &y& Elsevier]

This paper proposes a new framework in calculating the ex post prices for the spot electricity market. The proposed method finds a set of prices that are as consistent as possible with the actual outputs of resources correctly following their dispatch instructions. Two alternative consistency metrics are proposed in the paper. One measures the difference between the actual performance of an individual resource and its bid-based profit-maximizing response to the ex post prices in a perfectly competitive market. Another measures the difference between the ex post price and the price that supports the actual response of an individual resource. Compared to the existing approaches adopted in the real-time electricity markets in the U.S., the proposed method solves the ex post energy and ancillary service prices directly and simultaneously. It does not require heuristics that are hard to justify, and has a much clear definition for the pricing problem than the existing approaches do. Moreover, the proposed approach is flexible in the price control required by the market operators. Numerical examples are presented to further demonstrate the validity of this approach. [ABSTRACT FROM AUTHOR]

Abstract: This paper examines the relationship between contemporary racial inequality of schooling and the black–white wage gap in the U.S. In particular I ask: what policies would be effective at reducing the black–white wage gap in the U.S.? In order to address this question, I develop a model of human capital accumulation in which agents differ by race. I calibrate the model to reflect the U.S. system of education financing since the mid-1950s, and find that more than half of the black–white wage gap in the U.S. in the early 1990s can be accounted for by differential human capital accumulation by race. This indicates an increased role for policy in addressing racial inequality in the U.S. The results of the policy experiments conducted in this paper indicate that a conditional cash transfer program and a policy of decreased reliance on local property tax revenue would be effective in reducing the black–white skill and wage gaps. [Copyright &y& Elsevier]

This paper analyses the causal relationship between highway infrastructure and employment within the U.S. We estimate dynamic panel models in a vector autoregressive framework using time-series cross-sectional data on lane miles of roadway capacity and private sector employment for the 48 contiguous states over the period 1984–1997. The issue of spatial dependence is explicitly taken into account by means of a spatial filtering technique. Our analysis reveals evidence of employment growth temporally influenced by annual growth in the provision of major highways within the same state and all other states, as well as the other way around. However, the results show that the existence and direction of these temporal and spatial effects depend on the type of highways and time lags considered. [ABSTRACT FROM AUTHOR]

In Part I of this paper, we presented a large-scale airspace-planning and collaborative decision-making (APCDM) model that is part of a Federal Aviation Administration (FAA)-sponsored effort to enhance the management of the National Airspace System (NAS). Given a set of flights that must be scheduled during some planning horizon, along with alternative surrogate trajectories for each flight, we developed a mixed-integer programming model to select a set of flight plans from among these alternatives, subject to flight safety, airtraffic control workload, and airline equity considerations. The present paper offers insights related to, and a detailed description of, implementing this APCDM model, including the development of a comprehensive cost model, a study for prescribing a set of appropriate parameter values for the overall model, and an investigation on incorporating a suitable set of valid inequalities in the model formulation. Computational results are presented based on several test cases derived from the Enhanced Traffic Management System (ETMS) data provided by the FAA. The results indicate that under plausible probabilistic trajectory error assumptions and with the incorporation of star subgraph convex hull-based valid inequalities, the model offers a viable tool that can be used by the FAA for both tactical and strategic applications. [ABSTRACT FROM AUTHOR]

Energy system optimization models (ESOMs) should be used in an interactive way to uncover knife-edge solutions, explore alternative system configurations, and suggest different ways to achieve policy objectives under conditions of deep uncertainty. In this paper, we do so by employing an existing optimization technique called modeling to generate alternatives (MGA), which involves a change in the model structure in order to systematically explore the near-optimal decision space. The MGA capability is incorporated into Tools for Energy Model Optimization and Analysis (Temoa), an open source framework that also includes a technology rich, bottom up ESOM. In this analysis, Temoa is used to explore alternative energy futures in a simplified single region energy system that represents the U.S. electric sector and a portion of the light duty transport sector. Given the dataset limitations, we place greater emphasis on the methodological approach rather than specific results. [ABSTRACT FROM AUTHOR]

There are currently over 2.5 million breast cancer survivors in the United States and, according to the American Cancer Society, 10 to 20 percent of these women will develop recurrent breast cancer. Early detection of recurrence can avoid unnecessary radical treatment. However, self-examination or mammography screening may not discover a recurring cancer if the number of surviving cancer cells is small, while biopsy is too invasive and cannot be frequently repeated. It is therefore important to identify non-invasive biomarkers that can detect early recurrence. The present paper develops a mathematical model of cancer recurrence. The model, based on a system of partial differential equations, focuses on tissue biomarkers that include the plasminogen system. Among them, only uPAR is known to have significant correlation to its concentration in serum and could therefore be a good candidate for serum biomarker. The model includes uPAR and other associated cytokines and cells. It is assumed that the residual cancer cells that survived primary cancer therapy are concentrated in the same location within a region with a very small diameter. Model simulations establish a quantitative relation between the diameter of the growing cancer and the total uPAR mass in the cancer. This relation is used to identify uPAR as a potential serum biomarker for breast cancer recurrence. [ABSTRACT FROM AUTHOR]

Value stream mapping (VSM) assists in identifying opportunities for improvement by revealing the inefficiencies in the current state. However, several difficulties appear while evaluating such 'as-is' state for leaner future state. Trial and error method is often employed for continuous improvement to accomplish the desired level of future state. This causes numerous iterations and improper usage of resources which makes lean application costly and inefficient. In order to tackle this, an immersive virtual reality (IVR) approach to visualize and interact with the image of real models in a computer graphics environment is presented in this article. This allows conducting a quick experimentation in a virtual world to reach optimal future state without exhausting resources or incurring additional cost. In order to reinforce applicability and usefulness of the proposed framework, a case study of an US-based SME is also discussed. This paper first illustrates the implementation procedure of VSM in the manufacturing processes to develop current and future states. Data is collected for a year to analyse the current state and then IVR is used to validate results for future state. A reduction of more than 40 % in lead-time, 41 % in floor space and 47 % in manpower is achieved after a period of 3 months of implementing the recommendations. [ABSTRACT FROM AUTHOR]

Idiopathic pulmonary fibrosis (IPF) is a disease of unknown etiology, and life expectancy of 3-5 years after diagnosis. The incidence rate in the United States is estimated as high as 15 per 100,000 persons per year. The disease is characterized by repeated injury to the alveolar epithelium, resulting in inflammation and deregulated repair, leading to scarring of the lung tissue, resulting in progressive dyspnea and hypoxemia. The disease has no cure, although new drugs are in clinical trials and two agents have been approved for use by the FDA. In the present paper we develop a mathematical model based on the interactions among cells and proteins that are involved in the progression of the disease. The model simulations are shown to be in agreement with available lung tissue data of human patients. The model can be used to explore the efficacy of potential drugs. [ABSTRACT FROM AUTHOR]

Background: Annually since 2010, the University of Wisconsin Population Health Institute and the Robert Wood Johnson Foundation have produced the County Health Rankings--a "population health checkup" for the nation's over 3,000 counties. The purpose of this paper is to review the background and rationale for the Rankings, explain in detail the methods we use to create the health rankings in each state, and discuss the strengths and limitations associated with ranking the health of communities. Methods: We base the Rankings on a conceptual model of population health that includes both health outcomes (mortality and morbidity) and health factors (health behaviors, clinical care, social and economic factors, and the physical environment). Data for over 30 measures available at the county level are assembled from a number of national sources. Z-scores are calculated for each measure, multiplied by their assigned weights, and summed to create composite measure scores. Composite scores are then ordered and counties are ranked from best to worst health within each state. Results: Health outcomes and related health factors vary significantly within states, with over two-fold differences between the least healthy counties versus the healthiest counties for measures such as premature mortality, teen birth rates, and percent of children living in poverty. Ranking within each state depicts disparities that are not apparent when counties are ranked across the entire nation. Discussion: The County Health Rankings can be used to clearly demonstrate differences in health by place, raise awareness of the many factors that influence health, and stimulate community health improvement efforts. The Rankings draws upon the human instinct to compete by facilitating comparisons between neighboring or peer counties within states. Since no population health model, or rankings based off such models, will ever perfectly describe the health of its population, we encourage users to look to local sources of data to understand more about the health of their community. [ABSTRACT FROM AUTHOR]

In recently developed hierarchical age-period-cohort (HAPC) models, inferential questions arise: How can one assess or judge the significance of estimates of individual cohort and period effects in such models? And how does one assess the overall statistical significance of the cohort and/or the period effects? Beyond statistical significance is the question of substantive significance. This paper addresses these questions. In the context of empirical applications of linear and generalized linear mixed-model specifications of HAPC models using data on verbal test scores and voter turnout in U.S. presidential elections, respectively, we describe a two-step approach and a set of guidelines for assessing statistical significance. The guidelines include assessments of patterns of effects and statistical tests both for the effects of individual cohorts and time periods as well as for entire sets of cohorts and periods. The empirical applications show strong evidence that trends in verbal test scores are primarily cohort driven, while voter turnout is primarily a period phenomenon. [ABSTRACT FROM PUBLISHER]

A topic of recent interest in the retail financial sector has been the growth of credit unions or 'pure cooperatives'. Past credit union researchers built mathematical models of credit union operations. These models identified important operating characteristics but were modeled under assumptions of static operating environments. The model presented in this paper departs from the traditional static models and examines dynamic operation for a United States credit union. Its inter-temporal structure clarifies a number of issues-such as optimal equity retention and inter-temporal rate policy-not addressed by earlier studies. Given initial conditions, the model specifies equity retention and inter-temporal deposit and loan rate policies until an equilibrium state is reached. [ABSTRACT FROM AUTHOR]

Recently, there have been advances in the development of multidimensional poverty measures. Work is needed however on how to implement such measures. This paper deals with the process of selecting dimensions and setting weights in multidimensional poverty measurement using qualitative and quantitative methods in a participatory framework. We estimate the multidimensional poverty measures developed by Alkire and Foster for a particular group: persons with psychiatric diagnoses in the United States. To select relevant dimensions and their relative ordering, two discussion groups are convened: one consisting of persons with lived-experience expertise and the other consisting of people with mental health service provision or research expertise. Several methods are used to convert dimension rankings into weights. The selection and ordering of dimensions differed between the two discussion groups, as did the resulting poverty measures. For instance, the poverty headcount using the dimensions and weights of the 'lived experience' group ranged from 20.61 to 26.96% as compared to a range of 18.62-33.19% using those of the 'provider/researcher' group. One of the main results of this study is that the Alkire Foster method is sensitive to the selection of dimensions and the methods used to derive rankings and weights. It points toward the limitation of relying exclusively on small scale qualitative methods for the selection and ranking of dimensions. In addition, the participatory framework used in this study was found to be essential in interpreting results, in particular with respect to the limitations of the data set in measuring relevant dimensions. [ABSTRACT FROM AUTHOR]

Abstract: Breakup model is the key area of space debris environment modeling. NASA standard breakup model is currently the most widely used for general-purpose. It is a statistical model found based on space surveillance data and a few ground-based test data. NASA model takes the mass, impact velocity magnitude for input and provides the fragment size, area-to-mass ratio, velocity magnitude distributions for output. A more precise approach for spacecraft disintegration fragment analysis is presented in this paper. This approach is based on hypervelocity impact dynamics and takes the shape, material, internal structure and impact location etc. of spacecraft and impactor, which might greatly affect the fragment distribution, into consideration. The approach is a combination of finite element and particle methods, entitled finite element reconstruction (FER). By reconstructing elements from the particle debris cloud, reliable individual fragments are identified. Fragment distribution is generated with undirected graph conversion and connected component analysis. Ground-based test from literature is introduced for verification. In the simulation satellite targets and impactors are modeled in detail including the shape, material, internal structure and so on. FER output includes the total number of fragments and the mass, size and velocity vector of each fragment. The reported fragment distribution of FER shows good agreement with the test, and has good accuracy for small fragments. [Copyright &y& Elsevier]

Abstract: Patent users such as governments, inventors, and manufacturing organizations strive to identify the directions in which new technology is advancing, and their goal is to outline the boundaries of existing knowledge. The paper analyzes patent knowledge to identify research trends. A model based on knowledge extraction from patents and self-organizing maps for knowledge representation is presented. The model was tested on patents from the United States Patent and Trademark Office. The experiments show that the method provides both an overview of the directions of the trends and a drill-down perspective of current trends. [Copyright &y& Elsevier]

Abstract: Many governmental space activities need to be planned with a time horizon that extends beyond the comfort zone of reliable technology development assessments and predictions. In an environment of accelerating technological change, a methodological approach to addressing non-core technology trends and potentially disruptive, game-changing developments not yet linked to the space sector is increasingly important to complement efforts in core technology R&D planning. Various models and organisational setups aimed at fulfilling this purpose are in existence. These include, with varying levels of relevance to space, the National Aeronautics and Space Administration (NASA) Institute for Advanced Concepts (NIAC, operational form 1998 to 2007 and recently re-established), the Defence Advanced Research Projects Agency of the US Department of Defence, the Massachusetts Institute of Technology (MIT) Medialab, the early versions of Starlab, the Lockheed Skunk Works and the European Space Agency''s Advanced Concepts Team. Some of these organisations have been reviewed and assessed individually, though systematic comparison of their methods, approaches and results have not been published. This may be due in part to the relatively sparse scientific literature on organisational parameters for enabling disruptive innovation as well as to the lack of commonly agreed indicators for the evaluation of their performance. Furthermore, innovation support systems in the space sector are organised differently than in traditional, open competitive markets, which serve as the basis for most scholarly literature on the organisation of innovation. The present paper is intended to advance and stimulate discussion on the organisation of disruptive innovation mechanisms specifically for the space sector. It uses the examples of the NASA Institute for Advanced Concepts and the ESA Advanced Concepts Team, analyses their respective approaches and compares their results, leading to the proposal of measures for the analysis and eventual evaluation of research for disruptive innovation in the space sector. [Copyright &y& Elsevier]

This paper addresses the issue of data quality management in information systems within an enterprise. Motivated by legislative mandates such as the Sarbanes-Oxley Act of 2002 on the reliability and integrity of the data and the enterprise systems from which the data are produced, we propose a process-based modeling framework to assess the impact of data errors in the business process information flow and the resulting data quality metrics. This framework is then integrated with a business control framework in which the placement and effectiveness of control procedures alter the propagation of errors and, ultimately, the quality of the data in the business process. This integrated framework enables mathematical formulations of managerial problems that lead to effective data quality control strategies. We develop a two-stage multiple-choice knapsack model as a special case, and we illustrate the model and analysis through a revenue realization process. [ABSTRACT FROM AUTHOR]

This paper describes details of an automatic matrix decomposition approach for a reaction-based stream water quality model. The method yields a set of equilibrium equations, a set of kinetic-variable transport equations involving kinetic reactions only, and a set of component transport equations involving no reactions. Partial decomposition of the system of water quality constituent transport equations is performed via Gauss-Jordan column reduction of the reaction network by pivoting on equilibrium reactions to decouple equilibrium and kinetic reactions. This approach minimizes the number of partial differential advective-dispersive transport equations and enables robust numerical integration. Complete matrix decomposition by further pivoting on linearly independent kinetic reactions allows some rate equations to be formulated individually and explicitly enforces conservation of component species when component transport equations are solved. The methodology is demonstrated for a case study involving eutrophication reactions in the Des Moines River in Iowa, USA and for two hypothetical examples to illustrate the ability of the model to simulate sediment and chemical transport with both mobile and immobile water phases and with complex reaction networks involving both kinetic and equilibrium reactions. [ABSTRACT FROM AUTHOR]

Abstract: This paper employs concepts from information theory for choosing the dimension of a data set. We propose a relative information measure connected to Kullback–Leibler numbers. By ordering the series of the data set according to the measure, we are able to obtain a subset of a data set that is most informative. The method can be used as a first step in the construction of a dynamic factor model or a leading index, as illustrated with a Monte Carlo study and with the US macroeconomic data set of Stock and Watson . [Copyright &y& Elsevier]

Abstract: This paper provides a solution to address one of the requirements identified in the US Northwest 6th Power Plan, specifically, meeting an increase in the forecasted Pacific Northwest demand with renewable generation. A model is presented which evaluates one source of renewable generation, off-shore wind energy. The model analyzes different wind turbine design characteristics, assigns significance to potential synergistic effects of one design feature on another, and provides an optimized design relative to the cost, environment, robustness, and overall efficiency of an off-shore wind turbine. [Copyright &y& Elsevier]

This paper evaluates, for the first time, flash-flood guidance (FFG) values and recently developed gridded FFG (GFFG) used by the National Weather Service (NWS) to monitor and predict imminent flash flooding, which is the leading storm-related cause of death in the United States. It is envisioned that results from this study will be used 1) to establish benchmark performance of existing operational flash-flood prediction tools and 2) to provide information to NWS forecasters that reveals how the existing tools can be readily optimized. Sources used to evaluate the products include official reports of flash floods from the NWS Storm Data database, discharge measurements on small basins available from the U.S. Geological Survey, and witness reports of flash flooding collected during the Severe Hazards Analysis and Verification Experiment. Results indicated that the operational guidance values, with no calibration, were marginally skillful, with the highest critical success index of 0.20 occurring with 3-h GFFG. The false-alarm rates fell and the skill improved to 0.34 when the rainfall was first spatially averaged within basins and then reached 50%% of FFG for 1-h accumulation and exceeded 3-h FFG. Although the skill of the GFFG values was generally lower than that of their FFG counterparts, GFFG was capable of detecting the spatial variability of reported flash flooding better than FFG was for a case study in an urban setting. [ABSTRACT FROM AUTHOR]

Recently, showed that a simple system of coupled differential equations can be used for a quantitative description of the exploitation of non renewable resources in a free market economy. The present paper examines how the model describes the behavior of the system in terms of energy return for energy invested (EROEI) and net energy (energy returned minus energy expended). We show that the model generates a behavior of these factors comparable to the results obtained by other methods, for instance for the case of crude oil production in the US. [Copyright &y& Elsevier]

Trade data shows that real exchange rate fluctuates more than other variables such as consumption and GDP, and also presents significant deviations from the Law of One Price. In light of these facts, this paper develops and estimates a non-monetary DSGE model under financial autarky for the international trade of goods and services between Chile and the U.S. In this context, the higher volatility of the real exchange rate is explained by the existence of transaction costs and varying degrees of imperfect substitution in consumption between home and foreign goods which endogenously induce a home bias effect. The results reveal that the estimated transaction costs and the asymmetric home bias effect content in the data would be responsible for the low correlation between consumption in both countries and the higher real exchange rate fluctuations. Finally, the model is able to replicate much of the stylized facts observed in the data, but fails to address the Backus-Smith puzzle. [ABSTRACT FROM AUTHOR]

This paper considers how work psychologists define 'good' qualitative research in the work psychology domain. In addressing the assessment of quality in work psychology research, we draw on 22 in-depth interviews with work psychologists about their current practices and expectations around qualitative research. Using narrative analysis, the various plots and narratives that constitute how interviewees understand good qualitative research are identified. The implications of the use of these narratives for both how quality is understood and the use of qualitative research in this area are addressed. Drawing on Weick's concept of sensemaking as a theoretical framework, it is argued that the narratives identified enable the construction of a hegemonic understanding of what is good methodological practice within the work psychology discipline. The implications of this for the work psychology field and the methodological practices of work psychologists are considered. [ABSTRACT FROM AUTHOR]

Abstract: An emission pre-processing tool is generally needed to transform a bulk annual emission inventory into gridded, temporal (monthly, weekly, and hourly), and speciated emissions in order to use complex air quality models such as the Community Multi-scale Air Quality (CMAQ) model to assess control strategies, forecast air quality, and investigate pollution formation and transport processes. To support the regional air quality modeling in the Pearl River Delta (PRD), we developed an emission pre-processing system, Sparse Matrix Operator Kernel Emissions-PRD (SMOKE-PRD), based on the U.S. Environmental Protection Agency (USEPA)/SMOKE model. This paper introduces the methods and procedures for adapting the SMOKE model to the PRD regional bulk emissions. These include the compilation of the PRD local source-class clarification codes, the incorporation of the PRD local emission inventory, and the updating of spatial, temporal, and chemical speciation information. The SMOKE-PRD system was evaluated, and a case study on ozone simulation was conducted to demonstrate the applicability of the SMOKE-PRD system. Results show that the model can properly simulate temporal variations, spatial patterns, and peak values of O3 concentrations in the PRD region, suggesting the SMOKE-PRD system was successfully localized and can be used to provide model-ready emissions for regional air quality modeling in the PRD region. This work can be extended for adapting the SMOKE model to process emissions for modeling use in other regions of China. [Copyright &y& Elsevier]

Existing research has uncovered little evidence against the hypothesis of US crime rates being unit root processes, despite the uncomfortable implications of this assumption. In light of this, the present paper draws upon noted changes in the temporal patterns of US crime rates since 1960 to undertake an informed approach to testing of the unit root hypothesis which incorporates two potential points of structural change. The results obtained show the unit root hypothesis to be rejected for all classifications of criminal activity examined over the period 1960 to 2007. In addition, the dates of the detected breakpoints are supported by a variety of arguments available in the existing criminology literature concerning alternative determinants of crime and their movements. Interestingly, a difference is observed in the nature of the breaks detected for violent and property crimes. However, potential explanations for this are again found in theoretical arguments available in the criminology literature. Finally, the implications of the current findings for the properties of crime, its subsequent statistical analysis and past and future research are discussed. [ABSTRACT FROM AUTHOR]

Modeling spatially distributed phenomena in terms of its controlling factors is a recurring problem in geoscience. Most efforts concentrate on predicting the value of response variable in terms of controlling variables either through a physical model or a regression model. However, many geospatial systems comprises complex, nonlinear, and spatially non-uniform relationships, making it difficult to even formulate a viable model. This paper focuses on spatial partitioning of controlling variables that are attributed to a particular range of a response variable. Thus, the presented method surveys spatially distributed relationships between predictors and response. The method is based on association analysis technique of identifying emerging patterns, which are extended in order to be applied more effectively to geospatial data sets. The outcome of the method is a list of spatial footprints, each characterized by a unique 'controlling pattern'-a list of specific values of predictors that locally correlate with a specified value of response variable. Mapping the controlling footprints reveals geographic regionalization of relationship between predictors and response. The data mining underpinnings of the method are given and its application to a real world problem is demonstrated using an expository example focusing on determining variety of environmental associations of high vegetation density across the continental United States. [ABSTRACT FROM AUTHOR]

We examine the relationship between offshoring and the labor market in an occupational choice model of trade and endogenous growth where workers are employed on the basis of their individual skill levels. Trade liberalization leads to offshoring and reduces employment in the manufacturing sector. Displaced workers move into traditional and innovation sectors according to their skill levels, shaping real wages and aggregate productivity in the manufacturing sector. The paper aims to show how inter-sectoral labor market adjustments, highlighted by skill heterogeneity, could be a possible explanation for the simultaneous rise in productivity and reduction in real wages that have coincided with the sharp escalation of offshoring activities in the U.S. manufacturing sector since 2004. ( JEL F16, F23, J24) [ABSTRACT FROM AUTHOR]

In this paper, I explore the flexibility of the workweek in the United States, using the FIFA Soccer World Cup as a natural experiment. My empirical strategy exploits the exogenous variation that arises due to which country hosts the World Cup, as this will determine the time games are broadcast across different time zones in the United States. The hour of the day when games are broadcast differentially affects hours of work across different time zones. Further, the calendar timing of the World Cup allows me to compare labor market outcomes in June/July for a worker in World Cup year t, with the outcomes in June/July for a worker in non-World Cup years t + 1, t + 2 and t + 3. My results highlight the importance of the worker's pay frequency in their workweek flexibility, as all differences in weekly hours of work due to the World Cup are concentrated among salary paid workers. Also, my results show that after controlling for observable demographic characteristics as well as year and month fixed effects, a worker reduces on average his hours of work during the World Cup by statistically significant estimates that range from 9 weekly minutes to 28 weekly minutes, depending on specification choice and time of the day during which World Cup games are broadcast live in the United States. ( JEL J22) [ABSTRACT FROM AUTHOR]

This paper reviews the re-emergence of delays as a source of concern at the Canada-US border. We reassess their economic impacts in light of new economic research and conduct model-based numerical simulations to estimate the regional composition of trade impacts and welfare costs within Canada. We find ample reason for concern about the re-emergence of these delays, as the economic consequences are likely to be particularly acute for Ontario and Quebec. Our findings have significant public policy relevance to Canada at both national and regional levels given the current renewed interests in border protection issues. [ABSTRACT FROM AUTHOR]

Hospital cost shifting-charging private payers more in response to shortfalls in public payments-has long been part of the debate over health care policy. Despite the abundance of theoretical and empirical literature on the subject, it has not been critically reviewed and interpreted since Morrisey did so nearly fifteen years ago. Much has changed since then, in both empirical technique and the health care landscape. This article examines the theoretical and empirical literature on cost shifting since 1996, synthesizes the predominant findings, suggests their implications for the future of health care costs, and puts them in the current policy context. The relevant literature was identified by database search. Papers describing policies were considered first, since policy shapes the health care market in which cost shifting may or may not occur. Theoretical works were examined second, as theory provides hypotheses and structure for empirical work. The empirical literature was analyzed last in the context of the policy environment and in light of theoretical implications for appropriate econometric specification. Most of the analyses and commentary based on descriptive, industrywide hospital payment-to-cost margins by payer provide a false impression that cost shifting is a large and pervasive phenomenon. More careful theoretical and empirical examinations suggest that cost shifting can and has occurred, but usually at a relatively low rate. Margin changes also are strongly influenced by the evolution of hospital and health plan market structures and changes in underlying costs. Policymakers should view with a degree of skepticism most hospital and insurance industry claims of inevitable, large-scale cost shifting. Although some cost shifting may result from changes in public payment policy, it is just one of many possible effects. Moreover, changes in the balance of market power between hospitals and health care plans also significantly affect private prices. Since they may increase hospitals' market power, provisions of the new health reform law that may encourage greater provider integration and consolidation should be implemented with caution. [ABSTRACT FROM AUTHOR]

Human life expectancy has risen in most developed countries over several decades, causing observed demographic shifts. Many researchers have developed models to determine the expectancy of life at birth. Yet due to the complexity of the real-world mortality data, and recent global economy impacts, there is a great demand to search for new models to accurately predict the life expectancy, especially in the United States. In this paper, we focus on the analysis of mortality rate in the United States over a period of six decades (data from 1946 to 2005) with considerations of the six most common distribution functions in the mortality area. These functions are: Gompertz, Gompertz-Makeham, logistic, log logistic, loglog, and Weibull. Given complex mortality data, we develop models including algorithms to compute the mortality measures such as mortality rate, and then select the best function for predicting the life expectancy in the United States. The modeling results include life expectancy at birth, life expectancy at each age, mortality rate, and forecasting models. We also discuss a new risk-cost function with respect to life expectancy, and determine the optimal threshold lifetime level that maximizes the expected risk cost. Numerical examples are given to illustrate the expected risk-cost results. The proposed risk-cost optimization model, and the optimal lifetime threshold value can help the policy-decision makers of related healthcare organizations including insurance companies to carefully perform the tradeoff between the cost and benefits. This approach can affect both short term and long term related healthcare policies and plans. The results show that the logistic distribution uniquely out performs other distributions based on the mean square error criterion. We find that on average the life expectancy at birth in the United States in 2005 for both sexes, males, and females are 84.0, 81.9, and 84.6 years, respectively. This new result shows that the true life expectancy on average in the U.S. is significantly larger than in existing reports. Life expectancy obviously changes as one will get older. By late adulthood, a person's chances of living longer increase as is reflected by the life expectancy function. For example, although the life expectancy from birth in the United States in 2005 is 84.0 years, those who live to age 65 will have an average of 20.4 additional years left to live, making their life expectancy almost 85.4 years. Similarly, those who live to age 75 will gain an additional few years, making their life expectancy almost 87.6 years. On average, a child who will be born in the US in 2015 can expect to live 85.5 years, and in 2025 a child born can expect to live nearly 87 years. [ABSTRACT FROM AUTHOR]

Background: Diagnosis-based risk adjustment is becoming an important issue globally as a result of its implications for payment, high-risk predictive modelling and provider performance assessment. The Taiwanese National Health Insurance (NHI) programme provides universal coverage and maintains a single national computerized claims database, which enables the application of diagnosis-based risk adjustment. However, research regarding risk adjustment is limited. This study aims to examine the performance of the Adjusted Clinical Group (ACG) case-mix system using claims-based diagnosis information from the Taiwanese NHI programme. Methods: A random sample of NHI enrollees was selected. Those continuously enrolled in 2002 were included for concurrent analyses (n = 173,234), while those in both 2002 and 2003 were included for prospective analyses (n = 164,562). Health status measures derived from 2002 diagnoses were used to explain the 2002 and 2003 health expenditure. A multivariate linear regression model was adopted after comparing the performance of seven different statistical models. Split-validation was performed in order to avoid overfitting. The performance measures were adjusted R² and mean absolute prediction error of five types of expenditure at individual level, and predictive ratio of total expenditure at group level. Results: The more comprehensive models performed better when used for explaining resource utilization. Adjusted R² of total expenditure in concurrent/prospective analyses were 4.2%/4.4% in the demographic model, 15%/10% in the ACGs or ADGs (Aggregated Diagnosis Group) model, and 40%/22% in the models containing EDCs (Expanded Diagnosis Cluster). When predicting expenditure for groups based on expenditure quintiles, all models underpredicted the highest expenditure group and overpredicted the four other groups. For groups based on morbidity burden, the ACGs model had the best performance overall. Conclusions: Given the widespread availability of claims data and the superior explanatory power of claims-based risk adjustment models over demographics-only models, Taiwan;s government should consider using claims-based models for policy-relevant applications. The performance of the ACG case-mix system in Taiwan was comparable to that found in other countries. This suggested that the ACG system could be applied to Taiwan's NHI even though it was originally developed in the USA. Many of the findings in this paper are likely to be relevant to other diagnosis-based risk adjustment methodologies. [ABSTRACT FROM AUTHOR]

Climate change, uncertain future water supplies, growing population, and increased water demands continue to raise the importance of finding cost-effective water conservation measures. Irrigated agriculture is the world's largest water user, so governments, donor organizations, water suppliers, and farmers continue to look for measures that would produce more crop per drop. Despite the importance of promoting water conservation in agriculture, little work has been done that integrates hydrologic, economic, institutional, and policy dimensions of water conservation. This paper presents an integrated basin scale analysis of water conservation subsidies for irrigated agriculture. A dynamic, nonlinear programming model is developed and applied for the Upper Rio Grande Basin of Colorado, New Mexico, and Texas, USA. Several potential public subsidies of drip irrigation are analyzed for their economic and hydrologic impacts at both the farm and basin levels. Results indicate that water conservation subsidies for drip irrigation produce several effects. These include greater on-farm implementation of water-conserving technology, less water applied to crops, more water consumed by crops, increased farm income, greater crop production, more land irrigated, and increased total water-related economic benefits for the basin. Findings provide a framework for designing and implementing water conservation policies for irrigated agriculture. [Copyright &y& Elsevier]

Many detention basins built before 1990 are not equipped with storm-water quality control device. With the latest developments in low impact development for storm-water management, these existing detention basins need modifications on their outlet structures to increase on-site runoff treatment and disposal. An outlet shall be designed to have, at least, three levels of release, including water quality release over 12–48 h, low flow release for 10-year event, and 100-year high flow release. All these efforts are to aim at the full spectrum runoff treatment that is not only to capture the minor and major events but also to store microevents. Over the years, the empirical methods under different assumptions have been developed for determining the design storm-water quality control volume (WQCV). To improve the consistency in storm-water detention designs, this paper presents a mathematical model that produces the synthetic runoff-volume capture curves normalized by the local average rainfall event-depth. A runoff-volume capture curve defines the relationship between WQCV and runoff capture ratio on a long-term basis. A higher runoff capture ratio requires a larger storage volume. Using the runoff capture curve as the basis, the WQCV can be consistently determined for the preselected runoff capture target such as the 80% recommended by the U.S. Environmental Protection Agency in 1986. A case study illustrates how to retrofit an existing outfall concrete vault with a perforated plate and a micropool for WQCV. With a three-level release control, the outfall box can have a slow release for microevents and a fast release for extreme events. This procedure has been recommended for designing a new basin and retrofitting an existing one for the metro Denver area. Details can be found in the UD-DETENTION computer model available at www.udfcd.org at no cost to download. [ABSTRACT FROM AUTHOR]