Exploration of the scalability of LocFaults approach for error localization with While-loops programs

A model checker can produce a trace of counterexample, for an erroneous program, which is often long and difficult to understand. In general, the part about the loops is the largest among the instructions in this trace. This makes the location of errors in loops critical, to analyze errors in the overall program. In this paper, we explore the scala-bility capabilities of LocFaults, our error localization approach exploiting paths of CFG(Control Flow Graph) from a counterexample to calculate the MCDs (Minimal Correction Deviations), and MCSs (Minimal Correction Subsets) from each found MCD. We present the times of our approach on programs with While-loops unfolded b times, and a number of deviated conditions ranging from 0 to n. Our preliminary results show that the times of our approach, constraint-based and flow-driven, are better compared to BugAssist which is based on SAT and transforms the entire program to a Boolean formula, and further the information provided by LocFaults is more expressive for the user

Testing Nonlinear Logit Models of Performance Effectiveness Ratings: Cooperative Extension and Organic Farmers

Survey evidence from U.S. organic farmers is evaluated to identify the factors influencing effectiveness ratings of cooperative extension advisors by organic farmers. A nonlinear logit model is specified for the ratings provided by organic producers, and critical demographic and management factors that influence the ratings are identified. The impact of the organic farmers’ status in transitioning to organic production is highlighted. The results indicate that part-time, newer adopters of organic farming methods are more likely to rate extension service providers as effective providers of information. Scenarios to predict extension effectiveness when interacting with specific groups of organic farmers are developed.cooperative extension, nonlinear logit model, organic farming, performance ratings, Agribusiness, Farm Management, Productivity Analysis, C25, Q16, Q01,

Adaptive microfoundations for emergent macroeconomics

In this paper we present the basics of a research program aimed at providing microfoundations to macroeconomic theory on the basis of computational agentbased adaptive descriptions of individual behavior. To exemplify our proposal, a simple prototype model of decentralized multi-market transactions is offered. We show that a very simple agent-based computational laboratory can challenge more structured dynamic stochastic general equilibrium models in mimicking comovements over the business cycle.Microfoundations of macroeconomics, Agent-based economics, Adaptive behavior

Relative status and well-being: evidence from U.S. suicide deaths

This paper empirically assesses the theory of interpersonal income comparison using individual level data on suicide deaths in the United States. We model suicide as a choice variable, conditional on exogenous risk factors, reflecting an individual's assessment of current and expected future utility. Our empirical analysis considers whether suicide risk is systematically related to the income of others, holding own income and other individual factors fixed. We estimate proportional hazards and probit models of the suicide hazard using two separate and independent data sets: (1) the National Longitudinal Mortality Study and (2) the Detailed Mortality Files combined with the 5 percent Public Use Micro Sample of the 1990 decennial census. Results from both data sources show that, controlling for own income and individual characteristics, individual suicide risk rises with reference group income. This result holds for reference groups defined broadly, such as by county, and more narrowly by county and one demographic marker (e.g., age, sex, race). These findings are robust to alternative specifications and cannot be explained by geographic variation in cost of living, access to emergency medical care, mismeasurement of deaths by suicide, or by bias due to endogeneity of own income. Our results confirm findings using self-reported happiness data and are consistent with models of utility featuring "external habit" or "Keeping Up with the Joneses" preferences.Income distribution ; Suicide

Techniques for automated parameter estimation in computational models of probabilistic systems

The main contribution of this dissertation is the design of two new algorithms for automatically synthesizing values of numerical parameters of computational models of complex stochastic systems such that the resultant model meets user-specified behavioral specifications. These algorithms are designed to operate on probabilistic systems – systems that, in general, behave differently under identical conditions. The algorithms work using an approach that combines formal verification and mathematical optimization to explore a model\u27s parameter space. The problem of determining whether a model instantiated with a given set of parameter values satisfies the desired specification is first defined using formal verification terminology, and then reformulated in terms of statistical hypothesis testing. Parameter space exploration involves determining the outcome of the hypothesis testing query for each parameter point and is guided using simulated annealing. The first algorithm uses the sequential probability ratio test (SPRT) to solve the hypothesis testing problems, whereas the second algorithm uses an approach based on Bayesian statistical model checking (BSMC). The SPRT-based parameter synthesis algorithm was used to validate that a given model of glucose-insulin metabolism has the capability of representing diabetic behavior by synthesizing values of three parameters that ensure that the glucose-insulin subsystem spends at least 20 minutes in a diabetic scenario. The BSMC-based algorithm was used to discover the values of parameters in a physiological model of the acute inflammatory response that guarantee a set of desired clinical outcomes. These two applications demonstrate how our algorithms use formal verification, statistical hypothesis testing and mathematical optimization to automatically synthesize parameters of complex probabilistic models in order to meet user-specified behavioral propertie

IEA ECES Annex 31 Final Report - Energy Storage with Energy Efficient Buildings and Districts: Optimization and Automation

At present, the energy requirements in buildings are majorly met from non-renewable sources where the contribution of renewable sources is still in its initial stage. Meeting the peak energy demand by non-renewable energy sources is highly expensive for the utility companies and it critically influences the environment through GHG emissions. In addition, renewable energy sources are inherently intermittent in nature. Therefore, to make both renewable and nonrenewable energy sources more efficient in building/district applications, they should be integrated with energy storage systems. Nevertheless, determination of the optimal operation and integration of energy storage with buildings/districts are not straightforward. The real strength of integrating energy storage technologies with buildings/districts is stalled by the high computational demand (or even lack of) tools and optimization techniques. Annex 31 aims to resolve this gap by critically addressing the challenges in integrating energy storage systems in buildings/districts from the perspective of design, development of simplified modeling tools and optimization techniques

Elucidating the sustained decline in under‐three child linear growth faltering in Nepal, 1996-2016

Childhood linear growth faltering remains a major public health concern in Nepal. Nevertheless, over the past 20 years, Nepal sustained one of the most rapid reductions in the prevalence of stunting worldwide. First, our study analysed the trends in height-for-age z-score (HAZ), stunting prevalence, and available nutrition-sensitive and nutrition-specific determinants of linear growth faltering in under-three children across Nepal's Family Health Survey 1996 and Nepal's Demographic and Health Surveys 2001, 2006, 2001, and 2016. Second, we constructed pooled multivariable linear regression models and decomposed the contributions of our time-variant determinants on the predicted changes in HAZ and stunting over the past two decades. Our findings indicate substantial improvements in HAZ (38.5%) and reductions in stunting (-42.6%) and severe stunting prevalence (-63.9%) in Nepalese children aged 0-35 months. We also report that the increment in HAZ, across the 1996-2016 period, was significantly associated (confounder-adjustedp< .05) with household asset index, maternal and paternal years of education, maternal body mass index and height, basic child vaccinations, preceding birth interval, childbirth in a medical facility, and prenatal doctor visits. Furthermore, our quantitative decomposition of HAZ identified advances in utilisation of health care and related services (31.7% of predicted change), household wealth accumulation (25%), parental education (21.7%), and maternal nutrition (8.3%) as key drivers of the long-term and sustained progress against child linear growth deficits. Our research reiterates the multifactorial nature of chronic child undernutrition and the need for coherent multisectoral nutrition-sensitive and nutrition-specific strategies at national scale to further improve linear growth in Nepal