Using In Vitro High‐Throughput Screening Data for Predicting Benzo[k]Fluoranthene Human Health Hazards

Today there are more than 80,000 chemicals in commerce and the environment. The potential human health risks are unknown for the vast majority of these chemicals as they lack human health risk assessments, toxicity reference values, and risk screening values. We aim to use computational toxicology and quantitative high‐throughput screening (qHTS) technologies to fill these data gaps, and begin to prioritize these chemicals for additional assessment. In this pilot, we demonstrate how we were able to identify that benzo[k]fluoranthene may induce DNA damage and steatosis using qHTS data and two separate adverse outcome pathways (AOPs). We also demonstrate how bootstrap natural spline‐based meta‐regression can be used to integrate data across multiple assay replicates to generate a concentration–response curve. We used this analysis to calculate an in vitro point of departure of 0.751 μM and risk‐specific in vitro concentrations of 0.29 μM and 0.28 μM for 1:1,000 and 1:10,000 risk, respectively, for DNA damage. Based on the available evidence, and considering that only a single HSD17B4 assay is available, we have low overall confidence in the steatosis hazard identification. This case study suggests that coupling qHTS assays with AOPs and ontologies will facilitate hazard identification. Combining this with quantitative evidence integration methods, such as bootstrap meta‐regression, may allow risk assessors to identify points of departure and risk‐specific internal/in vitro concentrations. These results are sufficient to prioritize the chemicals; however, in the longer term we will need to estimate external doses for risk screening purposes, such as through margin of exposure methods.     

Stochastic metafrontiers

ABSTRACT

We consider the case of production units arranged into a number of groups. All units within a group choose output–input combinations from the same production possibilities set that is represented by a stochastic frontier model. The metafrontier is the envelope of the group-specific frontiers. We are interested in the metafrontier distance, which is the amount by which the group-specific frontier lies below the metafrontier.

Previous work has measured the metafrontier distance using the deterministic portion of the frontier. In a stochastic frontier model, this is not appropriate. We show how to evaluate the metafrontier distance, and we demonstrate the empirical relevance of this issue.     

State Immigration Policies: The Role of State Compacts and Interest Groups on Immigration Legislation

US states are active in enacting immigration policies, which vary widely and have substantial impact on the lives of immigrants. Our understanding of what produces these divergent state laws remains limited. Qualitative research demonstrates the importance of a 2010 immigration compact, supported by a powerful religious organization, in shaping immigration policies in Utah, and the Utah Compact was held up as a model for other states. But is the experience of Utah applicable across other states? We test the effects of compacts and interest groups on immigration policy adoption across all 50 states between 2005 and 2013. Our findings suggest that compacts are actually associated with more restrictive immigration policy. Although states with compacts are more likely to pass inclusive immigration laws, these are counterbalanced by higher numbers of exclusive laws. Both religious and non‐religious interests groups are associated with policy, but they do not explain the effects of compacts.     

Split Hamiltonian Monte Carlo

We show how the Hamiltonian Monte Carlo algorithm can sometimes be speeded up by “splitting” the Hamiltonian in a way that allows much of the movement around the state space to be done at low computational cost. One context where this is possible is when the log density of the distribution of interest (the potential energy function) can be written as the log of a Gaussian density, which is a quadratic function, plus a slowly-varying function. Hamiltonian dynamics for quadratic energy functions can be analytically solved. With the splitting technique, only the slowly-varying part of the energy needs to be handled numerically, and this can be done with a larger stepsize (and hence fewer steps) than would be necessary with a direct simulation of the dynamics. Another context where splitting helps is when the most important terms of the potential energy function and its gradient can be evaluated quickly, with only a slowly-varying part requiring costly computations. With splitting, the quick portion can be handled with a small stepsize, while the costly portion uses a larger stepsize. We show that both of these splitting approaches can reduce the computational cost of sampling from the posterior distribution for a logistic regression model, using either a Gaussian approximation centered on the posterior mode, or a Hamiltonian split into a term that depends on only a small number of critical cases, and another term that involves the larger number of cases whose influence on the posterior distribution is small.     

An Examination of the Communication Styles Associated with Psychopathy and Their Influence on Observer Impressions

Psychopathic individuals are characterized as “intra-species predators”—callous, impulsive, aggressive, and proficient at interpersonal manipulation. For example, despite their high risk for re-offending, psychopathic offenders often receive early release on parole. While reputed to be social chameleons, research suggests that even naive observers can accurately infer high levels of psychopathic traits in others with very brief exposures to behavior, but accuracy degrades with extended observation. We utilized a lens model approach to examine the communication styles (emotional facial expressions, body language, and verbal content) of offenders varying in levels of psychopathic traits using “thin slice” video clips of psychological assessment interviews and to reveal which cues observers use to inform their evaluations of psychopathy. Psychopathic traits were associated with more (a) Duchenne smiles, (b) negative (angry) emotional language, and (c) hand gestures (illustrators). Further, psychopathy was associated with a marked behavioral incongruence; when individuals scoring high in psychopathic traits engaged in Duchenne smiles they were also more likely to use angry language. Naïve observers relied on each of these valid behavioral signals to quickly and accurately detect psychopathic traits. These findings provide insight into psychopathic communication styles, opportunities for improving the detection of psychopathic personality traits, and may provide an avenue for understanding successful psychopathic manipulation.     

The Nigerian Civil Registration and Vital Statistics System: Contexts,Institutions, Operation

Civil Registration and Vital Statistics (CRVS) Systems are playing increasing roles in national and global data infrastructure, facilitating the achievement of key developmental goals. The performance of CRVS systems in many developing countries including Nigeria is sub optimal and information on their structure and operations scanty. This paper characterizes the statutory, institutional, and operational elements and social contexts of the Nigerian CRVS System. It includes a context analysis of the system and a review of improvement strategies and interventions. The paper shows that the Nigerian CRVS System is built on viable statutory and institutional platforms—the constitutional enshrinement of: universal, compulsory and continuous civil registration and, a central registration institution—the National Population Commission (NPC). NPC has registration hierarchy and infrastructure deployed at every level of political administration and mechanisms for efficient coordination of registration and production of vital statistics on live-births, deaths and stillbirths amongst other vital events. The major weaknesses of the system include inadequate financing and deployment of registration facilities, conflicting statutes and institutional arrangements for the registration of key events like death and stillbirths. Other weaknesses include intra-organizational conflicts in resource allocation and weak ICT infrastructure within the NPC. These are compounded by overarching contextual issues namely registration unfriendly sociocultural norms, weak national data infrastructure, systemic corruption, poverty and undeveloped civic culture. Domestic initiatives and interventions to improve the system have focused on birth registration, while multilateral interventions have only made a modest impact on the system. Thus, holistic in-country improvement initiatives supported with robust interventions are imperative to overcome weaknesses in the Nigerian CRVS system. However fundamental improvements in CRVS systems in developing countries like Nigeria may likely only follow sustainable solutions to overarching contextual issues especially poor infrastructure, weak institutions, poverty and systemic corruption.     

A Generalized Estimating Equation in Longitudinal Data to Determine an Efficiency Indicator for Football Teams

Over the years football has attracted enormous interest from various fields of study, attracting attention both for its sporting and social aspects. Professional business operators consider football an important industry with enormous potential both in terms of its size and growth, and also because of indirect benefits due to the popularity gained by investors and management of football teams. The focus of the analysis has been on what characterizes most football clubs, and determines their particular economic and financial needs. The aim of this paper is to establish an efficiency measurement for football team financial resource allocation. In particular, we analysed the impact that the income statement, Net equity and Team value variables have on the points achieved by football teams playing in “Serie A” championship (Italian league). The method used in our study is a generalized estimating equation (GEE) for longitudinal count data. In addition we consider a coefficient of determination in the GEE approach based on Wald Statistics, and we propose a modified Mallow’s Cp for choosing the best model. Finally we propose an AFRSport index based on the differences between observed and theoretical points, in order to identify those teams that efficiently employ their financial resources.

     

Volunteering in Retirement and Its Impact on Seniors Subjective Quality of Life Through Personal Outlook: A Study of Older Australians

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - This study examines the subjective quality of life of globally expanding senior citizens post-retirement, from a...