On the Assumption of Bivariate Normality in Selection Models: A Copula Approach Applied to Estimating HIV Prevalence

Background: Heckman-type selection models have been used to control HIV prevalence estimates for selection bias when participation in HIV testing and HIV status are associated after controlling for observed variables. These models typically rely on the strong assumption that the error terms in the participation and the outcome equations that comprise the model are distributed as bivariate normal.
Methods: We introduce a novel approach for relaxing the bivariate normality assumption in selection models using copula functions. We apply this method to estimating HIV prevalence and new confidence intervals (CI) in the 2007 Zambia Demographic and Health Survey (DHS) by using interviewer identity as the selection variable that predicts participation (consent to test) but not the outcome (HIV status).
Results: We show in a simulation study that selection models can generate biased results when the bivariate normality assumption is violated. In the 2007 Zambia DHS, HIV prevalence estimates are similar irrespective of the structure of the association assumed between participation and outcome. For men, we estimate a population HIV prevalence of 21% (95% CI = 16%–25%) compared with 12% (11%–13%) among those who consented to be tested; for women, the corresponding figures are 19% (13%–24%) and 16% (15%–17%).
Conclusions: Copula approaches to Heckman-type selection models are a useful addition to the methodological toolkit of HIV epidemiology and of epidemiology in general. We develop the use of this approach to systematically evaluate the robustness of HIV prevalence estimates based on selection models, both empirically and in a simulation study.

Aggressiveness as a component of fighting ability in pigs using a game-theoretical framework

Understanding animal contests has benefited greatly from employing the concept of fighting ability, termed resource-holding potential (RHP), with body size/weight typically used as a proxy. However, victory does not always go to the larger/heavier contestant and the existing RHP approach thereby fails to accurately predict contest outcome. Aggressiveness, typically studied as a personality trait, might explain part of this discrepancy. We investigated whether aggressiveness forms a component of RHP, examining effects on contest outcome, duration and phases, plus physiological measures of costs (lactate and glucose). Furthermore, using the correct theoretical framework, we provide the first study to investigate whether individuals gather and use information on aggressiveness as part of an assessment strategy. Pigs, Sus scrofa, were assessed for aggressiveness in resident-intruder tests whereby attack latency reflects aggressiveness. Contests were then staged between size-matched animals diverging in aggressiveness. Individuals with a short attack latency in the resident-intruder test almost always initiated the first bite and fight in the subsequent contest. However, aggressiveness had no direct effect on contest outcome, whereas bite initiation did lead to winning in contests without an escalated fight. This indirect effect suggests that aggressiveness is not a component of RHP, but rather reflects a signal of intent. Winner and loser aggressiveness did not affect contest duration or its separate phases, suggesting aggressiveness is not part of an assessment strategy. A greater asymmetry in aggressiveness prolonged contest duration and the duration of displaying, which is in a direction contrary to assessment models based on morphological traits. Blood lactate and glucose increased with contest duration and peaked during escalated fights, highlighting the utility of physiological measures as proxies for fight cost. Integrating personality traits into the study of contest behaviour, as illustrated here, will enhance our understanding of the subtleties of agonistic interactions.

Solar coronal magnetic fields derived using seismology techniques applied to omnipresent sunspot waves

Sunspots on the surface of the Sun are the observational signatures of intense manifestations of tightly packed magnetic field lines, with near-vertical field strengths exceeding 6,000 G in extreme cases1. It is well accepted that both the plasma density and the magnitude of the magnetic field strength decrease rapidly away from the solar surface, making high-cadence coronal measurements through traditional Zeeman and Hanle effects difficult as the observational signatures are fraught with low-amplitude signals that can become swamped with instrumental noise2, 3. Magneto-hydrodynamic (MHD) techniques have previously been applied to coronal structures, with single and spatially isolated magnetic field strengths estimated as 9–55 G (refs 4,5,6,7). A drawback with previous MHD approaches is that they rely on particular wave modes alongside the detectability of harmonic overtones. Here we show, for the first time, how omnipresent magneto-acoustic waves, originating from within the underlying sunspot and propagating radially outwards, allow the spatial variation of the local coronal magnetic field to be mapped with high precision. We find coronal magnetic field strengths of 32 ± 5 G above the sunspot, which decrease rapidly to values of approximately 1 G over a lateral distance of 7,000 km, consistent with previous isolated and unresolved estimations. Our results demonstrate a new, powerful technique that harnesses the omnipresent nature of sunspot oscillations to provide magnetic field mapping capabilities close to a magnetic source in the solar corona.

A Scheme Design of Cloud + End Technology in Demand Side Management

Demand Side Management (DSM) plays an important role in Smart Grid. It has large scale access points, massive users, heterogeneous infrastructure and dispersive participants. Moreover, cloud computing which is a service model is characterized by resource on-demand, high reliability and large scale integration and so on and the game theory is a useful tool to the dynamic economic phenomena. In this study, a scheme design of cloud + end technology is proposed to solve technical and economic problems of the DSM. The architecture of cloud + end is designed to solve technical problems in the DSM. In particular, a construct model of cloud + end is presented to solve economic problems in the DSM based on game theories. The proposed method is tested on a DSM cloud + end public service system construction in a city of southern China. The results demonstrate the feasibility of these integrated solutions which can provide a reference for the popularization and application of the DSM in china.

Exact and heuristic methods for solving Boolean games

Boolean games are a framework for reasoning about the rational behavior of agents whose goals are formalized using propositional formulas. Compared to normal form games, a well-studied and related game framework, Boolean games allow for an intuitive and more compact representation of the agents’ goals. So far, Boolean games have been mainly studied in the literature from the Knowledge Representation perspective, and less attention has been paid on the algorithmic issues underlying the computation of solution concepts. Although some suggestions for solving specific classes of Boolean games have been made in the literature, there is currently no work available on the practical performance. In this paper, we propose the first technique to solve general Boolean games that does not require an exponential translation to normal-form games. Our method is based on disjunctive answer set programming and computes solutions (equilibria) of arbitrary Boolean games. It can be applied to a wide variety of solution concepts, and can naturally deal with extensions of Boolean games such as constraints and costs. We present detailed experimental results in which we compare the proposed method against a number of existing methods for solving specific classes of Boolean games, as well as adaptations of methods that were initially designed for normal-form games. We found that the heuristic methods that do not require all payoff matrix entries performed well for smaller Boolean games, while our ASP based technique is faster when the problem instances have a higher number of agents or action variables.

The Development of TASTER, a Cognitive Training Game Using Human-Centered Design, Tailored for Children with Global and Specific Cognitive Impairments

Children with Prader-Willi syndrome often exhibit challenging behavior in response to changes to routine. This phenomenon has been linked to a deficit in task switching ability which has been observed in children with the syndrome. TASTER is a cognitive training game which is being designed with input from a group of children with Prader- Willi syndrome, which aims to train task switching ability and thus reduce associated challenging behavior.

A biological survey method applied to seafloor massive sulphides (SMS) with contagiously distributed hydrothermal-vent fauna

Strategies for mitigation of seafloor massive sulphide (SMS) extraction in the deep sea include establishment of suitable reference sites that allow for studies of natural environmental variability and that can serve as sources of larvae for re-colonisation of extracted hydrothermal fields. In this study, we characterize deep-sea vent communities in Manus Basin (Bismarck Sea, Papua New Guinea) and use macrofaunal data sets from a proposed reference site (South Su) and a proposed mine site (Solwara 1) to test the hypothesis that there was no difference in macrofaunal community structure between the sites. We used dispersion weighting to adjust taxa-abundance matrices to down-weight the contribution of contagious distributions of numerically abundant taxa. Faunal assemblages of 3 habitat types defined by biogenic taxa (2 provannid snails, Alviniconcha spp. and Ifremeria nautilei; and a sessile barnacle, Eochionelasmus ohtai) were distinct from one another and from the vent peripheral assemblage, but were not differentiable from mound-to-mound within a site or between sites. Mussel and tubeworm populations at South Su but not at Solwara 1 enhance the taxonomic and habitat diversity of the proposed reference site. © Inter-Research 2012.

Employment regulation, game theory, and the lacuna in employee participation in liberal economies

Employee participation is a vital ingredient of what the International Labour Organization (ILO) calls ‘representation security’. This article provides theoretical and empirical insights relating to social policy impact of worker participation, specifically the European Information and Consultation Directive (ICD) for employee voice rights. While existing research on the ICD offers important empirical insights, there is a need for further theoretical analysis to examine the potential effectiveness of the regulations in liberal market economies (LMEs). Drawing on data from 16 case studies, the article uses game theory and the prisoner's dilemma framework to explain why national implementing legislation is largely ineffective in diffusing mutual gains cooperation in two LMEs: UK and the Republic of Ireland. Three theoretical (metaphorical) propositions advance understanding of the policy impact of national information & consultation regulations in LMEs.

Applied behaviour analysis: What do teachers of students with autism spectrum disorder know

With rising numbers of school-aged children with autism educated in mainstream classrooms and applied behaviour analysis (ABA) considered the basis of best practice, teachers’ knowledge in this field has become a key concern for inclusion. Self-reported knowledge of ABA of special needs teachers (n=165) was measured and compared to their actual knowledge of ABA demonstrated in accurate responses to a multiple-choice test. Findings reported here show that teachers’ self-perceived knowledge exceeded actual knowledge and that actual knowledge of ABA was not related to training received by government agency. Implications for teacher training are discussed.