A classification model for continuous responses: Identifying risk perception groups on health-related activities.

In the current literature on latent variable models, much effort has been put on the development of dichotomous and polytomous cognitive diagnostic models (CDMs) for assessments. Recently, the possibility of using continuous responses in CDMs has been brought to discussion. But no Bayesian approach has been developed yet for the analysis of CDMs when responses are continuous. Our work is the first Bayesian framework for the continuous deterministic inputs, noisy, and gate (DINA) model. We also propose new interpretations for item parameters in this DINA model, which makes the analysis more interpretable than before. In addition, we have conducted several simulations to evaluate the performance of the continuous DINA model through our Bayesian approach. Then, we have applied the proposed DINA model to a real data example of risk perceptions for individuals over a range of health-related activities. The application results exemplify the high potential of the use of the proposed continuous DINA model to classify individuals in the study.

Estimating the DINA model parameters using the No-U-Turn Sampler.

The deterministic inputs, noisy, "and" gate (DINA) model is a popular cognitive diagnosis model (CDM) in psychology and psychometrics used to identify test takers' profiles with respect to a set of latent attributes or skills. In this work, we propose an estimation method for the DINA model with the No-U-Turn Sampler (NUTS) algorithm, an extension to Hamiltonian Monte Carlo (HMC) method. We conduct a simulation study in order to evaluate the parameter recovery and efficiency of this new Markov chain Monte Carlo method and to compare it with two other Bayesian methods, the Metropolis Hastings and Gibbs sampling algorithms, and with a frequentist method, using the Expectation-Maximization (EM) algorithm. The results indicated that NUTS algorithm employed in the DINA model properly recovers all parameters and is accurate for all simulated scenarios. We apply this methodology in the mental health area in order to develop a new method of classification for respondents to the Beck Depression Inventory. The implementation of this method for the DINA model applied to other psychological tests has the potential to improve the medical diagnostic process.

The medicinal animal markets in the metropolitan region of Natal City, northeastern Brazil.

AIM OF THE STUDY: This study investigates the trade of animals for medicinal purposes in Natal metropolitan area, northeastern Brazil, to document which animal species are used, how and for what purposes. This study also discusses the implications of the use of zootherapeutics for wildlife conservation. MATERIALS AND METHODS: Based on interviews with merchants of medicinal animals in all open fairs of the metropolitan region of Natal City, we calculated the informant consensus factor (ICF) to determine the consensus over which species are effective for particular ailments, as well as the species relative importance to determine the extent of potential utilization of each species. RESULTS: We describe the therapeutic effects of 23 animal species used medicinally. The zootherapeutical products sold commercially are used to treat 34 health problems that were classified into 14 broad categories. We also highlight those species valued for their effectiveness against a range of ailments. The highest ICF value (1.0) was cited for diseases of the circulatory system, which include relief of symptoms such as stroke, hemorrhage, varicose veins and edema. DISCUSSION AND CONCLUSION: Our study indicated that the local population holds a great deal of ethnomedical knowledge about their local animal resources, and highlights the need for clinical investigations of these traditional remedies to test the safety and efficacy. The animal species identified in this study not only hold high medicinal value for local populations, but could potentially be a source of healing compounds that could aid pharmaceutical research. While the impact of these practices on animal populations is unknown, the high extractive value of these animal populations and the associated medicinal traditional knowledge, needs to be considered in any conservation strategy aimed at the faunistic resources of this area.

Combinations of drugs in the Treatment of Obesity.

Obesity is a chronic disease associated with excess morbidity and mortality. Clinical treatment, however, currently offers disappointing results, with very high rates of weight loss failure or weight regain cycles, and only two drugs (orlistat and sibutramine) approved for long-term use. Drugs combinations can be an option for its treatment but, although widely used in clinical practice, very few data are available in literature for its validation. Our review focuses on the rationale for their use, with advantages and disadvantages; on combinations often used, with or without studies; and on new perspectives of combinations being studied mainly by the pharmaceutical industry.

Seasonality of insects in the semi-arid Caatinga of northeastern Brazil / Sazonalidade de insetos na Caatinga do Nordeste Brasileiro

Insects are essential to tropical ecosystems functioning. In semi-arid regions, the increase in abundance and/or activity (e.g. reproduction and foraging behavior) of insects is usually associated with climatic variables. The present study investigates which climatic variables are best predictors of insect abundance in an area of Caatinga in northeastern Brazil. Individuals were sampled for 24 months using Malaise and pitfall traps, and beating trays. A total of 58925 individuals belonging to 20 insect orders were collected. The most abundant orders were Hymenoptera, Diptera, Collembola and Coleoptera. Most orders studied showed a clear maximum abundance in the rainy season. Rainfall and humidity were the best predictors of insect abundance in the Caatinga. However, no climatic variable could explain Psocoptera and Blattodea variance in abundance/activity. Our results suggest that climatic changes associated with rainfall patterns in the Caatinga may affect ecosystem processes and services that depend direct or indirectly on insect abundance/activity.

Os insetos são abundantes e essenciais para o funcionamento dos ecossistemas terrestres tropicais. No entanto, a abundância e/ou atividade (e.g. reprodução ou forrageio) destes organismos podem ser fortemente influenciadas pelas variáveis climáticas. Este estudo examina quais as variáveis climáticas podem atuar como preditoras da abundância e/ou atividade dos insetos em uma área de Caatinga do Nordeste brasileiro. Ao longo de 24 meses, os insetos foram coletados mensalmente utilizando armadilhas Malaise, armadilhas tipo "pitfall" e guarda-chuva entomológico. Um total de 58925 indivíduos de 20 ordens foi coletado. As ordens mais abundantes foram Hymenoptera, Diptera, Collembola e Coleoptera. Entre as doze ordens mais abundantes, dez apresentaram os seus maiores picos durante a estação chuvosa. A precipitação e a umidade relativa foram os principais preditores dos padrões de abundância e/ou atividade dos insetos na caatinga. Nenhuma variável climática foi relacionada com o número de indivíduos coletados de Psocoptera e Blattodea. Os efeitos das variáveis climáticas sobre os insetos sugerem que alterações no clima da caatinga, especialmente em seu padrão de precipitação, podem afetar os serviços ecossistêmicos que dependem direta e indiretamente da abundância e/ou atividade destes organismos.