Multivariate measurement error models based on scale mixtures of the skew-normal distribution

Scale mixtures of the skew-normal (SMSN) distribution is a class of asymmetric thick-tailed distributions that includes the skew-normal (SN) distribution as a special case. The main advantage of these classes of distributions is that they are easy to simulate and have a nice hierarchical representation facilitating easy implementation of the expectation-maximization algorithm for the maximum-likelihood estimation. In this paper, we assume an SMSN distribution for the unobserved value of the covariates and a symmetric scale mixtures of the normal distribution for the error term of the model. This provides a robust alternative to parameter estimation in multivariate measurement error models. Specific distributions examined include univariate and multivariate versions of the SN, skew-t, skew-slash and skew-contaminated normal distributions. The results and methods are applied to a real data set.

Designing Novel Antitrypanosomal Agents from a Mixed Graph-Theoretical Substructural Approach

Chagas disease is nowadays the most serious parasitic health problem. This disease is caused by Trypanosoma cruzi. The great number of deaths and the insufficient effectiveness of drugs against this parasite have alarmed the scientific community worldwide. In an attempt to overcome this problem, a model for the design and prediction of new antitrypanosomal agents was obtained. This used a mixed approach, containing simple descriptors based on fragments and topological substructural molecular design descriptors. A data set was made up of 188 compounds, 99 of them characterized an antitrypanosomal activity and 88 compounds that belong to other pharmaceutical categories. The model showed sensitivity, specificity and accuracy values above 85%. Quantitative fragmental contributions were also calculated. Then, and to confirm the quality of the model, 15 structures of molecules tested as antitrypanosomal compounds (that we did not include in this study) were predicted, taking into account the information on the abovementioned calculated fragmental contributions. The model showed an accuracy of 100% which means that the ""in silico"" methodology developed by our team is promising for the rational design of new antitrypanosomal drugs. (C) 2009 Wiley Periodicals, Inc. J Comput Chem 31: 882-894. 2010

Dereplication of Bromotyrosine-derived Metabolites by LC-PDA-MS and Analysis of the Chemical Profile of 14 Aplysina Sponge Specimens from the Brazilian Coastline

In order to investigate the chemical profile of 14 specimens of Aplysina spp. marine sponges, we have developed a method based on LC-PDA-MS for the detection of bromotyrosine-derived metabolites. The method enabled the dereplication of three distinct chemotypes of bromotyrosine-derived compounds based on UV absorptions, which were further refined by electrospray ionization-mass spectrometry analysis of the brominated quasi-molecular ion clusters. This procedure led to either a single compound assignment, or a maximum of two possible isobaric compounds. The dereplication study indicated that the chemical profile of the 14 specimens of Aplysina spp. analyzed presented practically the same dibromotyrosine-derived compounds. The results obtained suggested a possible biogenetic pathway for the formation of dibromotyrosine-derived compounds of wide occurrence in Verongida sponges.

Genetic Control of Residual Variance for Teat Number in Pigs

The genetic improvement in litter size in pigs has been substantial during the last 10-15 years. The number of teats on the sow must increase as well to meet the needs of the piglets, because each piglet needs access to its own teat. We applied a genetic heterogeneity model on teat numberin sows, and estimated medium-high heritability for teat number (0.5), but low heritability for residual variance (0.05), indicating that selection for reduced variance might have very limited effect. A numerically positive correlation (0.8) between additive genetic breeding values for mean and for variance was found, but because of the low heritability for residual variance, the variance will increase very slowly with the mean.

Acupuncture with manual and electrical stimulation for labour pain : a longitudinal randomised controlled trial

Background: Acupuncture is commonly used to reduce pain during labour despite contradictory results. The aim of this study is to evaluate the effectiveness of acupuncture with manual stimulation and acupuncture with combined manual and electrical stimulation (electro-acupuncture) compared with standard care in reducing labour pain. Our hypothesis was that both acupuncture stimulation techniques were more effective than standard care, and that electro-acupuncture was most effective.  Methods: A longitudinal randomised controlled trial. The recruitment of participants took place at the admission to the labour ward between November 2008 and October 2011 at two Swedish hospitals. 303 nulliparous women with normal pregnancies were randomised to: 40 minutes of manual acupuncture (MA), electro-acupuncture (EA), or standard care without acupuncture (SC). Primary outcome: labour pain, assessed by Visual Analogue Scale (VAS). Secondary outcomes: relaxation, use of obstetric pain relief during labour and post-partum assessments of labour pain. The sample size calculation was based on the primary outcome and a difference of 15 mm on VAS was regarded as clinically relevant, this gave 101 in each group, including a total of 303 women.  Results: Mean estimated pain scores on VAS (SC: 69.0, MA: 66.4 and EA: 68.5), adjusted for: treatment, age, education, and time from baseline, with no interactions did not differ between the groups (SC vs MA: mean difference 2.6, 95% confidence interval [CI] -1.7-6.9 and SC vs EA: mean difference 0.6 [95% CI] -3.6-4.8). Fewer number of women in the EA group used epidural analgesia (46%) than women in the MA group (61%) and SC group (70%) (EA vs SC: odds ratio [OR] 0.35; [95% CI] 0.19-0.67).  Conclusions: Acupuncture does not reduce women's experience of labour pain, neither with manual stimulation nor with combined manual and electrical stimulation. However, fewer women in the EA group used epidural analgesia thus indicating that the effect of acupuncture with electrical stimulation may be underestimated. These findings were obtained in a context with free access to other forms of pain relief.

Towards Motivation-based Plan Evaluation

AI planning systems tend to be disembodied and are not situated within the environment for which plans are generated, thus losing information concerning the interaction between the system and its environment. This paper argues that such information may potentially be valuable in constraining plan formulation, and presents both an agent- and domainindependent architecture that extends the classical AI planning framework to take into account context, or the interaction between an autonomous situated planning agent and its environment. The paper describes how context constrains the goals an agent might generate, enables those goals to be prioritised, and constrains plan selection.

Uma análise do ensino jurídico no Brasil

O Ensino Jurídico no Brasil, passa hoje por uma crise que remonta desde as suas origens. Inúmeras metodologias e modificações curriculares foram aplicadas com o intuito de superá-las. No entanto, nenhuma mudança surtiu o efeito desejado, pois o ensino do direito e os profissionais que com ele trabalham permaneceram com uma visão positivo-dogmática do mesmo. O presente trabalho terá como meta, através do relato da história do Ensino Jurídico no Brasil, analisar as teorias e métodos didáticos, pontuando o processo ensino-aprendizagem, as suas fases, posturas do educador que se insere no perfil de um formador não só de técnicas mas de cidadãos agentes do direito. Das estruturas das instituições de ensino jurídico e da postura dos alunos que a buscam, detectando as falhas que levaram e intensificaram a crise aqui verificada. Por fim, mostraremos algumas propostas de ensino que visam estimular a interdisciplinaridade através da alternância do "saber" e do "fazer", tomando assim os conteúdos apresentados em sala mensuráveis e mais próximo possível da realidade técnica e social.

A panel data approach to economic forecasting: the bias-corrected average forecast

In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular it delivers a zero-limiting mean-squared error if the number of forecasts and the number of post-sample time periods is sufficiently large. We also develop a zero-mean test for the average bias. Monte-Carlo simulations are conducted to evaluate the performance of this new technique in finite samples. An empirical exercise, based upon data from well known surveys is also presented. Overall, these results show promise for the bias-corrected average forecast.

Robustness of stationary tests under long-memory alternatives

This paper investigates the presence of long memory in financiaI time series using four test statistics: V/S, KPSS, KS and modified R/S. There has been a large amount of study on the long memory behavior in economic and financiaI time series. However, there is still no consensus. We argue in this paper that spurious short-term memory may be found due to the incorrect use of data-dependent bandwidth to estimating the longrun variance. We propose a partially adaptive lag truncation procedure that is robust against the presence of long memory under the alternative hypothesis and revisit several economic and financiaI time series using the proposed bandwidth choice. Our results indicate the existence of spurious short memory in real exchange rates when Andrews' formula is employed, but long memory is detected when the proposed lag truncation procedure is used. Using stock market data, we also found short memory in returns and long memory in volatility.

O processo de auto-avaliação institucional do sistema nacional de avaliação da educação superior - SINAES como ferramenta de gestão Estratégica nas IES: Um Estudo de Caso

O objetivo do presente trabalho foi mostrar a importância do processo de autoavaliação do SINAES Sistema Nacional de Avaliação da Educação Superior ¿ SINAES como um instrumento de Gestão Estratégica nas Instituições de Ensino Superior. Os objetivos específicos foram identificar os pontos fortes e pontos fracos do sistema de autoavaliação; efetuar análises comparativas acerca do nível de desenvolvimento dos trabalhos de autoavalição em algumas IES¿s e identificar o posicionamento de alguns gestores das Instituições de Ensino Superior quanto à utilização do processo de autoavaliação do SINAES no gerenciamento estratégico da IES. A pesquisa teve como base o estudo de caso realizado na FAMA ¿ Faculdade Atenas Maranhense, o qual comportou sua avaliação institucional e uma pesquisa realizada em oito Instituições de Ensino Superior com a aplicação de questionários aos gestores dessas instituições. A relevância da pesquisa concentrase na busca de identificar se algumas Instituições de Ensino Superior, de acordo com a amostra definida e que são atingidas pela Lei 10.861, já finalizaram o processo de avaliação, assim como se utilizam as dimensões trabalhadas como instrumentos de gestão estratégica, o que se constitui em uma contribuíção significativa, tanto para o meio acadêmico, quanto empresarial. Defendese a idéia de que a avaliação institucional, como uma prática complexa, requer a sua estreita vinculação a todo o processo decisório na IES, notadamente daqueles que dizem respeito às questões mais substantivas para a manutenção e crescimento dessa instituição. Concluiuse que na FAMA, Faculdade Atenas Maranhense, a autoavaliação vem auxiliando os gestores na ampliação da visão sobre a instituição e a melhorarem os pontos mais fracos.