Machine learning prediction of multiple anthelmintic resistance and gastrointestinal nematode control in sheep flocks.

The high prevalence of Haemonchus contortus and its anthelmintic resistance have affected sheep production worldwide. Machine learning approaches are able to investigate the complex relationships among the factors involved in resistance. Classification trees were built to predict multidrug resistance from 36 management practices in 27 sheep flocks. Resistance to five anthelmintics was assessed using a fecal egg count reduction test (FECRT), and 20 flocks with FECRT < 80% for four or five anthelmintics were considered resistant. The data were randomly split into training (75%) and test (25%) sets, resampled 1,000 times, and the classification trees were generated for the training data. Of the 1,000 trees, 24 (2.4%) showed 100% accuracy, sensitivity, and specificity in predicting a flock as resistant or susceptible for the test data. Forage species was a split common to all 24 trees, and the most frequent trees (12/24) were split by forage species, grazing pasture area, and fecal examination. The farming system, Suffolk sheep breed, and anthelmintic choice criteria were practices highlighted in the other trees. These management practices can be used to predict the anthelmintic resistance status and guide measures for gastrointestinal nematode control in sheep flocks

Major multiform erythema with sertraline

A sertralina é frequentemente utilizada para o tratamento de síndromes depressivos e ansiosos. Os efeitos secundários são geralmente transitórios e dependentes da dosagem. Descrevemos o caso clínico de uma mulher de 76 anos com síndrome depressivo e introdução recente da sertralina que recorreu ao serviço de urgência por febre e erupção cutânea difusa com dois dias de evolução. Ao exame objetivo observavam-se pápulas eritematosas em alvo dispersas pelo corpo e exulcerações da mucosa oral. Foi efetuada uma biopsia cutânea para exame histopatológico com diagnóstico de eritema multiforme major secundário à sertralina. A doente suspendeu o fármaco em causa e iniciou prednisolona oral com resolução do quadro clínico. Embora pouco frequentes, existem casos descritos de reação cutânea grave associada à sertralina

Data mining framework for fatty liver disease classification in ultrasound: a hybrid feature extraction paradigm

PURPOSE: Fatty liver disease (FLD) is an increasing prevalent disease that can be reversed if detected early. Ultrasound is the safest and ubiquitous method for identifying FLD. Since expert sonographers are required to accurately interpret the liver ultrasound images, lack of the same will result in interobserver variability. For more objective interpretation, high accuracy, and quick second opinions, computer aided diagnostic (CAD) techniques may be exploited. The purpose of this work is to develop one such CAD technique for accurate classification of normal livers and abnormal livers affected by FLD. METHODS: In this paper, the authors present a CAD technique (called Symtosis) that uses a novel combination of significant features based on the texture, wavelet transform, and higher order spectra of the liver ultrasound images in various supervised learning-based classifiers in order to determine parameters that classify normal and FLD-affected abnormal livers. RESULTS: On evaluating the proposed technique on a database of 58 abnormal and 42 normal liver ultrasound images, the authors were able to achieve a high classification accuracy of 93.3% using the decision tree classifier. CONCLUSIONS: This high accuracy added to the completely automated classification procedure makes the authors' proposed technique highly suitable for clinical deployment and usage

CMS Monte Carlo production in the WLCG computing Grid

Monte Carlo production in CMS has received a major boost in performance and scale since the past CHEP06 conference. The production system has been re-engineered in order to incorporate the experience gained in running the previous system and to integrate production with the new CMS event data model, data management system and data processing framework. The system is interfaced to the two major computing Grids used by CMS, the LHC Computing Grid (LCG) and the Open Science Grid (OSG). Operational experience and integration aspects of the new CMS Monte Carlo production system is presented together with an analysis of production statistics. The new system automatically handles job submission, resource monitoring, job queuing, job distribution according to the available resources, data merging, registration of data into the data bookkeeping, data location, data transfer and placement systems. Compared to the previous production system automation, reliability and performance have been considerably improved. A more efficient use of computing resources and a better handling of the inherent Grid unreliability have resulted in an increase of production scale by about an order of magnitude, capable of running in parallel at the order of ten thousand jobs and yielding more than two million events per day

Análise de metodologias para correção atmosférica e estimativa do albedo da superfície usando imagens Landsat 5, TM.

Este trabalho objetivou analisar a aplicação de diferentes metodologias para correção atmosférica e estimativa do albedo da superfície com imagens Landsat 5 ? TM para a região que abrange parte do megaleque aluvial do rio Taquari (Pantanal). Foram avaliados os métodos de correção atmosférica DOS (dark object subtraction), método de correção baseado na componente haze da transformação tasseled cap, o 6S (Second Simulation of the Satellite Signal in the Solar Spectrum) e o método de correção implementado no algoritmo SEBAL (Surface Energy Balance Algorithm for Land). Para o cálculo do albedo, três diferentes fórmulas de estimativas foram utilizadas. Os resultados obtidos apontam a existência de uma forte variação dos valores de albedo encontrados conforme o método de correção dos efeitos atmosféricos e da escolha da fórmula de estimativa do albedo de superfície. Dentre as fórmulas utilizadas para estimativa do albedo, a fórmula de Allen et al. foi a que apresentou menos sensibilidade ao tipo de correção atmosférica adotada

The impact of brief intensive trauma-focused treatment for PTSD on symptoms of borderline personality disorder

Objective: To investigate the effects of a brief, intensive, direct trauma-focused treatment programme for individuals with PTSD on BPD symptom severity. Methods: Individuals (n = 72) with severe PTSD (87.5% had one or more comorbidities; 52.8% fulfilled the criteria for the dissociative subtype of PTSD) due to multiple traumas (e.g. 90.3% sexual abuse) participated in an intensive eight-day trauma-focused treatment programme consisting of eye movement desensitization and reprocessing (EMDR) and prolonged exposure (PE) therapy, physical activity, and psychoeducation. Treatment did not include any form of stabilization (e.g. emotion regulation training) prior to trauma-focused therapy. Assessments took place at pre- and post-treatment (Borderline Symptom List, BSL-23; PTSD symptom severity, Clinician Administered PTSD Scale for DSM-5, CAPS-5), and across the eight treatment days (PTSD Checklist, PCL-5). Results: Treatment resulted in significant decreases of BPD symptoms (Cohen’s d = 0.70). Of the 35 patients with a positive screen for BPD at pre-treatment, 32.7% lost their positive screen at post-treatment. No adverse events nor dropouts occurred during the study time frame, and none of the patients experienced symptom deterioration in response to treatment. Conclusion: The results suggest that an intensive trauma-focused treatment is a feasible and safe treatment for PTSD patients with clinically elevated symptoms of BPD, and that BPD symptoms decrease along with the PTSD symptoms

Estudo do índice de área foliar de pastagens em diferentes níveis de degradação com aplicação de imagens Landsat 5 - TM e dados de campo.

A área foliar é um parâmetro chave na avaliação do crescimento das plantas, podendo ser tanto medida quanto estimada (Figueredo Júnior et al., 2005). Segundo Pereira e Machado (1987) a área foliar é um fator que depende do número e tamanho das folhas e de seu estádio fenológico. A relação entre a área foliar de toda vegetação e a unidade de área de solo ocupada por essa vegetação é denominada de índice de área foliar (IAF). Como a fotossíntese depende da área foliar, a produtividade de uma cultura será tanto maior quanto mais próximo for do IAF máximo potencial e quanto mais tempo permanecer ativa; retardando a senescência (Figueredo Júnior et al., 2005). Zanchi et al. (2009) afirmam existir poucas informações referentes a variação espacial da biomassa vegetal, altura da pastagem e do índice de área foliar de pastagens. Estes autores sugerem que as variações naturais no IAF, altura e biomassa de algumas espécies, respondem às variações sazonais e interanuais do clima e da umidade do solo. Neste sentido, a análise espacial do IAF com uso dados de satélite pode ser um importante indicador da biomassa em áreas extensas. Diante do exposto, este trabalho teve como objetivo a aplicação de técnicas de sensoriamento remoto e dados de campo no estudo do índice de área foliar de pastagens de Brachiaria em diferentes níveis de degradação na região de Guararapes, SP