Association between milk yield and serial locomotion score assessments in UK dairy cows

This study investigated the effect of lameness, measured by serial locomotion scoring over a 12-mo period, on the milk yield of UK dairy cows. The data set consisted of 11,735 records of test-day yield and locomotion scores collected monthly from 1,400 cows kept on 7 farms. The data were analyzed in a multilevel linear regression model to account for the correlation of repeated measures of milk yield within cow. Factors affecting milk yield included farm of origin, stage of lactation, parity, season, and whether cows were ever lame or ever severely lame during the study period. Cows that had been severely lame 4, 6, and 8 mo previously gave 0.51 kg/d, 0.66 kg/d, and 1.55 kg/d less milk, respectively. A severe case of lameness in the first month of lactation reduced 305-d milk yield by 350 kg; this loss may be avoidable by prompt, effective treatment. Larger reductions can be expected when cases persist or recur. Evidence-based control plans are needed to reduce the incidence and prevalence of lameness in high yielding cows to improve welfare and productivity

Nature value: the evolution of this concept Valor da natureza: a evolução desse conceito

More attention has been paid to environmental matters in recent years, mainly due to the current scenario of accentuated environmental degradation. The economic valuation of nature goods can contribute to the decision-making process in environment management, generating a more comprehensive informational base. This paper aims to present, in a historic perspective, the different concepts attributed to nature goods and were related to the current predominant perspectives of nature analyses. For this purpose, this paper presents the different concepts attributed to value since the pre-classical period, when nature were viewed as inert and passive providers of goods and services, this view legitimized nature's exploration without concern over the preservation and conservation of nature. The capacity of nature to absorb the impact of human action appears to be reaching its limit, considering the irreversibility, the irreproducibility and the possibility of collapse. The appropriate method for valuing natural resources is not known, but more important than the method is to respect and incorporate the particular characteristics of the nature goods into this process. These characteristics must be valuated in order to arrive at a more consistence approach to nature value and promote sustainability.<br>Nos últimos anos, mais atenção tem sido dada às questões ambientais, principalmente decorrente do atual cenário de acentuada degradação. A avaliação econômica dos recursos naturais pode contribuir com o processo de tomada de decisão na gestão ambiental, gerando uma importante base de informações. Neste artigo, buscou-se apresentar, em uma perspectiva histórica, os diferentes conceitos atribuídos ao valor dos recursos naturais e como eles se relacionam às perspectivas atuais de análise ambiental. Com essa finalidade, foram apresentados os conceitos atribuídos ao valor desde o período pré-clássico, quando a natureza era vista como fornecedora inerte e passiva de produtos e serviços, visão que legitimou sua exploração, sem considerações quanto à sua preservação e conservação. A capacidade da natureza de absorver o impacto das ações humanas parece estar chegando ao seu limite, em razão da irreversibilidade, irreprodutibilidade e possibilidade de colapso. Não se conhece um método totalmente apropriado para se avaliar os recursos naturais, porém, mais importante seria respeitar e incorporar as características particulares dos recursos naturais nesse processo. Essas características devem ser valoradas, a fim de se chegar a uma aproximação mais consistente do valor da natureza e promover a sustentabilidade

DNA modification study of major depressive disorder: Beyond locus-by-locus comparisons

Contains fulltext : 160014.pdf (Publisher’s version ) (Open Access)Background: Major depressive disorder (MDD) exhibits numerous clinical and molecular features that are consistent with putative epigenetic misregulation. Despite growing interest in epigenetic studies of psychiatric diseases, the methodologies guiding such studies have not been well defined. Methods: We performed DNA modification analysis in white blood cells from monozygotic twins discordant for MDD, in brain prefrontal cortex, and germline (sperm) samples from affected individuals and control subjects (total N = 304) using 8.1K CpG island microarrays and fine mapping. In addition to the traditional locus-by-locus comparisons, we explored the potential of new analytical approaches in epigenomic studies. Results: In the microarray experiment, we detected a number of nominally significant DNA modification differences in MDD and validated selected targets using bisulfite pyrosequencing. Some MDD epigenetic changes, however, overlapped across brain, blood, and sperm more often than expected by chance. We also demonstrated that stratification for disease severity and age may increase the statistical power of epimutation detection. Finally, a series of new analytical approaches, such as DNA modification networks and machine-learning algorithms using binary and quantitative depression phenotypes, provided additional insights on the epigenetic contributions to MDD. Conclusions: Mapping epigenetic differences in MDD (and other psychiatric diseases) is a complex task. However, combining traditional and innovative analytical strategies may lead to identification of disease-specific etiopathogenic epimutations.10 p

Spatio-temporal spike pattern classification in neuromorphic systems

Spike-based neuromorphic electronic architectures offer an attractive solution for implementing compact efficient sensory-motor neural processing systems for robotic applications. Such systems typically comprise event-based sensors and multi-neuron chips that encode, transmit, and process signals using spikes. For robotic applications, the ability to sustain real-time interactions with the environment is an essential requirement. So these neuromorphic systems need to process sensory signals continuously and instantaneously, as the input data arrives, classify the spatio-temporal information contained in the data, and produce appropriate motor outputs in real-time. In this paper we evaluate the computational approaches that have been proposed for classifying spatio-temporal sequences of spike-trains, derive the main principles and the key components that are required to build a neuromorphic system that works in robotic application scenarios, with the constraints imposed by the biologically realistic hardware implementation, and present possible system-level solutions