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Motivation Resistance co-occurrence within first-line anti-tuberculosis (TB) drugs is a common phenomenon. Existing methods based on genetic data analysis of Mycobacterium tuberculosis (MTB) have been able to predict resistance of MTB to individual drugs, but have not considered the resistance co-occurrence and cannot capture latent structure of genomic data that corresponds to lineages. Results We used a large cohort of TB patients from 16 countries across six continents where whole-genome sequences for each isolate and associated phenotype to anti-TB drugs were obtained using drug susceptibility testing recommended by the World Health Organization. We then proposed an end-to-end multi-task model with deep denoising auto-encoder (DeepAMR) for multiple drug classification and developed DeepAMR_cluster, a clustering variant based on DeepAMR, for learning clusters in latent space of the data. The results showed that DeepAMR outperformed baseline model and four machine learning models with mean AUROC from 94.4% to 98.7% for predicting resistance to four first-line drugs [i.e. isoniazid (INH), ethambutol (EMB), rifampicin (RIF), pyrazinamide (PZA)], multi-drug resistant TB (MDR-TB) and pan-susceptible TB (PANS-TB: MTB that is susceptible to all four first-line anti-TB drugs). In the case of INH, EMB, PZA and MDR-TB, DeepAMR achieved its best mean sensitivity of 94.3%, 91.5%, 87.3% and 96.3%, respectively. While in the case of RIF and PANS-TB, it generated 94.2% and 92.2% sensitivity, which were lower than baseline model by 0.7% and 1.9%, respectively. t-SNE visualization shows that DeepAMR_cluster captures lineage-related clusters in the latent space. Availability and implementation The details of source code are provided at http://www.robots.ox.ac.uk/∼davidc/code.php. Supplementary information Supplementary data are available at Bioinformatics online.

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Apresenta-se uma definição de sustentabilidade baseada na segunda lei da termodinâmica e mostra-se que, a partir essa definição, é possível desatrelar o crescimento econômico do uso dos recursos naturais, a fim de evitar que as forças do mercado se oponham a uma reestruturação do setor energético que tenha o objetivo de passar da atual matriz energética, que é insustentável, para uma que o sejausando apenas as fontes renováveis de energia de que o Brasil dispõe. A transição da matriz insustentável para uma sustentável implicará uma crescente racionalização do consumo, paralelamente ao emprego de energias renováveis e à redução do emprego de fontes não renováveis, tais como o petróleo e o gás natural. A partir de meados do presente século, a adaptação dos padrões de consumo e o desenvolvimento tecnológico permitirão que o emprego de fontes renováveis vá deslocando mais rapidamente as fontes não-renováveis, levando-as a uma posição tendente à anulação até o fim do século. No corpo da tese discute-se o emprego do princípio da precaução no planejamento energético e demonstra-se que o Brasil tem condições para se tornar praticamente independente de fontes não-renováveis de energia.

Cross-border acquisitions (CBAs) have extensively been used by Multilatinas as a preferred entry mode in foreign markets, quickly providing access to resources, competencies and local intelligence without the burden of starting up a greenfield investment and bearing its associated risk to face the liability of foreignness. Using fixed-effects, generalized least square (FEGLS) regressions applied on a panel data sample of 602 CBA deals announced during the 1989-2011 period by 182 Multilatinas competing in 74 industries and headquartered in Argentina, Brazil, Chile, Colombia, Mexico, Peru and Venezuela, the impact of cultural and psychic distances (as perceived by investors) on the performance of these CBA deals (measured by acquirers' shareholders' short term announcement returns) was evaluated. Key emerging conclusions are that: a) the national cultural distance composite index, based on Hofstede's four dimensions seems to better predict investors' reaction to CBA announcements in comparison with the other "psychic" distance concepts, such as the administrative and geographical distances between home and host countries; b) investors' perceptions regarding the cultural dissimilarities between these countries are factored in their response as an anticipation of the expected difficulties that acquiring firms' will have during the post-merger integration process, as predicted by the several theoretical streams that focus on the role of culture in M&A; c) due to the positive and significant moderating effect of the uncertainty avoidance dimension, investors seem also to perceive that acquirers from home countries characterized by high uncertainty avoidance scores will be able to better handle the challenges that they will face in the post-merger integration stage, to the extent that these firms, as recognized in the cross-cultural research literature, have been associated with a preference for organizational rules and procedures that increase the chances of a successful completion of the merger or acquisition deal; d) although its role is recognized in the crosscultural literature, power distance levels have no significant moderating effect on the cultural distance-M&A performance relationship. The models are robust to varying lengths of event windows and to alternative measurements of cultural distance, such as those based on the framework developed by the GLOBE project (House, Hanges, Javidan, Dorfman, & Gupta, 2004) and on the country cultural cluster maps proposed by Ronen and Shenkar (2013). Limitations of this study are pointed out and future research directions are suggested in order to advance our knowledge and understanding of the antecedents of the performance of the cross-border acquisitions made by Multilatinas.