Phylogenetic analyses using molecular markers reveal ecological lineages in Medetera (Diptera: Dolichopodidae)

Medetera Fischer von Waldheim is the most speciose genus in the Medeterinae, with a nearly ubiquitous global distribution. Phylogenetic relationships within Medetera and between Medetera and four other medeterine genera were investigated using mitochondrial (COI, 16S) and nuclear (18S) markers to test morphological hypotheses. Our results confirm most of Bickel's hypotheses. Thrypticus Gerstäcker shows a sister-group relationship with Medetera + Dolichophorus Lichtwardt. The Medetera species included here split into two clades. One clade corresponds to the M. diadema L. - veles Loew species group sensu Bickel. The second clade is largely composed of the M. apicalis (Zetterstedt) species group sensu Bickel and the M. aberrans Wheeler species group sensu Bickel + Dolichophorus. Although most Medeterinae are associated with plants (mainly trees), species in at least two separate lineages demonstrate a secondary return to terrestrial habitats. The implication of this evolutionary phenomenon is briefly discusse

MMT: New Open Source MT for the Translation Industry

MMT is a new open source machine translation software specifically addressing the needs of the translation industry. In this paper we describe its overall architecture and provide details about its major components. We report performance results on a multi-domain benchmark based on public data, on two translation directions, by comparing MMT against state-of-theart commercial and research phrase-based and neural MT systems

The Matecat Tool

© 2014 The Authors. Published by Dublin City University and Association for Computational Linguistics. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://www.aclweb.org/anthology/C14-2028We present a new web-based CAT tool providing translators with a professional work environment, integrating translation memories, terminology bases, concordancers, and machine translation. The tool is completely developed as open source software and has been already successfully deployed for business, research and education. The MateCat Tool represents today probably the best available open source platform for investigating, integrating, and evaluating under realistic conditions the impact of new machine translation technology on human post-editing

The Matecat Tool

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MMT: New open source MT for the translation industry

MMT is a new open source machine translation software specifically addressing the needs of the translation industry. In this paper we describe its overall architecture and provide details about its major components. We report performance results on a multi-domain benchmark based on public data, on two translation directions, by comparing MMT against state-of-theart commercial and research phrase-based and neural MT systems

Age-prioritized use of antivirals during an influenza pandemic

<p>Abstract</p> <p>Background</p> <p>The WHO suggested that governments stockpile, as part of preparations for the next influenza pandemic, sufficient influenza antiviral drugs to treat approximately 25% of their populations. Our aim is two-fold: first, since in many countries the antiviral stockpile is well below this level, we search for suboptimal strategies based on treatment provided only to an age-dependent fraction of cases. Second, since in some countries the stockpile exceeds the suggested minimum level, we search for optimal strategies for post-exposure prophylactic treatment of close contacts of cases.</p> <p>Methods</p> <p>We used a stochastic, spatially structured individual-based model, considering explicit transmission in households, schools and workplaces, to simulate the spatiotemporal spread of an influenza pandemic in Italy and to evaluate the efficacy of interventions based on age-prioritized use of antivirals.</p> <p>Results</p> <p>Our results show that the antiviral stockpile required for treatment of cases ranges from 10% to 35% of the population for <it>R</it>₀in 1.4 – 3. No suboptimal strategies, based on treatment provided to an age-dependent fraction of cases, were found able to remarkably reduce both clinical attack rate and antiviral drugs needs, though they can contribute to largely reduce the excess mortality. Treatment of all cases coupled with prophylaxis provided to younger individuals is the only intervention resulting in a significant reduction of the clinical attack rate and requiring a relatively small stockpile of antivirals.</p> <p>Conclusion</p> <p>Our results strongly suggest that governments stockpile sufficient influenza antiviral drugs to treat approximately 25% of their populations, under the assumption that <it>R</it>₀is not much larger than 2. In countries where the number of antiviral stockpiled exceeds the suggested minimum level, providing prophylaxis to younger individuals is an option that could be taken into account in preparedness plans. In countries where the number of antivirals stockpiled is well below 25% of the population, priority should be decided based on age-specific case fatality rates. However, late detection of cases (administration of antivirals 48 hours after the clinical onset of symptoms) dramatically affects the efficacy of both treatment and prophylaxis.</p

The GLEaMviz computational tool, a publicly available software to explore realistic epidemic spreading scenarios at the global scale

<p>Abstract</p> <p>Background</p> <p>Computational models play an increasingly important role in the assessment and control of public health crises, as demonstrated during the 2009 H1N1 influenza pandemic. Much research has been done in recent years in the development of sophisticated data-driven models for realistic computer-based simulations of infectious disease spreading. However, only a few computational tools are presently available for assessing scenarios, predicting epidemic evolutions, and managing health emergencies that can benefit a broad audience of users including policy makers and health institutions.</p> <p>Results</p> <p>We present "GLEaMviz", a publicly available software system that simulates the spread of emerging human-to-human infectious diseases across the world. The GLEaMviz tool comprises three components: the client application, the proxy middleware, and the simulation engine. The latter two components constitute the GLEaMviz server. The simulation engine leverages on the Global Epidemic and Mobility (GLEaM) framework, a stochastic computational scheme that integrates worldwide high-resolution demographic and mobility data to simulate disease spread on the global scale. The GLEaMviz design aims at maximizing flexibility in defining the disease compartmental model and configuring the simulation scenario; it allows the user to set a variety of parameters including: compartment-specific features, transition values, and environmental effects. The output is a dynamic map and a corresponding set of charts that quantitatively describe the geo-temporal evolution of the disease. The software is designed as a client-server system. The multi-platform client, which can be installed on the user's local machine, is used to set up simulations that will be executed on the server, thus avoiding specific requirements for large computational capabilities on the user side.</p> <p>Conclusions</p> <p>The user-friendly graphical interface of the GLEaMviz tool, along with its high level of detail and the realism of its embedded modeling approach, opens up the platform to simulate realistic epidemic scenarios. These features make the GLEaMviz computational tool a convenient teaching/training tool as well as a first step toward the development of a computational tool aimed at facilitating the use and exploitation of computational models for the policy making and scenario analysis of infectious disease outbreaks.</p