Diversity and evolution of Amazonian birds : implications for conservation and biogeography

Amazonia has been a focus of interest since the early days of biogeography as an intrinsically complex and extremely diverse region. This region comprises an intricate mosaic that includes diverse types of forest formations, flooded environments and open vegetation. Increased knowledge about the distribution of species in Amazonia has led to the recognition of complex biogeographic patterns. The confrontation of these biogeographic patterns with information on the geological and climatic history of the region has generated several hypotheses dedicated to explain the origin of the biological diversity. Genomic information, coupled with knowledge of Earth's history, especially the evolution of the Amazonian landscape. presents fascinating possibilities for understanding the mechanisms that govern the origin and maintenance of diversity patterns in one of the most diverse regions of the world. For this we will increasingly need more intense and coordinated interactions between researchers studying biotic diversification and the evolution of landscapes. From the interaction between these two fields of knowledge that are in full development, an increasingly detailed understanding of the historical mechanisms related to the origin of the species will surely arise.Peer reviewe

Transcriptional regulatory networks controlling woolliness in peach in response to preharvest gibberellin application and cold storage

BACKGROUND: Postharvest fruit conservation relies on low temperatures and manipulations of hormone metabolism to maintain sensory properties. Peaches are susceptible to chilling injuries, such as ‘woolliness’ that is caused by juice loss leading to a ‘wooly’ fruit texture. Application of gibberellic acid at the initial stages of pit hardening impairs woolliness incidence, however the mechanisms controlling the response remain unknown. We have employed genome wide transcriptional profiling to investigate the effects of gibberellic acid application and cold storage on harvested peaches. RESULTS: Approximately half of the investigated genes exhibited significant differential expression in response to the treatments. Cellular and developmental process gene ontologies were overrepresented among the differentially regulated genes, whereas sequences in cell death and immune response categories were underrepresented. Gene set enrichment demonstrated a predominant role of cold storage in repressing the transcription of genes associated to cell wall metabolism. In contrast, genes involved in hormone responses exhibited a more complex transcriptional response, indicating an extensive network of crosstalk between hormone signaling and low temperatures. Time course transcriptional analyses demonstrate the large contribution of gene expression regulation on the biochemical changes leading to woolliness in peach. CONCLUSION: Overall, our results provide insights on the mechanisms controlling the complex phenotypes associated to postharvest textural changes in peach and suggest that hormone mediated reprogramming previous to pit hardening affects the onset of chilling injuries. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12870-015-0659-2) contains supplementary material, which is available to authorized users

Growing neural gas as a memory mechanism of a heuristic to solve a community detection problem in networks

Iterative heuristics are commonly used to address combinatorial optimization problems. However, to meet both robustness and efficiency with these methods when their iterations are independent, it is necessary to consider a high number of iterations or to include local search-based strategies in them. Both approaches are very time-consuming and, consequently, not efficient for medium and large-scale instances of combinatorial optimization problems. In particular, the community detection problem in networks is well-known due to the instances with hundreds to thousands of vertices. In the literature, the heuristics to detect communities in networks that use a local search are those that achieve the partitions with the best solution values. Nevertheless, they are not suitable to tackle medium to large scale networks. This paper presents an adaptive heuristic, named GNGClus, that uses the neural network Growing Neural Gas to play the role of memory mechanism. The computational experiment with LFR networks indicates that the proposed strategy significantly outperformed the same solution method with no memory mechanism. In addition, GNGClus was very competitive with a version of the heuristic that employs an elite set of solutions to guide the solution search. (C) 2016 The Authors. Published by Elsevier B.V.Instituto de Ciência e Tecnologia, Universidade Federal de São Paulo (UNIFESP) Av. Cesare M. G. Lattes, 1201, Eugênio de Mello, São José dos Campos-SP, CEP: 12247-014, BrasilInstituto de Ciência e Tecnologia, Universidade Federal de São Paulo (UNIFESP) Av. Cesare M. G. Lattes, 1201, Eugênio de Mello, São José dos Campos-SP, CEP: 12247-014, BrasilWeb of Scienc

Companies’ Response to Consumerization and their Motivation Factors for Implementation

The use of private-owned technological devices for professional activities is an even frequent and inevitable phenomenon. The variety of gadgets, the lack of control about their getting into the enterprise’s network and accessing information stands a growing challenge for Information Technology management and for the entire organization. By using a qualitative approach (content analysis) to examine cases of success in the acceptance of consumerization, this work aims to identify some motivation factors based in real experiences. Based on these factors, an organizational motivation profile classification emerges. Finally, a diagram based on Information System success is proposed intending to call for further research concerning consumerization

Twitter, Presidential Debates and Attention Economy: A Symbiosis between Television Audience and Social Media Users during Campaign Season

The year 2017 was an intense electoral year in Chile, both parliamentary and presidential. In this context, by using computer intelligence, an interdisciplinary team conducted a collection and volumetric analysis of over 3 million Twitter messages belonging to users that mentioned, at least once, any of the presidential candidates, both in the first and second voting round. Our goal was focused on analyzing the relationship between traditional media (radio and television) and Twitter, probing user interactions during the broadcast of live political shows, with emphasis on presidential debates. For this purpose, we carried out a volumetric analysis of all mentions in social media during the broadcast of live political shows to characterize the digital attention of the audience, under different parameters. Our results show that there is high user interest in the digital debate regarding presidential debates, a positive correlation between traditional media and Twitter during the broadcast of live political shows, and that, also, the latter trigger social media; furthermore, we verify the double screen phenomenon made possible by mobile platforms.El año 2017 fue un año de intensa actividad electoral en Chile, tanto parlamentaria como presidencial. En ese marco, mediante el uso de inteligencia computacional, un equipo interdisciplinario realizó una recolección y análisis volumétrico de más de 3 millones mensajes en Twitter pertenecientes a usuarios que mencionaran, al menos una vez, a alguno de los candidatos al sillón presidencial, tanto de primera como de segunda vuelta. Nuestro objetivo estuvo centrado en analizar la relación entre medios tradicionales (radio y televisión) y Twitter, explorando las interacciones de los usuarios durante la transmisión de programas políticos en vivo, con énfasis en los debates presidenciales. Para ello realizamos un análisis volumétrico de todas las menciones en la red social durante la emisión de los programas políticos en vivo para caracterizar la atención digital de la audiencia, bajo diferentes parámetros. Nuestros resultados muestran que existe un alto interés de los usuarios por debatir digitalmente en torno a los debates presidenciales, una correlación positiva entre medios tradicionales y Twitter durante la emisión de programas políticos en vivo, y que, además, estos últimos activan la red social; igualmente se verifica el fenómeno de la doble pantalla gracias al uso de plataformas móviles