Programming of thermoelectric generation systems based on a heuristic composition of ant colonies

a b s t r a c t Studies related to biologically inspired optimization techniques, which are used for daily operational scheduling of thermoelectric generation systems, indicate that combinations of biologically inspired computation methods together with other optimization techniques have an important role to play in obtaining the best solutions in the shortest amount of processing time. Following this line of research, this article uses a methodology based on optimization by an ant colony to minimize the daily scheduling cost of thermoelectric units. The proposed model uses a Sensitivity Matrix (SM) based on the information provided by the Lagrange multipliers to improve the biologically inspired search process. Thus, a percentage of the individuals in the colony use this information in the evolutionary process of the colony. The results achieved through the simulations indicate that the use of the SM results in quality solutions with a reduced number of individuals

NLP based model for individual plant dispatch in long term hydrothermal planning

This paper presents a method to the hydrothermal dispatch using optimization techniques based on non linear programming techniques. To do so, the expected cost-to-go functions from a long term operation plannning strategic decision model are used. This decision model is based on stochastic dual dynamic programming and energy equivalent reservoirs. The proposed method considers a set of historical water inflow scenarios to the hydroelectric reservoirs. Those scenarios are used to simulate the long term operation planning to a given horizon. The results obtained from this disaggregation model (MIUH) are compared with those from the model officially adopted in the Brazilian power system, SUISHI-O. The latter is based on operation heuristics aiming at operating the reservoir maintaining the water storag e in similar levels, that is, trying to operate them in parallel.Este trabalho apresenta um modelo de despacho hidrotérmico à usinas individualizadas, utilizando métodos de otimização baseados em programação não linear. Para tanto, considera-se funções de custo futuro geradas por um modelo de decisão estratégica baseado em programação dinâmica e sistemas equivalentes de energia. O modelo proposto considera diversos cenários históricos de afluências hidrológicas às usinas hidrelétricas, os quais são simulados para um horizonte de planejamento da operação de médio/longo prazo. Os resultados obtidos através do modelo proposto, denominado Modelo Individualizado de Usinas Hidráulicas (MIUH), são comparados com os resultados obtidos a partir da utilização do modelo SUISHI-O adotado pelo Operador Nacional do Sistema Elétrico Brasileiro (ONS)

Euphol, a tetracyclic triterpene, from Euphorbia tirucalli induces autophagy and sensitizes temozolomide cytotoxicity on glioblastoma cells

Glioblastoma (GBM) is the most frequent and aggressive type of brain tumor. There are limited therapeutic options for GBM so that new and effective agents are urgently needed. Euphol is a tetracyclic triterpene alcohol, and it is the main constituent of the sap of the medicinal plant Euphorbia tirucalli. We previously identified anti-cancer activity in euphol based on the cytotoxicity screening of 73 human cancer cells. We now expand the toxicological screening of the inhibitory effect and bioactivity of euphol using two additional glioma primary cultures. Euphol exposure showed similar cytotoxicity against primary glioma cultures compared to commercial glioma cells. Euphol has concentration-dependent cytotoxic effects on cancer cell lines, with more than a five-fold difference in the IC50 values in some cell lines. Euphol treatment had a higher selective cytotoxicity index (0.64-3.36) than temozolomide (0.11-1.13) and reduced both proliferation and cell motility. However, no effect was found on cell cycle distribution, invasion and colony formation. Importantly, the expression of the autophagy-associated protein LC3-II and acidic vesicular organelle formation were markedly increased, with Bafilomycin A1 potentiating cytotoxicity. Finally, euphol also exhibited antitumoral and antiangiogenic activity in vivo, using the chicken chorioallantoic membrane assay, with synergistic temozolomide interactions in most cell lines. In conclusion, euphol exerted in vitro and in vivo cytotoxicity against glioma cells, through several cancer pathways, including the activation of autophagy-associated cell death. These findings provide experimental support for further development of euphol as a novel therapeutic agent for GBM, either alone or in combination chemotherapy.The work was supported by the Amazonia Fitomedicamentos (FITO05/2012) Ltda. and Barretos Cancer Hospital, all from Brazil

2 nd Brazilian Consensus on Chagas Disease, 2015

Abstract Chagas disease is a neglected chronic condition with a high burden of morbidity and mortality. It has considerable psychological, social, and economic impacts. The disease represents a significant public health issue in Brazil, with different regional patterns. This document presents the evidence that resulted in the Brazilian Consensus on Chagas Disease. The objective was to review and standardize strategies for diagnosis, treatment, prevention, and control of Chagas disease in the country, based on the available scientific evidence. The consensus is based on the articulation and strategic contribution of renowned Brazilian experts with knowledge and experience on various aspects of the disease. It is the result of a close collaboration between the Brazilian Society of Tropical Medicine and the Ministry of Health. It is hoped that this document will strengthen the development of integrated actions against Chagas disease in the country, focusing on epidemiology, management, comprehensive care (including families and communities), communication, information, education, and research

Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences

The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & Nemésio 2007; Donegan 2008, 2009; Nemésio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on 18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based researchers who signed it in the short time span from 20 September to 6 October 2016

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio