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O Brasil é reconhecido mundialmente pelo seu excelente desempenho econômico e produtivo nos setores agropecuários. Com o crescimento da demanda mundial por alimentos o país ampliou sua área produtivas através da criação da última fronteira agrícola do mundo (MATOPIBA). A fim de apresentar a importância dessa fronteira agrícola no Brasil, construiu-se e analisou-se uma matriz de Insumo-Produto Inter-Regional contendo fluxos comerciais entre as regiões do MATOPIBA, Resto no Norte (RN), Resto do Nordeste (RNDT) e Restante do Brasil (RB). Tal matriz apresentou desagregação para 14 setores nas quatro regiões. Concluiu-se que, os setores do MATOPIBA, apesar de apresentarem menores multiplicadores de produção em relação ao RB, possui as maiores taxas de transbordamento de investimentos para as demais regiões, apresentando assim, capacidade mais elevada em impulsionar a indústria nacional do que qualquer outra região do modelo. E o choque na demanda final, nos principais setores agrícolas da região do MATOPIBA, apresentou grande perspectiva de crescimento em todo modelo, tonando-se provavelmente, grande alvo para investimentos futuros.Abstract: Brazil is recognized worldwide for its excellent economic and productive performance in the agricultural sectors. With the growth in world demand for food, the country expanded its productive area through the creation of the last agricultural frontier in the world (MATOPIBA). In order to present the importance of this agricultural frontier in Brazil, an Inter-Regional Input-Output matrix was constructed and analyzed containing trade flows between the regions of MATOPIBA, Resto no Norte (RN), Rest of Northeast (RNDT) and Rest of Brazil (RB). It was concluded that the MATOPIBA sectors, despite having lower production multipliers in relation to the RB, have the highest investment spillover rates to the other regions, thus presenting a higher capacity to boost the national industry than any other region of the model. And the shock in the final demand, in the main agricultural sectors of the MATOPIBA region, presented great growth perspective in every model.

The current study aimed to qualitatively investigate the perceived determinants of success in professional esports athletes. Guided by the bioecological model (BronfenbrennerMorris, 2006), thematic analysis was used to explore elite esports athletes' perceptions of success determinants. Semi-structured interviews were conducted with seven elite esports athletes. The interviews were used to investigate players' psychology when playing well, training in elite esports, and working in esports teams. Deductive and inductive analyses were conducted to capture the core themes of success in esports within the bioecological model. When playing well, elite esports athletes experienced high levels of confidence, uninterrupted focus, and flow states. Elite esport athletes use mental strategies to help regulate their emotions and remain mindful in the presence of "tilt". Furthermore, breathing techniques and tactical breaks were used when players felt nervous or when trying to "reset" from a stressful situation. When working in elite esport teams, players reported using strategies to improve team cohesion and that the biggest challenge was interpersonal disagreements. The results contribute to the growing body of literature highlighting the psychological similarities between elite esports and traditional sports athletes and serve as an index for future research into high-performance in esports.

La présente étude a évalué les effets de la formation d'un éventuel accord de libéralisation commerciale entre le Brésil, les États-Unis, l'Union Européenne et la Chine sur le PIB, sur le bien-être et sur les échanges commerciaux des pays membres. Pour atteindre l’objectif de ce travail, l’équilibre général calculable a été utilisé comme base, modélisé par le Projet d’Analyse de l’Équilibre Général (PAEG) pour les régions brésiliennes désagrégées. Les résultats indiquent une croissance du PIB, une amélioration du bien-être, ainsi qu'une amélioration d’échanges commerciaux brésiliens, représenté par les importations et les exportations. Abstract: The present study evaluated the effects of the formation of a possible free trade agreement between Brazil, the United States, the European Union and China in the GDP, welfare and trade of the member countries. In order to achieve the objective of this work, the computable general equilibrium was used as a basis, being modeled by General Equilibrium Analysis Project (GEAP) for the disaggregated Brazilian regions. The results show GDP growth, improved welfare, and improved Brazilian trade represented by imports and exports. Keywords: USA, European Union, China, PAEG. Recebido em: novembro/2019. Aprovado em: agosto/2020.

Bronchoalveolar lavage (BAL) is a key clinical and research tool in lung transplantation (LTx). However, BAL collection and processing are not standardized across LTx centers. This International Society for Heart and Lung Transplantation-supported consensus document on BAL standardization aims to clarify definitions and propose common approaches to improve clinical and research practice standards. The following 9 areas are covered: (1) bronchoscopy procedure and BAL collection, (2) sample handling, (3) sample processing for microbiology, (4) cytology, (5) research, (6) microbiome, (7) sample inventory/tracking, (8) donor bronchoscopy, and (9) pediatric considerations. This consensus document aims to harmonize clinical and research practices for BAL collection and processing in LTx. The overarching goal is to enhance standardization and multicenter collaboration within the international LTx community and enable improvement and development of new BAL-based diagnostics. ispartof: JOURNAL OF HEART AND LUNG TRANSPLANTATION vol:39 issue:11 pages:1171-1190 ispartof: location:United States status: published

We describe our use of balloon-expandable stents in pulmonary arteries for a variety of indications. This is an endovascular technique that provides an alternative treatment option to treat some forms of complex pulmonary artery disease when standard surgical or other endovascular options are not possible. This case series describes the successful treatment of four patients with different pulmonary artery diseases. Indications for stent placement include multiple broad-necked pulmonary artery pseudoaneurysms, symptomatic malignant pulmonary artery narrowing and post-surgical iatrogenic pulmonary artery stenosis. No stent-related complication had been identified from 3 months to 4 years of follow-up. All surviving patients have experienced sustained symptomatic improvement.

Introduction: This study expands results from recent prostatic urethral lift (PUL) clinical trials by examining outcomes within a large unconstrained multicenter data set. Methods: Retrosp...

Although Paraguay has a surplus of electricity generation capacity, an underdeveloped electricity transmission and distribution infrastructure has constrained economic growth. The trajectory of future electricity demand is therefore important for planning purposes. We create electricity demand scenarios for Paraguay between 2017 and 2050 for two climatic scenarios, the Representative Concentration Pathways (RCPs) 4.5 (medium atmospheric CO2 concentration) and 8.5 (high atmospheric CO2 concentration), in combination with three socio-economic scenarios, the Shared Socio-economic Pathways SSP1, SSP3 and SSP5. Using historical climatic and socio-economic data from 1985 to 2010, we estimate an autoregressive distributed lag model for Paraguayan power demand with an in-sample symmetric mean absolute percentage error (sMAPE) of 2.3% and an out-of-sample (2011–2016) ex-post sMAPE of 4.6%. We re-estimate the parameters on the full dataset 1985–2016 and produce electricity demand projections until 2050 for the selected scenarios. The scenarios show an increase in power demand until the period 2045, after which two of the six scenarios show a decline and the remainder continue increasing at a slower rate. The SSP1- and SSP5-based scenarios reach an annual demand of 65–80 TWh/year around 2045–2050, and the scenarios based on SSP3 reach an annual demand of 100–115 TWh/year around 2050. In addition to aid in energy planning, these scenarios may provide input to negotiations with neighbouring countries regarding Paraguay’s surplus generation capacity.

Background: The endothelial glycocalyx, a sieve-like structure located on the luminal surface of all blood vessels, has been found to be integral to regulation of capillary permeability and mechanotransduction. Given this, we investigated the role of endothelial glycocalyx breakdown products in organ donors and recipients in terms of acceptability for transplant and risk of primary graft dysfunction (PGD). Methods: Endothelial glycocalyx breakdown products were measured in the peripheral blood of 135 intended and actual organ donors. Breakdown product levels were tested for association with donor demographic and clinical data, organ acceptability for transplant along with lung recipient outcomes (n = 35). Liquid chromatography mass spectrometry analysis was performed to confirm glycosaminoglycan levels and sulfation patterns on donor samples (n = 15). In transplant recipients (n = 50), levels were measured pretransplant and daily for 4 days posttransplant. Levels were correlated with PGD severity and intubation time. Results: Decreased hyaluronan levels in peripheral blood independently predicted organ acceptability in intended and actual donors (odds ratio, 0.96; [95% confidence interval, 0.93-0.99] P = 0.026). Furthermore, high donor syndecan-1 levels were associated with PGD in recipients (3142 [1575-4829] versus 6229 [4009-8093] pg/mL; P = 0.045). In recipient blood, levels of syndecan-1 were correlated with severe (grades 2-3) PGD at 72 hours posttransplant (5982 [3016-17191] versus 3060 [2005-4824] pg/mL; P = 0.01). Conclusions: Endothelial glycocalyx breakdown occurs in lung transplant donors and recipients and predicts organ acceptability and development of PGD. Glycocalyx breakdown products may be useful biomarkers in transplantation, and interventions to protect the glycocalyx could improve transplant outcomes.

This study proposes a novel supply-side mechanism driving economic structural transformation: grid electrification. Increasing electricity availability affects the reallocation of inputs to more productive activities through generating higher returns and lowering entry costs in sectors with greater infrastructure intensity. The results of modeling and econometric analysis based on Brazil's historical data over the period 1970-2006 confirm that the manufacturing sector benefits the most in these two dimensions, followed by services and agriculture. The expansion of electricity infrastructure explains about 17 percent of this process and 32 percent of the observed increase in GDP per capita. Simulations of a multisector neoclassical growth model with heterogeneous firms help assessing the effectiveness of different electrification policies.

Soft polytomies emerge due to the application of handmade supertrees in phylogenetic community analysis, thus increasing uncertainties regarding phylogenetic diversity or community structure indices. Real-time integration of advances in phylogenetic knowledge among species from public data repositories, such as Open Tree of Life, may reduce this uncertainty. Based on an interface with Open Tree of Life, the Community Tree Optimizer (ComTreeOpt) classifies families from user-specific lists into resolvable and non-resolvable families, builds resolved subtrees for resolvable families and inserts them in the megatree previously pruned to species from non-resolvable families. Community trees optimized by ComTreeOpt show 30–50% fewer polytomies than non-optimized community trees, reducing the uncertainties in phylogenetic diversity and dispersion metrics that are due to a lack of phylogenetic resolution. ComTreeOpt enhances user-specific community trees in a rapid and inexpensive way based on available phylogenetic information, thus increasing the confidence in the metrics of phylogenetic diversity and dispersion.

Background Pulmonary arterial hypertension (PAH) is a progressively fatal disease. Parenteral prostanoids, including intravenous (IV) epoprostenol, are the most effective therapies for PAH. As epoprostenol requires continuous infusion, therapy is challenging and use is managed by specialist units. Aims To describe the clinical outcomes for the use of IV epoprostenol in an Australian pulmonary vascular disease unit and identify opportunities to improve its use. Method We conducted a retrospective chart review of all adult patients who received IV epoprostenol for PAH at Prince Charles Hospital. Data were collected at baseline, initiation of epoprostenol and quarterly to the end of the audit period or the discontinuation of epoprostenol. Descriptive statistics were performed and comparisons made to epoprostenol initiation. Kaplan-Meier curves were used to estimate survival outcomes. Results Thirty-nine patients received epoprostenol therapy. Most (87.2%) were female, had connective tissue disease (46.2%) or idiopathic PAH (35.9%) and had a World Health Organization functional Class of III or IV at initiation. The mean duration of epoprostenol therapy was 2.9 years. Intravenous epoprostenol was associated with favourable outcomes; 1, 3 and 5-year survival rates since initiation of 90.0, 75.8 and 68.2%; robust improvements in functional class; and improvements in 6-min walking distance of 160.4 m at 3 years; 94.9% patients experienced at least one drug-related adverse event and line complications were common. Conclusion Epoprostenol therapy was associated with impressive survival rates and durable improvements in functional outcomes. Epoprostenol therapy is challenging; however, it is manageable by the majority of patients with most experiencing positive, sustainable outcomes.

With the advent of Big Data platforms like Apache Storm, computations once deemed infeasible locally become possible at scale. However, doing so entails orchestrating powerful yet expensive clusters. With its focus on stream processing, Storm optimizes for low-latency and high throughput. However, to realize this goal and thereby maximize the utility of these clusters' resources, operators must execute these tasks under their optimal configurations. Yet, the search space for finding such configurations is so vast and time-consuming to explore so as to be effectively intractable due to issues like the temporal overhead of testing new candidate configurations, the sheer number of permutations of parameters within each configuration and their interdependence among each other. In order to efficiently cover the search space, we automate the process with genetic algorithms. Moreover, we fuse this technique not only with additional cluster information gleaned from JMX profiling and Storm performance data but also with classifiers constructed from training data from past executions of a plethora of Storm topologies. Utilizing a diverse set of Storm benchmark topologies as evaluation data, we show that the fully enhanced genetic algorithms can efficiently find configurations that perform on average 4.67x better than "rules of thumb"-derived manual baselines. Moreover, we demonstrate that our fully refined classifiers enhance the GA throughput on average across the topologies by 22% while reducing search time by a factor of 6.47x.

INTRODUCTION AND OBJECTIVES:Recent clinical trials reveal significant advantages Prostatic Urethra Lift (PUL) provides patients suffering from LUTS/BPH, however few studies have evaluated outcomes ...

Application performance monitoring in large data centers relies on either deploying expensive and specialized hardware at fixed locations or heavily customizing applications and collecting logs spread across thousands of servers. Such an endeavor makes performance diagnosis a time-consuming task for cloud providers and a problem beyond the control of cloud customers. We address this problem using emerging software defined paradigms such as Software Defined Networking and Network Function Virtualization as well as big data technologies. In this paper, we propose NetAlytics: a non-intrusive distributed performance monitoring system for cloud data centers. NetAlytics deploys customized monitors in the middle of the network which are transparent to end host applications, and leverages a real-time big data framework to analyze application behavior in a timely manner. NetAlytics can scale to packet rates of 40Gbps using only four monitoring cores and fifteen processing cores. Its placement algorithm can be tuned to minimize network bandwidth cost or server resources, and can reduce monitoring traffic overheads by a factor of 4.5. We present experiments that demonstrates how NetAlytics can be used to troubleshoot performance problems in load balancers, present comprehensive performance analysis, and provide metrics that drive automation tools, all while providing both low overhead monitors and scalable analytics.

We describe a stochastic dynamic programming model for maximising the revenue generated by regasification of LNG (liquefied natural gas) from storage tanks at importation terminals in relation to a natural gas spot market. We present three numerical resolution strategies: a posterior optimal strategy, a rolling intrinsic strategy and a full option strategy based on a least-squares Monte Carlo algorithm. We then compare model simulation results to the observed behaviour of three LNG importation terminals in the UK for the period April 2011 to April 2012, and find that there was low correlation between the observed regasification decisions of the operators and those suggested by the three simulated strategies. However, the actions suggested by the model simulations would have generated significantly higher revenues, suggesting that the facilities might have been operated sub-optimally. A further numerical experiment shows that increasing the storage and regasification capacities of a facility can significantly increase the achievable revenue, even without altering the amount of LNG received, by allowing operators more flexibility to defer regasification.

We present a framework for incorporating weather uncertainty into electricity demand forecasting when weather patterns cannot be assumed to be stable, such as in climate change scenarios. This is done by first calibrating an econometric model for electricity demand on historical data, and subsequently applying the model to a large number of simulated weather paths, together with projections for the remaining determinants. Simulated weather paths are generated based on output from a global circulation model, using a method that preserves the trend and annual seasonality of the first and second moments, as well as the spatial and serial correlations. The application of the framework is demonstrated by creating long-term, probabilistic electricity demand forecasts for Brazil for the period 2016–2100 that incorporates weather uncertainty for three climate change scenarios. All three scenarios indicate steady growth in annual average electricity demand until reaching a peak of approximately 1071–1200 TWh in 2060, then subsequently a decline, largely reflecting the trajectory of the population projections. The weather uncertainty in all scenarios is significant, with up to 400 TWh separating the 10th and the 90th percentiles, or approximately ±17% relative to the mean.