809 resultados para Real-world process
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Now 40, Colby’s Environmental Studies Program is growing exponentially, equipping students to tackle real-world problems.
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Building Risk-Neutral Densities (RND) from options data can provide market-implied expectations about the future behavior of a financial variable. And market expectations on financial variables may influence macroeconomic policy decisions. It can be useful also for corporate and financial institutions decision making. This paper uses the Liu et all (2007) approach to estimate the option-implied Risk-neutral densities from the Brazilian Real/US Dollar exchange rate distribution. We then compare the RND with actual exchange rates, on a monthly basis, in order to estimate the relative risk-aversion of investors and also obtain a Real-world density for the exchange rate. We are the first to calculate relative risk-aversion and the option-implied Real World Density for an emerging market currency. Our empirical application uses a sample of Brazilian Real/US Dollar options traded at BM&F-Bovespa from 1999 to 2011. The RND is estimated using a Mixture of Two Log-Normals distribution and then the real-world density is obtained by means of the Liu et al. (2007) parametric risktransformations. The relative risk aversion is calculated for the full sample. Our estimated value of the relative risk aversion parameter is around 2.7, which is in line with other articles that have estimated this parameter for the Brazilian Economy, such as Araújo (2005) and Issler and Piqueira (2000). Our out-of-sample evaluation results showed that the RND has some ability to forecast the Brazilian Real exchange rate. Abe et all (2007) found also mixed results in the out-of-sample analysis of the RND forecast ability for exchange rate options. However, when we incorporate the risk aversion into RND in order to obtain a Real-world density, the out-of-sample performance improves substantially, with satisfactory results in both Kolmogorov and Berkowitz tests. Therefore, we would suggest not using the “pure” RND, but rather taking into account risk aversion in order to forecast the Brazilian Real exchange rate.
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Brasil e outros mercados emergentes continuarão a apresentar muitas oportunidades de investimento nos próximos anos. Profissionais financeiros que gerenciam os processos de orçamento de capital nas empresas terão grandes desafios a enfrentar. Características específicas destes projetos como preços ligados a commodities (por exemplo: petróleo e gás e projetos agrícolas) e as incertezas habituais relacionadas com os mercados emergentes são desafios adicionais. Neste cenário, ferramentas mais sofisticadas de orçamento de capital como Opções Reais, oferece uma teoria mais robusta para lidar com incerteza, flexibilidade gerencial, e os resultados voláteis embutidas nestas oportunidades. A teoria de Opções Reais assume que o envolvimento dos gestores nos projetos gera valor à medida que potencializam os bons resultados ou reduzem as perdas por abandonar projetos com maus resultados. O objetivo principal desta pesquisa foi aplicar a análise de Opções Reais para um projeto de investimento e discutir o processo e os resultados da metodologia. O estudo de caso analisa retroativamente um projeto de investimento na Colômbia e compara os resultados sob o tradicional VPL e Opções Reais. As técnicas de avaliação foram realizadas como se estivessem sendo aplicadas no momento em que o projeto foi aprovado, e depois comparadas com o desempenho real do projeto. O estudo de caso avaliado possui dois tipos de Opções Reais: primeiro, o efeito de uma opção para cancelar um contrato que é analisado a partir da perspectiva do cliente que pode exercer essa opção, e o segundo, a opção de abandonar e adiar a partir da perspectiva da empresa que irá executar a investimento.
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Includes bibliography
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Background Current recommendations for antithrombotic therapy after drug-eluting stent (DES) implantation include prolonged dual antiplatelet therapy (DAPT) with aspirin and clopidogrel >= 12 months. However, the impact of such a regimen for all patients receiving any DES system remains unclear based on scientific evidence available to date. Also, several other shortcomings have been identified with prolonged DAPT, including bleeding complications, compliance, and cost. The second-generation Endeavor zotarolimus-eluting stent (E-ZES) has demonstrated efficacy and safety, despite short duration DAPT (3 months) in the majority of studies. Still, the safety and clinical impact of short-term DAPT with E-ZES in the real world is yet to be determined. Methods The OPTIMIZE trial is a large, prospective, multicenter, randomized (1: 1) non-inferiority clinical evaluation of short-term (3 months) vs long-term (12-months) DAPT in patients undergoing E-ZES implantation in daily clinical practice. Overall, 3,120 patients were enrolled at 33 clinical sites in Brazil. The primary composite endpoint is death (any cause), myocardial infarction, cerebral vascular accident, and major bleeding at 12-month clinical follow-up post-index procedure. Conclusions The OPTIMIZE clinical trial will determine the clinical implications of DAPT duration with the second generation E-ZES in real-world patients undergoing percutaneous coronary intervention. (Am Heart J 2012;164:810-816.e3.)
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Objectives: Previous research conducted in the late 1980s suggested that vehicle impacts following an initial barrier collision increase severe occupant injury risk. Now over 25years old, the data are no longer representative of the currently installed barriers or the present US vehicle fleet. The purpose of this study is to provide a present-day assessment of secondary collisions and to determine if current full-scale barrier crash testing criteria provide an indication of secondary collision risk for real-world barrier crashes. Methods: To characterize secondary collisions, 1,363 (596,331 weighted) real-world barrier midsection impacts selected from 13years (1997-2009) of in-depth crash data available through the National Automotive Sampling System (NASS) / Crashworthiness Data System (CDS) were analyzed. Scene diagram and available scene photographs were used to determine roadside and barrier specific variables unavailable in NASS/CDS. Binary logistic regression models were developed for second event occurrence and resulting driver injury. To investigate current secondary collision crash test criteria, 24 full-scale crash test reports were obtained for common non-proprietary US barriers, and the risk of secondary collisions was determined using recommended evaluation criteria from National Cooperative Highway Research Program (NCHRP) Report 350. Results: Secondary collisions were found to occur in approximately two thirds of crashes where a barrier is the first object struck. Barrier lateral stiffness, post-impact vehicle trajectory, vehicle type, and pre-impact tracking conditions were found to be statistically significant contributors to secondary event occurrence. The presence of a second event was found to increase the likelihood of a serious driver injury by a factor of 7 compared to cases with no second event present. The NCHRP Report 350 exit angle criterion was found to underestimate the risk of secondary collisions in real-world barrier crashes. Conclusions: Consistent with previous research, collisions following a barrier impact are not an infrequent event and substantially increase driver injury risk. The results suggest that using exit-angle based crash test criteria alone to assess secondary collision risk is not sufficient to predict second collision occurrence for real-world barrier crashes.
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Outside of relatively limited crash testing with large trucks, very little is known regarding the performance of traffic barriers subjected to real-world large truck impacts. The purpose of this study was to investigate real-world large truck impacts into traffic barriers to determine barrier crash involvement rates, the impact performance of barriers not specifically designed to redirect large trucks, and the real-world performance of large-truck-specific barriers. Data sources included the Fatality Analysis Reporting System (2000-2009), the General Estimates System (2000-2009) and 155 in-depth large truck-to-barrier crashes from the Large Truck Crash Causation Study. Large truck impacts with a longitudinal barrier were found to comprise 3 percent of all police-reported longitudinal barrier impacts and roughly the same proportion of barrier fatalities. Based on a logistic regression model predicting barrier penetration, large truck barrier penetration risk was found to increase by a factor of 6 for impacts with barriers designed primarily for passenger vehicles. Although large-truck-specific barriers were found to perform better than non-heavy vehicle specific barriers, the penetration rate of these barriers were found to be 17 percent. This penetration rate is especially a concern because the higher test level barriers are designed to protect other road users, not the occupants of the large truck. Surprisingly, barriers not specifically designed for large truck impacts were found to prevent large truck penetration approximately half of the time. This suggests that adding costlier higher test level barriers may not always be warranted, especially on roadways with lower truck volumes.
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Recently, the Centre for Immunity, Infection and Evolution sponsored a one-day symposium entitled "Wild Immunology." The CIIE is a new Wellcome Trust-funded initiative with the remit to connect evolutionary biology and ecology with research in immunology and infectious diseases in order to gain an interdisciplinary perspective on challenges to global health. The central question of the symposium was, "Why should we try to understand infection and immunity in wild systems?" Specifically, how does the immune response operate in the wild and how do multiple coinfections and commensalism affect immune responses and host health in these wild systems? The symposium brought together a broad program of speakers, ranging from laboratory immunologists to infectious disease ecologists, working on wild birds, unmanaged animals, wild and laboratory rodents, and on questions ranging from the dynamics of coinfection to how commensal bacteria affect the development of the immune system. The meeting on wild immunology, organized by Amy Pedersen, Simon Babayan, and Rick Maizels, was held at the University of Edinburgh on 30 June 2011.
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Previous research conducted in the late 1980’s suggested that vehicle impacts following an initial barrier collision increase severe occupant injury risk. Now over twenty-five years old, the data used in the previous research is no longer representative of the currently installed barriers or US vehicle fleet. The purpose of this study is to provide a present-day assessment of secondary collisions and to determine if full-scale barrier crash testing criteria provide an indication of secondary collision risk for real-world barrier crashes. The analysis included 1,383 (596,331 weighted) real-world barrier midsection impacts selected from thirteen years (1997-2009) of in-depth crash data available through the National Automotive Sampling System (NASS) / Crashworthiness Data System (CDS). For each suitable case, the scene diagram and available scene photographs were used to determine roadside and barrier specific variables not available in NASS/CDS. Binary logistic regression models were developed for second event occurrence and resulting driver injury. Barrier lateral stiffness, post-impact vehicle trajectory, vehicle type, and pre-impact tracking conditions were found to be statistically significant contributors toward secondary event occurrence. The presence of a second event was found to increase the likelihood of a serious driver injury by a factor of seven compared to cases with no second event present. Twenty-four full-scale crash test reports were obtained for common non-proprietary US barriers, and the risk of secondary collisions was determined using recommended evaluation criteria from NCHRP Report 350. It was found that the NCHRP Report 350 exit angle criterion alone was not sufficient to predict second collision occurrence for real-world barrier crashes.
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We present a model of spike-driven synaptic plasticity inspired by experimental observations and motivated by the desire to build an electronic hardware device that can learn to classify complex stimuli in a semisupervised fashion. During training, patterns of activity are sequentially imposed on the input neurons, and an additional instructor signal drives the output neurons toward the desired activity. The network is made of integrate-and-fire neurons with constant leak and a floor. The synapses are bistable, and they are modified by the arrival of presynaptic spikes. The sign of the change is determined by both the depolarization and the state of a variable that integrates the postsynaptic action potentials. Following the training phase, the instructor signal is removed, and the output neurons are driven purely by the activity of the input neurons weighted by the plastic synapses. In the absence of stimulation, the synapses preserve their internal state indefinitely. Memories are also very robust to the disruptive action of spontaneous activity. A network of 2000 input neurons is shown to be able to classify correctly a large number (thousands) of highly overlapping patterns (300 classes of preprocessed Latex characters, 30 patterns per class, and a subset of the NIST characters data set) and to generalize with performances that are better than or comparable to those of artificial neural networks. Finally we show that the synaptic dynamics is compatible with many of the experimental observations on the induction of long-term modifications (spike-timing-dependent plasticity and its dependence on both the postsynaptic depolarization and the frequency of pre- and postsynaptic neurons).
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This study investigated the use of real-world contexts during instruction in a high school physics class - through building file folder bridges- and the resulting effect upon student interest in the subject matter, level of understanding, and degree of retention. In particular, the study focused upon whether increases in student interest were attained through the use of real-world contexts, and if the elevated interest level led to a higher degree of subject matter understanding than would be achieved using more traditional teaching methods. The study also determined whether using real-world contexts ultimately resulted in achievement of greater levels of knowledge retention by students. Class observations during traditionally taught units and during units that incorporated real-world contexts, along with a post-graduation questionnaire, were used to assess differences in student interest levels. Student pre- and post-unit test scores were evaluated and compared to determine if statistical differences existed in levels of understanding resulting from the different teaching methods. The post-graduation questionnaire results provided evidence of retention that could be related back to teaching methods. The results of this study revealed the importance of incorporating real-world contexts into science and mathematics courses. Students better understood the relevance of the lessons, which led to higher levels of interest and greater understanding than was achieved through more traditional teaching methods. The use of real-world contexts improved knowledge retention.
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This research project measured the effects of real-world content in a science classroom by determining change (deep knowledge of life science content, including ecosystems from MDE – Grade Level Content Expectations) in a subset of students (6th Grade Science) that may result from the addition of curriculum (real-world content of rearing trout in the classroom). Data showed large gains from the pre-test to post-test in students from both the experimental and control groups. The ecology unit with the implementation of real-world content [trout] was even more successful, and improved students’ deep knowledge of ecosystem content from Michigan’s Department of Education Grade Level Content Expectations. The gains by the experimental group on the constructed response section of the test, which included higher cognitive level items, were significant. Clinical interviews after the post-test confirmed increases in deep knowledge of ecosystem concepts in the experimental group, by revealing that a sample of experimental group students had a better grasp of important ecology concepts as compared to a sample of control group students.