934 resultados para Road Crashes
Resumo:
Introduction The incidence of American cutaneous leishmaniasis (ACL) is increasing in Latin America, especially in Brazil, where 256,587 cases were confirmed in the last decade. Methods This study used a Bayesian model to examine the spatial and temporal distribution of ACL cases between 2000 and 2009 in 61 counties of State of Maranhão located along the three main road and railway corridors. Results During the study period, 13,818 cases of ACL were recorded. There was a significant decrease in the incidence of ACL in the ten study years. The recorded incidence rate ranged from 7.36 to 241.45 per 100,000 inhabitants. The relative risk increased in 77% of the counties, decreased in 18% and was maintained in only five counties. Conclusions Although there was a decreased incidence of the disease, ACL was present in all of the examined municipalities, thus maintaining the risk of contracting this illness.
Resumo:
Sonae MC is considered the first success case of Kaizen in the retail industry. Before becoming a true role model for so many companies, there was a long road to walk. However, it may still be hard to understand the steps taken on the way. How could a training program develop into an integral continuous improvement system, and how did it affect the company – its people, culture, operations and strategy? How was it possible to get everyone on board? How could it be sustained until today, when Kaizen usually fails in the West? What were the critical factors for success?
Resumo:
In broad sense, Project Financing1 as a mean of financing large scale infrastructural projects worldwide has had a steady growth in popularity for the last 20 years. This growth has been relatively unscathed from most economic cycles. However in the wake of the 2007 systemic Financial Crisis, Project Financing was also in trouble. The liquidity freeze and credit crunch that ensued affected all parties involved. Traditional Lenders, of this type of financial instrument, locked-in long-term contractual obligations, were severely hit with scarcity of funding compounded by rapidly increasing cost of funding. All the while, Banks were “rescued” by the concerted actions of Central Banks and other Multi-Lateral Agencies around the world but at the same time “stressed” by upcoming regulatory effort (Basel Committee). This impact resulted in specific changes to this type of long-term financing. Changes such as Commercial Banks’ increased risk aversion; pricing increase and maturities decrease of credit facilities; enforcement of Market Disruption Event clauses; partial responsibility for project risk by Multilateral Agencies; and adoption of utility-like availability payments in other industrial sectors such as transportation and even social infrastructure. To the extent possible, this report is then divided in three parts. First, it begins with a more instructional part, touching academic literature (theory) and giving the Banks perspective (practice), but mostly as an overview of Project Finance for awareness’ sake. The renowned Harvard Business School professor – Benjamin Esty, states2 that Project Finance is a “relatively unexplored territory for both empirical and theoretical research” which means that academic research efforts are lagging the practice of Project Finance. Second, the report presents a practical case regarding the first Road Concession in Portugal in 1998 ending with the lessons learned 10 years after Financial Close. Lastly, the report concludes with the analysis of the current trends and changes to the industry post Financial Crisis of the late 2000’s. To achieve this I’ll reference relevant papers, books on the subject, online articles and my own experience in the Project Finance Department at a major Portuguese Investment Bank. Regarding the latter, with the signing of a confidentiality agreement, I’m duly omitting sensitive and proprietary bank information.
Resumo:
Nowadays, road accidents are a major public health problem, which increase is forecasted if road safety is not treated properly, dying about 1.2 million people every year around the globe. In 2012, Portugal recorded 573 fatalities in road accidents, on site, revealing the largest decreasing of the European Union for 2011, along with Denmark. Beyond the impact caused by fatalities, it was calculated that the economic and social costs of road accidents weighted about 1.17% of the Portuguese gross domestic product in 2010. Visual Analytics allows the combination of data analysis techniques with interactive visualizations, which facilitates the process of knowledge discovery in sets of large and complex data, while the Geovisual Analytics facilitates the exploration of space-time data through maps with different variables and parameters that are under analysis. In Portugal, the identification of road accident accumulation zones, in this work named black spots, has been restricted to annual fixed windows. In this work, it is presented a dynamic approach based on Visual Analytics techniques that is able to identify the displacement of black spots on sliding windows of 12 months. Moreover, with the use of different parameterizations in the formula usually used to detect black spots, it is possible to identify zones that are almost becoming black spots. Through the proposed visualizations, the study and identification of countermeasures to this social and economic problem can gain new grounds and thus the decision- making process is supported and improved.
Resumo:
This paper aims at developing a collision prediction model for three-leg junctions located in national roads (NR) in Northern Portugal. The focus is to identify factors that contribute for collision type crashes in those locations, mainly factors related to road geometric consistency, since literature is scarce on those, and to research the impact of three modeling methods: generalized estimating equations, random-effects negative binomial models and random-parameters negative binomial models, on the factors of those models. The database used included data published between 2008 and 2010 of 177 three-leg junctions. It was split in three groups of contributing factors which were tested sequentially for each of the adopted models: at first only traffic, then, traffic and the geometric characteristics of the junctions within their area of influence; and, lastly, factors which show the difference between the geometric characteristics of the segments boarding the junctionsâ area of influence and the segment included in that area were added. The choice of the best modeling technique was supported by the result of a cross validation made to ascertain the best model for the three sets of researched contributing factors. The models fitted with random-parameters negative binomial models had the best performance in the process. In the best models obtained for every modeling technique, the characteristics of the road environment, including proxy measures for the geometric consistency, along with traffic volume, contribute significantly to the number of collisions. Both the variables concerning junctions and the various national highway segments in their area of influence, as well as variations from those characteristics concerning roadway segments which border the already mentioned area of influence have proven their relevance and, therefore, there is a rightful need to incorporate the effect of geometric consistency in the three-leg junctions safety studies.
Resumo:
We test whether cross-delisted firms from the major U.S. stock exchanges experience an increase in crash risk associated with earnings management. Consistent with our prediction, we find that earnings management have a greater positive impact on stock price crash risk post-cross-delisting when compared to a sample of still cross-listed firms. Moreover, our results suggest that this effect is more pronounced for crossdelisted firms from countries with weaker investor protection and poorer quality of their information environment. We further examine whether managers’ ability to manipulate earnings increases post-cross-delisting around seasoned equity offerings. Our evidence shows that cross-delisted firms that engage in earnings management to inflate reported earnings prior to a seasoned equity offering are more likely to observe a subsequent stock price crash.
Resumo:
Nowadays, recycling has become a very important objective for the society in the scope of a closed loop product life cycle. In recent years, new recycling techniques have been developed in the area of road pavements that allow the incorporation of high percentages of reclaimed asphalt (RA) materials in recycled asphalt mixtures. The use of foamed bitumen for production of recycled asphalt mixtures is one of those techniques, which also allows the reduction of the mixing temperatures (warm mix technology). However, it is important to evaluate if this solution can maintain or improve the performance of the resulting mixtures. Thus, the main aim of the present study is to assess the performance of warm recycled asphalt mixtures incorporating foamed bitumen as the new binder and 50% RA, in comparison with a control mixture using conventional bitumen. Four mixtures have been produced with 50% RA, one of them at typical high mixing temperatures with a conventional bitumen (control mixture) and the other three with foamed bitumen at different production temperatures. These four mixtures were tested to evaluate their compactability and water sensitivity. The laboratory test results showed that the production of recycled mixtures with foamed bitumen can be reduced by 40ºC without changing the performance of the resulting mixtures.
Resumo:
High levels of marine salt deposition present in coastal areas have a relevant effect on road runoff characteristics. This study assesses this effect with the purpose of identifying the relationships between monitored water quality parameters and intrinsic site variables. To achieve this objective, an extensive monitoring program was conducted on a Portuguese coastal highway. The study included 30 rainfall events, in different weather, traffic, and salt deposition conditions. The evaluations of various water quality parameters were carried out in over 200 samples. In addition, the meteorological, hydrological, and traffic parameters were continuously measured. The salt deposition rates were determined by means of a wet candle device, which is an innovative feature of the monitoring program. The relation between road runoff pollutants and independent variables associated with weather, traffic, and salt deposition conditions was assessed. Significant correlations among pollutants were observed. A high salinity concentration and its influence on the road runoff were confirmed. Furthermore, the concentrations of the most relevant pollutants seemed to be very dependent on some meteorological variables, particularly the duration of the antecedent dry period prior to each rainfall event and the average wind speed.
Resumo:
The research aimed to establish tyre-road noise models by using a Data Mining approach that allowed to build a predictive model and assess the importance of the tested input variables. The data modelling took into account three learning algorithms and three metrics to define the best predictive model. The variables tested included basic properties of pavement surfaces, macrotexture, megatexture, and uneven- ness and, for the first time, damping. Also, the importance of those variables was measured by using a sensitivity analysis procedure. Two types of models were set: one with basic variables and another with complex variables, such as megatexture and damping, all as a function of vehicles speed. More detailed models were additionally set by the speed level. As a result, several models with very good tyre-road noise predictive capacity were achieved. The most relevant variables were Speed, Temperature, Aggregate size, Mean Profile Depth, and Damping, which had the highest importance, even though influenced by speed. Megatexture and IRI had the lowest importance. The applicability of the models developed in this work is relevant for trucks tyre-noise prediction, represented by the AVON V4 test tyre, at the early stage of road pavements use. Therefore, the obtained models are highly useful for the design of pavements and for noise prediction by road authorities and contractors.
Resumo:
prova tipográfica / uncorrected proof
Resumo:
At present, Spain faces one of the key moments in planning the future design of the infrastructure network. As a consequence of the critical role played by haulage in intra-European trade, the most important investments are those that guarantee that road haulage traffic can move freely at the borders. That is why it is necessary to make serious evaluations of the economic and social profitability of these investments. Normally the most significant social benefit of investment projects in transport infrastructure is time saving, which in turn changes traffic intensity. In this article we analyse the changes in the user excess caused by public investment in transport infrastructure planned by the Spanish government and which will be located on the border between Spain and France. In particular, we study the increase in network user surplus for HGV traffic in the Spanish and French border zones in the Pyrenees.
Resumo:
Recent concessions in France and in the US have resulted in a dramatic difference in the valuation placed on the toll roads; the price paid by the investors in France was twelve times current cash flow whereas investors paid sixty times current cash flow for the U.S. toll roads. In this paper we explore two questions: What accounts for the difference in these multiples, and what are the implications with respect to the public interest. Our analysis illustrates how structural and procedural decisions made by the public owner affect the concession price. Further, the terms of the concession have direct consequences that are enjoyed or borne by the various stakeholders of the toll road.
Resumo:
This paper demonstrates that an asset pricing model with least-squares learning can lead to bubbles and crashes as endogenous responses to the fundamentals driving asset prices. When agents are risk-averse they need to make forecasts of the conditional variance of a stock’s return. Recursive updating of both the conditional variance and the expected return implies several mechanisms through which learning impacts stock prices. Extended periods of excess volatility, bubbles and crashes arise with a frequency that depends on the extent to which past data is discounted. A central role is played by changes over time in agents’ estimates of risk.