Comparative analysis of strut-and-tie models using Smooth Evolutionary Structural Optimization

The strut-and-tie models are widely used in certain types of structural elements in reinforced concrete and in regions with complexity of the stress state, called regions D, where the distribution of deformations in the cross section is not linear. This paper introduces a numerical technique to determine the strut-and-tie models using a variant of the classical Evolutionary Structural Optimization, which is called Smooth Evolutionary Structural Optimization. The basic idea of this technique is to identify the numerical flow of stresses generated in the structure, setting out in more technical and rational members of strut-and-tie, and to quantify their value for future structural design. This paper presents an index performance based on the evolutionary topology optimization method for automatically generating optimal strut-and-tie models in reinforced concrete structures with stress constraints. In the proposed approach, the element with the lowest Von Mises stress is calculated for element removal, while a performance index is used to monitor the evolutionary optimization process. Thus, a comparative analysis of the strut-and-tie models for beams is proposed with the presentation of examples from the literature that demonstrates the efficiency of this formulation. © 2013 Elsevier Ltd.

An assessment of the economic and social impacts of climate change on the energy sector in the Caribbean

The present report assesses the economic and social impacts of climate change on the energy sector in Antigua and Barbuda, the Bahamas, Barbados, Belize, Cuba, Dominica, the Dominican Republic, Haiti, Grenada, Guyana, Jamaica, Saint Kitts and Nevis, Saint Vincent and the Grenadines, Saint Lucia, Suriname, and Trinidad and Tobago. In the study, the Artificial Neural Network methodology was employed to model the relationship between climate change and energy demand. The viability of the actions proposed were assessed using cost benefit analyses based on models from the National Renewable Energy Laboratory (NREL) of the United States of America.

An assessment of the economic impact of climate change on the Agriculture, Health and Tourism sectors in Jamaica

This report analyses the agriculture, health and tourism sectors in Jamaica to assess the potential economic impacts of climate change on the sectors. The fundamental aim of this report is to assist with the development of strategies to deal with the potential impact of climate change on Jamaica. It also has the potential to provide essential input for identifying and preparing policies and strategies to help move the Region closer to solving problems associated with climate change and attaining individual and regional sustainable development goals. Some of the key anticipated manifestations of climate change for the Caribbean include elevated air and sea-surface temperatures, sea-level rise, possible changes in extreme events and a reduction in freshwater resources. The economic impact of climate change on the three sectors was estimated for the A2 and B2 IPCC scenarios until 2050. An evaluation of various adaptation strategies was also undertaken for each sector using standard evaluation techniques. The outcomes from investigating the agriculture sector indicate that for the sugar-cane subsector the harvests under both the A2 and B2 scenarios decrease at first and then increase as the mid-century mark is approached. With respect to the yam subsector the results indicate that the yield of yam will increase from 17.4 to 23.1 tonnes per hectare (33%) under the A2 scenario, and 18.4 to 23.9 (30%) tonnes per hectare under the B2 scenario over the period 2011 to 2050. Similar to the forecasts for yam, the results for escallion suggest that yields will continue to increase to mid-century. Adaptation in the sugar cane sub-sector could involve replanting and irrigation that appear to generate net benefits at the three selected discount rates for the A2 scenario, but only at a discount rate of 1% for the B2 scenario. For yam and escallion, investment in irrigation will earn significant net benefits for both the A2 and B2 scenarios at the three selected rates of discount. It is recommended that if adaptation strategies are part of a package of strategies for improving efficiency and hence enhancing competitiveness, then the yields of each crop can be raised sufficiently to warrant investment in adaptation to climate change. The analysis of the health sector demonstrates the potential for climate change to add a substantial burden to the future health systems in Jamaica, something that that will only compound the country’s vulnerability to other anticipated impacts of climate change. The results clearly show that the incidence of dengue fever will increase if climate change continues unabated, with more cases projected for the A2 scenario than the B2. The models predicted a decrease in the incidence of gastroenteritis and leptospirosis with climate change, indicating that Jamaica will benefit from climate change with a reduction in the number of cases of gastroenteritis and leptospirosis. Due to the long time horizon anticipated for climate change, Jamaica should start implementing adaptation strategies focused on the health sector by promoting an enabling environment, strengthening communities, strengthening the monitoring, surveillance and response systems and integrating adaptation into development plans and actions. Small-island developing states like Jamaica must be proactive in implementing adaptation strategies, which will reduce the risk of climate change. On the global stage the country must continue to agitate for the implementation of the mitigation strategies for developed countries as outlined in the Kyoto protocol. The results regarding the tourism sector suggest that the sector is likely to incur losses due to climate change, the most significant of which is under the A2 scenario. Climatic features, such as temperature and precipitation, will affect the demand for tourism in Jamaica. By 2050 the industry is expected to lose US$ 132.2 million and 106.1 million under the A2 and B2 scenarios, respectively. In addition to changes in the climatic suitability for tourism, climate change is also likely to have important supply-side effects from extreme events and acidification of the ocean. The expected loss from extreme events is projected to be approximately US$ 5.48 billion (A2) and US$ 4.71 billion (B2). Even more devastating is the effect of ocean acidification on the tourism sector. The analysis shows that US$ 7.95 billion (A2) and US$ 7.04 billion is expected to be lost by mid-century. The benefit-cost analysis indicates that most of the adaptation strategies are expected to produce negative net benefits, and it is highly likely that the cost burden would have to be carried by the state. The options that generated positive ratios were: redesigning and retrofitting all relevant tourism facilities, restoring corals and educating the public and developing rescue and evacuation plans. Given the relative importance of tourism to the macroeconomy one possible option is to seek assistance from multilateral funding agencies. It is recommended that the government first undertake a detailed analysis of the vulnerability of each sector and, in particular tourism, to climate change. Further, more realistic socio-economic scenarios should be developed so as to inform future benefit-cost analysis.

An assessment of the economic impact of climate change on the coastal and human settlements Sector in Barbados

This study assesses the potential economic impact of climate change on coastal human settlements in the Caribbean, with specific reference to Barbados, and evaluates the costs and benefits of undertaking various adaptation strategies. The aim is to assist Caribbean territories in developing the strategies and capacity needed to deal with the potential impact of severe weather events that are anticipated to occur with increased frequency and intensity as a result of climate change. Some of the key anticipated manifestations of climate change for the Caribbean include elevated air and sea-surface temperatures, sea-level rise, possible changes in extreme events and a reduction in freshwater resources.This research focuses on how human settlements distributed along the coast of Guyana, especially those in low elevation coastal zones (LECZ)are affected by these impacts. Focusing on three potential transmission sources - sea-level rise, stronger storm hazards and increased precipitation – the study considers the vulnerability of populations in the LECZ areas and estimates the overall threat posed by climate change to coastal populations and infrastructure. Vulnerability to climate change (measured as exposed assets) was estimated for four emission scenarios as outlined by the Special Report on Emissions Scenarios (SRES), namely the A1, A2, B1 and B2 scenarios for the period 2010 to 2100 and as detailed by the Intergovernmental Panel on Climate Change (IPCC), using global circulation models (GCM) and storm surge hazard maps.

An assessment of the economic impact of climate change on the Agriculture Sector in Jamaica

The agricultural sector‟s contribution to GDP and to exports in Jamaica has been declining with the post-war development process that has led to the differentiation of the economy. In 2010, the sector contributed 5.8% of GDP, and 3% to the exports (of goods), but with 36% of employment, it continues to be a major employer. With a little less than half of the population living in rural communities, agricultural activities, and their linkages with other economic activities, continue to play an important role as a source of livelihoods, and by extension, the economic development of the country. Sugar cane cultivation has, with the exception of a couple of decades in the twentieth century when it was superseded by bananas, dominated the agricultural export sector for centuries as the source of the raw materials for the manufacture of sugar for export. In 2005, sugar cane itself accounted for 6.4% of the sector‟s contribution to GDP, and 52% of the contribution of agricultural exports to GDP. Production for the domestic market has long been the larger subsector, organized around the production of root crops, especially yams, vegetables and condiments. To analyse the potential impact of climate change on the agricultural sector, this study selected three important crops for detailed examination. In particular, the study selected sugar cane because of its overwhelming importance to the export subsector of agriculture, and yam and escallion for both their contribution to the domestic subsector as well as the preeminent role yams and escallion play in the economic activities of the communities in the hills of central Jamaica, and the plains of the southwest respectively. As with other studies in this project, the methodology adopted was to compare the estimated values of output on the SRES A2 and B2 Scenarios with the value of output on a “baseline” Business As Usual (BAU), and then estimate the net benefits of investment in the relevant to climate change for the selected crops. The A2 and B2 Scenarios were constructed by applying forecasts of changes in temperature and precipitation generated by INSMET from ECHAM inspired climate models. The BAU “baseline” was a linear projection of the historical trends of yields for each crop. Linear models of yields were estimated for each crop with particular attention to the influence of the two climate variables – temperature and precipitation. These models were then used to forecast yields up to 2050 (table1). These yields were then used to estimate the value of output of the selected crop, as well as the contribution to overall GDP, on each Scenario. The analysis suggested replanting sugar cane with heat resistant varieties, rehabilitating irrigation systems where they existed, and establishing technologically appropriate irrigation systems where they were not for the three selected crops.

Correlação entre parâmetros estimados pelos testes Colour Assessment and Diagnosis e Cambridge Colour Test na avaliação da discriminação de cores

Os testes Colour Assessment and Diagnosis (CAD) e Cambridge Colour Test (CCT) têm sido amplamente utilizados em pesquisas básicas e clínicas, devido à alta sensibilidade e especificidade de seus resultados. Estes testes utilizam diferentes paradigmas de estimulação para estimar os limiares de discriminação de cor. Pouco se sabe sobre a relação de cada paradigma na avaliação da discriminação de cor nesses testes. Sendo assim, este trabalho objetiva comparar os parâmetros de avaliação da discriminação de cor estimados pelos testes CAD e CCT em sujeitos tricromatas e com discromatopsia congênita. Foram avaliados 59 sujeitos tricromatas e 38 sujeitos discromatópsicos (16 protans, 22 deutans) com idade média de 26,32 ± 8,9 anos. Foram testados 66 sujeitos nos testes CAD e CCT, 29 sujeitos no teste CAD e 2 sujeitos no teste CCT. O fenótipo da visão de cores de todos os sujeitos foi determinado através de uma bateria de testes psicofísicos e a estimativa dos limiares de discriminação de cor foi avaliada pelos testes CAD e CCT. Os dados de limiares de discriminação de cor foram ajustados a funções de elipse. Os critérios analisados para cada sujeito foram: a área da elipse, o ângulo de rotação e tamanho dos vetores protan, deutan e tritan. Para cada um dos parâmetros foi realizada: estatística descritiva, análise da dispersão dos parâmetros entre os testes CAD e CCT e dos parâmetros em conjunto, razão entre os parâmetros, correlação dos parâmetros a três modelos matemáticos e análise de concordância. Os parâmetros de área e tamanho dos vetores deutan e tritan do subgrupo tricromata; área e tamanho do vetor tritan do subgrupo protan; e tamanho dos vetores protan e tritan do subgrupo deutan apresentaram equivalência entre os resultados de ambos os testes. Os parâmetros de área, ângulo de rotação e tamanho dos vetores protan e tritan apresentaram concordância de medidas entre os testes CAD e CCT. Fatores como as localizações distintas das coordenadas centrais dos testes CAD e CCT e a disposição espacial dos vetores no espaço de cor da CIE 1976 no teste CCT podem ter influenciado na determinação de limiares de discriminação cromática de ambos os testes. Apesar de utilizarem paradigmas distintos na configuração da estimulação, os testes CAD e CCT são equiparáveis.

Typology of companies networks for competitive assessment: an application in higher education institutions

Taking into account the changes in the market scenario by virtue of globalization, Institutes of Higher Education (IES) as well as other organizations seek their competitive stability. For that reason, it is up to organizations to adopt innovative models of management for their operations aimed at improving results. Company networks consist of a model that is perfect for uniting efforts through cooperation among partners in a given business, which can involve ties of different natures. This paper shows the development and the application of an auxiliary technique to analyze the intensity, nature and importance of internal and external relations in the formation of results for a company network. For such, a multiple case study was conducted at two IES in the State of São Paulo and their networks of partners and employees in order to observe their specificities and organizational strategies. The study demonstrated the existence of specific performance criteria (pillars) for each IES and its network, resulting from its competitive reality. It reveals evidence that the education pillar is strengthened in both cases, and the research pillar is growing, although it is the weakest. The outreach pillar is the most robust in the public IES and the financial sustainability pillar is relevant for the private IES, and it was only detected in this IES.

Validation of the Geriatric Oral Health Assessment Index in complete denture wearers

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Avaliação da erosão hídrica e transporte de sedimentos através do modelo hidrossedimentológico SWAT (Soil and Water Assessment Tool)

Pós-graduação em Geociências e Meio Ambiente - IGCE

A Model-Based Approach for Small-Signal Stability Assessment of Unbalanced Power Systems

In this paper, a modeling technique for small-signal stability assessment of unbalanced power systems is presented. Since power distribution systems are inherently unbalanced, due to its lines and loads characteristics, and the penetration of distributed generation into these systems is increasing nowadays, such a tool is needed in order to ensure a secure and reliable operation of these systems. The main contribution of this paper is the development of a phasor-based model for the study of dynamic phenomena in unbalanced power systems. Using an assumption on the net torque of the generator, it is possible to precisely define an equilibrium point for the phasor model of the system, thus enabling its linearization around this point, and, consequently, its eigenvalue/eigenvector analysis for small-signal stability assessment. The modeling technique presented here was compared to the dynamic behavior observed in ATP simulations and the results show that, for the generator and controller models used, the proposed modeling approach is adequate and yields reliable and precise results.

Homogeneity assessment of a station climate series (1933-2005) in the Metropolitan Area of Sao Paulo: instruments change and urbanization effects

This work assessed homogeneity of the Institute of Astronomy, Geophysics and Atmospheric Sciences (IAG) weather station climate series, using various statistical techniques. The record from this target station is one of the longest in Brazil, having commenced in 1933 with observations of precipitation, and temperatures and other variables later in 1936. Thus, it is one of the few stations in Brazil with enough data for long-term climate variability and climate change studies. There is, however, a possibility that its data may have been contaminated by some artifacts over time. Admittedly, there was an intervention on the observations in 1958, with the replacement of instruments, for which the size of impact has not been yet evaluated. The station transformed in the course of time from rural to urban, and this may also have influenced homogeneity of the observations and makes the station less representative for climate studies over larger spatial scales. Homogeneity of the target station was assessed applying both absolute, or single station tests, and tests relatively to regional climate, in annual scale, regarding daily precipitation, relative humidity, maximum (TMax), minimum (TMin), and wet bulb temperatures. Among these quantities, only precipitation does not exhibit any inhomogeneity. A clear signal of change of instruments in 1958 was detected in the TMax and relative humidity data, the latter certainly because of its strong dependence on temperature. This signal is not very clear in TMin, but it presents non-climatic discontinuities around 1953 and around 1970. A significant homogeneity break is found around 1990 for TMax and wet bulb temperature. The discontinuities detected after 1958 may have been caused by urbanization, as the observed warming trend in the station is considerably greater than that corresponding to regional climate.

Influence Assessment in an Heteroscedastic Errors-in-Variables Model

The main goal of this article is to consider influence assessment in models with error-prone observations and variances of the measurement errors changing across observations. The techniques enable to identify potential influential elements and also to quantify the effects of perturbations in these elements on some results of interest. The approach is illustrated with data from the WHO MONICA Project on cardiovascular disease.

Mayaro Virus Infection in Amazonia: A Multimodel Inference Approach to Risk Factor Assessment

Background: Arboviral diseases are major global public health threats. Yet, our understanding of infection risk factors is, with a few exceptions, considerably limited. A crucial shortcoming is the widespread use of analytical methods generally not suited for observational data - particularly null hypothesis-testing (NHT) and step-wise regression (SWR). Using Mayaro virus (MAYV) as a case study, here we compare information theory-based multimodel inference (MMI) with conventional analyses for arboviral infection risk factor assessment. Methodology/Principal Findings: A cross-sectional survey of anti-MAYV antibodies revealed 44% prevalence (n = 270 subjects) in a central Amazon rural settlement. NHT suggested that residents of village-like household clusters and those using closed toilet/latrines were at higher risk, while living in non-village-like areas, using bednets, and owning fowl, pigs or dogs were protective. The "minimum adequate" SWR model retained only residence area and bednet use. Using MMI, we identified relevant covariates, quantified their relative importance, and estimated effect-sizes (beta +/- SE) on which to base inference. Residence area (beta(Village) = 2.93 +/- 0.41; beta(Upland) = -0.56 +/- 0.33, beta(Riverbanks) = -2.37 +/- 0.55) and bednet use (beta = -0.95 +/- 0.28) were the most important factors, followed by crop-plot ownership (beta = 0.39 +/- 0.22) and regular use of a closed toilet/latrine (beta = 0.19 +/- 0.13); domestic animals had insignificant protective effects and were relatively unimportant. The SWR model ranked fifth among the 128 models in the final MMI set. Conclusions/Significance: Our analyses illustrate how MMI can enhance inference on infection risk factors when compared with NHT or SWR. MMI indicates that forest crop-plot workers are likely exposed to typical MAYV cycles maintained by diurnal, forest dwelling vectors; however, MAYV might also be circulating in nocturnal, domestic-peridomestic cycles in village-like areas. This suggests either a vector shift (synanthropic mosquitoes vectoring MAYV) or a habitat/habits shift (classical MAYV vectors adapting to densely populated landscapes and nocturnal biting); any such ecological/adaptive novelty could increase the likelihood of MAYV emergence in Amazonia.

Risk assessment behaviors associated with corticosterone trigger the defense reaction to social isolation in rats: Role of the anterior cingulate cortex

The extent to which the hypothalamic-pituitary-adrenal axis is activated by short-term and long-term consequences of stress is still open to investigation. This study aimed to determine (i) the correlation between plasma corticosterone and exploratory behavior exhibited by rats subjected to the elevated plus maze (EPM) following different periods of social isolation, (ii) the effects of the corticosterone synthesis blocker, metyrapone, on the behavioral consequences of isolation, and (iii) whether corticosterone produces its effects through an action on the anterior cingulate cortex, area 1 (Cg1). Rats were subjected to 30-min, 2-h, 24-h, or 7-day isolation periods before EPM exposure and plasma corticosterone assessments. Isolation for longer periods of time produced greater anxiogenic-like effects on the EPM. However, stretched attend posture (SAP) and plasma corticosterone concentrations were increased significantly after 30 min of isolation. Among all of the behavioral categories measured in the EPM, only SAP positively correlated with plasma corticosterone. Metyrapone injected prior to the 24 h isolation period reversed the anxiogenic effects of isolation. Moreover, corticosterone injected into the Cg1 produced a selective increase in SAP. These findings indicate that risk assessment behavior induced by the action of corticosterone on Cg1 neurons initiates a cascade of defensive responses during exposure to stressors.

Covariates of high-risk human papillomavirus (HPV) infections are distinct for incident CIN1, CIN2 and CIN3 as disclosed by competing-risks regression models

Background: In addition to the oncogenic human papillomavirus (HPV), several cofactors are needed in cervical carcinogenesis, but whether the HPV covariates associated with incident i) CIN1 are different from those of incident ii) CIN2 and iii) CIN3 needs further assessment. Objectives: To gain further insights into the true biological differences between CIN1, CIN2 and CIN3, we assessed HPV covariates associated with incident CIN1, CIN2, and CIN3. Study Design and Methods: HPV covariates associated with progression to CIN1, CIN2 and CIN3 were analysed in the combined cohort of the NIS (n = 3,187) and LAMS study (n = 12,114), using competing-risks regression models (in panel data) for baseline HR-HPV-positive women (n = 1,105), who represent a sub-cohort of all 1,865 women prospectively followed-up in these two studies. Results: Altogether, 90 (4.8%), 39 (2.1%) and 14 (1.4%) cases progressed to CIN1, CIN2, and CIN3, respectively. Among these baseline HR-HPV-positive women, the risk profiles of incident GIN I, CIN2 and CIN3 were unique in that completely different HPV covariates were associated with progression to CIN1, CIN2 and CIN3, irrespective which categories (non-progression, CIN1, CIN2, CIN3 or all) were used as competing-risks events in univariate and multivariate models. Conclusions: These data confirm our previous analysis based on multinomial regression models implicating that distinct covariates of HR-HPV are associated with progression to CIN1, CIN2 and CIN3. This emphasises true biological differences between the three grades of GIN, which revisits the concept of combining CIN2 with CIN3 or with CIN1 in histological classification or used as a common end-point, e.g., in HPV vaccine trials.