A climate change risk analysis for world ecosystems

We quantify the risks of climate-induced changes in key ecosystem processes during the 21st century by forcing a dynamic global vegetation model with multiple scenarios from 16 climate models and mapping the proportions of model runs showing forest/nonforest shifts or exceedance of natural variability in wildfire frequency and freshwater supply. Our analysis does not assign probabilities to scenarios or weights to models. Instead, we consider distribution of outcomes within three sets of model runs grouped by the amount of global warming they simulate: <2°C (including simulations in which atmospheric composition is held constant, i.e., in which the only climate change is due to greenhouse gases already emitted), 2–3°C, and >3°C. High risk of forest loss is shown for Eurasia, eastern China, Canada, Central America, and Amazonia, with forest extensions into the Arctic and semiarid savannas; more frequent wildfire in Amazonia, the far north, and many semiarid regions; more runoff north of 50°N and in tropical Africa and northwestern South America; and less runoff in West Africa, Central America, southern Europe, and the eastern U.S. Substantially larger areas are affected for global warming >3°C than for <2°C; some features appear only at higher warming levels. A land carbon sink of ≈1 Pg of C per yr is simulated for the late 20th century, but for >3°C this sink converts to a carbon source during the 21st century (implying a positive climate feedback) in 44% of cases. The risks continue increasing over the following 200 years, even with atmospheric composition held constant.

Entropic risk analysis by a high level decision support system (e-FDSS) for construction SMEs

The method of entropy has been useful in evaluating inconsistency on human judgments. This paper illustrates an entropy-based decision support system called e-FDSS to the solution of multicriterion risk and decision analysis in projects of construction small and medium enterprises (SMEs). It is optimized and solved by fuzzy logic, entropy, and genetic algorithms. A case study demonstrated the use of entropy in e-FDSS on analyzing multiple risk criteria in the predevelopment stage of SME projects. Survey data studying the degree of impact of selected project risk criteria on different projects were input into the system in order to evaluate the preidentified project risks in an impartial environment. Without taking into account the amount of uncertainty embedded in the evaluation process; the results showed that all decision vectors are indeed full of bias and the deviations of decisions are finally quantified providing a more objective decision and risk assessment profile to the stakeholders of projects in order to search and screen the most profitable projects.

The SAFE FOODS framework for improved risk analysis of foods

Three main changes to current risk analysis processes are proposed to improve their transparency, openness, and accountability. First, the addition of a formal framing stage would allow interested parties, experts and officials to work together as needed to gain an initial shared understanding of the issue, the objectives of regulatory action, and alternative risk management measures. Second, the scope of the risk assessment is expanded to include the assessment of health and environmental benefits as well as risks, and the explicit consideration of economic- and social-impacts of risk management action and their distribution. Moreover approaches were developed for deriving improved information from genomic, proteomic and metabolomic profiling methods and for probabilistic modelling of health impacts for risk assessment purposes. Third, in an added evaluation stage, interested parties, experts, and officials may compare and weigh the risks, costs, and benefits and their distribution. As part of a set of recommendations on risk communication, we propose that reports on each stage should be made public.

Style analysis in real estate markets: beyond the sectors and regions dichotomy

While style analysis has been studied extensively in equity markets, applications of this valuable tool for measuring and benchmarking performance and risk in a real estate context are still relatively new. Most previous real estate studies on this topic have identified three investment categories (rather than styles): sectors, administrative regions and economic regions. However, the low explanatory power reveals the need to extend this analysis to other investment styles. We identify four main real estate investment styles and apply a multivariate model to randomly generated portfolios to test the significance of each style in explaining portfolio returns. Results show that significant alpha performance is significantly reduced when we account for the new investment styles, with small vs. big properties being the dominant one. Secondly, we find that the probability of obtaining alpha performance is dependent upon the actual exposure of funds to style factors. Finally we obtain that both alpha and systematic risk levels are linked to the actual characteristics of portfolios. Our overall results suggest that it would be beneficial for real estate fund managers to use these style factors to set benchmarks and to analyze portfolio returns.

Risk premia in covered bond markets

The authors empirically explore risk premia in mortgage covered bond markets. Using a large panel dataset of covered bond asset swap spreads, they study the impact of different legal and economic environments. Conducting an in-depth analysis of this market, the authors find significant but small differences between countries during normal market periods. However, these differences are much stronger during times of economic crisis. Moreover, they find that developments in the real estate market are of relatively little importance during stable market periods. During economic distress, however, they are of high importance for explaining risk premia in covered bond markets

The Genetics of Alzheimer`s Disease in Brazil: 10 Years of Analysis in a Unique Population

Alzheimer`s Disease (AD) is the most common type of dementia among the elderly, with devastating consequences for the patient, their relatives, and caregivers. More than 300 genetic polymorphisms have been involved with AD, demonstrating that this condition is polygenic and with a complex pattern of inheritance. This paper aims to report and compare the results of AD genetics studies in case-control and familial analysis performed in Brazil since our first publication, 10 years ago. They include the following genes/markers: Apolipoprotein E (APOE), 5-hidroxytryptamine transporter length polymorphic region (5-HTTLPR), brain-derived neurotrophin factor (BDNF), monoamine oxidase A (MAO-A), and two simple-sequence tandem repeat polymorphisms (DXS1047 and D10S1423). Previously unpublished data of the interleukin-1 alpha (IL-1 alpha) and interleukin-1 beta (IL-1 beta) genes are reported here briefly. Results from others Brazilian studies with AD patients are also reported at this short review. Four local families studied with various markers at the chromosome 21, 19, 14, and 1 are briefly reported for the first time. The importance of studying DNA samples from Brazil is highlighted because of the uniqueness of its population, which presents both intense ethnical miscegenation, mainly at the east coast, but also clusters with high inbreeding rates in rural areas at the countryside. We discuss the current stage of extending these studies using high-throughput methods of large-scale genotyping, such as single nucleotide polymorphism microarrays, associated with bioinformatics tools that allow the analysis of such extensive number of genetics variables, with different levels of penetrance. There is still a long way between the huge amount of data gathered so far and the actual application toward the full understanding of AD, but the final goal is to develop precise tools for diagnosis and prognosis, creating new strategies for better treatments based on genetic profile.

Risky business: social media metrics and political risk analysis

A quantificação do risco país – e do risco político em particular – levanta várias dificuldades às empresas, instituições, e investidores. Como os indicadores econômicos são atualizados com muito menos freqüência do que o Facebook, compreender, e mais precisamente, medir – o que está ocorrendo no terreno em tempo real pode constituir um desafio para os analistas de risco político. No entanto, com a crescente disponibilidade de “big data” de ferramentas sociais como o Twitter, agora é o momento oportuno para examinar os tipos de métricas das ferramentas sociais que estão disponíveis e as limitações da sua aplicação para a análise de risco país, especialmente durante episódios de violência política. Utilizando o método qualitativo de pesquisa bibliográfica, este estudo identifica a paisagem atual de dados disponíveis a partir do Twitter, analisa os métodos atuais e potenciais de análise, e discute a sua possível aplicação no campo da análise de risco político. Depois de uma revisão completa do campo até hoje, e tendo em conta os avanços tecnológicos esperados a curto e médio prazo, este estudo conclui que, apesar de obstáculos como o custo de armazenamento de informação, as limitações da análise em tempo real, e o potencial para a manipulação de dados, os benefícios potenciais da aplicação de métricas de ferramentas sociais para o campo da análise de risco político, particularmente para os modelos qualitativos-estruturados e quantitativos, claramente superam os desafios.

Business Plan, financial and risk analysis from the start-up mathrix

Mathrix is an e-learning math website that will be launched in March 2016. This master thesis offered a unique chance to interact with experienced supervisors in venture capitalism and project investment. It could serve as guidelines for entrepreneurs who intend to raise funds. Starting with the company’s business plan, the thesis focuses on estimating the company’s value with its return on investment using three scenarios and taking into consideration the risks evolved.

Metabolic syndrome and its associated risk factors in Brazilian postmenopausal women

Objective To evaluate the prevalence of metabolic syndrome (MetS) and its associated risk factors in Brazilian postmenopausal women.Methods In this cross-sectional study, a total of 368 postmenopausal women, aged 40-75 years, seeking health care at a public outpatient center in Southeastern Brazil, were included. According to the US National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) guidelines, MetS was diagnosed in subjects with three or more of the following: waist circumference >= 88 cm, blood pressure >= 130/85 mHg, triglycerides >= 150 mg/dl, high density lipoprotein cholesterol <50 mg/dl and glucose >= 110 mg/dl. Data on past medical history, tobacco use, anthropometric indicators, and values of C-reactive protein (CRP) were collected. Multivariate analysis, using a logistic regression model (odds ratio, OR) was used to evaluate the influence of various simultaneous MetS risk factors.Results The prevalence of having at least three, four and five MetS diagnostic criteria were met in 39.6%, 16.8% and 3.8% of the cases, respectively. The most prevalent risk factor was abdominal obesity, affecting 62.5% of women. The risk of MetS increased with a personal history of diabetes (OR 5.95, 95% confidence interval (CI) 2.82-12.54), hypertension (OR 4.52, 95% CI 2.89-7.08), cardiovascular disease (OR 2.16, 95% CI 1.18-3.94) and high CRP (>1 mg/dl) (OR 3.35, 95% CI 1.65-6.79). Plasma CRP levels increased with the number of MetS components present. Age, time since menopause and smoking had no influence, while hormone therapy reduced MetS risk (OR 0.64, 95% CI 0.42-0.97).Conclusion Metabolic syndrome was highly prevalent among Brazilian postmenopausal women seeking gynecologic health care. Abdominal obesity, diabetes, hypertension and high CRP were strong MetS predictors and hormone therapy appeared to play a protective role for this condition.

Metabolic syndrome and dietary components are associated with coronary artery disease risk score in free-living adults: a cross-sectional study

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Potentially inappropriate medications used by the elderly: Prevalence and risk factors in Brazilian care homes

Abstract. Background: The use of potentially inappropriate medications (PIM) among the elderly is a serious public health problem because it is intrinsically linked to increased morbidity and mortality, causing high costs to public health systems. This study's objective was to verify the prevalence of and the factors associated with the use of PIMs by elderly Brazilians in institutional settings. Methods. We performed a transversal study, by consulting the case files of elderly people living in Long Term Care for the Elderly (LTC) in towns in the State of São Paulo, Brazil, as well as structured interviews with the nurses responsible for them.We identified PIMs using the list of recently updated Beers criteria developed by a group of specialists from the American Geriatrics Society (AGS), who reviewed the criteria based on studies with high scientific evidence levels. We defined the factors studied to evaluate the association with PIM use prior to the statistical analyses, which were the chi-square test and multiple logistic regression. Results: Among the elderly who used drugs daily, 82.6% were taking at least one PIM, with antipsychotics (26.5%) and analgesics (15.1%) being the most commonly used. Out of all the medications used, 32.4% were PIMs, with 29.7% of these being PIMs that the elderly should avoid independent of their condition, 1.1% being inappropriate medication for older adults with certain illnesses or syndromes, and 1.6% being medications that older adults should use with caution. In the multivariate analysis, the factors associated with PIM use were: polypharmacy (p = 0.0187), cerebrovascular disease (p = 0.0036), psychiatric disorders (p < 0.0001) and dependency (p = 0.0404). Conclusions: The results of this study showed a high prevalence of PIM use in institutionalized elderly Brazilian patients. and the associated factors were polypharmacy, psychiatric disorders, cerebrovascular diseases and dependency. © 2013 Lima et al.; licensee BioMed Central Ltd.

Information and communication technologies for disaster risk management in the Caribbean

Includes bibliography.

Information and communication technology for disaster risk management in the Caribbean: subregional solutions to the challenge of limited human resource capacity

This document was adapted from a paper originally presented to the 8th Annual Caribbean Conference of Comprehensive Disaster Management, held in Montego Bay, Jamaica in December, 2013. It summarizes several activities that ECLAC has undertaken to assess the current state of information and communications technology (ICT) in the field of disaster risk management (DRM) as practiced in the Caribbean. These activities included an in-depth study that encompassed a survey of disaster management organizations in the region, an Expert Group Meeting attended by the heads of several national disaster offices, and a training workshop for professionals working in DRM in the Caribbean. One of the notable conclusions of ECLAC’s investigation on this topic is that the lack of human capacity is the single largest constraint that is faced in the implementation of ICT projects for DRM in the Caribbean. In considering strategies to address the challenge of limited human capacity at a regional level, two separate issues are recognized – the need to increase the ICT capabilities of disaster management professionals, and the need to make ICT specialists available to disaster management organizations to advise and assist in the implementation of technology-focused projects. To that end, two models are proposed to engage with this issue at a regional level. The first entails the establishment of a network of ICT trainers in the Caribbean to help DRM staff develop a strategic understanding of how technology can be used to further their organizational goals. The second is the development of “Centres of Excellence” for ICT in the Caribbean, which would enable the deployment of specialized ICT expertise to national disaster management offices on a project-by-project basis.