56 resultados para risks of networking
Resumo:
This paper investigates Willingness to Accept (WTA) Genetic Modification (GM) foods based on experimental auctions carried out in the USA, UK and France. It explores perceptions of risk and benefits, moral concerns and their antecedents, attitudes to the environment and technology and trust in various sources using Structural Equation Modelling (SEM). Trust in information provided by industry proved to be the most important determinant of risk/benefit perceptions and WTA followed by general attitudes to the environment and technology. Education and age are also enhance perceived benefits and lower perceived risks of GM. Perception of risk/benefit and moral concerns all have significant effects on consumers' WTA but the perceived benefits are most important. The research suggests that trust-building by industry would be the most effective in enhancing GM acceptance.
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Objective: To determine the risk of lung cancer associated with exposure at home to the radioactive disintegration products of naturally Occurring radon gas. Design: Collaborative analysis of individual data from 13 case-control studies of residential radon and lung cancer. Setting Nine European countries. Subjects 7148 cases Of lung cancer and 14 208 controls. Main outcome measures: Relative risks of lung cancer and radon gas concentrations in homes inhabited during the previous 5-34 years measured in becquerels (radon disintegrations per second) per cubic incite (Bq/m(3)) Of household air. Results: The mean measured radon concentration in homes of people in tire control group was 97 Bq/m(3), with 11% measuring > 200 and 4% measuring > 400 Bq/m(3). For cases of lung cancer the mean concentration was 104 Bq/m(3). The risk of lung cancer increased by 8.4% (95% confidence interval 3.0% to 15.8%) per 100 Bq/m(3) increase in measured radon (P = 0.0007). This corresponds to an increase of 16% (5% to 31%) per 100 Bq/m(3) increase in usual radon-that is, after correction for the dilution caused by random uncertainties in measuring radon concentrations. The dose-response relation seemed to be linear with no threshold and remained significant (P=0.04) in analyses limited to individuals from homes with measured radon < 200 Bq/m(3). The proportionate excess risk did not differ significantly with study, age, sex, or smoking. In the absence of other causes of death, the absolute risks of lung cancer by age 75 years at usual radon concentrations of 0, 100, and 400 Bq/m(3) would be about 0.4%, 0.5%, and 0.7%, respectively, for lifelong non-smokers, and about 25 times greater (10%, 12%, and 16%) for cigarette smokers. Conclusions: Collectively, though not separately, these studies show appreciable hazards from residential radon, particularly for smokers and recent ex-smokers, and indicate that it is responsible for about 2% of all deaths from cancer in Europe.
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Background: Depression in fathers in the postnatal period is associated with an increased risk of behavioural problems in their offspring, particularly for boys. The aim of this study was to examine for differential effects of depression in fathers on children's subsequent psychological functioning via a natural experiment comparing prenatal and postnatal exposure. Methods:In a longitudinal population cohort study (the Avon Longitudinal Study of Parents and Children (ALSPAC)) we examined the associations between depression in fathers measured in the prenatal and postnatal period (measured using the Edinburgh Postnatal Depression Scale), and later behavioural/emotional and psychiatric problems in their children, assessed at ages 31/2 and 7 years. Results: Children whose fathers were depressed in both the prenatal and postnatal periods had the highest risks of subsequent psychopathology, measured by total problems at age 31/2 years (Odds Ratio 3.55; 95% confidence interval 2.07, 6.08) and psychiatric diagnosis at age 7 years (OR 2.54; 1.19, 5.41). Few differences emerged when prenatal and postnatal depression exposure were directly compared, but when compared to fathers who were not depressed, boys whose fathers had postnatal depression only had higher rates of conduct problems aged 31/2 years (OR 2.14; 1.22, 3.72) whereas sons of the prenatal group did not (OR 1.41; .75, 2.65). These associations changed little when controlling for maternal depression and other potential confounding factors. Conclusions: The findings of this study suggest that the increased risk of later conduct problems, seen particularly in the sons of depressed fathers, maybe partly mediated through environmental means. In addition, children whose fathers are more chronically depressed appear to be at a higher risk of emotional and behavioural problems. Efforts to identify the precise mechanisms by which transmission of risk may occur should be encouraged to enable the development of focused interventions to mitigate risks for young children.
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The possibilities and need for adaptation and mitigation depends on uncertain future developments with respect to socio-economic factors and the climate system. Scenarios are used to explore the impacts of different strategies under uncertainty. In this chapter, some scenarios are presented that are used in the ADAM project for this purpose. One scenario explores developments with no mitigation, and thus with high temperature increase and high reliance on adaptation (leading to 4oC increase by 2100 compared to pre-industrial levels). A second scenario explores an ambitious mitigation strategy (leading to 2oC increase by 2100 compared to pre-industrial levels). In the latter scenario, stringent mitigation strategies effectively reduces the risks of climate change, but based on uncertainties in the climate system a temperature increase of 3oC or more cannot be excluded. The analysis shows that, in many cases, adaptation and mitigation are not trade-offs but supplements. For example, the number of people exposed to increased water resource stress due to climate change can be substantially reduced in the mitigation scenario, but even then adaptation will be required for the remaining large numbers of people exposed to increased stress. Another example is sea level rise, for which adaptation is more cost-effective than mitigation, but mitigation can help reduce damages and the cost of adaptation. For agriculture, finally, only the scenario based on a combination of adaptation and mitigation is able to avoid serious climate change impacts.
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Although the use of climate scenarios for impact assessment has grown steadily since the 1990s, uptake of such information for adaptation is lagging by nearly a decade in terms of scientific output. Nonetheless, integration of climate risk information in development planning is now a priority for donor agencies because of the need to prepare for climate change impacts across different sectors and countries. This urgency stems from concerns that progress made against Millennium Development Goals (MDGs) could be threatened by anthropogenic climate change beyond 2015. Up to this time the human signal, though detectable and growing, will be a relatively small component of climate variability and change. This implies the need for a twin-track approach: on the one hand, vulnerability assessments of social and economic strategies for coping with present climate extremes and variability, and, on the other hand, development of climate forecast tools and scenarios to evaluate sector-specific, incremental changes in risk over the next few decades. This review starts by describing the climate outlook for the next couple of decades and the implications for adaptation assessments. We then review ways in which climate risk information is already being used in adaptation assessments and evaluate the strengths and weaknesses of three groups of techniques. Next we identify knowledge gaps and opportunities for improving the production and uptake of climate risk information for the 2020s. We assert that climate change scenarios can meet some, but not all, of the needs of adaptation planning. Even then, the choice of scenario technique must be matched to the intended application, taking into account local constraints of time, resources, human capacity and supporting infrastructure. We also show that much greater attention should be given to improving and critiquing models used for climate impact assessment, as standard practice. Finally, we highlight the over-arching need for the scientific community to provide more information and guidance on adapting to the risks of climate variability and change over nearer time horizons (i.e. the 2020s). Although the focus of the review is on information provision and uptake in developing regions, it is clear that many developed countries are facing the same challenges. Copyright © 2009 Royal Meteorological Society
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Commercial real estate investors have well-established methods to assess the risks of a property investment in their home country. However, when the investment decision is overseas another dimension of uncertainty overlays the analysis. This additional dimension, typically called country risk, encompasses the uncertainty of achieving expected financial results solely due to factors relating to the investment’s location in another country. However, very little has been done to examine the effects of country risk on international real estate returns, even though in international investment decisions considerations of country risk dominate asset investment decisions. This study extends the literature on international real estate diversification by empirically estimating the impact of country risk, as measured by Euromoney, on the direct real estate returns of 15 countries over the period 1998-2004, using a pooled regression analysis approach. The results suggest that country risk data may help investor’s in their international real estate decisions since the country risk data shows a significant and consistent impact on real estate return performance.
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Multi-factor approaches to analysis of real estate returns have, since the pioneering work of Chan, Hendershott and Sanders (1990), emphasised a macro-variables approach in preference to the latent factor approach that formed the original basis of the arbitrage pricing theory. With increasing use of high frequency data and trading strategies and with a growing emphasis on the risks of extreme events, the macro-variable procedure has some deficiencies. This paper explores a third way, with the use of an alternative to the standard principal components approach – independent components analysis (ICA). ICA seeks higher moment independence and maximises in relation to a chosen risk parameter. We apply an ICA based on kurtosis maximisation to weekly US REIT data using a kurtosis maximising algorithm. The results show that ICA is successful in capturing the kurtosis characteristics of REIT returns, offering possibilities for the development of risk management strategies that are sensitive to extreme events and tail distributions.
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Investing in real estate markets overseas means venturing into the unknown, where you meet unfamiliar political and economic environments, unstable currencies, strange cultures and languages, and so although the advantages of international diversification might appear attractive, the risks of international investment must not be overlooked. However, capital markets are becoming global markets, and commercial real estate markets are no exception, accordingly despite the difficulties posed by venturing overseas no investor can overlook the potential international investment holds out. Thus, what strategies are appropriate for capitalising on this potential? Three issues must be considered: (1) the potential of the countries real estate market in general; (2) the potential of the individual market sectors; and (3) the investment process itself. Although each step in foreign real estate investment is critical, the initial assessment of opportunities is especially important. Various methods can be used to achieve this but a formal and systematic analysis of aggregate market potential should prove particularly fruitful. The work reported here, therefore, develops and illustrates such a methodology for the over 50 international real estate markets.
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There is growing evidence of changes in the timing of important ecological events, such as flowering in plants and reproduction in animals, in response to climate change, with implications for population decline and biodiversity loss. Recent work has shown that the timing of breeding in wild birds is changing in response to climate change partly because individuals are remarkably flexible in their timing of breeding. Despite this work, our understanding of these processes in wild populations remains very limited and biased towards species from temperate regions. Here, we report the response to changing climate in a tropical wild bird population using a long-term dataset on a formerly critically endangered island endemic, the Mauritius kestrel. We show that the frequency of spring rainfall affects the timing of breeding, with birds breeding later in wetter springs. Delays in breeding have consequences in terms of reduced reproductive success as birds get exposed to risks associated with adverse climatic conditions later on in the breeding season, which reduce nesting success. These results, combined with the fact that frequency of spring rainfall has increased by about 60 per cent in our study area since 1962, imply that climate change is exposing birds to the stochastic risks of late reproduction by causing them to start breeding relatively late in the season.
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Interest in the effects of insulin on the heart came with the recognition that hyperglycemia in the context of myocardial infarction is associated with increased risks of mortality, congestive heart failure, or cardiogenic shock. More recently, instigated by research findings on stress hyperglycemia in critical illness, this interest has been extended to the influence of insulin on clinical outcome after cardiac surgery. Even in nondiabetic individuals, stress hyperglycemia commonly occurs as a key metabolic response to critical illness, eg, after surgical trauma. It is recognized as a major pathophysiological feature of organ dysfunction in the critically ill. The condition stems from insulin resistance brought about by dysregulation of key homeostatic processes, which implicates immune/inflammatory, endocrine, and metabolic pathways. It has been associated with adverse clinical outcomes, including increased mortality, increased duration of mechanical ventilation, increased intensive care unit (ICU) and hospital stay, and increased risk of infection. Hyperglycemia in critical illness is managed with exogenous insulin as standard treatment; however, there is considerable disagreement among experts in the field as to what target blood glucose level is optimal for the critically ill patient. Conventionally, the aim of insulin therapy has been to maintain blood glucose levels below the renal threshold, typically 220 mg/dL (12.2 mmol/L). In recent years, some have advocated tight glycemic control (TGC) with intensive insulin therapy (IIT) to normalize blood glucose levels to within the euglycemic range, typically 80 to 110 mg/dL (4.4–6.1 mmol/L).
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For decades regulators in the energy sector have focused on facilitating the maximisation of energy supply in order to meet demand through liberalisation and removal of market barriers. The debate on climate change has emphasised a new type of risk in the balance between energy demand and supply: excessively high energy demand brings about significantly negative environmental and economic impacts. This is because if a vast number of users is consuming electricity at the same time, energy suppliers have to activate dirty old power plants with higher greenhouse gas emissions and higher system costs. The creation of a Europe-wide electricity market requires a systematic investigation into the risk of aggregate peak demand. This paper draws on the e-Living Time-Use Survey database to assess the risk of aggregate peak residential electricity demand for European energy markets. Findings highlight in which countries and for what activities the risk of aggregate peak demand is greater. The discussion highlights which approaches energy regulators have started considering to convince users about the risks of consuming too much energy during peak times. These include ‘nudging’ approaches such as the roll-out of smart meters, incentives for shifting the timing of energy consumption, differentiated time-of-use tariffs, regulatory financial incentives and consumption data sharing at the community level.
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An unlisted property fund is a private investment vehicle which aims to provide direct property total returns and may also employ financial leverage which will accentuate performance. They have become a far more prevalent institutional property investment conduit since the early 2000’s. Investors have been primarily attracted to them due to the ease of executing a property exposure, both domestically and internationally, and for their diversification benefits given the capital intensive nature of constructing a well diversified commercial property investment portfolio. However, despite their greater prominence there has been little academic research conducted on the performance and risks of unlisted property fund investments. This can be attributed to a paucity of available data and limited time series where it exists. In this study we have made use of a unique dataset of institutional UK unlisted non-listed property funds over the period 2003Q4 to 2011Q4, using a panel modelling framework in order to determine the key factors which impact on fund performance. The sample provided a rich set of unlisted property fund factors including market exposures, direct property characteristics and the level of financial leverage employed. The findings from the panel regression analysis show that a small number of variables are able to account for the performance of unlisted property funds. These variables should be considered by investors when assessing the risk and return of these vehicles. The impact of financial leverage upon the performance of these vehicles through the recent global financial crisis and subsequent UK commercial property market downturn was also studied. The findings indicate a significant asymmetric effect of employing debt finance within unlisted property funds.
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Foot-and-mouth disease virus (FMDV) is a significant economically and distributed globally pathogen of Artiodactyla. Current vaccines are chemically inactivated whole virus particles that require large-scale virus growth in strict bio-containment with the associated risks of accidental release or incomplete inactivation. Non-infectious empty capsids are structural mimics of authentic particles with no associated risk and constitute an alternate vaccine candidate. Capsids self-assemble from the processed virus structural proteins, VP0, VP3 and VP1, which are released from the structural protein precursor P1-2A by the action of the virus-encoded 3C protease. To date recombinant empty capsid assembly has been limited by poor expression levels, restricting the development of empty capsids as a viable vaccine. Here expression of the FMDV structural protein precursor P1-2A in insect cells is shown to be efficient but linkage of the cognate 3C protease to the C-terminus reduces expression significantly. Inactivation of the 3C enzyme in a P1-2A-3C cassette allows expression and intermediate levels of 3C activity resulted in efficient processing of the P1-2A precursor into the structural proteins which assembled into empty capsids. Expression was independent of the insect host cell background and leads to capsids that are recognised as authentic by a range of anti-FMDV bovine sera suggesting their feasibility as an alternate vaccine.
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Climate models predict a large range of possible future temperatures for a particular scenario of future emissions of greenhouse gases and other anthropogenic forcings of climate. Given that further warming in coming decades could threaten increasing risks of climatic disruption, it is important to determine whether model projections are consistent with temperature changes already observed. This can be achieved by quantifying the extent to which increases in well mixed greenhouse gases and changes in other anthropogenic and natural forcings have already altered temperature patterns around the globe. Here, for the first time, we combine multiple climate models into a single synthesized estimate of future warming rates consistent with past temperature changes. We show that the observed evolution of near-surface temperatures appears to indicate lower ranges (5–95%) for warming (0.35–0.82 K and 0.45–0.93 K by the 2020s (2020–9) relative to 1986–2005 under the RCP4.5 and 8.5 scenarios respectively) than the equivalent ranges projected by the CMIP5 climate models (0.48–1.00 K and 0.51–1.16 K respectively). Our results indicate that for each RCP the upper end of the range of CMIP5 climate model projections is inconsistent with past warming.
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Increased risks of extinction to populations of animals and plants under changing climate have now been demonstrated for many taxa. This study assesses the extinction risks to species within an important genus of pollinating bees (Colletes: Apidae) by estimating the expected changes in the area and isolation of suitable habitat under predicted climatic condition for 2050. Suitable habitat was defined on the basis of the presence of known forage plants as well as climatic suitability. To investigate whether ecological specialisation was linked to extinction risk we compared three species which were generalist pollen foragers on several plant families with three species which specialised on pollen from a single plant species. Both specialist and generalist species showed an increased risk of extinction with shifting climate, and this was particularly high for the most specialised species (Colletes anchusae and C. wolfi). The forage generalist C. impunctatus, which is associated with Boreo-Alpine environments, is potentially threatened through significant reduction in available climatic niche space. Including the distribution of the principal or sole pollen forage plant, when modelling the distribution of monolectic or narrowly oligolectic species, did not improve the predictive accuracy of our models as the plant species were considerably more widespread than the specialised bees associated with them.