Risk-taking behaviours in adolescent boys and girls : sexuality and dietary health

This study examined adolescents' reported sexual and dietary health-risk behaviours and perceptions. Specifically, this study analyzed the data of 600 students (300 male~ 300 female) in grades 9, I 1, and OAC (mean, standard deviation). The mean age of the students in the sample is 16 with a standard deviation of 1.6. The study was a secondary analysis ofthe first-year data of a 3-year longitudinal study conducted by Youth Lifestyle Choices-Community University Research Alliance (YLC-CURA) on adolescents. To explore sexuality and dietary health, this study purposefully selected sections of the survey that represented sex and dieting behaviours of adolescents. Separate gender and age data analyses revealed different patterns among the variables. Specifically., findings revealed that adolescents who engaged in recent sexual activities were more likely to have a relatively more positive body image perception and were relatively more likely to engage in disordered eating. Across both genders and 3 age levels, adolescents reported that despite their unhealthy dietary habits they felt that dieting was not a high-risk behaviour. Results were discussed in terms of educational implication for sexual health programs.

On some aspects of coherent risk measures and their applications

Le sujet principal de cette thèse porte sur les mesures de risque. L'objectif général est d'investiguer certains aspects des mesures de risque dans les applications financières. Le cadre théorique de ce travail est celui des mesures cohérentes de risque telle que définie dans Artzner et al (1999). Mais ce n'est pas la seule classe de mesure du risque que nous étudions. Par exemple, nous étudions aussi quelques aspects des "statistiques naturelles de risque" (en anglais natural risk statistics) Kou et al (2006) et des mesures convexes du risque Follmer and Schied(2002). Les contributions principales de cette thèse peuvent être regroupées selon trois axes: allocation de capital, évaluation des risques et capital requis et solvabilité. Dans le chapitre 2 nous caractérisons les mesures de risque avec la propriété de Lebesgue sur l'ensemble des processus bornés càdlàg (continu à droite, limité à gauche). Cette caractérisation nous permet de présenter deux applications dans l'évaluation des risques et l'allocation de capital. Dans le chapitre 3, nous étendons la notion de statistiques naturelles de risque à l'espace des suites infinies. Cette généralisation nous permet de construire de façon cohérente des mesures de risque pour des bases de données de n'importe quelle taille. Dans le chapitre 4, nous discutons le concept de "bonnes affaires" (en anglais Good Deals), pour notamment caractériser les situations du marché où ces positions pathologiques sont présentes. Finalement, dans le chapitre 5, nous essayons de relier les trois chapitres en étendant la définition de "bonnes affaires" dans un cadre plus large qui comprendrait les mesures de risque analysées dans les chapitres 2 et 3.

Assessment of meat authenticity using bioinformatics, targeted peptide biomarkers and high-resolution mass spectrometry

In recent years, we observed a significant increase of food fraud ranging from false label claims to the use of additives and fillers to increase profitability. Recently in 2013, horse and pig DNA were detected in beef products sold from several retailers. Mass spectrometry has become the workhorse in protein research and the detection of marker proteins could serve for both animal species and tissue authentication. Meat species authenticity will be performed using a well defined proteogenomic annotation, carefully chosen surrogate tryptic peptides and analysis using a hybrid quadrupole-Orbitrap mass spectrometer. Selected mammalian meat samples were homogenized, proteins were extracted and digested with trypsin. The samples were analyzed using a high-resolution mass spectrometer. The chromatography was achieved using a 30 minutes linear gradient along with a BioBasic C8 100 × 1 mm column at a flow rate of 75 µL/min. The mass spectrometer was operated in full-scan high resolution and accurate mass. MS/MS spectra were collected for selected proteotypic peptides. Muscular proteins were methodically analyzed in silico in order to generate tryptic peptide mass lists and theoretical MS/MS spectra. Following a comprehensive bottom-up proteomic analysis, we were able to detect and identify a proteotypic myoglobin tryptic peptide [120-134] for each species with observed m/z below 1.3 ppm compared to theoretical values. Moreover, proteotypic peptides from myosin-1, myosin-2 and -hemoglobin were also identified. This targeted method allowed a comprehensive meat speciation down to 1% (w/w) of undesired product.

Risk Aversion in Inventory Management

Traditional inventory models focus on risk-neutral decision makers, i.e., characterizing replenishment strategies that maximize expected total profit, or equivalently, minimize expected total cost over a planning horizon. In this paper, we propose a framework for incorporating risk aversion in multi-period inventory models as well as multi-period models that coordinate inventory and pricing strategies. In each case, we characterize the optimal policy for various measures of risk that have been commonly used in the finance literature. In particular, we show that the structure of the optimal policy for a decision maker with exponential utility functions is almost identical to the structure of the optimal risk-neutral inventory (and pricing) policies. Computational results demonstrate the importance of this approach not only to risk-averse decision makers, but also to risk-neutral decision makers with limited information on the demand distribution.

Uncertainty assessment of a process-based integrated catchment model of phosphorus

Despite the many models developed for phosphorus concentration prediction at differing spatial and temporal scales, there has been little effort to quantify uncertainty in their predictions. Model prediction uncertainty quantification is desirable, for informed decision-making in river-systems management. An uncertainty analysis of the process-based model, integrated catchment model of phosphorus (INCA-P), within the generalised likelihood uncertainty estimation (GLUE) framework is presented. The framework is applied to the Lugg catchment (1,077 km2), a River Wye tributary, on the England–Wales border. Daily discharge and monthly phosphorus (total reactive and total), for a limited number of reaches, are used to initially assess uncertainty and sensitivity of 44 model parameters, identified as being most important for discharge and phosphorus predictions. This study demonstrates that parameter homogeneity assumptions (spatial heterogeneity is treated as land use type fractional areas) can achieve higher model fits, than a previous expertly calibrated parameter set. The model is capable of reproducing the hydrology, but a threshold Nash-Sutcliffe co-efficient of determination (E or R 2) of 0.3 is not achieved when simulating observed total phosphorus (TP) data in the upland reaches or total reactive phosphorus (TRP) in any reach. Despite this, the model reproduces the general dynamics of TP and TRP, in point source dominated lower reaches. This paper discusses why this application of INCA-P fails to find any parameter sets, which simultaneously describe all observed data acceptably. The discussion focuses on uncertainty of readily available input data, and whether such process-based models should be used when there isn’t sufficient data to support the many parameters.

Evaluating the risk of non-point source pollution from biosolids: integrated modelling of nutrient losses at field and catchment scales

A semi-distributed model, INCA, has been developed to determine the fate and distribution of nutrients in terrestrial and aquatic systems. The model simulates nitrogen and phosphorus processes in soils, groundwaters and river systems and can be applied in a semi-distributed manner at a range of scales. In this study, the model has been applied at field to sub-catchment to whole catchment scale to evaluate the behaviour of biosolid-derived losses of P in agricultural systems. It is shown that process-based models such as INCA, applied at a wide range of scales, reproduce field and catchment behaviour satisfactorily. The INCA model can also be used to generate generic information for risk assessment. By adjusting three key variables: biosolid application rates, the hydrological connectivity of the catchment and the initial P-status of the soils within the model, a matrix of P loss rates can be generated to evaluate the behaviour of the model and, hence, of the catchment system. The results, which indicate the sensitivity of the catchment to flow paths, to application rates and to initial soil conditions, have been incorporated into a Nutrient Export Risk Matrix (NERM).

Population-level assessment of risks of pesticides to birds and mammals in the UK

It is generally acknowledged that population-level assessments provide,I better measure of response to toxicants than assessments of individual-level effects. population-level assessments generally require the use of models to integrate potentially complex data about the effects of toxicants on life-history traits, and to provide a relevant measure of ecological impact. Building on excellent earlier reviews we here briefly outline the modelling options in population-level risk assessment. Modelling is used to calculate population endpoints from available data, which is often about Individual life histories, the ways that individuals interact with each other, the environment and other species, and the ways individuals are affected by pesticides. As population endpoints, we recommend the use of population abundance, population growth rate, and the chance of population persistence. We recommend two types of model: simple life-history models distinguishing two life-history stages, juveniles and adults; and spatially-explicit individual-based landscape models. Life-history models are very quick to set up and run, and they provide a great deal or insight. At the other extreme, individual-based landscape models provide the greatest verisimilitude, albeit at the cost of greatly increased complexity. We conclude with a discussion of the cations of the severe problems of parameterising models.

An integrated assessment of carbon dioxide capture and storage in the UK

Geological carbon dioxide storage (CCS) has the potential to make a significant contribution to the decarbonisation of the UK. Amid concerns over maintaining security, and hence diversity, of supply, CCS could allow the continued use of coal, oil and gas whilst avoiding the CO2 emissions currently associated with fossil fuel use. This project has explored some of the geological, environmental, technical, economic and social implications of this technology. The UK is well placed to exploit CCS with a large offshore storage capacity, both in disused oil and gas fields and saline aquifers. This capacity should be sufficient to store CO2 from the power sector (at current levels) for a least one century, using well understood and therefore likely to be lower-risk, depleted hydrocarbon fields and contained parts of aquifers. It is very difficult to produce reliable estimates of the (potentially much larger) storage capacity of the less well understood geological reservoirs such as non-confined parts of aquifers. With the majority of its large coal fired power stations due to be retired during the next 15 to 20 years, the UK is at a natural decision point with respect to the future of power generation from coal; the existence of both national reserves and the infrastructure for receiving imported coal makes clean coal technology a realistic option. The notion of CCS as a ‘bridging’ or ‘stop-gap’ technology (i.e. whilst we develop ‘genuinely’ sustainable renewable energy technologies) needs to be examined somewhat critically, especially given the scale of global coal reserves. If CCS plant is built, then it is likely that technological innovation will bring down the costs of CO2 capture, such that it could become increasingly attractive. As with any capitalintensive option, there is a danger of becoming ‘locked-in’ to a CCS system. The costs of CCS in our model for UK power stations in the East Midlands and Yorkshire to reservoirs in the North Sea are between £25 and £60 per tonne of CO2 captured, transported and stored. This is between about 2 and 4 times the current traded price of a tonne of CO2 in the EU Emissions Trading Scheme. In addition to the technical and economic requirements of the CCS technology, it should also be socially and environmentally acceptable. Our research has shown that, given an acceptance of the severity and urgency of addressing climate change, CCS is viewed favourably by members of the public, provided it is adopted within a portfolio of other measures. The most commonly voiced concern from the public is that of leakage and this remains perhaps the greatest uncertainty with CCS. It is not possible to make general statements concerning storage security; assessments must be site specific. The impacts of any potential leakage are also somewhat uncertain but should be balanced against the deleterious effects of increased acidification in the oceans due to uptake of elevated atmospheric CO2 that have already been observed. Provided adequate long term monitoring can be ensured, any leakage of CO2 from a storage site is likely to have minimal localised impacts as long as leaks are rapidly repaired. A regulatory framework for CCS will need to include risk assessment of potential environmental and health and safety impacts, accounting and monitoring and liability for the long term. In summary, although there remain uncertainties to be resolved through research and demonstration projects, our assessment demonstrates that CCS holds great potential for significant cuts in CO2 emissions as we develop long term alternatives to fossil fuel use. CCS can contribute to reducing emissions of CO2 into the atmosphere in the near term (i.e. peak-shaving the future atmospheric concentration of CO2), with the potential to continue to deliver significant CO2 reductions over the long term.

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.

A value chain approach to animal diseases risk management: technical foundations and practical framework for field application

Classical risk assessment approaches for animal diseases are influenced by the probability of release, exposure and consequences of a hazard affecting a livestock population. Once a pathogen enters into domestic livestock, potential risks of exposure and infection both to animals and people extend through a chain of economic activities related to producing, buying and selling of animals and products. Therefore, in order to understand economic drivers of animal diseases in different ecosystems and to come up with effective and efficient measures to manage disease risks from a country or region, the entire value chain and related markets for animal and product needs to be analysed to come out with practical and cost effective risk management options agreed by actors and players on those value chains. Value chain analysis enriches disease risk assessment providing a framework for interdisciplinary collaboration, which seems to be in increasing demand for problems concerning infectious livestock diseases. The best way to achieve this is to ensure that veterinary epidemiologists and social scientists work together throughout the process at all levels.

Development of a food-exchange model to replace saturated fat with MUFAS and n-6 PUFAS in adults at moderate cardiovascular risk

The recommendation to reduce saturated fatty acid (SFA) consumption to ≤10% of total energy (%TE) is a key public health target aimed at lowering cardiovascular disease (CVD) risk. Replacement of SFA with unsaturated fats may provide greater benefit than replacement with carbohydrates, yet the optimal type of fat is unclear. The aim was to develop a flexible food-exchange model to investigate the effects of substituting SFAs with monounsaturated fatty acids (MUFAs) or n-6 (ω-6) polyunsaturated fatty acids (PUFAs) on CVD risk factors. In this parallel study, UK adults aged 21-60 y with moderate CVD risk (50% greater than the population mean) were identified using a risk assessment tool (n = 195; 56% females). Three 16-wk isoenergetic diets of specific fatty acid (FA) composition (%TE SFA:%TE MUFA:%TE n-6 PUFA) were designed using spreads, oils, dairy products, and snacks as follows: 1) SFA-rich diet (17:11:4; n = 65); 2) MUFA-rich diet (9:19:4; n = 64); and 3) n-6 PUFA-rich diet (9:13:10; n = 66). Each diet provided 36%TE total fat. Dietary targets were broadly met for all intervention groups, reaching 17.6 ± 0.4%TE SFA, 18.5 ± 0.3%TE MUFA, and 10.4 ± 0.3%TE n-6 PUFA in the respective diets, with significant overall diet effects for the changes in SFA, MUFA, and n-6 PUFA between groups (P < 0.001). There were no differences in the changes of total fat, protein, carbohydrate, and alcohol intake or anthropometric measures between groups. Plasma phospholipid FA composition showed changes from baseline in the proportions of total SFA, MUFA, and n-6 PUFA for each diet group, with significant overall diet effects for total SFA and MUFA between groups (P < 0.001). In conclusion, successful implementation of the food-exchange model broadly achieved the dietary target intakes for the exchange of SFA with MUFA or n-6 PUFA with minimal disruption to the overall diet in a free-living population. This trial was registered at clinicaltrials.gov as NCT01478958.

Assessment and improvement of biotransfer models to cow’s milk and beef used in exposure assessment tools for organic pollutants

The aim of this study was to assess and improve the accuracy of biotransfer models for the organic pollutants (PCBs, PCDD/Fs, PBDEs, PFCAs, and pesticides) into cow’s milk and beef used in human exposure assessment. Metabolic rate in cattle is known as a key parameter for this biotransfer, however few experimental data and no simulation methods are currently available. In this research, metabolic rate was estimated using existing QSAR biodegradation models of microorganisms (BioWIN) and fish (EPI-HL and IFS-HL). This simulated metabolic rate was then incorporated into the mechanistic cattle biotransfer models (RAIDAR, ACC-HUMAN, OMEGA, and CKow). The goodness of fit tests showed that RAIDAR, ACC-HUMAN, OMEGA model performances were significantly improved using either of the QSARs when comparing the new model outputs to observed data. The CKow model is the only one that separates the processes in the gut and liver. This model showed the lowest residual error of all the models tested when the BioWIN model was used to represent the ruminant metabolic process in the gut and the two fish QSARs were used to represent the metabolic process in the liver. Our testing included EUSES and CalTOX which are KOW-regression models that are widely used in regulatory assessment. New regressions based on the simulated rate of the two metabolic processes are also proposed as an alternative to KOW-regression models for a screening risk assessment. The modified CKow model is more physiologically realistic, but has equivalent usability to existing KOW-regression models for estimating cattle biotransfer of organic pollutants.

The risk of water stress

Water resources are under stress in many regions due to increasing demands and, in places, falling quality. Climate change has the potential to change the risks of water stress.1 The focus in this section is on strategic definitions of water stress, which are based on generalized indicators of the amount of water that is available and the demands on that resource. Operational definitions, on the other hand, are typically based on the reliability of the supply of appropriate quality water and are strongly determined by local conditions.

The risk of river flooding

This section of the report outlines the effect of different levels of climate change on exposure to river flood risk, at national and watershed scales.