A long-term risk management tool for electricity markets using swarm intelligence

This paper addresses the optimal involvement in derivatives electricity markets of a power producer to hedge against the pool price volatility. To achieve this aim, a swarm intelligence meta-heuristic optimization technique for long-term risk management tool is proposed. This tool investigates the long-term opportunities for risk hedging available for electric power producers through the use of contracts with physical (spot and forward contracts) and financial (options contracts) settlement. The producer risk preference is formulated as a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance of return and the expectation are based on a forecasted scenario interval determined by a long-term price range forecasting model. This model also makes use of particle swarm optimization (PSO) to find the best parameters allow to achieve better forecasting results. On the other hand, the price estimation depends on load forecasting. This work also presents a regressive long-term load forecast model that make use of PSO to find the best parameters as well as in price estimation. The PSO technique performance has been evaluated by comparison with a Genetic Algorithm (GA) based approach. A case study is presented and the results are discussed taking into account the real price and load historical data from mainland Spanish electricity market demonstrating the effectiveness of the methodology handling this type of problems. Finally, conclusions are dully drawn

Why do women invest in pre-pregnancy health and care? A qualitative investigation with women attending maternity services

Background Despite the importance attributed to good pre-pregnancy care and its potential to improve pregnancy and child health outcomes, relatively little is known about why women invest in pre-pregnancy health and care. We sought to gain insight into why women invested in pre-pregnancy health and care. Methods We carried out 20 qualitative in-depth interviews with pregnant or recently pregnant women who were drawn from a survey of antenatal clinic attendees in London, UK. Interviewees were purposively sampled to include high and low investors in pre-pregnancy health and care, with variation in age, partnership status, ethnicity and pre-existing medical conditions. Data analysis was conducted using the Framework method. Results We identified three groups in relation to pre-pregnancy health and care: 1) The “prepared” group, who had high levels of pregnancy planning and mostly positive attitudes to micronutrient supplementation outside of pregnancy, carried out pre-pregnancy activities such as taking folic acid and making changes to diet and lifestyle. 2) The “poor knowledge” group, who also had high levels of pregnancy planning, did not carry out pre-pregnancy activities and described themselves as having poor knowledge. Elsewhere in their interviews they expressed a strong dislike of micronutrient supplementation. 3) The “absent pre-pregnancy period” group, had the lowest levels of pregnancy planning and also expressed anti-supplement views. Even discussing the pre-pregnancy period with this group was difficult as responses to questions quickly shifted to focus on pregnancy itself. Knowledge of folic acid was poor in all groups. Conclusion Different pre-pregnancy care approaches are likely to be needed for each of the groups. Among the “prepared” group, who were proactive and receptive to health messages, greater availability of information and better response from health professionals could improve the range of pre-pregnancy activities carried out. Among the “poor knowledge” group, better response from health professionals might yield greater uptake of pre-pregnancy information. A different, general health strategy might be more appropriate for the “absent pre-pregnancy period” group. The fact that general attitudes to micronutrient supplementation were closely related to whether or not women invested in pre-pregnancy health and care was an unanticipated finding and warrants further investigation.This report is independent research commissioned and funded by the Department of Health Policy Research Programme Pre-Pregnancy Health and Care in England: Exploring Implementation and Public Health Impact, 006/0068

High catechin concentrations detected in Withania somnifera (ashwagandha) by high performance liquid chromatography analysis

<p>Abstract</p> <p>Background</p> <p><it>Withania somnifera </it>is an important medicinal plant traditionally used in the treatment of many diseases. The present study was carried out to characterize the phenolic acids, flavonoids and 1,1-diphenyl-2-picrylhydrazyl radical (DPPH) scavenging activities in methanolic extracts of <it>W. somnifera </it>fruits, roots and leaves (WSFEt, WSREt and WSLEt).</p> <p>Methods</p> <p>WSFEt, WSREt and WSLEt was prepared by using 80% aqueous methanol and total polyphenols, flavonoids as well as DPPH radical scavenging activities were determined by spectrophotometric methods and phenolic acid profiles were determined by HPLC methods.</p> <p>Results</p> <p>High concentrations of both phenolics and flavonoids were detected in all parts of the plant with the former ranging between 17.80 ± 5.80 and 32.58 ± 3.16 mg/g (dry weight) and the latter ranging between 15.49 ± 1.02 and 31.58 ± 5.07 mg/g. All of the three different plant parts showed strong DPPH radical scavenging activities (59.16 ± 1.20 to 91.84 ± 0.38%). Eight polyphenols (gallic, syringic, benzoic, p-coumaric and vanillic acids as well as catechin, kaempferol and naringenin) have been identified by HPLC in parts of the plant as well. Among all the polyphenols, catechin was detected in the highest concentration (13.01 ± 8.93 to 30.61 ± 11.41 mg/g).</p> <p>Conclusion</p> <p>The results indicating that <it>W. somnifera </it>is a plant with strong therapeutic properties thus further supporting its traditional claims. All major parts of <it>W. somnifera </it>such as the roots, fruits and leaves provide potential benefits for human health because of its high content of polyphenols and antioxidant activities with the leaves containing the highest amounts of polyphenols specially catechin with strong antioxidant properties.</p

A long-term risk management tool for electricity markets using swarm intelligence

This paper addresses the optimal involvement in derivatives electricity markets of a power producer to hedge against the pool price volatility. To achieve this aim, a swarm intelligence meta-heuristic optimization technique for long-term risk management tool is proposed. This tool investigates the long-term opportunities for risk hedging available for electric power producers through the use of contracts with physical (spot and forward contracts) and financial (options contracts) settlement. The producer risk preference is formulated as a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance of return and the expectation are based on a forecasted scenario interval determined by a long-term price range forecasting model. This model also makes use of particle swarm optimization (PSO) to find the best parameters allow to achieve better forecasting results. On the other hand, the price estimation depends on load forecasting. This work also presents a regressive long-term load forecast model that make use of PSO to find the best parameters as well as in price estimation. The PSO technique performance has been evaluated by comparison with a Genetic Algorithm (GA) based approach. A case study is presented and the results are discussed taking into account the real price and load historical data from mainland Spanish electricity market demonstrating the effectiveness of the methodology handling this type of problems. Finally, conclusions are dully drawn

Data provenance and trust establishment in the Internet of Things

The Internet of Things (IoT) is a network of heterogeneous networks encompassing various forms of communications form the current traditional communication models to ubiquitous and pervasive machine to machine communications. In such an ever expanding, dynamic, and complex environment, it becomes vital to know the origin or the source of data and whether this data can be trusted or no. This requires not only accurate, secure, and correct data collection processes; but also provisioning of data provenance throughout the life‐cycle of an IoT device and the data it produces. To this end, this work introduces a provenance‐based trust management solution, which provides a trust establishment mechanism amongst communicating devices in the IoT. It provides a way to quantitatively assess the trustworthiness of data supplied by a given IoT device. Thus, providing a novel solution to preserve data provenance of IoT devices. This IoT data provenance solution extends the capabilities of our previously proposed IoT platform known as the IoT‐management platform, which aimed at preserving the privacy of users in the IoT

Vitamin E Reduces Oxidative Stress Markers and Modulates Wound Repair in Aged Animals

Previous studies from our laboratory demonstrated an age-related functional decline in wound repair. Emerging evidence from our group and others favours the involvement of oxidative damage in the pathogenesis of age-related deficits. The aim of this study was to investigate the impact of vitamin E therapy on modulating oxidative stress markers and repair of full-thickness wounds in aged animals. Twenty four-month-old Sprague-Dawley rats were treated with vitamin E for short-term (40mg/kg, i.p. every other day for 2 weeks) or long-term (for 12 months in advance, 10g/kg, incorporated in food). The results indicate that both treatments were effective in reducing oxidative damage and in accelerating wound closure in aged rats. However, an initial increase in wound size was observed in both treated groups. This side effect of a single antioxidant therapy could reflect the importance of oxidants in the early stages of the repair process

A privacy risk assessment for the Internet of Things in healthcare

The Internet of Things (IoT) brings connectivity to about every object found in the physical space. It extends connectivity not only to mobile and wearable devices but also to everyday objects. From connected fridges and cars to fully interconnected smart cities, the IoT creates opportunities in numerous domains. This paper briefly highlights the promising applications of IoT in healthcare. The privacy challenges, risks, and vulnerabilities posed by the diversity and heterogeneity of communications in the IoT are then identified, followed by a privacy risk assessment