Risk Measures Research Articles

Self-Rated Health in Middle Age and Risk of Hospitalizations and Death: Recurrent Event Analysis of the ARIC Study

BackgroundSelf-rated health is a simple measure that may identify individuals who are at a higher risk for hospitalization or death.ObjectiveTo quantify the association between a single measure of self-rated health and future risk of recurrent hospitalizations or death.ParticipantsAtherosclerosis Risk in Communities (ARIC) study, a community-based prospective cohort study of middle-aged men and women with follow-up beginning from 1987 to 1989.Main MeasuresWe quantified the associations between initial self-rated health with risk of recurrent hospitalizations and of death using a recurrent events survival model that allowed for dependency between the rates of hospitalization and hazards of death, adjusted for demographic and clinical factors.Key ResultsOf the 14,937 ARIC cohort individuals with available self-rated health and covariate information, 34% of individuals reported “excellent” health, 47% “good,” 16% “fair,” and 3% “poor” at study baseline. After a median follow-up of 27.7 years, 1955 (39%), 3569 (51%), 1626 (67%), and 402 (83%) individuals with “excellent,” “good,” “fair,” and “poor” health, respectively, had died. After adjusting for demographic factors and medical history, a less favorable self-rated health status was associated with increased rates of hospitalization and death. As compared to those reporting “excellent” health, adults with “good,” “fair,” and “poor” health had 1.22 (1.07 to 1.40), 2.01 (1.63 to 2.47), and 3.13 (2.39 to 4.09) times the rate of hospitalizations, respectively. The hazards of death also increased with worsening categories of self-rated health, with “good,” “fair,” and “poor” health individuals experiencing 1.30 (1.12 to 1.51), 2.15 (1.71 to 2.69), and 3.40 (2.54 to 4.56) times the hazard of death compared to “excellent,” respectively.ConclusionsEven after adjusting for demographic and clinical factors, having a less favorable response on a single measure of self-rated health taken in middle age is a potent marker of future hospitalizations and death.

The Positive and Negative Suicidal Ideation Inventory among Portuguese Adolescents: Factor Structure and Gender Invariance.

Suicide worldwide is an issue that needs to be addressed, and adolescents are an at-risk group. Assessing suicidal ideation is central to tackling the issue of suicide. The Positive and Negative Suicidal Ideation inventory is a widely validated measure of suicidal ideation, and yet, very little is known about its invariance across various groups. The present study aimed to adapt and test the PANSI's structure in a Portuguese sample while testing its gender invariance. A total of 750 middle and high school students were recruited for the study, and data were collected on various suicide risk and protective factors, including the Portuguese-translated PANSI. Data were put through exploratory and confirmatory factor analysis. Kaiser's criterion and scree plot both extracted two factors (64.10% variance explained). Confirmatory factor analysis also supported the PANSI's structure (TLI = 0.943). The PANSI showed good reliability (α ≥ 0.83) and good construct and discriminative validity. The PANSI also exhibited scalar, but not strict, invariance. Overall, these results were similar to previous versions of this scale. The PANSI is a reliable measure of suicide risk among Portuguese adolescents. Future studies should further replicate these results in other cultures and expand on them by testing for invariance across other demographic variables.

Risk Measurement, Analysis, and Prediction Methods for Online Financial Services

The analysis and research on the risk of online financial business is divided into four main areas; the construction of metrics, analysis and modeling, risk prediction, and risk monitoring and control. It mainly uses high-frequency data to update the dynamic factor model, converts the results to low-frequency data to derive the systematic risk indicators; based on the Markov interval transformation model, the unpredictable and uncertain mechanisms are used as stochastic variables to identify the characteristics of the risk changes to cope with the Internet financial risks. The study concludes that the Internet financial risk has a certain trend and periodicity, and the presented market is relatively stable; due to the close connection between Internet finance and traditional financial industry, the resonance effect can bring certain risk to the whole financial market, and it is still necessary to pay attention to the changing risk factors and take corresponding risk management measures.

Associations between monitor-independent movement summary (MIMS) and fall risk appraisal combining fear of falling and physiological fall risk in community-dwelling older adults.

Introduction: Fall Risk Appraisal (FRA), a process that integrates perceived and objective fall risk measures, serves as a crucial component for understanding the incongruence between fear of falling (FOF) and physiological fall risk in older adults. Despite its importance, scant research has been undertaken to investigate how habitual physical activity (PA) levels, quantified in Monitor-Independent Movement Summary (MIMS), vary across FRA categories. MIMS is a device-independent acceleration summary metric that helps standardize data analysis across studies by accounting for discrepancies in raw data among research-grade and consumer devices. Objective: This cross-sectional study explores the associations between MIMS (volume and intensity) and FRA in a sample of older adults in the United States. Methods: We assessed FOF (Short Falls Efficacy Scale-International), physiological fall risk (balance: BTrackS Balance, leg strength: 30-s sit-to-stand test) and 7-day free-living PA (ActiGraph GT9X) in 178 community-dwelling older adults. PA volume was summarized as average daily MIMS (MIMS/day). PA intensity was calculated as peak 30-min MIMS (average of highest 30 non-consecutive MIMS minutes/day), representing a PA index of higher-intensity epochs. FRA categorized participants into following four groups: Rational (low FOF-low physiological fall risk), Irrational (high FOF-low physiological fall risk), Incongruent (low FOF-high physiological fall risk) and Congruent (high FOF-high physiological fall risk). Results: Compared to rational group, average MIMS/day and peak 30-min MIMS were, respectively, 15.8% (p = .025) and 14.0% (p = .004) lower in irrational group, and 16.6% (p = .013) and 17.5% (p < .001) lower in congruent group. No significant differences were detected between incongruent and rational groups. Multiple regression analyses showed that, after adjusting for age, gender, and BMI (reference: rational), only irrational FRA was significantly associated with lower PA volume (β = -1,452.8 MIMS/day, p = .034); whereas irrational and congruent FRAs were significantly associated with lower "peak PA intensity" (irrational: β = -5.40 MIMS/day, p = .007; congruent: β = -5.43 MIMS/day, p = .004). Conclusion: These findings highlight that FOF is a significant barrier for older adults to participate in high-intensity PA, regardless of their balance and strength. Therefore, PA programs for older adults should develop tailored intervention strategies (cognitive reframing, balance and strength exercises, or both) based on an individual's FOF and physiological fall risk.

Real Estate Development Feasibility and Hurdle Rate Selection

Real estate developers typically assess potential projects using feasibility analyses and industry-standard heuristics, which include capital costs, return on costs, and a subjective risk measure. This study explores real estate developers’ decision-making practices in selecting hurdle rates and common feasibility analysis techniques, surveying 225 Australian and New Zealand developers. The main findings are that most developers use specific ‘go/no-go’ hurdle rate mechanisms irrespective of primary real estate type, with the majority using margin on development cost (MDC) or internal rate of return (IRR); the boundaries between traditional speculative development and real estate investment through the use of securitization methods have become blurred; many developers use both quantitative metrics, with qualitative methods and specific structural checks to manage the risks involved; and the two most frequent methods of determining site value prior to acquisition are the residual land value and discounted cash flow methods. Most place a heavy reliance on industry-accepted heuristics and do not have a predetermined process and method for altering or adapting the chosen hurdle rates and benchmarks. This research provides a contribution to property development practice from the Antipodean perspective which until now has been more focused on the UK view, enabling more generalized application internationally.

Prognostic value of myocardial flow reserve vs corrected myocardial flow reserve in patients without obstructive coronary artery disease

BackgroundMyocardial flow reserve (MFR) by positron emission tomography (PET) is a validated measure of cardiovascular risk. Elevated resting rate pressure product (RPP = heart rate x systolic blood pressure) can cause high resting myocardial blood flow (MBF), resulting in reduced MFR despite normal/near-normal peak stress MBF. When resting MBF is high, it is not known if RPP-corrected MFR (MFRcorrected) helps reclassify CV risk. We aimed to study this question in patients without obstructive coronary artery disease (CAD). MethodsWe retrospectively studied patients referred for rest/stress cardiac PET at our center from 2006 to 2020. Patients with abnormal perfusion (summed stress score >3) or prior coronary artery bypass grafting (CABG) were excluded. MFRcorrected was defined as stress MBF/corrected rest MBF where corrected rest MBF = rest MBF x 10,000/RPP. The primary outcome was major cardiovascular events (MACE): cardiovascular death or myocardial infarction. Associations of MFR and MFRcorrected with MACE were assessed using unadjusted and adjusted Cox regression. Results3276 patients were followed for a median of 7 (IQR 3–12) years. 1685 patients (51%) had MFR <2.0, and of those 366 (22%) had an MFR ≥2.0 after RPP correction. MFR <2.0 was associated with an increased absolute risk of MACE (HR 2.24 [1.79–2.81], P < 0.0001). Among patients with MFR <2.0, the risk of MACE was not statistically different between patients with an MFRcorrected ≥2.0 compared with those with MFRcorrected <2.0 (1.9% vs 2.3% MACE/year, HR 0.84 [0.63–1.13], P = 0.26) even after adjustment for confounders (P = 0.66). ConclusionsIn patients without overt obstructive CAD and MFR< 2.0, there was no significant difference in cardiovascular risk between patients with discordant (≥2.0) and concordant (<2) MFR following RPP correction. This suggests that RPP-corrected MFR may not consistently provide accurate risk stratification in patients with normal perfusion and MFR <2.0. Stress MBF and uncorrected MFR should be reported to more reliably convey cardiovascular risk beyond perfusion results.

Cross-exchange crypto risk: A high-frequency dynamic network perspective

Cross-exchange crypto trading presents inherent risks, particularly for centralized exchanges. Investors observe exacerbating crypto volatility and counterparty risk and would like to quantify these elements of crypto trades. The multiple exchanges require a multivariate view on the structures of risk spillover across exchanges. Here, a Multivariate Heterogeneous AutoRegression (MHAR) model is designed and analyzed, accommodating the stylized facts of crypto markets, including 24/7 trading and the long-memory effect on return variations. The proposed MHAR approach clearly reveals the intensity of interconnectedness among exchanges during extreme events, e.g., the Bitcoin market. Additionally, one observes extremely volatile eigenvector centralities of Futures Exchange Ltd (FTX), suggesting potential implications for its bankruptcy. Furthermore, portfolios that account for the dynamics of partial correlations or eigenvector centralities offer promising results in terms of risk measures.

Revolutionizing Health Management: Developing a Wearable Device for Real-time Heart Rate Measurement and Prediction of Hypertension Risks

This research paper introduces SyncFit, a wearable gadget coupled with a web platform for instant heart rate monitoring and hypertension risk forecasting. The gadget employs a Python-based random forest algorithm to scrutinize heart rate data and anticipate abnormal rates signaling hypertension risk. The web platform, constructed with Streamlit and Firebase, grants users access to their heart rate analysis and hypertension risk evaluation. The research showcases SyncFit's capability to transform health management by enabling individuals to proactively monitor their health and predict risks, thereby facilitating optimization of their wellness journey. SyncFit enhances user experience with a range of features beyond its core functions, ensuring effortless integration into daily routines. Its sleek, ergonomic design prioritizes comfort, enabling seamless wear throughout the day. Additionally, its intuitive interface and user-friendly controls facilitate easy navigation and customization, catering to diverse user preferences. SyncFit's robust construction and advanced tech establish a new benchmark for wearable health monitors, blending style and functionality to empower users in their wellness journey. SyncFit commits to constant improvement and innovation, with ongoing R&amp;D aimed at expanding capabilities and addressing emerging health challenges. Future versions will integrate more sensors and advanced analytics, offering a deeper understanding of health. Integration with AI and cloud tech will revolutionize personalized health management, making preventive care proactive, empowering individuals to optimize well-being. Key Words: wearable device, heart rate, hypertension risk, web application, machine learning, artificial intelligence, streamlit.

Quantum Monte Carlo simulations for financial risk analytics: scenario generation for equity, rate, and credit risk factors

Monte Carlo (MC) simulations are widely used in financial risk management, from estimating value-at-risk (VaR) to pricing over-the-counter derivatives. However, they come at a significant computational cost due to the number of scenarios required for convergence. If a probability distribution is available, Quantum Amplitude Estimation (QAE) algorithms can provide a quadratic speed-up in measuring its properties as compared to their classical counterparts. Recent studies have explored the calculation of common risk measures and the optimisation of QAE algorithms by initialising the input quantum states with pre-computed probability distributions. If such distributions are not available in closed form, however, they need to be generated numerically, and the associated computational cost may limit the quantum advantage. In this paper, we bypass this challenge by incorporating scenario generation – i.e. simulation of the risk factor evolution over time to generate probability distributions – into the quantum computation; we refer to this process as Quantum MC (QMC) simulations. Specifically, we assemble quantum circuits that implement stochastic models for equity (geometric Brownian motion), interest rate (mean-reversion models), and credit (structural, reduced-form, and rating migration credit models) risk factors. We then integrate these models with QAE to provide end-to-end examples for both market and credit risk use cases.

An extreme worst-case risk measure by expectile

Abstract Expectiles have received increasing attention as a risk measure in risk management because of their coherency and elicitability at the level $\alpha\geq1/2$ . With a view to practical risk assessments, this paper delves into the worst-case expectile, where only partial information on the underlying distribution is available and there is no closed-form representation. We explore the asymptotic behavior of the worst-case expectile on two specified ambiguity sets: one is through the Wasserstein distance from a reference distribution and transforms this problem into a convex optimization problem via the well-known Kusuoka representation, and the other is induced by higher moment constraints. We obtain precise results in some special cases; nevertheless, there are no unified closed-form solutions. We aim to fully characterize the extreme behaviors; that is, we pursue an approximate solution as the level $\alpha $ tends to 1, which is aesthetically pleasing. As an application of our technique, we investigate the ambiguity set induced by higher moment conditions. Finally, we compare our worst-case expectile approach with a more conservative method based on stochastic order, which is referred to as ‘model aggregation’.

Projection of PT Aneka Tambang Tbk Share Risk Value Based on Backpropagation Artificial Neural Network Forecasting Result

PT Aneka Tambang Tbk (ANTAM) received an award as the most sought-after stock issuer in Indonesia in 2016. That stock continued to attract investors in 2022 due to a 105% increase in net profit and a 19% increase in sales from the previous year. Despite the upward trend, investors still had doubts due to the fluctuating movement of ANTAM's stock prices. Therefore, forecasting was needed to determine the future movement of stock prices. The Backpropagation Neural Network method had good capabilities for fluctuating data types. However, this method has the disadvantage of a lengthy iteration process. To handle this limitation, The Nguyen-Widrow weighted setting was applied to address this constraint. The expected Shortfall (ES) method used the forecasting results to measure investment risk. This research uses ANTAM stock closing price data from May 2, 2018, to May 31, 2023. Based on the analysis results, the best architecture was obtained with a configuration of 5-11-1, using Nguyen-Widrow weight initialization and a combination of a learning rate of 0.5 and momentum of 0.9. This architecture yielded a prediction error based on the Mean Absolute Percentage Error (MAPE) of 1.9947%. Risk measurement with the ES method based on the prediction for the next 60 periods showed that at a 95% confidence level, the risk value was 0.002181; at a 90% confidence level, it was 0.002165; at an 85% confidence level, it was 0.002148, and at an 80% confidence level, it was 0.002132.

Novel collision risk measurement method for multi-ship encounters via velocity obstacles and temporal proximity

The collision risk assessment of multi-ship encounters in busy waters is of great significance for collision risk early warning and the intelligent supervision of maritime traffic. In this paper, a quantitative and visual evaluation method is proposed to describe changes in multi-ship collision risk in the velocity space according to multi-ship collision risk characteristics. Non-linear velocity obstacles and closest point of approach were combined to measure the risk of ship collision from the perspective of both the difficulty and urgency of the encounter. The proposed method was verified via case studies using historical Automatic Identification System data for the East China Sea. The method advantages were confirmed via comparison to the conventional time-varying collision risk and collision risk index methods. The results show that the proposed method can quantify changes in multi-ship collision risk more intuitively and effectively. The proposed method could be further developed as a new risk indicator for maritime traffic safety management and could aid in the navigation safety of manned and unmanned ships.

Measuring DeFi risk

Decentralized finance (DeFi) lending has grown from nonexistent in 2017 to nearly $45 billion in total value locked across the three largest protocols in December 2021 before falling to roughly $15 billion in July 2023. The platforms use cryptocurrencies as collateral, matching speculative margin traders with yield-seeking depositors. Depositors receive claims guaranteed by a basket of collateral. We develop a framework that requires only knowledge of total deposits and borrowings to measure the total protocol risk to lenders and borrowers. Using data from major protocols, the risk measures show that system fragility increased beyond reasonable levels around mid-2021, and we identify time periods exposing lenders to a potential collateral loss conditional on continuing extreme fluctuations in coin prices. Moreover, our results indicate that the liquidation process, a risk mitigation strategy, is not timely and is less effective when risk levels are high. Overall, the model provides two easily implementable aggregate risk metrics that capture the perspectives of synthetic investors and provide early warning signals as the industry moves from collateral-guaranteed deposits to fiat money.

A New Measure of Climate Transition Risk Based on Distance to a Global Emission Factor Frontier

Targeted financing of transition to a "net zero" global economy entails climate transition risk. We propose a measure of transition risk at the country-sector dyad level composed of five tiers of transition risk based on two factors: i) the gap between a dyad's existing emission factor (EF) – a measure of the greenhouse gas intensity of output – and the global 'frontier' sectoral EF, and ii) a dyad's recent convergence towards the frontier EF. Dyads that are either close to the frontier or converging towards the frontier carry lower transition risk. Our measure, using 45 sectors across 66 countries, accounts for both direct greenhouse gas emissions as well as those that enter into production through complex supply chains as captured by intercountry, input-output tables, and can be applied at different levels of stringency to high-, middle-, and low-income economies. Our measure thus accounts for, and sheds light on, EF reductions through investment in lower emissions production techniques in own facilities as well as sourcing intermediate inputs with lower embodied emissions.

Health Outcomes and Health Services Utilization Evaluation Protocol: Assessing the Impact of the Nova Scotia Rapid Access and Stabilization Program

IntroductionEmergency psychiatric care, unplanned hospital admissions, and inpatient health care are the costliest forms of mental health care. According to Statistics Canada (2018), almost 18% (5.3 million) of Canadians reported needing mental health support. However, just above half of this figure (56.2%) have reported their needs were fully met. To further expand capacity and access to mental health care in the province, Nova Scotia Health has launched a novel mental health initiative, the Rapid Access, and Stabilization Program (RASP).ObjectivesThis study evaluates the effectiveness and impact of the RASP on high-cost health services utilization (e.g. ED visits, mobile crisis visits, and inpatient treatments) and related costs. It also assesses healthcare partners’ (e.g. healthcare providers, policymakers, community leaders) perceptions and patient experiences and satisfaction with the program and identifies sociodemographic characteristics, psychological conditions, recovery, well-being, and risk measures in the assisted population.MethodsThis is a hypothesis-driven program evaluation study that employs a mixed methods approach. A within-subject comparison will examine health services utilization data from patients attending RASP, one year before and one year after their psychiatry assessment at the program. A controlled between-subject comparison will use historical data from a control population will examine whether possible changes in high-cost health services utilization are associated with the intervention (RASP). The primary analysis involves extracting secondary data from provincial information systems, electronic medical records, and regular self-reported clinical assessments. Additionally, a qualitative sub-study will examine patient experience and satisfaction, and examine health care partners’ impressions.ResultsThe results for the primary, secondary, and qualitative outcome measures to be available within 6 months of study completion. We expect that RASP evaluation findings will demonstrate a minimum 10% reduction in high-cost health services utilization and corresponding 10% cost savings, and also a reduction in the wait times for patient consultations with psychiatrists to less than 30 calendar days. In addition, we anticipate that patients, healthcare providers, and healthcare partners would express high levels of satisfaction with the new service.ConclusionsThis study will demonstrate the results of the Mental Health and Addictions Program (MHAP) efforts to provide stepped-care, particularly community-based support, to individuals with mental illnesses. Results will provide new insights into a novel community-based approach to mental health service delivery and contribute to knowledge on how to implement mental health programs across varying contexts.Disclosure of InterestNone Declared

Cardiovascular disease risk in Australians following plant-based dietary patterns compared to regular meat eaters

The adoption of dietary patterns emphasising higher intakes of plant foods and lower intakes of animal foods (plant-based diets, PBDs), continue to rise worldwide. PBDs have been associated with a lower risk of cardiovascular morbidity and mortality as well as major risk factors such as overweight/obesity and type 2 diabetes. Evidence regarding the dietary profile and disease risk associated with various PBDs in comparison to traditional meat-eating diets are scarce within the Australian population. The aim of this study is to investigate the 5-year and 10-year risk of developing cardiovascular disease (CVD) among Australians habitually following various PBDs compared to a regular meat diet (RMD). The Plant-based Diet (PBD) Study is a cross-sectional study consisting of healthy adults between aged 30-75 years from the Hunter Region (NSW) between 2021-2023. A validated FFQ was used to assess eligibility and categorise individuals who were habitually consuming one of five dietary patterns for at least 6 months into the following groups: vegan (nil animal products), lacto-vegetarian (LOV, including eggs and dairy), pesco-vegetarian (PV, including seafood with/without dairy and eggs), semi-vegetarian (SV, minimal consumption of animal products) or RMDs (including animal meat daily or multiple times/day)(1). 5-year and 10-year CVD risk was quantified using the Framingham Risk Equation(2) and the Australian Absolute CVD risk calculator, respectively. CVD risk and other quantitative measures was compared using One-way ANOVA or Kruskal Wallis, and Chi-square or Fisher’s Exact for qualitative data. Directed acyclic graphs displayed confounding variables and mediators and a regression model was used to adjust for these. A total of 240 participants (median age 55(16), 77.5% female) with 48 participants in each group showed a significant difference in predicted 5-year risk of CVD (P&lt;0.05), however 10-year risk did not significantly differ across groups. 5-year CVD risk was significantly lower in the vegan group (1%) compared to the RMD, SV, PV, and LOV diet groups (all 2%). In comparison to a vegan diet, crude association showed those consuming a RMD had a 2.4% (95% CI 0.7, 4.1) higher 5-year risk of developing CVD, followed by 1.7% in LOV (95% CI 0.6, 2.9), 1.8% in PV (95% CI 0.5, 3), and 1.1% in SV (95% CI 0.2, 2.1). Significance was lost after adjusting for confounders such as age, gender, smoking status, alcohol intake, physical activity levels and BMI. This is the first study to purposefully sample Australians habitually following PBD, presenting novel population-based evidence for CVD risk. These findings suggest more restrictive PBDs such as vegan diets when compared to RMD may lead to lower CVD risk, however population-based longitudinal studies primary investigating the development of CVDs in the context of PBDs are warranted.

Markov decision processes with risk-sensitive criteria: an overview

AbstractThe paper provides an overview of the theory and applications of risk-sensitive Markov decision processes. The term ’risk-sensitive’ refers here to the use of the Optimized Certainty Equivalent as a means to measure expectation and risk. This comprises the well-known entropic risk measure and Conditional Value-at-Risk. We restrict our considerations to stationary problems with an infinite time horizon. Conditions are given under which optimal policies exist and solution procedures are explained. We present both the theory when the Optimized Certainty Equivalent is applied recursively as well as the case where it is applied to the cumulated reward. Discounted as well as non-discounted models are reviewed.

Risk-constrained bidding and offering strategy for sector-coupled electricity-hydrogen systems incorporating accessibility level of mobility sector

To enhance the economic viability of integrated energy systems, it is important to balance risk and reward while ensuring operational flexibility and compliance with regulatory constraints. Developing an integrated risk measurement method for energy trading in energy markets that complies with regulatory constraints adds another layer of complexity, especially when dealing with large-scale heterogeneous energy systems, such as those dominated by green hydrogen. Ensuring adherence to market regulations, grid codes, and flexible requirements requires a thorough understanding of legal frameworks and policy considerations, as well as integrating regulatory constraints into the bidding/offering strategies. To address these challenges and enable the profitable development of integrated electricity-hydrogen energy systems (IEHSs), this paper develops a risk-constrained bidding/offering self-scheduling strategy for IEHSs that allows for simultaneous trading in day-ahead energy and reserve electricity markets. The developed self-scheduling strategy regulates hydrogen and power flow in a centralized manner, taking into account the operational limits of the power sector, hydrogen fueling stations (HFSs), electric vehicle parking lots, fuel cell vehicle parking lots, and renewable energy sources. As a salient feature, the important human-related factors in the mobility sector are included in the proposed strategy to motivate private owners to collaborate with IEHSs and to accommodate the charging demand of vehicles with electricity market signals. To obtain the robust day-ahead schedule, economic risks associated with renewable power generation, calls for reserve deployment, and electricity market prices are taken into consideration. Towards this end, a stochastic adaptive robust optimization approach is proposed to control the risk of profit variability, which is solved by a nested column-and-constraint generation algorithm. The effectiveness and feasibility of the proposed strategy are verified using the modified IEEE 14-bus test system, as a standard scale of local IEHSs. The numerical results highlight the synergies impact between HFSs and the power sector, resulting in an increase in the profit of the IEHS from $101.654k to $275.078k. Furthermore, the IEHS can improve its profit margin and competitiveness by employing the tri-level stochastic adaptive robust optimization approach. This approach ensures that the IEHS is resistant to sudden changes in real-time interactions, even with an 8.14% increase in the imbalance cost.

Footprints of Stress in Vitiligo: Association of the 5-HTR2C rs6318 Variant

Abstract Vitiligo is a chronic, progressive autoimmune dermatological disease, and stress is known to have an impact on the development of vitiligo. However, the effect of the serotonin pathway and its impact have not been clearly explained for disease progression. Thus, this study aimed to clarify the stress induced serotonin receptor 5-HTR2C rs6318 variant and its association with vitiligo pathogenesis. Case-control study was conducted with 108 vitiligo patients and 107 age-sex matched, unrelated healthy control group. Real Time-PCR analysis was used for genotyping the 5-HTR2C variation. Genotype and allele frequencies, genotype distributions, Hardy-Weinberg Equilibrium (HWE) and vitiligo-related risk measurements were examined. Genotype correlations of the variant were also analyzed based on gender difference, age onset, Koebner phenomenon history, triggered with stress, clinical subgroups, treatment types, the presence of other autoimmune diseases, vitiligo presence in family members and other auto-immune diseases in relatives. Statistical differences in 5HT-R2C receptor genotypes and allele frequencies between patients and controls were not detected. Genotype frequencies were not in agreement with Hardy-Weinberg Equilibrium in the patients’ group (p&lt;0.00001). The frequency of the risk allele (allele C) was not significantly different between the patient and control groups (p=0.1392). However, in the clinical subgroup analysis, the risk allele presence was detected to be significantly higher for early age onset (&lt;40 years) vitiligo development (p=0.035, OR=Infinity, RR=1.391) and lower in Koebner phenomenon history (p=0.0276, OR= 0.219, RR=0.325). In conclusion, although there was no association between the 5-HTR2C variant rs6318 and vitiligo, current results indicate that there is an association between the 5HTR2C rs6318 variant C allele and early onset vitiligo development.

Uncontrolled eating is associated with higher impulsiveness, risk taking and novelty-seeking

Previous studies suggest that trait disinhibition as measured by the Three Factor eating Questionnaire (TFEQ) is related to selected measures of impulsivity and risk taking. However, the factor validity of the original trait disinhibition measure has been questioned, and a revised scale of uncontrolled eating consequently developed. To date few studies have revisited the relationship between impulsivity and the uncontrolled and emotional eating scales of the revised TFEQ. In the present study, 283 participants (208 women) completed the revised TFEQ alongside a battery of measures of impulsivity and risk taking in an online study. The total and all subscale scores on the Barratt Impulsiveness Scale were significantly associated with scores on the uncontrolled, but not emotional or restrained, TFEQ scale. Likewise, risky behaviour indexed by the average number of pumps per trial on the Balloon Analogue Risk Task were also associated with uncontrolled, but not emotional or restrained, eating, and the same pattern of associations were also found for the novelty, but not intensity, subscales of the Arnetts Inventory of Sensation Seeking. Overall these data suggest that uncontrolled eating is related to wider personality traits of risky decision making, novelty seeking and wider cognitive impulsivity, which may in turn increase of future weight gain.