Handling Computation Hardness and Time Complexity Issue of Battery Energy Storage Scheduling in Microgrids by Deep Reinforcement Learning

With the development of microgrids (MGs), an energy management system (EMS) is required to ensure the stable and economically efficient operation of the MG system. In this paper, an intelligent EMS is proposed by exploiting the deep reinforcement learning (DRL) technique. DRL is employed as the effective method for handling the computation hardness of optimal scheduling of the charge/discharge of battery energy storage in the MG EMS. Since the optimal decision for charge/discharge of the battery depends on its state of charge given from the consecutive time steps, it demands a full-time horizon scheduling to obtain the optimum solution. This, however, increases the time complexity of the EMS and turns it into an NP-hard problem. By considering the energy storage system’s charging/discharging power as the control variable, the DRL agent is trained to investigate the best energy storage control method for both deterministic and stochastic weather scenarios. The efficiency of the strategy suggested in this study in minimizing the cost of purchasing energy is also shown from a quantitative perspective through programming verification and comparison with the results of mixed integer programming and the heuristic genetic algorithm (GA)

High-Performance Atomically-Thin Room-Temperature NO2 Sensor.

The development of room-temperature sensing devices for detecting small concentrations of molecular species is imperative for a wide range of low-power sensor applications. We demonstrate a room-temperature, highly sensitive, selective, stable, and reversible chemical sensor based on a monolayer of the transition-metal dichalcogenide Re0.5Nb0.5S2. The sensing device exhibits a thickness-dependent carrier type, and upon exposure to NO2 molecules, its electrical resistance considerably increases or decreases depending on the layer number. The sensor is selective to NO2 with only minimal response to other gases such as NH3, CH2O, and CO2. In the presence of humidity, not only are the sensing properties not deteriorated but also the monolayer sensor shows complete reversibility with fast recovery at room temperature. We present a theoretical analysis of the sensing platform and identify the atomically sensitive transduction mechanism

Food insecurity in adults with severe mental illness living in Northern England: Peer research interview findings

\ua9 2023 The Authors. International Journal of Mental Health Nursing published by John Wiley & Sons Australia, Ltd.Food insecurity means that a person does not have access to sufficient nutritious food for normal growth and health. Food insecurity can lead to many health problems such as obesity, heart disease, diabetes, and other long term health conditions. People living with a severe mental illness are more likely to experience food insecurity than people without mental illness. Peer-led in-depth interviews were conducted with adults with severe mental illness from Northern England, during which their experiences of food insecurity and strategies to tackle food insecurity were discussed. Interviews took place between March and December 2022, with interviews being transcribed and analysed using deductive and inductive thematic analysis. Thirteen interviews were conducted, finding that food insecurity in adults with severe mental illness was often a long-standing issue. Unemployment, the cost-of-living crisis and fuel poverty impacted on experiences of food insecurity. Difficulties accessing food banks such as transport, stigma, and the limited selection of available food was also discussed. Strategies to tackle food insecurity centred on making food banks more accessible and improving the quality of available food. Future research should aim to eradicate food insecurity for adults with severe mental illness, as limited research and action focuses on this population group over and above ‘mental illness’ or ‘poor mental health’. Removing barriers to accessing food such as lack of transport, and providing food which is of adequate nutritional quality, should be prioritised, as well as tackling the stigma and accessibility issues surrounding food banks use

Strategic Ingestion of High-Protein Dairy Milk during a Resistance Training Program Increases Lean Mass, Strength, and Power in Trained Young Males

Background: We evaluated the effects of high-protein dairy milk ingestion on changes in body composition, strength, power, and skeletal muscle regulatory markers following 6 weeks of resistance training in trained young males. Methods: Thirty resistance-trained young males (age: 27 ± 3 years; training experience: 15 ± 2 months) were randomly assigned to one of two groups: high-protein dairy milk (both whey and casein) + resistance training (MR; n = 15) or isoenergetic carbohydrate (maltodextrin 9%) + resistance training (PR; n = 15). Milk and placebo were ingested immediately post-exercise (250 mL; 30 g protein) and 30 min before sleep (250 mL; 30 g protein). Before and after 6 weeks of linear periodized resistance training (4 times/week), body composition (bioelectrical impedance), strength, power, and serum levels of skeletal muscle regulatory markers (insulin-like growth factor 1 (IGF-1), growth hormone, testosterone, cortisol, follistatin, myostatin, and follistatin–myostatin ratio) were assessed. Results: The MR group experienced a significantly higher (p 0.05) increase in lean mass, strength, and power (upper- and lower-body) than the PR group. Further, IGF-1, growth hormone, testosterone, follistatin, and follistatin–myostatin ratio were significantly increased, while cortisol and myostatin significantly decreased in the MR group than the PR group (p 0.05). Conclusions: The strategic ingestion of high-protein dairy milk (post-exercise and pre-sleep) during 6 weeks of resistance training augmented lean mass, strength, power, and altered serum concentrations of skeletal muscle regulatory markers in trained young males compared to placebo

The impact of, and views on, school food intervention and policy in young people aged 11-18 years in Europe: a mixed methods systematic review

Understanding the social and environmental influencers of eating behaviours has the potential to improve health outcomes for young people. This review aims to explore the effectiveness of school nutrition interventions and the perceptions of young people experiencing a nutrition focused intervention or change in school food policy. A comprehensive systematic search identified studies published between 1 December 2007 to 20 February 2020. Twenty‐seven studies were included: 22 quantitative studies of nutrition related outcomes and five qualitative studies reporting views and perceptions of young people (combined sample of 22,138 participants, mean ages 12–18 years). The primary outcome was nutrition knowledge/dietary behaviours, with secondary outcomes exploring body mass index (BMI) and wellbeing. Due to the heterogeneity of studies, a narrative results description is presented. The findings demonstrate that school nutrition programmes can be effective in reducing sugar, sugar sweetened beverages (SSB) and saturated fat and increasing fruit and vegetable (FV) intake. The lived experiences of young people in a school context provide valuable insights that should be considered in the development of effective school food policy and interventions. This review affirms the significant role that schools can play in supporting good nutrition in all young people and provides opportunities to inform the school food agenda

Food insecurity in adults with severe mental illness living in Northern England: A co-produced cross-sectional study

\ua9 2024 The Authors. Nutrition & Dietetics published by John Wiley & Sons Australia, Ltd on behalf of Dietitians Australia.Aim: This study aimed to explore food insecurity prevalence and experiences of adults with severe mental illness living in Northern England. Methods: This mixed-methods cross-sectional study took place between March and October 2022. Participants were adults with self-reported severe mental illness living in Northern England. The survey included demographic, health, and financial questions. Food insecurity was measured using the US Department of Agriculture Adult Food Security measure. Quantitative data were analysed using descriptive statistics and binary logistic regression; and qualitative data using content analysis. Results: In total, 135 participants completed the survey, with a mean age of 44.7 years (SD: 14.1, range: 18–75 years). Participants were predominantly male (53.3%), white (88%) and from Yorkshire (50.4%). The food insecurity prevalence was 50.4% (n = 68). There was statistical significance in food insecurity status by region (p = 0.001); impacts of severe mental illness on activities of daily living (p = 0.02); and the Covid pandemic on food access (p < 0.001). The North West had the highest prevalence of food insecurity (73.3%); followed by the Humber and North East regions (66.7%); and Yorkshire (33.8%). In multivariable binary logistic regression, severe mental illness\u27 impact on daily living was the only predictive variable for food insecurity (odds ratio = 4.618, 95% confidence interval: 1.071–19.924, p = 0.04). Conclusion: The prevalence of food insecurity in this study is higher than is reported in similar studies (41%). Mental health practitioners should routinely assess and monitor food insecurity in people living with severe mental illness. Further research should focus on food insecurity interventions in this population

Clinical Subtypes of Depression Are Associated with Specific Metabolic Parameters and Circadian Endocrine Profiles in Women: The Power Study

Major depressive disorder (MDD) has been associated with adverse medical consequences, including cardiovascular disease and osteoporosis. Patients with MDD may be classified as having melancholic, atypical, or undifferentiated features. The goal of the present study was to assess whether these clinical subtypes of depression have different endocrine and metabolic features and consequently, varying medical outcomes.Premenopausal women, ages 21 to 45 years, with MDD (N = 89) and healthy controls (N = 44) were recruited for a prospective study of bone turnover. Women with MDD were classified as having melancholic (N = 51), atypical (N = 16), or undifferentiated (N = 22) features. Outcome measures included: metabolic parameters, body composition, bone mineral density (BMD), and 24 hourly sampling of plasma adrenocorticotropin (ACTH), cortisol, and leptin.Compared with control subjects, women with undifferentiated and atypical features of MDD exhibited greater BMI, waist/hip ratio, and whole body and abdominal fat mass. Women with undifferentiated MDD characteristics also had higher lipid and fasting glucose levels in addition to a greater prevalence of low BMD at the femoral neck compared to controls. Elevated ACTH levels were demonstrated in women with atypical features of depression, whereas higher mean 24-hour leptin levels were observed in the melancholic subgroup.Pre-menopausal women with various features of MDD exhibit metabolic, endocrine, and BMD features that may be associated with different health consequences.ClinicalTrials.gov NCT00006180