Cluster Analysis and Model Comparison Using Smart Meter Data.

Load forecasting plays a crucial role in the world of smart grids. It governs many aspects of the smart grid and smart meter, such as demand response, asset management, investment, and future direction. This paper proposes time-series forecasting for short-term load prediction to unveil the load forecast benefits through different statistical and mathematical models, such as artificial neural networks, auto-regression, and ARIMA. It targets the problem of excessive computational load when dealing with time-series data. It also presents a business case that is used to analyze different clusters to find underlying factors of load consumption and predict the behavior of customers based on different parameters. On evaluating the accuracy of the prediction models, it is observed that ARIMA models with the (P, D, Q) values as (1, 1, 1) were most accurate compared to other values

Grain size-dependent magnetic and electric properties in nanosized YMnO3 multiferroic ceramics

Magnetic and electric properties are investigated for the nanosized YMnO3 samples with different grain sizes (25 nm to 200 nm) synthesized by a modified Pechini method. It shows that magnetic and electric properties are strongly dependent on the grain size. The magnetic characterization indicates that with increasing grain size, the antiferromagnetic (AFM) transition temperature increases from 52 to 74 K. A corresponding shift of the dielectric anomaly is observed, indicating a strong correlation between the electric polarization and the magnetic ordering. Further analysis suggests that the rising of AFM transition temperature with increasing grain size should be from the structural origin, in which the strength of AFM interaction as well as the electrical polarization is dependent on the in-plane lattice parameters. Furthermore, among all samples, the sample with grain size of 95 nm is found to have the smallest leakage current density (< 1 μA/cm2)

Childhood emotional trauma and cyberbullying perpetration among emerging adults: a multiple mediation model of the role of problematic social media use and psychopathology

Research suggests that a small minority of social media users experience problems as a result of their online use. The purpose of the present study was to examine the association of cyberbullying perpetration and problematic social media use with childhood emotional trauma, Cluster B (narcissistic, histrionic, antisocial, and borderline) personality traits, dissociative experiences (DEs), depression, and self-esteem in a nonclinical undergraduate sample. A total of 344 university students volunteered to complete a questionnaire that included measures on the aforementioned dimensions. Thirty-eight percent of the participants had emotional neglect and 27% had emotional abuse, while 44% of them demonstrated at least one cyberbullying perpetration behavior. Results indicated that cyberbullying perpetrators had higher scores on problematic social media use, dissociative experiences, Cluster B traits, depression and childhood emotional trauma, and lower on self-esteem. Path analysis demonstrated that, while adjusting for gender and age, childhood emotional trauma was directly and indirectly associated with cyberbullying perpetration via Cluster B traits. Moreover, depression and dissociation were directly associated with problematic social media use. The findings of this study emphasize the important direct role of childhood emotional trauma and pathological personality traits on cyberbullying perpetration

Analysis of turbulence and surface growth models on the estimation of soot level in ethylene non-premixed flames

Soot prediction in a combustion system has become a subject of attention, as many factors influence its accuracy. An accurate temperature prediction will likely yield better soot predictions, since the inception, growth and destruction of the soot are affected by the temperature. This paper reported the study on the influences of turbulence closure and surface growth models on the prediction of soot levels in turbulent flames. The results demonstrated that a substantial distinction was observed in terms of temperature predictions derived using the k-ε and the Reynolds stress models, for the two ethylene flames studied here amongst the four types of surface growth rate model investigated, the assumption of the soot surface growth rate proportional to the particle number density, but independent on the surface area of soot particles, ƒ(As) = ρNs , yields in closest agreement with the radial data. Without any adjustment to the constants in the surface growth term, other approaches where the surface growth directly proportional to the surface area and square root of surface area, ƒ(As) = As and ƒ(As) = √As, result in an under- prediction of soot volume fraction. These results suggest that predictions of soot volume fraction are sensitive to the modelling of surface growth

‘Gatekeepers’ of Islamic financial circuits: Analysing urban geographies of the global Shari’a elite

This paper analyses the importance of 'Shari'a scholars' in the Islamic Financial Services (IFS) sector, which has been a growing global practice since the 1970s. Based on Shari'a Law, IFS firms provide banking, finance and insurance respecting faith-based prohibitions on interest, speculation and risk taking. Although IFS firms operate across a variety of scales and involve a range of actors, this paper focuses on the transnational capacities of Shari'a experts employed by IFS firms. These scholars use their extensive knowledge of Shari'a Law to assess the 'Islamic' character of a firm's operations, and assist the development of Shari'a-compliant products. As they embody necessary entry-points into Islamic circuits of knowledge and authority, members of what we dub the 'global Shari'a elite' can be regarded as 'gatekeepers' of Islamic financial circuits. Drawing on a comprehensive data source we present a geographical analysis of Shari'a board membership, nationality and educational background of 253 Shari'a scholars. The results show that the global Shari'a elite connects a limited number of IFS hubs (e. g. Dubai, Kuala Lumpur, Kuwait City, Manama, and London) to knowledge and authority networks falling outside 'mainstream' business and service spheres

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P &lt; 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Clinical characteristics with inflammation profiling of long COVID and association with 1-year recovery following hospitalisation in the UK: a prospective observational study

Background No effective pharmacological or non-pharmacological interventions exist for patients with long COVID. We aimed to describe recovery 1 year after hospital discharge for COVID-19, identify factors associated with patient-perceived recovery, and identify potential therapeutic targets by describing the underlying inflammatory profiles of the previously described recovery clusters at 5 months after hospital discharge. Methods The Post-hospitalisation COVID-19 study (PHOSP-COVID) is a prospective, longitudinal cohort study recruiting adults (aged ≥18 years) discharged from hospital with COVID-19 across the UK. Recovery was assessed using patient-reported outcome measures, physical performance, and organ function at 5 months and 1 year after hospital discharge, and stratified by both patient-perceived recovery and recovery cluster. Hierarchical logistic regression modelling was performed for patient-perceived recovery at 1 year. Cluster analysis was done using the clustering large applications k-medoids approach using clinical outcomes at 5 months. Inflammatory protein profiling was analysed from plasma at the 5-month visit. This study is registered on the ISRCTN Registry, ISRCTN10980107, and recruitment is ongoing. Findings 2320 participants discharged from hospital between March 7, 2020, and April 18, 2021, were assessed at 5 months after discharge and 807 (32·7%) participants completed both the 5-month and 1-year visits. 279 (35·6%) of these 807 patients were women and 505 (64·4%) were men, with a mean age of 58·7 (SD 12·5) years, and 224 (27·8%) had received invasive mechanical ventilation (WHO class 7–9). The proportion of patients reporting full recovery was unchanged between 5 months (501 [25·5%] of 1965) and 1 year (232 [28·9%] of 804). Factors associated with being less likely to report full recovery at 1 year were female sex (odds ratio 0·68 [95% CI 0·46–0·99]), obesity (0·50 [0·34–0·74]) and invasive mechanical ventilation (0·42 [0·23–0·76]). Cluster analysis (n=1636) corroborated the previously reported four clusters: very severe, severe, moderate with cognitive impairment, and mild, relating to the severity of physical health, mental health, and cognitive impairment at 5 months. We found increased inflammatory mediators of tissue damage and repair in both the very severe and the moderate with cognitive impairment clusters compared with the mild cluster, including IL-6 concentration, which was increased in both comparisons (n=626 participants). We found a substantial deficit in median EQ-5D-5L utility index from before COVID-19 (retrospective assessment; 0·88 [IQR 0·74–1·00]), at 5 months (0·74 [0·64–0·88]) to 1 year (0·75 [0·62–0·88]), with minimal improvements across all outcome measures at 1 year after discharge in the whole cohort and within each of the four clusters. Interpretation The sequelae of a hospital admission with COVID-19 were substantial 1 year after discharge across a range of health domains, with the minority in our cohort feeling fully recovered. Patient-perceived health-related quality of life was reduced at 1 year compared with before hospital admission. Systematic inflammation and obesity are potential treatable traits that warrant further investigation in clinical trials. Funding UK Research and Innovation and National Institute for Health Research