Quantum battery charging by non-equilibrium steady-state currents

We present an analysis of the availability and maximum extractable work of quantum batteries in the presence of charge and/or heat steady-state currents. Quantum batteries are modelled as non-interacting open quantum systems (mesoscopic systems) strongly coupled to two thermal and particle reservoirs within the framework of non-equilibrium Green's function theory in a steady-state regime. We found that the battery can be charged manifestly by a steady-state charge current compared to heat one, especially, in an off-resonant transport regime. It allows us to reliably access the performance of the quantum batteries in the high bias-charging regime.Comment: new Refs. adde

FDiBC: A Novel Fraud Detection Method in Bank Club based on Sliding Time and Scores Window

One of the recent strategies for increasing the customer’s loyalty in banking industry is the use of customers’ club system. In this system, customers receive scores on the basis of financial and club activities they are performing, and due to the achieved points, they get credits from the bank. In addition, by the advent of new technologies, fraud is growing in banking domain as well. Therefore, given the importance of financial activities in the customers’ club system, providing an efficient and applicable method for detecting fraud is highly important in these types of systems. In this paper, we propose a novel sliding time and scores window-based method, called FDiBC (Fraud Detection in Bank Club), to detect fraud in bank club. In FDiBC, firstly, based on each score obtained by customer members of bank club, 14 features are derived, then, based on all the scores of each customer member, five sliding time and scores window-based feature vectors are proposed. For generating training and test data set from the obtained scores of fraudster and common customers in the customers’ club system of a bank, a positive and a negative label are used, respectively. After generating training data set, learning is performed through two approaches: 1) clustering and binary classification with OCSVM method for positive data, i.e. fraudster customers, and 2) multi-class classification including SVM, C4.5, KNN, and Naïve Bayes methods. The results reveal that FDiBC has the ability to detect fraud with 78% accuracy and thus can be used in practice

Safe sex norm questionnaire for female sex workers:development and validation study in Iran

Objectives: The aim of the present study was to develop and validate a safe sex norm questionnaire as an appropriate instrument which would be adaptable to the female sex worker (FSW) population.Study design: A mixed method study.Methods: Appropriate content was prepared through a literature review. Content validation indices were assessed using interviews with content experts and lay experts. A conservative approach was used to assess the inter-rater agreement among the participants about the instrument relevance and clarity. The scale content validity index was computed using the average method. Non-parametric Mokken scale analysis was used for assessing scalability and unidimensionality of the questionnaire in a sample of 170 FSWs in Tehran. To evaluate the reliability and internal consistency of the questionnaire intra-class correlation and Cronbach's alpha were employed.Results: A list of 34 items was finalized, with subscales for actual behavioral norms and for perceived norms. The relevance of the actual and perceived norms subscales in the final questionnaire was higher than 96%; clarity of the subtests was 99% and higher. The comprehensiveness of the actual and perceived norms subscales was 85% for both. Mokken scale analysis showed that the two subscales were distinct constructs, and all items are good indicators for the constructs.Conclusion: Our findings support that the safe sex norm questionnaire is a valid and reliable measure that would be useful to harm reduction programs and help effective HIV prevention among female sex workers. (C) 2018 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.</p

An analytic review on impacts of conceptual map implicated in multimedia on social skills improvement of mentally retarded learners

Backgrounds and Objectives:The use of concept maps is one of the new educational approaches that is rooted in the constructivist approach. In constructivism, the importance of knowledge is emphasized by relating the learned information to the new one. In this relational view and based on the concept map approach, people search between previous and new learning, people make their own schemas or mind maps, and in new learning, these mind maps are extensively revised and reconstructed. Concept map is a tool for showing the relationships between concepts in a coherent and hierarchical way that facilitates meaningful learning, because in this method the concepts are not scattered components but are in the form of a network of relationships to each other. Concept maps are also effective in facilitating creative thinking due to their unique features. The present study describes effectiveness of conceptual map implicated through multimedia on social skills improvement among learners with mental retardation. Teaching on the basis of concept mapping known as an active method to teach social skills for learners with special learning needs (as mental retarded). Methods and Materials: Quasi-experimental research method is used with pretest-posttest instrument. Sample of the study is equal to society includes14 mild mental retarded students (aged 16-14 years). It is a researcher-made questionnaire measures learners with mental retardation social skills improvement included three components as interaction with others, social adaptive behavior and self-control. Questionnaires' Reliability estimated by Cronbach's alpha (0.80). Mann-Whitney U test used to analyses the data, compartments of the pre- post-test scores in experimental group after the intervention. The Wilcoxon Signed rank test with the effect size is also approached to data analyzing Findings: It is revealed that there is a significant difference in pre-test and posttest scores of students in different level of social skills. So implementation of concept mapping plus to using multimedia could enable mentally retarded students as it is suggested to construct their minding's as well improvement of their social skills. Conclusion: Learning to apply a concept map in the form of multimedia can improve the learning of subscales in the social skills subset, adaptive social behavior, improve the learning of social skills in the form of interaction with others, learn social skills in the form of self-control and keep components such as having clean your own desk, discussing your feelings and emotions, reacting appropriately to strangers, separating good and bad habits, and expressing happiness will be effective when you succeed in your control component. Experience of teaching with teacher-made concept map methods in combination with multimedia shows the effect of using active and modern methods in education for meaningful learning in children with mental disabilities, objectifying the teachings of students with mental disabilities with up-to-date and effective educational media such as photos, videos, animations and other educational software, providing educational resources required for social skills appropriate to the appropriate time conditions for children with mental disabilities and drawing maps to communicate between the main and secondary components of concepts related to social skills. Educational groups and organizations are recommended to pay attention to this group of students in developing and improving their learning

Implication of NMDA-NO pathway in the antidepressant-like effect of ellagic acid in male mice

Depression is one the common psychiatric disorders through the world. Nitric oxide (NO) and N-methyl-d-aspartate receptor (NMDA-R) are involved in the pathophysiology of depression. Previous studies have been reported various pharmacological properties for ellagic acid (EA). We aimed to evaluate possible involvement of NMDA-NO pathway in the antidepressant-like effect of EA. To do this, we used relevant behavioral tests to evaluate depressive-like behavior. In order to find effective and sub-effective doses of agents, mice treated with EA (6.25, 12.5, 25, 50 and 100 mg/kg), L-NAME (5 and 10 mg/kg), L-arg (25 and 50 mg/kg), NMDA (75 and 150 mg/kg) and ketamine (0.25 and 0.5 mg/kg). Furthermore, mice were treated with combination of sub-effective dose of EA plus sub-effective doses of L-NAME and/or ketamine as well as treated with effective dose of EA in combination of effective doses of L-arg and/or NMDA. Level of NO and gene expression of NR2A and NR2B subunits of NMDA-R were assessed in the hippocampus. Results showed that EA dose dependently provoked antidepressant-like effects and also decreased the hippocampal NO level as well as expression of NMDA-Rs. Co-administration of sub-effective doses of L-NAME or ketamine with sub-effective dose of EA potentiated the effect of EA on behaviors, NO level as well as NMDA-Rs gene expression in the hippocampus. However, co-treatment of effective dose of EA with effective doses of L-arg or NMDA mitigated effects of EA. In conclusion, our data suggested that NMDA-NO, partially at least, are involved in the antidepressant-like effect of EA

Plasma lipids and risk of aortic valve stenosis: a Mendelian randomization study

AIMS: Aortic valve stenosis is commonly considered a degenerative disorder with no recommended preventive intervention, with only valve replacement surgery or catheter intervention as treatment options. We sought to assess the causal association between exposure to lipid levels and risk of aortic stenosis. METHODS AND RESULTS: Causality of association was assessed using two-sample Mendelian randomization framework through different statistical methods. We retrieved summary estimations of 157 genetic variants that have been shown to be associated with plasma lipid levels in the Global Lipids Genetics Consortium that included 188 577 participants, mostly European ancestry, and genetic association with aortic stenosis as the main outcome from a total of 432 173 participants in the UK Biobank. Secondary negative control outcomes included aortic regurgitation and mitral regurgitation. The odds ratio for developing aortic stenosis per unit increase in lipid parameter was 1.52 [95% confidence interval (CI) 1.22-1.90; per 0.98 mmol/L] for low density lipoprotein (LDL)-cholesterol, 1.03 (95% CI 0.80-1.31; per 0.41 mmol/L) for high density lipoprotein (HDL)-cholesterol, and 1.38 (95% CI 0.92-2.07; per 1 mmol/L) for triglycerides. There was no evidence of a causal association between any of the lipid parameters and aortic or mitral regurgitation. CONCLUSION: Lifelong exposure to high LDL-cholesterol increases the risk of symptomatic aortic stenosis, suggesting that LDL-lowering treatment may be effective in its prevention

Stratification of diabetes in the context of comorbidities, using representation learning and topological data analysis

\ua9 2023, The Author(s). Diabetes is a heterogenous, multimorbid disorder with a large variation in manifestations, trajectories, and outcomes. The aim of this study is to validate a novel machine learning method for the phenotyping of diabetes in the context of comorbidities. Data from 9967 multimorbid patients with a new diagnosis of diabetes were extracted from Clinical Practice Research Datalink. First, using BEHRT (a transformer-based deep learning architecture), the embeddings corresponding to diabetes were learned. Next, topological data analysis (TDA) was carried out to test how different areas in high-dimensional manifold correspond to different risk profiles. The following endpoints were considered when profiling risk trajectories: major adverse cardiovascular events (MACE), coronary artery disease (CAD), stroke (CVA), heart failure (HF), renal failure (RF), diabetic neuropathy, peripheral arterial disease, reduced visual acuity and all-cause mortality. Kaplan Meier curves were plotted for each derived phenotype. Finally, we tested the performance of an established risk prediction model (QRISK) by adding TDA-derived features. We identified four subgroups of patients with diabetes and divergent comorbidity patterns differing in their risk of future cardiovascular, renal, and other microvascular outcomes. Phenotype 1 (young with chronic inflammatory conditions) and phenotype 2 (young with CAD) included relatively younger patients with diabetes compared to phenotypes 3 (older with hypertension and renal disease) and 4 (older with previous CVA), and those subgroups had a higher frequency of pre-existing cardio-renal diseases. Within ten years of follow-up, 2592 patients (26%) experienced MACE, 2515 patients (25%) died, and 2020 patients (20%) suffered RF. QRISK3 model’s AUC was augmented from 67.26% (CI 67.25–67.28%) to 67.67% (CI 67.66–67.69%) by adding specific TDA-derived phenotype and the distances to both extremities of the TDA graph improving its performance in the prediction of CV outcomes. We confirmed the importance of accounting for multimorbidity when risk stratifying heterogenous cohort of patients with new diagnosis of diabetes. Our unsupervised machine learning method improved the prediction of clinical outcomes