Analysis of the benefits of Regenerative Braking in Urban Railway Traction System

Increasing environmental awareness and the requirement for lower project costs is forcing transit system suppliers to think more innovatively and engineer more accurately to strengthen their competitive edge. Of late, clients more often desire a system that is optimized to minimize the energy consumed during operation; a requirement that is often imposed upon transit system suppliers through financially binding energy commitments. Electric rail transit systems are large consumers of energy. In trains with regenerative braking capability, a fraction of the energy used to power a train is regenerated during braking. This regenerated energy, if recuperated and reused, can result in economic as well as technical merits. One of the ways that this could be achieved is with the implementation of Wayside Energy Storage System (WESS). In addition to reducing energy consumption, energy storage systems can be operated to regulate system voltage levels, provide backup power in the event of a utility power outage, and relieve demand on the utility during the costlier operating periods. This dissertation presents a stacked-benefits analysis of regenerative energy and wayside energy storage for New York City Transit (NYCT), and examines how the electric utility and the transit system can collaborate to gain the best value of energy storage

A Secure Healthcare 5.0 System Based on Blockchain Technology Entangled with Federated Learning Technique

In recent years, the global Internet of Medical Things (IoMT) industry has evolved at a tremendous speed. Security and privacy are key concerns on the IoMT, owing to the huge scale and deployment of IoMT networks. Machine learning (ML) and blockchain (BC) technologies have significantly enhanced the capabilities and facilities of healthcare 5.0, spawning a new area known as "Smart Healthcare." By identifying concerns early, a smart healthcare system can help avoid long-term damage. This will enhance the quality of life for patients while reducing their stress and healthcare costs. The IoMT enables a range of functionalities in the field of information technology, one of which is smart and interactive health care. However, combining medical data into a single storage location to train a powerful machine learning model raises concerns about privacy, ownership, and compliance with greater concentration. Federated learning (FL) overcomes the preceding difficulties by utilizing a centralized aggregate server to disseminate a global learning model. Simultaneously, the local participant keeps control of patient information, assuring data confidentiality and security. This article conducts a comprehensive analysis of the findings on blockchain technology entangled with federated learning in healthcare. 5.0. The purpose of this study is to construct a secure health monitoring system in healthcare 5.0 by utilizing a blockchain technology and Intrusion Detection System (IDS) to detect any malicious activity in a healthcare network and enables physicians to monitor patients through medical sensors and take necessary measures periodically by predicting diseases.Comment: 20 pages, 6 tables, 3 figure

Big data assisted CRAN enabled 5G SON architecture

The recent development of Big Data, Internet of Things (IoT) and 5G network technology offers a plethora of opportunities to the IT industry and mobile network operators. 5G cellular technology promises to offer connectivity to massive numbers of IoT devices while meeting low-latency data transmission requirements. A deficiency of the current 4G networks is that the data from IoT devices and mobile nodes are merely passed on to the cloud and the communication infrastructure does not play a part in data analysis. Instead of only passing data on to the cloud, the system could also contribute to data analysis and decision-making. In this work, a Big Data driven self-optimized 5G network design is proposed using the knowledge of emerging technologies CRAN, NVF and SDN. Also, some technical impediments in 5G network optimization are discussed. A case study is presented to demonstrate the assistance of Big Data in solving the resource allocation problem

A Novel Dynamic Appliance Clustering Scheme in a Community Home Energy Management System for Improved Stability and Resiliency of Microgrids

Power scheduling of domestic appliances is a vital preference for bridging the gap between demand and generation of electricity in a microgrid. For a stable microgrid, an acceptable mechanism must reduce the peak to average ratio (PAR) of power demand with supplementary benefits for consumers as reduced electricity charges. Recent studies have focused on PAR and cost reduction for a small consumer population. Furthermore, researchers have mainly considered homogeneous consumer loads. This study focuses on residential power scheduling for electricity cost reduction for consumers and load profile PAR curtailment for a relatively large consumer population with non-homogeneous loads. A sample population of 1000 consumers from various classes of society is considered. The proposed dynamic clustered community home energy management system (DCCHEMS) allows the clustering of appliances based on time overlap criteria. Comparatively flatter power demand is attained by utilizing the clustered appliances in conjunction with particle swarm optimization under the influence of user-defined constraints. Modified inclined block rates with real-time electricity pricing strategies are deployed to minimize the electricity costs. DCCHEMS achieved higher efficiency rates in contrast to the traditional non-clustering and static clustering optimization schemes. An improvement of 21% in peak to average ratio, 4% in cost reduction, and 19% in variance to mean ratio is obtained

Efficacy and Safety of Varenicline for Smoking Cessation in Schizophrenia: A Meta-Analysis

Objective: Smoking represents a major public health problem among patients with schizophrenia. To this end, some studies have investigated the efficacy of varenicline for facilitating smoking cessation in schizophrenia patients. The present review seeks to synthesize the results of these studies as well as document the reported side effects of using this medication. Methods: An electronic search was performed using five major databases: PubMed, Scopus, EMBASE, Web of Science, and Cochrane Library. Included in the current analysis were randomized clinical trials (RCTs) that have investigated the effect of varenicline in promoting smoking cessation in patients with schizophrenia. Risk of bias among included RCTs was assessed using the Cochrane Collaboration’s quality assessment tool. Results: Among the 828 screened articles, only four RCTs, which involved 239 participants, were eligible for meta-analysis. In patients with schizophrenia, varenicline treatment when compared to placebo significantly reduced the number of cigarettes consumed per day [SMD (95% CI) = 0.89(0.57–1.22)] and expired carbon monoxide levels [SMD (95% CI) = 0.50 (0.06–0.94)] respectively. Conclusion: Despite a limited number of studies included in the meta-analysis, our results suggest that varenicline is an effective and safe drug to assist smoking cessation in patients with schizophrenia. Future large-scale well-designed RCTs are required to validate these findings

Chitosan-based bio-composite modified with thiocarbamate moiety for decontamination of cations from the aqueous media

Herein, we report the development of chitosan (CH)-based bio-composite modified with acrylonitrile (AN) in the presence of carbon disulfide. The current work aimed to increase the Lewis basic centers on the polymeric backbone using single-step three-components (chitosan, carbon disulfide, and acrylonitrile) reaction. For a said purpose, the thiocarbamate moiety was attached to the pendant functional amine (NH2) of chitosan. Both the pristine CH and modified CH-AN bio-composites were first characterized using numerous analytical and imaging techniques, including 13C-NMR (solid-form), Fourier-transform infrared spectroscopy (FTIR), elemental investigation, thermogravimetric analysis, and scanning electron microscopy (SEM). Finally, the modified bio-composite (CH-AN) was deployed for the decontamination of cations from the aqueous media. The sorption ability of the CH-AN bio-composite was evaluated by applying it to lead and copper-containing aqueous solution. The chitosan-based CH-AN bio-composite exhibited greater sorption capacity for lead (2.54 mmol g−1) and copper (2.02 mmol g−1) than precursor chitosan from aqueous solution based on Langmuir sorption isotherm. The experimental findings fitted better to Langmuir model than Temkin and Freundlich isotherms using linear regression method. Different linearization of Langmuir model showed different error functions and isothermal parameters. The nonlinear regression analysis showed lower values of error functions as compared with linear regression analysis. The chitosan with thiocarbamate group is an outstanding material for the decontamination of toxic elements from the aqueous environment251226CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQNão temThis research was funded by the academy of sciences for developing world (TWAS) and The Brazilian National Council for Scientific and Technological Development (CNPq) fellowship to AK. The APC was funded by MDPI, St. Alban-Anlage 66, 4052 Basel, Switzerlan

Ethnoveterinary Study of Medicinal Plants in a Tribal Society of Sulaiman Range

The aims of the present study were (i) to document ethnoveterinary plants and their formulation techniques in an unexplored region of Pakistan and (ii) to select candidate medicinal plants with high consensus factor and fidelity value for further in vitro investigation. A total of 60 informants were interviewed using semistructured questionnaire. A total of 41 plants belonging to 30 families were used to treat livestock ailments in study area. Mostly leaves (47%) were used in recipes formulation mostly in the form of decoction. Gastrointestinal infections were found more common and majority of the plants were used against cow (31) and buffaloes (24) ailments. Recovery time of majority of the recipes was three to four days. Informant consensus factor (Fic) results have shown a high degree of consensus for gastrointestinal, respiratory, and reproductive (0.95 each) ailments. Fidelity level (FL) results showed that Asparagus gracilis ranked first with FL value 93% followed by Rumex hastatus ranked second (91%) and Tinospora cordifolia ranked third (90%). Aged farmers and nomads had more traditional knowledge as compared to younger ones. Plants with high Fic and FL values could be further investigated in vitro for the search of some novel bioactive compounds and young generation should be educated regarding ethnoveterinary practices

Engineering functionalized chitosan-based sorbent material : characterization and sorption of toxic elements

The present study reports the engineering of functionalized chitosan (CH)-based biosorbent material. Herein, a two-step reaction was performed to chemically modify the CH using 1,4-bis(3-aminopropyl) piperazine to incorporate nitrogen basic centers for cations sorption from the aqueous environment. The resultant functionalized chitosan-based sorbent material was designated as CH-ANP and characterized using various analytical techniques, including elemental analysis, Fourier-transform infrared spectroscopy (FTIR), 13C NMR (in solid-state), X-ray diffraction, and thermal analysis. Then, the newly engineered CH-ANP was employed for the removal of copper, lead, and cadmium in the aqueous medium. Langmuir sorption isotherm analysis revealed that the highest sorption abilities achieved were 2.82, 1.96, and 1.60 mmol g−1 for copper, cadmium, and lead, respectively. Linear and nonlinear regression methods were deployed on the sorption data to study the behavior of the Langmuir, the Freundlich, and the Temkin sorption isotherms. Among the four different forms, the Langmuir isotherm type 1 fit well to the experimental data as compared to the other models. It also showed the lowest values of error, and a higher correlation coefficient than the Freundlich and Temkin models; thus it was the best fit with the experimental data compared to the latter two models. In conclusion, the findings suggest that chemically modified novel materials with enhanced Lewis basic centers are useful and promising candidates for the sorption of various toxic cations in aqueous solution9235138CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQThis research was funded by The acadmey of sciences for developing world (TWAS) and The Brazilian National Council for Scientific and Technological Development (CNPq) fellowship to AK. The APC was funded by MDPI, St. Alban-Anlage 66, 4052 Basel, Switzerlan

Cognitive Behavioral Therapy versus Eye Movement Desensitization and Reprocessing in Patients with Posttraumatic Stress Disorder: Systematic Review and Meta-analysis of Randomized Clinical Trials

Background Post-traumatic stress disorder (PTSD) is prevalent in children, adolescents and adults. It can occur alone or in comorbidity with other disorders. A broad range of psychotherapies such as cognitive behavioral therapy (CBT) and eye movement desensitization and reprocessing (EMDR) have been developed for the treatment of PTSD. Aim Through quantitative meta-analysis, we aimed to compare the efficacy of CBT and EMDR: (i) relieving the post-traumatic symptoms, and (ii) alleviating anxiety and depression, in patients with PTSD. Methods We systematically searched EMBASE, Medline and Cochrane central register of controlled trials (CENTRAL) for articles published between 1999 and December 2017. Randomized clinical trials (RCTs) that compare CBT and EMDR in PTSD patients were included for quantitative meta-analysis using RevMan Version 5. Results Fourteen studies out of 714 were finally eligible. Meta-analysis of 11 studies (n = 547) showed that EMDR is better than CBT in reducing post-traumatic symptoms [SDM (95% CI) = -0.43 (-0.73 – -0.12), p = 0.006]. However, meta-analysis of four studies (n = 186) at three-month follow-up revealed no statistically significant difference [SDM (95% CI) = -0.21 (-0.50 – 0.08), p = 0.15]. The EMDR was also better than CBT in reducing anxiety [SDM (95% CI) = -0.71 (-1.21 – -0.21), p = 0.005]. Unfortunately, there was no difference between CBT and EMDR in reducing depression [SDM (95% CI) = -0.21 (-0.44 – 0.02), p = 0.08]. Conclusion The results of this meta-analysis suggested that EMDR is better than CBT in reducing post-traumatic symptoms and anxiety. However, there was no difference reported in reducing depression. Large population randomized trials with longer follow-up are recommended to build conclusive evidence