A prototype of an energy-efficient MAGLEV train : a step towards cleaner train transport

The magnetic levitation (MAGLEV) train uses magnetic field to suspend, guide, and propel vehicle onto the track. The MAGLEV train provides a sustainable and cleaner solution for train transportation by significantly reducing the energy usage and greenhouse gas emissions as compared to traditional train transportation systems. In this paper, we propose an advanced control mechanism using an Arduino microcontroller that selectively energizes the electromagnets in a MAGLEV train system to provide dynamic stability and energy efficiency. We also design the prototype of an energy-efficient MAGLEV train that leverages our proposed control mechanism. In our MAGLEV train prototype, the levitation is achieved by creating a repulsive magnetic field between the train and the track using magnets mounted on the top-side of the track and bottom-side of the vehicle. The propulsion is performed by creating a repulsive magnetic field between the permanent magnets attached on the sides of the vehicle and electromagnets mounted at the center of the track using electrodynamic suspension (EDS). The electromagnets are energized via a control mechanism that is applied through an Arduino microcontroller. The Arduino microcontroller is programmed in such a way to propel and guide the vehicle onto the track by appropriate switching of the electromagnets. We use an infrared-based remote-control device for controlling the power, speed, and direction of the vehicle in both the forward and the backward direction. The proposed MAGLEV train control mechanism is novel, and according to the best of our knowledge is the first study of its kind that uses an Arduino-based microcontroller system for control mechanism. Experimental results illustrate that the designed prototype consumes only 144 W-hour (Wh) of energy as compared to a conventionally designed MAGLEV train prototype that consumes 1200 Wh. Results reveal that our proposed control mechanism and prototype model can reduce the total power consumption by 8.3 x as compared to the traditional MAGLEV train prototype, and can be applied to practical MAGLEV trains with necessary modifications. Thus, our proposed prototype and control mechanism serves as a first step towards cleaner engineering of train transportation systems

Towards better guidance on caseload thresholds to promote positive tuberculosis treatment outcomes:a cohort study

BACKGROUND: In low-incidence countries, clinical experience of tuberculosis is becoming more limited, with potential consequences for patient outcomes. In 2007, the Department of Health released a guidance 'toolkit' recommending that tuberculosis patients in England should not be solely managed by clinicians who see fewer than 10 cases per year. This caseload threshold was established to try to improve treatment outcomes and reduce transmission, but was not evidence based. We aimed to assess the association between clinician or hospital caseload and treatment outcomes, as well as the relative suitability of making recommendations using each caseload parameter. METHODS: Demographic and clinical data for tuberculosis cases in England notified to Public Health England's Enhanced Tuberculosis Surveillance system between 2003 and 2012 were extracted. Mean clinician and hospital caseload over the past 3 years were calculated and treatment outcomes grouped into good/neutral and unfavourable. Caseloads over time and their relationship with outcomes were described and analysed using random effects logistic regression, adjusted for clustering. RESULTS: In a fully adjusted multivariable model (34,707 cases)there was very strong evidence that management of tuberculosis by clinicians with fewer than 10 cases per year was associated with greater odds of an unfavourable outcome compared to clinicians who managed greater numbers of cases (cluster-specific odds ratio, 1.14; 95 % confidence interval, 1.05-1.25; P = 0.002). The relationship between hospital caseload and treatment outcomes was more complex and modified by a patient's place of birth and ethnicity. The clinician caseload association held after adjustment for hospital caseload and when the clinician caseload threshold was reduced down to one. CONCLUSIONS: Despite the relative ease of making recommendations at the hospital level and the greater reliability of recorded hospital versus named clinician, our results suggest that clinician caseload thresholds are more suitable for clinical guidance. The current recommended clinician caseload threshold is functional. Sensitivity analyses reducing the threshold indicated that clinical experience is pertinent even at very low average caseloads, which is encouraging for low burden settings

Type 1 diabetes mellitus induces structural changes and molecular remodelling in the rat kidney

There is much evidence that diabetes mellitus (DM) –induced hyperglycemia (HG) is responsible for kidney failure or nephropathy leading to cardiovascular complications. Cellular and molecular mechanism(s) whereby DM can damage the kidney is still not fully understood. This study investigated the effect of streptozotocin (STZ)-induced diabetes (T1DM) on the structure and associated molecular alterations of the isolated rat left kidney following 2 and 4 months of the disorder compared to the respective age-matched controls. The results revealed hypertrophy and general disorganized architecture of the kidney characterized by expansion in glomerular borders, tubular atrophy and increased vacuolization of renal tubular epithelial cells in the diabetic groups compared to controls. Electron microscopic analysis revealed ultrastructural alterations in the left kidney highlighted by an increase in glomerular basement membrane width. In addition, increased caspase-3 immuno-reactivity was observed in the kidney of T1DM animals compared to age-matched controls. These structural changes were associated with elevated extracellular matrix (ECM) deposition and consequently, altered gene expression profile of ECM key components, together with elevated levels of key mediators (MMP9, integrin 5α, TIMP4, CTGF, vimentin) and reduced expressions of Cx43 and MMP2 of the ECM. Marked hypertrophy of the kidney was highlighted by increased atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP) gene expression. These changes also correlated with increased TGFβ1 activity, gene expression in the left kidney and elevated active TGFβ1 in plasma of T1DM rats compared to control. The results clearly demonstrated that TIDM could elicit severe structural changes and alteration in biochemical markers (remodeling) in the kidney leading to diabetic nephropathy (DN)

Impact of unstable environment on the brain drain of highly skilled professionals, healthcare workers, researchers, and research productivity in Pakistan

Background: The geo-strategic position of Pakistan on the world map is incredibly important and idyllic as the country is considered the gateway to central Asia. Pakistan has faced political instability for the last three decades, causing a brain drain and adversely affecting socioeconomic growth. This study aims to investigate the impact of an unstable environment on the brain drain of highly skilled professionals, healthcare workers, researchers, and research productivity in Pakistan from January 2000 to December 2022. Material and Methods: The data were recorded from the World Bank, the Higher Education Commission (HEC) Pakistan, the Pakistan Medical and Dental Council (PMDC), the Bureau of Emigration and Overseas Employment (BEOS), Pakistan, Academic Ranking of World Universities (ARWU), and Web of Science Clarivate Analytics. Initially, 32 documents were selected in this study, and finally, eight fact sheets, official government websites, and international organizations were included. Results: The result revealed that due to political instability, in 2022 about 832,339 highly qualified and accomplished experts headed abroad, among them 17976 (2.15%) were highly qualified and 20865 (2.50%) were highly competent professionals. These include accountants 7197 (0.86%), engineers 6,093 (0.73%), agricultural experts 3,110 (0.37%), doctors 2,464 (0.29%), computer experts 2,147 (0.25%), nurses and paramedics 1768 (0.21%), technicians 23347 (2.80%), electricians 20322 (2.44%), and schools and university faculty 1004 (0.12%). Pakistan has a total of 380 Higher Education Commission-indexed academic journals, among them 11 (2.89%) academic journals were indexed in the Web of Science and 23 journals were placed in the Web of Science emerging indexing. Among these journals, only one journal surpassed the impact factor of more than 2.0. The quartile ranking of Pakistani journals is 01 journal in Q2; 02 in Q3; and the remaining 08 journals in Q4. From August 1947 to December 2022, Pakistan produced a total of 259249 research articles, and from January 2000 to December 2022, the number of articles published was 248457 (95.83%). Since the last 22 years, the trend of research publications was continuously increased; however, the rising trend decreased in 2022 with a declined rate of 1263 (3.42%). Conclusion: The unstable sociopolitical environment in Pakistan caused a brain drain of highly qualified and skilled professionals and impaired the global standing of universities, academic journals, and research productivity in Pakistan. Pakistan must resolve the instability and establish sustainable policies to minimize the brain drain of highly qualified and skilled experts and convalesce their academic institutes and their research productivity for the development of the nation

Evaluation of the training program to train HIV treatment center staff in Pakistan

Introduction In Pakistan, HIV training programs, especially for health professionals working in HIV treatment centers, are limited. Consequently, there is little data about HIV awareness among physicians and allied health workers and how it may affect their care for people living with HIV (PLWH). Recently, the Global Fund to Fight AIDS, Tuberculosis, and Malaria (GFATM) grant Principal Recipient UNDP engaged an NGO experienced in HIV/AIDS training, on a competitive basis, to develop a training manual and conduct training of all categories of HIV treatment centers staff. The goal of this study was to assess the training program\u27s influence on trainees\u27 (both physicians and allied health staff) knowledge and abilities and describe its major lessons. Methodology This was a one-group pre-post test study, carried out between January 17 and February 22, 2023. The study was carried out in three phases. In the first phase, a team of experts developed an antiretroviral treatment (ART) training manual. In the second phase, 9- and three-day training workshops were conducted in six different cities of Pakistan, which were attended by physicians and allied health staff working in different HIV treatment centers across Pakistan. The workshops had plenary lectures, discussions, role plays, video cases, and case studies. In the third phase, a quiz, comprising multiple/best choice questions (MCQs/BCQs) and true and false questions, was administered before (pre) and after the workshop (post) to assess the impact of these training sessions in enhancing the level of HIV knowledge, especially related to ART. The workshop was attended by a total of 256 health workers from different cities in Pakistan. The participants had backgrounds in medical science, psychology, laboratory science, nursing, and computer science. Pre-and post-test responses were statistically analyzed to determine the impact of the training program on participant\u27s knowledge. For this, the Shapiro-Wilk test was applied to test data normality, followed by the application of paired t-test or Wilcoxon Signed Rank Test for normally and non-normally distributed data, respectively. Finally, a chi-square test was applied to examine the significant (p\u3c0.05) association between training workshops and improvement in the participant\u27s level of understanding of HIV. In all statistical tests, p\u3c0.05 was considered significant. Results The results from our study showed that before the training session, both physicians and allied staff possessed limited knowledge about HIV-related domains. After the workshops, participants from all cities demonstrated a uniform enhancement of knowledge related to different HIV-related domains, evident from the improvement in post-test scores compared to pre-test scores (p\u3c0.0001). The chi-square test showed a significant association between training workshops and improvement in the participant\u27s level of understanding about HIV (p-values for BCQ, MCQ, and true and false: 0.001, 0.0047, and 0.0024, respectively). Conclusions Pre- and post-test evaluation provides an objective, data-driven method for measuring the impact of educational interventions in improving healthcare workers\u27 awareness about HIV. The results emphasize the role of continuous workshops and training programs in enhancing the knowledge and understanding of healthcare and allied health workers regarding HIV

Sex-disparities in chest pain workup: a retrospective cohort review of a university based clinical decision pathway

Abstract Background Females have historically lower rates of cardiovascular testing when compared to males. Clinical decision pathways (CDP) that utilize standardized risk-stratification methods may balance this disparity. We sought to determine whether clinical decision pathways could minimize sex-based differences in the non-invasive workup of chest pain in the emergency department (ED). Moreover, we evaluated whether the HEART score would minimize sex-based differences in risk-stratification. Methods We conducted a retrospective cohort review of adult ED encounters for chest pain where CDP was employed. Primary outcome was any occurrence of non-invasive imaging (coronary CTA, stress imaging), invasive testing, intervention (PCI or CABG), or death. Secondary outcomes were 30-day major adverse cardiac events (MACE). We stratified HEART scores and primary/secondary outcomes by sex. Results A total of 1078 charts met criteria for review. Mean age at presentation was 59 years. Females represented 47% of the population. Low, intermediate, and high-risk patients as determined by the HEART score were 17%, 65%, and 18% of the population, respectively, without any significant differences between males and females. Non-invasive testing was similar between males and females when stratified by risk. Males categorized as high risk underwent more coronary angiogram (33% vs. 16%, p = 0.01) and PCI (18% vs. 8%, p = 0.04) than high risk females, but this was not seen in patients categorized as low or intermediate risk. Males experienced more MACE than females (8% vs. 3%, p = 0.001). Conclusions We identified no sex-based differences in risk-stratification or non-invasive testing when the CDP was used. High risk males, however, underwent more coronary angiogram and PCI than high risk females, and consequently males experienced more overall MACE than females. This disparity may be explained by sex-based differences in the pathophysiology driving each patient’s presentation

A Machine Learning and Blockchain Based Efficient Fraud Detection Mechanism

In this paper, we address the problems of fraud and anomalies in the Bitcoin network. These are common problems in e-banking and online transactions. However, as the financial sector evolves, so do the methods for fraud and anomalies. Moreover, blockchain technology is being introduced as the most secure method integrated into finance. However, along with these advanced technologies, many frauds are also increasing every year. Therefore, we propose a secure fraud detection model based on machine learning and blockchain. There are two machine learning algorithms—XGboost and random forest (RF)—used for transaction classification. The machine learning techniques train the dataset based on the fraudulent and integrated transaction patterns and predict the new incoming transactions. The blockchain technology is integrated with machine learning algorithms to detect fraudulent transactions in the Bitcoin network. In the proposed model, XGboost and random forest (RF) algorithms are used to classify transactions and predict transaction patterns. We also calculate the precision and AUC of the models to measure the accuracy. A security analysis of the proposed smart contract is also performed to show the robustness of our system. In addition, an attacker model is also proposed to protect the proposed system from attacks and vulnerabilities

Algae and Hydrophytes as Potential Plants for Bioremediation of Heavy Metals from Industrial Wastewater

Aquatic bodies contaminated by heavy metals (HMs) are one of the leading issues due to rapidly growing industries. The remediation of using algae and hydrophytes acts as an environmentally friendly and cost effective. This study was performed to investigate the pollution load, especially HMs, in the wastewater of the Gadoon Industrial Estate and to utilize the hydrophytes (Typha latifolia (TL) and Eicchornia crassipes (EI)) and algae (Zygnema pectiantum (ZP) and Spyrogyra species (SS)) as bioremediators. The wastewater was obtained and assessed for physiochemical parameters before treating with the selected species. The pot experiment was performed for 40 days. Then the wastewater samples and selected species were obtained from each pot to analyze the metal removal efficiency and assess for metal concentrations using atomic absorption spectrophotometry. The dissolved oxygen (DO; 114 mg/L), total suspended solids (TSS; 89.30 mg/L), electrical conductivity (EC; 6.35 mS/cm), chemical oxygen demand (COD) (236 mg/L), biological oxygen demand (BOD; 143 mg/L), and total dissolved solids (TDS; 559.67 mg/L), pH (6.85) were analyzed. The HMs were noted as Zn (5.73 mg/L) and Cu (7.13 mg/L). The wastewater was then treated with the species, and significant reductions were detected in physicochemical characteristics of the wastewater such as DO (13.15–62.20%), TSS (9.18–67.99%), EC (74.01–91.18%), COD (25.84–73.30%), BOD (21.67–73.42%), and TDS (14.02–95.93%). The hydrophytes and algae removed up to 82.19% of the Zn and 85.13% of the Cu from the wastewater. The study revealed that the hydrophytes and algae significantly decreased the HM levels in the wastewater (p ≤ 0.05). The study found TL, EI, ZP, and SS as the best hyper accumulative species for Zn and Cu removal from wastewater. The HMs were removed in the order of Cu > Zn. The most efficient removal for Cu was found by Typha latifolia and Zn by Zygnema pectiantum. It was concluded that bioremediation is an environmentally friendly and cost-effective technique that can be used for the treatment of wastewater due to the efficiency of algae and hydrophytes species in terms of HM removal