Electrical and Electronic Waste Management–A Case Study in University of Duhok, Iraq

The aim of this paper is to estimate the perception, knowledge and attitude of the households towards electrical and electronic equipment waste (e-waste) management in Duhok city, Iraq. It also tried to identify current e-waste management practiced by households in Duhok. It has been found in this study that much of the electrical and electronic equipment was updated within two thirds of their designed lifetime. Most of the respondents informed that they just threw their e-waste to the waste bin. It can be concluded that all stakeholders of e-waste management, from the government and nongovernmental sectors should consider shifting the management options towards the top of the waste management hierarchy (prevention and waste minimization) by substituting the hazardous materials in e-waste and encouraging redesign of equipment for a better control of the negative impacts of e-waste. Keywords: e-waste management, awareness and attitude, product life time, updating time, deposit and disposa

Screening to Determine Prevalence of β-Thalassemia and Iron Deficiency Anemia Among Medical Students

According to the Thalassemia Federation of Pakistan, the mostly inherited disorder in Pakistan is β-thalassemia, which is characterized by a deficient, abnormal, or lack of β-globin chain synthesis and has a prevalence of 6%. The only method of controlling and preventing β-thalassemia is to increase awareness among students. This was an observational study using a random sampling technique. The Dow-Thalassemia awareness program recruited 915 medical students from the Dow Medical College (DMC) and Sindh Medical College (SMC) to voluntarily donate blood samples, which were analyzed by the naked eye single tube red cell osmotic fragility test (NESTROFT) and complete blood count and results were confirmed by high-performance liquid chromatography and analyzed using the NESTROFT. The samples were collected in 2012-2013. A total of 915 samples, out of these 390 samples, 390/915 (42.6%) samples were positive and complete blood count found 282 (72.3%) were positive for iron deficiency anemia. The remaining 108/390 (27.6%) were confirmed by high-performance liquid chromatography. Only 2.4 % subjects were positive for the β-thalassemia trait. Of 915 students, 57.4% of students were healthy, 39.2% had iron deficiency anemia, and 2.4% were carriers of the β-thalassemia trait. The overall prevalence of β-thalassemia was 38/915 (4.1%), which was lower than observed in previous studies. This study also demonstrated the NESTROFT can be used as a primary method of screening out healthy individuals, where approximately 50% require further screening for β-thalassemi

Artificially remediated plants impact soil physiochemical properties along the riparian zones of the three gorges dam in China

River ecosystem biodiversity and biogeochemical processes are shaped largely by riverside vegetation and soil. Moreover, river ecosystems provide ecological services influenced by the surrounding vegetation and soil interactions. However, the mechanisms by which artificially remediated plants (ARPs) and riparian soil interact to provide these benefits are still unclear among various ARPs. This study fills this gap and examines the impact of ARPs along the riparian zones of Three Gorges Dam (TGD) in Chongqing City, China. We sampled four varieties of ARPs from the Ruxi River Basin in the TGD. These varieties included Cynodon dactylon, Hemarthria altissima, Taxodium disticum, and Salix mastudana. Our results indicated substantial changes in soil physicochemical parameters. Comparably, T. distigum contains significantly higher soil chemical contents. Interestingly, principal component analysis explained almost 100% of the variance for all plant species in this study. Moreover, different vegetation types and soil chemical properties were positively correlated using Pearson correlation analysis (p < 0.05). Furthermore, all plant species exhibited strong negative correlations with physical characteristics (up to r = −1.00). Specifically, these mechanisms explain the interactions between ARPs and soil from riparian areas in the TGD. Hence, this study may facilitate ecological restoration and land management in degraded riparian areas

Article Review on World Bank Report, Optimal Design for a Minimum Wage Policy in Malaysia

There are many pros and cons with the implementation of minimum wage in Malaysia, since it is the first time. This article review is to analyze the World Bank report on Malaysian minimum wage policy that will be implemented in 2013. There are strength and weakness on the report. Moreover the review will also be analyzed from Islamic perspective since majority population in Malaysia is Muslim

Exploring the application of ICTs in decarbonizing the agriculture supply chain: a literature review and research agenda

The contemporary agricultural supply chain necessitates the integration of information and communication technologies to effectively mitigate the multifaceted challenges posed by climate change and rising global demand for food products. Furthermore, recent developments in information and communication technologies, such as blockchain, big data analytics, the internet of things, artificial intelligence, cloud computing, etc., have made this transformation possible. Each of these technologies plays a particular role in enabling the agriculture supply chain ecosystem to be intelligent enough to handle today's world's challenges. Thus, this paper reviews the crucial information and communication technologies-enabled agriculture supply chains to understand their potential uses and contemporary developments. The review is supported by 57 research papers from the Scopus database. Five research areas analyze the applications of the technology reviewed in the agriculture supply chain: food safety and traceability, security and information system management, wasting food, supervision and tracking, agricultural businesses and decision-making, and other applications not explicitly related to the agriculture supply chain. The study also emphasizes how information and communication technologies can help agriculture supply chains and promote agriculture supply chain decarbonization. An information and communication technologies application framework for a decarbonized agriculture supply chain is suggested based on the research's findings. The framework identifies the contribution of information and communication technologies to decision-making in agriculture supply chains. The review also offers guidelines to academics, policymakers, and practitioners on managing agriculture supply chains successfully for enhanced agricultural productivity and decarbonization

Benzimidazole containing acetamide derivatives attenuate neuroinflammation and oxidative stress in ethanol-induced neurodegeneration

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Oxidative stress-induced neuroinflammation is the prominent feature of neurodegenerative disorders, and is characterized by a gradual decline of structure and function of neurons. Many biochemical events emerge thanks to the result of this neurodegeneration, and ultimately provoke neuroinflammation, activation of microglia, and oxidative stress, leading to neuronal death. This cascade not only explains the complexity of events taking place across different stages, but also depicts the need for more effective therapeutic agents. The present study was designed to investigate the neuroprotective effects of newly synthesized benzimidazole containing acetamide derivatives, 3a (2-(4-methoxyanilino)-N-[1-(4-methylbenzene-1-sulfonyl)-1H-benzimidazol-2-yl] acetamide) and 3b (2-(Dodecylamino)-N-[1-(4-methylbenzene-1-sulfonyl)-1H-benzimidazol-2-yl] acetamide) against ethanol-induced neurodegeneration in the rat model. Both derivatives were characterized spectroscopically by proton NMR (1H-NMR) and carbon-13 NMR (13C-NMR) and evaluated for neuroprotective potential using different pharmacological approaches. In vivo experiments demonstrated that ethanol triggered neurodegeneration characterized by impaired antioxidant enzymes and elevated oxidative stress. Furthermore, ethanol administration induced neuroinflammation, as demonstrated by elevated expression of tumor necrotic factor (TNF-α), nuclear factor κB (NF-κB), cyclooxygenase-2 (COX2), and ionized calcium-binding adapter molecule-1 (Iba-1), which was further validated by enzyme-linked immunosorbent assay (ELISA). Treatment with 3a and 3b ameliorated the ethanol-induced oxidative stress, neuroinflammation, and memory impairment. The affinity of synthesized derivatives towards various receptors involved in neurodegeneration was assessed through docking analysis. The versatile nature of benzimidazole nucleus and its affinity toward several receptors suggested that it could be a multistep targeting neuroprotectant. As repetitive clinical trials of neuroprotectants targeting a single step of the pathological process have failed previously, our results suggested that a neuroprotective strategy of acting at different stages may be more advantageous to intervene in the vicious cycles of neuroinflammation

Novel Internet of Things based approach toward diabetes prediction using deep learning models

The integration of the Internet of Things with machine learning in different disciplines has benefited from recent technological advancements. In medical IoT, the fusion of these two disciplines can be extremely beneficial as it allows the creation of a receptive and interconnected environment and offers a variety of services to medical professionals and patients. Doctors can make early decisions to save a patient's life when disease forecasts are made early. IoT sensor captures the data from the patients, and machine learning techniques are used to analyze the data and predict the presence of the fatal disease i.e., diabetes. The goal of this research is to make a smart patient's health monitoring system based on machine learning that helps to detect the presence of a chronic disease in patient early and accurately. For the implementation, the diabetic dataset has been used. In order to detect the presence of the fatal disease, six different machine learning techniques are used i.e., Support Vector Machine (SVM), Logistic Regression, Artificial Neural Network (ANN), Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM). The performance of the proposed model is evaluated by using four evaluation metrics i.e., accuracy, precision, recall, and F1-Score. The RNN outperformed remaining algorithms in terms of accuracy (81%), precision (75%), and F1-Score (65%). However, the recall (56%) for ANN was higher as compared to SVM and logistic regression, CNN, RNN, and LSTM. With the help of this proposed patient's health monitoring system, doctors will be able to diagnose the presence of the disease earlier

Integrating humanities in healthcare: a mixed-methods study for development and testing of a humanities curriculum for front-line health workers in Karachi, Pakistan

Lady health workers (LHWs) provide lifesaving maternal and child health services to >60% of Pakistan’s population but are poorly compensated and overburdened. Moreover, LHWs’ training does not incorporate efforts to nurture attributes necessary for equitable and holistic healthcare delivery. We developed an interdisciplinary humanities curriculum, deriving its strengths from local art and literature, to enhance character virtues such as empathy and connection, interpersonal communication skills, compassion and purpose among LHWs. We tested the curriculum’s feasibility and impact to enhance character strengths among LHWs. We conducted a multiphase mixed-methods pilot study in two towns of Karachi, Pakistan. We delivered the humanities curriculum to 48 LHWs via 12 weekly sessions, from 15 June to 2 September 2021. We developed a multiconstruct character strength survey that was administered preintervention and postintervention to assess the impact of the training. In-depth interviews were conducted with a subset of randomly selected participating LHWs. Of 48 participants, 47 (98%) completed the training, and 34 (71%) attended all 12 sessions. Scores for all outcomes increased between baseline and endline, with highest increase (10.0 points, 95% CI 2.91 to 17.02; p=0.006) observed for empathy/connection. LHWs provided positive feedback on the training and its impact in terms of improving their confidence, empathy/connection and ability to communicate with clients. Participants also rated the sessions highly in terms of the content’s usefulness (mean: 9.7/10; SD: 0.16), the success of the sessions (mean: 9.7/10; SD: 0.17) and overall satisfaction (mean: 8.2/10; SD: 3.3). A humanities-based training for front-line health workers is a feasible intervention with demonstrated impact of nurturing key character strengths, notably empathy/connection and interpersonal communication. Evidence from this study highlights the value of a humanities-based training, grounded in local literature and cultural values, that can ultimately translate to improved well-being of LHWs thus contributing to better health outcomes among the populations they serve

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570