The deadly SARS-CoV-2 virus has infected more than 259,502,031 confirmed cases with 5,183,003 deaths in 223 countries during the last 22 months (Dec 2019–Nov 2021), whereas approximately 7,702,859,718, vaccine doses have been administered (WHO: https://covid19.who.int/ ) as of the 24th of Nov 2021. Recent announcements of test trial completion of several new vaccines resulted in the launching of immunization for the common person around the globe highlighting a ray of hope to cope with this infection. Meanwhile, genetic variations in SARS-CoV-2 and third layer of infection spread in numerous countries emerged as a stronger prototype than the parental. New and parental SARS-CoV-2 strains appeared as a risk factor for other pre-existing diseases like cancer, diabetes, neurological disorders, kidney, liver, heart, and eye injury. This situation requires more attention and re-structuring of the currently developed vaccines and/or drugs against SARS-CoV-2 infection. Although a decline in COVID-19 infection has been reported globally, an increase in COVID-19 cases in the subcontinent and east Mediterranean area could be alarming. In this review, we have summarized the current information about the SARS-CoV-2 biology, its interaction and possible infection pathways within the host, epidemiology, risk factors, economic collapse, and possible vaccine and drug development.
Background Undergraduate emergency medicine (EM) training is important because all medical graduates are expected to have basic emergency knowledge and skills regardless of their future speciality. EM clerkship should provide opportunities to improve not only knowledge and skills but also the self-efficacy of learners. This study aims to evaluate the expectations, opinions, and self-efficacy beliefs of medical students during a 4-week mandatory EM clerkship. Methods This study used a prospective longitudinal design with quantitative and qualitative survey methods. It includes final year medical students of the 2015–2016 academic year. Voluntary de-identified pre- and post-clerkship surveys included 25 statements. The post-clerkship survey included two open-ended questions asking participants to identify the best and worst three aspects of EM clerkship. Responses were analysed to determine themes or commonalities in participant comments indicative of the EM clerkship learning experiences and environment. Results Sixty-seven out of seventy-nine (85%) students responded to both pre- and post-clerkship surveys. Medical students’ expectations of EM clerkships’ effect on knowledge and skill acquisition were high, and a 4-week mandatory EM clerkship was able to meet their expectations. Medical students had very high expectations of EM clerkships’ educational environment. In most aspects, their experiences significantly exceeded their expectations ( p value < 0.001). The only exception was the duration of clerkship, which was deemed insufficient both at the beginning and at the end ( p value: 0.92). The students perceived that their self-efficacy improved significantly in the majority of basic EM skills and procedures ( p value < 0.001). Emergent qualitative themes in the study also supported these results. Conclusion This study showed that a 4-week mandatory EM clerkship increased medical students' perceived self-efficacy in basic emergency management skills. The EM clerkship met students' expectations on knowledge and skill acquisition, and exceeded students’ expectations on educational environment.
In the last two decades, advancements in artificial intelligence and data science have attracted researchers' attention to machine learning. Growing interests in applying machine learning algorithms can be observed in different scientific areas, including behavioral sciences. However, most of the research conducted in this area applied machine learning algorithms to imagining and physiological data such as EEG and fMRI and there are relatively limited non-imaging and non-physiological behavioral studies which have used machine learning to analyze their data. Therefore, in this perspective article, we aim to (1) provide a general understanding of models built for inference, models built for prediction (i.e., machine learning), methods used in these models, and their strengths and limitations; (2) investigate the applications of machine learning to categorical data in behavioral sciences; and (3) highlight the usefulness of applying machine learning algorithms to non-imaging and non-physiological data (e.g., clinical and categorical) data and provide evidence to encourage researchers to conduct further machine learning studies in behavioral and clinical sciences.
Background People with weakened immune systems may not develop adequate protection after taking two doses of the mRNA-combined COVID-19 vaccine. The additional dose may improve the level of protection against Covid-19. Objectives Current study aimed to evaluate the knowledge, attitude and determents of third COVID-19 vaccine booster dose acceptance among population in the UAE. Methods and materials This is online descriptive cross-sectional community-based study conducted among the students and faculty of Ajman University from 25 August to 20 October 2021. The questionnaire, which was in the English language, encompassed two sections containing 22 items. Section one gathered the demographic details of the respondents, while Section two used 13 questions to evaluate the respondents’ knowledge of and attitude to the third COVID-19 vaccine booster dose. Results 614 respondents participated in this study. The average knowledge score was 44.6% with a 95% confidence interval (CI) of [41%, 49%]. Better knowledge scores were observed in postgraduates (OR 4.29; 95% CI 2.28–8.11), employees in the healthcare sector (OR 1.62; 95% CI 1.05–2.51), participants who had relatives infected with the Covid-19 (OR 1.46; 95% CI 1.05–2.02), participants who had infected with Covid-19 (OR 2.21; 95% CI 1.43–3.43) and participants who had received first two doses of the COVID-19 vaccine (OR 2.08; 95% CI 1.40–3.11). The average attitude score was 70.2% with a 95% confidence interval (CI) of [69.2%, 71.2%]. Conclusion Necessary steps should be taken by the government and public health authorities, in line with the local culture, to increase vaccination acceptance and foster positive attitudes towards the vaccine. A suitable approach to this would be to develop an educational framework that could demonstrate the risks of vaccine avoidance or delay to the general population. Moreover, health authorities should pay more attention to the false information being disseminated across the internet, especially social media. Also, healthcare workers should be trained in vaccinology and virology to make sure that they are able to understand important developments in these fields and convey the findings to their patients.
Background Asthma is a significant public health issue that poses a substantial health and economic burden. Despite the availability of effective asthma medications, its management remain suboptimal. Recent asthma guidelines have highlighted the importance of pharmacist unique position and its interventional strategies in positively impacting asthma treatment outcomes. Therefore, this study aimed to assess the degree of Egyptian pharmacists’ knowledge, attitudes, as well as their practices towards asthma management in line with the recent asthma guidelines. Methods This cross-sectional study was conducted among 800 pharmacists working in different private and governmental sectors. The data were collected using a 37-item pre-validated self-administered KAP questionnaire. The data were analyzed using Student’s t-test and analysis of variance to assess the association between each KAP level and the sociodemographic variables at the significance level of 0.05. Results Of the 800 distributed questionnaire, a total of 550 participants (316 Male, and 234 Female) responded, representing a 68.7% response rate. The mean ± SD score of knowledge, attitude, practice, and barrier was 5.49 ± 1.65 (min = 0; max = 8), 23.5 ± 2.84 (min = 15, max = 30), 43.12 ± 8.61 (min = 28, max = 62), and 27.76 ± 3.72 (min = 17, max = 39), respectively. The results showed that poor knowledge, attitude, and practice scores were achieved by 30.54, 0, and 38.72% of participants, respectively. Conclusion Our findings revealed the inconsistencies between poor pharmacists’ knowledge and practices with respect to their positive attitudes. The lack of pharmacists’ knowledge and compliance to recent GINA guidelines in this study highlight the crucial need for effective Educational strategies that should better equip pharmacists for their potential role in asthma care.
Sets of baited hooks decrease in fishing efficacy over time as catch accumulates and bait is lost, and this complicates the quantification of fishing effort for species abundance calculations. Although hook-timers facilitate a more accurate estimation of fishing time, they cannot provide taxonomic information in the case of escapees or bait loss, nor can they provide information on animals that approach the gear but do not physically engage with it. To overcome these limitations, the present study attached sport action cameras to baited drumlines during a catch-and-release survey of sharks in the shallow, coastal waters of the eastern Caicos Bank, Turks and Caicos Islands. Overall, the true fishing time was found to be appreciably less than the apparent fishing time and more sharks approached or interacted with the gear than were successfully captured by it. Furthermore, shark-gear interactions varied by species while the amount of bait loss differed between deployment areas. Taken together, these findings suggest that baited-hook surveys underestimate shark abundance and that the magnitude of this error varies by species and habitat type.
In recent years, the van der Waals (vdW) Heterostructures (HTSs) are broadly studied for their capabilities to modulate the performance of two-dimensional (2D) materials. Herein, we constructed four types of vdW HTSs by vertically stacking the α-polytype and δ-polytype of single-layered SnS and SnSe. The constructed HTSs have been designated as HTS-I (SnS(α)/SnS(δ)), HTS-II (SnSe(α)/SnSe(δ)), HTS-III (SnS(α)/SnSe(δ)), and HTS-IV (SnSe(α)/SnS(δ)) and their physical properties are systematically explored by the first-principles approach. The electron density mapping revealed that the monolayers constituting these HTSs are stacked by vdW coupling which persists for interlayer distance (Δy) up to ∼7 Å. However, these tin-chalcogenide-based HTSs demonstrated the highest formation energies (Ef) and binding energies (Eb) for Δy = ∼3.75 Å. The electronic structure calculations revealed them as semiconductors of indirect bandgaps of magnitude 1.22, 1.28, 1.06, and 1.22 eV recorded for HTS-I, HTS-II, HTS-III, and HTS-IV, respectively. They exhibited type-II (staggered) band alignment where the valence band maximum occurs in the δ-type of monolayer and the conduction band minimum is located in α-type of monolayers that causes the splitting of the photo-generated electron-hole pairs at the interface. Therefore, the staggering gap and large density of states observed near the bandgap edges have triggered a significantly improved optical absorption in these HTSs compared to freestanding monolayers. Moreover, the transparent nature of these HTSs has been recognized against incident light of energy less than 5 eV. These predictions illustrate the development of vdW HTSs as an effective approach to improve the functionalities of 2D materials for advanced technological applications.
One of the currently proposed solutions for finding alternatives to fossil fuels and combating environmental pollution concerns the development of advanced materials for clean and renewable energy applications. An ongoing focus is devoted to the design of semiconductor-oriented heterogeneous photoelectrocatalytic, photocatalytic and electrocatalytic systems using fuel cells. In this regard, photocatalytic water splitting and carbon dioxide reduction stand as the two most promising processes for solving the energy crisis and mitigate the environmental pollution. However, these processes still demand for cost-efficient, stable, and environmentally benign photocatalysts. Metal–organic frameworks (MOFs) have emerged as adjustable and multipurpose materials that are now intensively investigated as a podium for applications in clean energy, including photocatalytic H2O splitting and CO2 reduction. Apart from representing an array of intrinsic structural and physicochemical characteristics, MOFs are well susceptible for various post-synthetic modifications to address specific challenges. Despite years of research in this field and a good number of seminal studies, further efforts should be geared toward the improvement of light absorption and stability of MOFs, which are the principal challenges that should be overcome. In this review, various strategies for designing MOFs and derived materials for advanced photocatalytic H2O splitting and CO2 reduction processes are discussed in detail, with a particular focus on the most recent progress in this area. Fundamental principles of photocatalysis, thermodynamics and kinetics, mechanistic features, and synthetic strategies for MOFs and derived nanomaterials and composites are exemplified to create a current state-of-the-art perception of this broad and highly important research topic. Industrial perspectives and projections on future research using MOFs and their composite photocatalytic materials are also elucidated. This review will be of assistance and a wake-up call to the scientific community in the field where the design and development of MOFs is blended with the materials science toward creating new solutions for clean energy production, using water splitting and carbon dioxide reduction as two key processes of paramount significance.
It is much debated whether natural resources are a curse or a blessing in contemporary literature. However, the literature is unable to document conclusive remarks on it, specifically in African countries. Given that, this study is an attempt to disclose the link between natural resources, economic complexity, and economic growth. A sample of 24 African economies for the years 1995–2017 was analyzed with the implications of the system GMM (generalized method of moments) model. This research deals with natural resource rents and economic complexity as predictors of economic growth while controlling for corruption, gross capital formation, total labor force, foreign direct investment inflow, and trade openness. The empirical findings first document the negative impact of natural resource rents while the positive impact of economic complexity on economic growth. However, a positive link was observed when economic complexity interacts with natural resources and conjunctionally affects economic growth. The empirical analysis further supplements the dynamic impact of control variables on economic growth. This study strengthens the views of natural resource curse (in individual analysis) and natural resources blessing (interaction effect) hypotheses and calls for more focus by policy officials on economic complexity to harvest the advantages from available natural resources.
Pusa 391, a mega desi chickpea variety with medium maturity duration is extensively cultivated in the Central Zone of India. Of late, this variety has become susceptible to Fusarium wilt (FW), which has drastic impact on its yield. Presence of variability in the wilt causing pathogen, Fusarium oxysporum f.sp. ciceri (foc) across geographical locations necessitates the role of pyramiding for FW resistance for different races (foc 1,2,3,4 and 5). Subsequently, the introgression lines developed in Pusa 391 genetic background were subjected to foreground selection using three SSR markers (GA16, TA 27 and TA 96) while 48 SSR markers uniformly distributed on all chromosomes, were used for background selection to observe the recovery of recurrent parent genome (RPG). BC 1 F 1 lines with 75-85% RPG recovery were used to generate BC 2 F 1. The plants that showed more than 90% RPG recovery in BC 2 F 1 were used for generating BC 3 F 1. The plants that showed more than 96% RPG recovery were selected and selfed to generate BC 3 F 3. Multi-location evaluation of advanced introgression lines (BC 2 F 3) in six locations for grain yield (kg/ha), days to fifty percent flowering, days to maturity, 100 seed weight and disease incidence was done. In case of disease incidence, the genotype IL1 (BGM 20211) was highly resistant to FW in Junagarh, Indore, New Delhi, Badnapur and moderately resistant at Sehore and Nandyal. GGE biplot analysis revealed that IL1(BGM20211) was the most stable genotype at Junagadh, Sehore and Nandyal. GGE biplot analysis revealed that IL1(BGM 20211) and IL4(BGM 20212) were the top performers in yield and highly stable across six environments and were nominated for Advanced Varietal Trials (AVT) of AICRP
Objective: Psoriatic arthritis (PsA), a chronic inflammatory disease characterized by heterogeneous clinical manifestations, substantially impacts the quality of life of affected individuals. This article aims at developing consensus recommendations for the management of PsA and associated comorbidities and screening and monitoring requirements of PsA therapies in the United Arab Emirates (UAE) population. Methods: An extensive review of present international and regional guidelines and publications on the pharmacological management, monitoring of therapies in the context of PsA was performed. Key findings from guidelines and literature were reviewed by a panel of experts from the UAE at several meetings to align with current clinical practices. Consensus statements were formulated based on collective agreement of the experts and members of Emirates Society for Rheumatology. Results: The consensus recommendations were developed to aid practitioners in clinical decision-making with respect to dosage recommendations for pharmacological therapies for PsA, including conventional drugs, non-biologic, and biologic therapies. Consensus recommendations for therapeutic options for the treatment of PsA domains, including peripheral arthritis, axial disease, enthesitis, dactylitis, psoriasis, and nail disease, were developed. The panel emphasized the importance of monitoring PsA therapies and arrived at a consensus on monitoring requirements for PsA therapies. The expert panel proposed recommendations for the management of common comorbidities associated with PsA. Conclusion: These consensus recommendations can guide physicians and healthcare professionals in the UAE in making proper treatment decisions, as well as efficiently managing comorbidities and monitoring therapies in patients with PsA.
This paper describes an experimental system for simultaneous permeation of a pressurized test gas through different gas permeable membranes and provides a proof of concept for a novel approach for gas identification/fingerprinting for potential construction of electronic noses. The design, construction, and use of a six-channel system which allows simultaneous gas permeation from a single pressurized gas compartment through six different parallel membranes are presented. The permeated gas is accumulated in confined spaces behind the respective membranes. The rate of gas pressure accumulation behind each membrane is recorded and used as a measure of the gas permeation rate through the membrane. The utilized gas permeable membranes include Teflon AF, silicone rubber, track-etch hydrophilic polycarbonate, track-etch hydrophobic polycarbonate, track-etch polyimide, nanoporous anodic aluminum oxide, zeolite ZSM-5, and zeolite NaY. An analogy between the rate of pressure accumulation of the permeating gas behind the membrane and the charging of an electric capacitor in a single series RC circuit is proposed and thoroughly validated. The simultaneous permeation rates through different membranes demonstrated a very promising potential as characteristic fingerprints for 10 test gases, that is, helium, neon, argon, hydrogen, nitrogen, carbon dioxide, methane, ethane, propane, and ethylene, which are selected as representative examples of mono-, di-, tri-, and polyatomic gases and to include some homologous series as well as to allow testing the potential of the proposed system to discriminate between closely related gases such as ethane and ethylene or carbon dioxide and propane which have almost identical molecular masses. Finally, a preliminary investigation of the possibility of applying the developed gas permeation system for semiquantitative analysis of the CO2-N2 binary mixture is also presented.
This study examines the association among the green energy production (GEP), green technological innovation (GTI), and green international trade (GIT) on the ecological footprints (EFP). In addition, this research applies fully modified least square (FMOLS) to estimate the empirical outcomes, while dynamic least square (DOLS) is used to check the robustness of the outcomes. Although, the selection of the assessment technique depends on the order of integration of the selected series. Before estimation, some diagnostic tests are also performed to ensure the reliability of the data set. Furthermore, the empirical outcomes of the present analysis are twofold: at begin, this research discovered a negative relationship between GEP and EFP. Secondly, this research reveals that GTI has also an adverse impact on EFP along with GIT, which is unsurprising. Results imply that advancement in green technological innovations tends to improve the EQ by reducing the level of EFP.
The effect of the exposure to thermo-switchable solvent (TSS) on cell wall disruption of Chlorella sp. microalgae was investigated. The combustion and kinetic behaviors of microalgae cells treated with TSS, which was maintained at its hydrophilic state for 1.5 h to disrupt the cell wall, were analyzed and compared with those of undisrupted cells. The X-ray diffraction (XRD) results showed a clear drop in the crystallinity of the TSS-treated samples, which was mainly due to the degradation of the cellulosic material. The results were confirmed from the thermogravimetric analysis, which showed a drop in the cellulosic material from 71.9% in the untreated sample to 49% for TSS-treated sample. The activation energy of TSS-treated sample from different non-isothermal models was 44.90–157.97 (FWO), 103.09–492.19 (KAS), and 100.60–478.89 kJ mol−1 (Starink). The values were lower at low conversions (x ≤ 0.5) than untreated samples whose activation energy was 70.67–152.98 (FWO), 195.38–465.58 (KAS), and 190.39–453.11 kJ mol−1 (Starink). The low activation energies for all models of TSS-treated samples indicate that less energy would be required for the thermal conversion processes, as compared with the untreated samples. The tested model-free methods reduce mass transfer limitations, with Flynn-Wall-Ozawa (FWO) compensating for experimental errors, whereas Kissinger-Akahira-Sunose (KAS) and Starink for providing precision to kinetic data depending on a good constant degree of conversion. The reaction mechanism was represented well by the Malek and Popescu. The results presented in this work provide deeper understanding of the effect of TSS on microalgae cell wall disruption.
Non-orthogonal multiple access (NOMA) along with cognitive radio (CR) have been recently configured as potential solutions to fulfill the extraordinary demands of the fifth generation (5G) and beyond (B5G) networks and support the Internet of Thing (IoT) applications. Multiple users can be served within the same orthogonal domains in NOMA via power-domain multiplexing, whilst CR allows secondary users (SUs) to access the licensed spectrum frequency. This work investigates the possibility of combining orthogonal frequency division multiple access (OFDMA), NOMA, and CR, referred to as hybrid OFDMA-NOMA CR network. With this hybrid technology, the licensed frequency is divided into several channels, such as a group SUs is served in each channel based on NOMA technology. In particular, a rate-maximization framework is developed, at which user pairing at each channel, power allocations for each user, and secondary users activities are jointly considered to maximize the sum-rate of the hybrid OFDMA-NOMA CR network, while maintaining a set of relevant NOMA and CR constraints. The developed sum-rate maximization framework is NP-hard problem, and cannot be solved through classical approaches. Accordingly, we propose a two-stage approach; in the first stage, we propose a novel user pairing algorithm. With this, an iterative algorithm based on the sequential convex approximation is proposed to evaluate the solution of the non-convex rate-maximization problem, in the second stage. Results show that our proposed algorithm outperforms the existing schemes, and CR network features play a major role in deciding the overall network’s performance.
In this study, a hot and desert location with an annual temperature of 27.1 °C and a very high radiation intensity of 2143 kWh/m², a solar system (ES) was approved to provide building cooling necessities. The cooling system, by connecting to the solar system, supplied a part of its required energy. The outer layer of the building walls was equipped with PCM (SP-21EK) with a melting point of 21–23 and latent heat of 170 kJ/kg. In the solar system, water was filled to absorb energy and then a combination of CF-MWCNTs and CF-GNPs nanoparticles were injected to the solar system to improve effectiveness. In July, when the radiation intensity was very high, the combination of PCM and SC condensed energy consumption (EC) by up to 46.48%. The presence of CF-MWCNTs and CF-GNPs at 0.1 wt% was useful in all conditions (2, 3 and 4 lit/min). In this case, the EC reduction was in the range of 360 to 1026 kWh. At lower concentrations, the nanoparticles not only were not worthwhile, in some cases increased EC by 937 kWh.
Reduced graphene oxide (rGO) has applications in Water purification, and Energy conversion. In this study, a water-based nanofluid containing rGO was formed at specific concentrations. The nanofluid Thermo-Rheology behavior was studied at room temperature to 50 °C. Viscosity was detected at specific RPMs from 10 to 100. The results showed that this nanofluid has excellent thermo-rheology properties. Flat plate solar collectors could heat the fluid inside using sunlight from a wide range of varied angles. Thus, the prepared nanofluid was used as the working fluid in the solar collector tubes. The results showed that this nanofluid can be used instead of water. The aims of this study are to optimize the process and lessen the examination costs, thus, Artificial Neural Networks algorithms of Orthogonal Distance Regression (ODR), Levenberg Marquardt (LM), and Fuzzy system of Recursive Least Squares were trained. Results proved that Artificial Neural Network and Fuzzy systems should be trained to predict the data of thermal conductivity and viscosity with acceptable coefficient of determination.
Aim We aimed to study the impact of the COVID-19 pandemic on the pattern of injury and outcome of hospitalized trauma patients in Al-Ain City, United Arab Emirates, to use this information in the preparedness for future pandemics. Methods We retrospectively compared the trauma registry data of all hospitalised trauma patients, who were treated at the two main trauma centres in Al-Ain City (Al-Ain Hospital and Tawam Hospital); those who were treated over 1 year before the pandemic ( n = 2002) and those who were treated at the first year of the COVID-19 pandemic ( n = 1468). Results There was a 26.7% reduction in the overall incidence of trauma admissions in the COVID-19 pandemic period. The mechanism of injury significantly differed between the two periods ( p < 0.0001, Fisher’s exact test). There was an absolute increase in the number of injuries, due to machinery and falling objects during the pandemic (39.7% and 54.1% respectively, p < 0.001). In contrast, road traffic collisions and falls were reduced by 33.5% and 31.3%, respectively. Location significantly differed between the two periods ( p < 0.0001, Fisher’s exact test). There was an absolute increase of 18.4% in workplace injuries and a reduction of 39.3% in home injuries over the study period. In addition, we observed relatively more workplace injuries and fewer home injuries during the pandemic (11.3% and 42.8% compared with 7.1% and 52.4%, respectively). Mortality was similar between the two periods (1.8% compared with 1.2%, p = 0.16, Fisher’s exact test). Conclusions The COVID-19 pandemic has modified the trauma risk exposure in our population. It reduced trauma hospital admissions by around 27%. Work-related injuries, including falling objects and machinery injuries, were relatively higher during the pandemic. Prevention of work-related injuries should be an important component of preparedness for future pandemics.
Institution pages aggregate content on ResearchGate related to an institution. The members listed on this page have self-identified as being affiliated with this institution. Publications listed on this page were identified by our algorithms as relating to this institution. This page was not created or approved by the institution. If you represent an institution and have questions about these pages or wish to report inaccurate content, you can contact us here.