Showing papers by "Jordan University of Science and Technology published in 2020"

Selective Naked-Eye Detection of SARS-CoV-2 Mediated by N Gene Targeted Antisense Oligonucleotide Capped Plasmonic Nanoparticles.

Abstract: The current outbreak of the pandemic coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) demands its rapid, convenient, and large-scale diagnosis to downregulate its spread within as well as across the communities. But the reliability, reproducibility, and selectivity of majority of such diagnostic tests fail when they are tested either to a viral load at its early representation or to a viral gene mutated during its current spread. In this regard, a selective "naked-eye" detection of SARS-CoV-2 is highly desirable, which can be tested without accessing any advanced instrumental techniques. We herein report the development of a colorimetric assay based on gold nanoparticles (AuNPs), when capped with suitably designed thiol-modified antisense oligonucleotides (ASOs) specific for N-gene (nucleocapsid phosphoprotein) of SARS-CoV-2, could be used for diagnosing positive COVID-19 cases within 10 min from the isolated RNA samples. The thiol-modified ASO-capped AuNPs agglomerate selectively in the presence of its target RNA sequence of SARS-CoV-2 and demonstrate a change in its surface plasmon resonance. Further, the addition of RNaseH cleaves the RNA strand from the RNA-DNA hybrid leading to a visually detectable precipitate from the solution mediated by the additional agglomeration among the AuNPs. The selectivity of the assay has been monitored in the presence of MERS-CoV viral RNA with a limit of detection of 0.18 ng/μL of RNA having SARS-CoV-2 viral load. Thus, the current study reports a selective and visual "naked-eye" detection of COVID-19 causative virus, SARS-CoV-2, without the requirement of any sophisticated instrumental techniques.

Distance learning in clinical medical education amid COVID-19 pandemic in Jordan: current situation, challenges, and perspectives

Abstract: As COVID-19 has been declared as a pandemic disease by the WHO on March 11th, 2020, the global incidence of COVID-19 disease increased dramatically. In response to the COVID-19 situation, Jordan announced the emergency state on the 19th of March, followed by the curfew on 21 March. All educational institutions have been closed as well as educational activities including clinical medical education have been suspended on the 15th of March. As a result, Distance E-learning emerged as a new method of teaching to maintain the continuity of medical education during the COVID-19 pandemic related closure of educational institutions. Distance E-Learning is defined as using computer technology to deliver training, including technology-supported learning either online, offline, or both. Before this period, distance learning was not considered in Jordanian universities as a modality for education. This study aims to explore the situation of distance E-learning among medical students during their clinical years and to identify possible challenges, limitations, satisfaction as well as perspectives for this approach to learning. This cross-sectional study is based on a questionnaire that was designed and delivered to medical students in their clinical years. For this study, the estimated sample size (n = 588) is derived from the online Raosoft sample size calculator. A total of 652 students have completed the questionnaire, among them, 538 students (82.5%) have participated in distance learning in their medical schools amid COVID-19 pandemic. The overall satisfaction rate in medical distance learning was 26.8%, and it was significantly higher in students with previous experience in distance learning in their medical schools as well as when instructors were actively participating in learning sessions, using multimedia and devoting adequate time for their sessions. The delivery of educational material using synchronous live streaming sessions represented the major modality of teaching and Internet streaming quality and coverage was the main challenge that was reported by 69.1% of students. With advances in technologies and social media, distance learning is a new and rapidly growing approach for undergraduate, postgraduate, and health care providers. It may represent an optimal solution to maintain learning processes in exceptional and emergency situations such as COVID-19 pandemic. Technical and infrastructural resources reported as a major challenge for implementing distance learning, so understanding technological, financial, institutional, educators, and student barriers are essential for the successful implementation of distance learning in medical education.

Rapid, Ultrasensitive, and Quantitative Detection of SARS-CoV-2 Using Antisense Oligonucleotides Directed Electrochemical Biosensor Chip.

Abstract: A large-scale diagnosis of the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) is essential to downregulate its spread within as well as across communities and mitigate the current out...

Dentists’ Awareness, Perception, and Attitude Regarding COVID-19 and Infection Control: Cross-Sectional Study Among Jordanian Dentists

Abstract: Background: Despite the availability of prevention guidelines and recommendations on infection control, many dental practices lack the minimum requirements for infection control. Objective: This study aimed to assess the level of awareness, perception, and attitude regarding the coronavirus disease (COVID-19) and infection control among Jordanian dentists. Methods: The study population consisted of dentists who worked in private clinics, hospitals, and health centers in Jordan. An online questionnaire was sent to a sample of Jordanian dentists in March 2020. The questionnaire was comprised of a series of questions about dentists’ demographic characteristics; their awareness of the incubation period, the symptoms of the disease, mode of transmission of COVID-19 and infection control measures for preventing COVID-19; and their attitude toward treating patients with COVID-19. Results: This study included a total of 368 dentists aged 22-73 years (mean 32.9 years, SD 10.6 years). A total of 112 (30.4%) dentists had completed a master or residency program in dentistry, 195 (53.0%) had received training in infection control in dentistry, and 28 (7.6%) had attended training or lectures regarding COVID-19. A total of 133 (36.1%) dentists reported that the incubation period is 1-14 days. The majority of dentists were aware of COVID-19 symptoms and ways of identifying patients at risk of having COVID-19, were able to correctly report known modes of transmission, and were aware of measures for preventing COVID-19 transmission in dental clinics. A total of 275 (74.7%) believed that it was necessary to ask patients to sit far from each other, wear masks while in the waiting room, and wash hands before getting in the dental chair to decrease disease transmission. Conclusions: Jordanian dentists were aware of COVID-19 symptoms, mode of transmission, and infection controls and measures in dental clinics. However, dentists had limited comprehension of the extra precautionary measures that protect the dental staff and other patients from COVID-19. National and international guidelines should be sent by the regional and national dental associations to all registered dentists during a crisis, including the COVID-19 pandemic, to make sure that dentists are well informed and aware of best practices and recommended disease management approaches.

A test-suite of non-convex constrained optimization problems from the real-world and some baseline results

Abstract: Real-world optimization problems have been comparatively difficult to solve due to the complex nature of the objective function with a substantial number of constraints. To deal with such problems, several metaheuristics as well as constraint handling approaches have been suggested. To validate the effectiveness and strength, performance of a newly designed approach should be benchmarked by using some complex real-world problems, instead of only the toy problems with synthetic objective functions, mostly arising from the area of numerical analysis. A list of standard real-life problems appears to be the need of the time for benchmarking new algorithms in an efficient and unbiased manner. In this study, a set of 57 real-world Constrained Optimization Problems (COPs) are described and presented as a benchmark suite to validate the COPs. These problems are shown to capture a wide range of difficulties and challenges that arise from the real life optimization scenarios. Three state-of-the-art constrained optimization methods are exhaustively tested on these problems to analyze their hardness. The experimental outcomes reveal that the selected problems are indeed challenging to these algorithms, which have been shown to solve many synthetic benchmark problems easily.

Machine Learning with Oversampling and Undersampling Techniques: Overview Study and Experimental Results

Abstract: Data imbalance in Machine Learning refers to an unequal distribution of classes within a dataset. This issue is encountered mostly in classification tasks in which the distribution of classes or labels in a given dataset is not uniform. The straightforward method to solve this problem is the resampling method by adding records to the minority class or deleting ones from the majority class. In this paper, we have experimented with the two resampling widely adopted techniques: oversampling and undersampling. In order to explore both techniques, we have chosen a public imbalanced dataset from kaggle website Santander Customer Transaction Prediction and have applied a group of well-known machine learning algorithms with different hyperparamters that give best results for both resampling techniques. One of the key findings of this paper is noticing that oversampling performs better than undersampling for different classifiers and obtains higher scores in different evaluation metrics.

Media's effect on shaping knowledge, awareness risk perceptions and communication practices of pandemic COVID-19 among pharmacists.

Abstract: Background Coronavirus disease (COVID-19), an infection of the zoonotic coronavirus, is presenting a healthcare challenge around the globe. This study aims to assess the levels of disease knowledge and risk perception among pharmacists. We also recognize predictors of risk perception and perceived media roles. Methods This is a questionnaire-base cross-sectional study. The questionnaire was developed on a web-based platform and invitations were sent to pharmacists nationwide to participate in the study using social media applications. Results A total of 486 pharmacists participated in this study, where females were dominant (78.6%, n = 382). Most (40.4%, n = 198) pharmacists scored 4 out of 5 in basic disease knowledge, and more than half were able to recognize common methods of spread. Risk was highly perceived among participants, and was predicted by gender, living area, and having children (p

Efficiency of flipped classroom with online-based teaching under COVID-19

Abstract: Due to the spread of COVID-19 worldwide, a large number of universities had to close their campuses. To maintain teaching and learning during this disruption to the traditional teaching, most unive...

Blockchain-Based Approach to Create a Model of Trust in Open and Ubiquitous Higher Education.

Abstract: Currently, the training of the future work force presents challenging problems to higher education. This training, in the form of practical and theoretical knowledge can come from multiple platforms, channels and means, both formal and informal. In addition, it is quite difficult to assess the knowledge skill level that a student has acquired to optimize their chances for future employability. This, together with the need to still manage academic curricula on paper, the problems of confidence when validating these documents and contrasting them with real knowledge, etc., means that management in higher education requires revolutionary new tools. This work evaluates the benefits of the blockchain (or distributed ledger) technology and advocates a decentralised model of confidence for transactions based on an academic crypto currency. In this approach blockchain is used to manage transactions of content, teaching and competencies, assessed by consensus by students, trainers and employers, to eliminate once and for all the “gap” between the academic world and the working world. This paper aims to address the current challenges of an increasingly dispersed, open and ubiquitous higher education. The proposed model can be implemented in any training institution to adapt its teaching to the specific needs of professional profiles validated by employers in the sector. This model has been validated by means of a prototype with more than acceptable results.

Acute stress disorder, coping self-efficacy and subsequent psychological distress among nurses amid COVID-19.

Abstract: Purpose Health care professionals, particularly nurses, are considered a vulnerable group to experience acute stress disorder (ASD) and subsequent psychological distress amid COVID-19 pandemic. This study aims to establish the prevalence of acute stress disorder and predictors of psychological distress among Jordanian nurses. Methods A quantitative, cross-sectional, descriptive and comparative design was used. Data were collected using a Web-based survey. A total of 448 Jordanian nurses (73% females) completed and returned the study questionnaire. Results The majority of nurses (64%) are experiencing ASD due to the COVID-19 pandemic and thus are at risk for PTSD predisposition. More than one-third of nurses (41%) are also suffering significant psychological distress. Among our sample, age, ASD and coping self-efficacy significantly predicted psychological distress. More specifically, younger nurses are more prone to experience psychological distress than older ones. While higher scores on ASD showed more resultant psychological distress, coping self-efficacy was a protective factor. Conclusion Given that individuals who suffer from ASD are predisposed to PTSD, follow-up with nurses to screen for PTSD and referral to appropriate psychological services is pivotal. Coping self-efficacy is found to ameliorate the effect of psychological distress on nurses' traumatic experience. Such findings warrant intensive efforts from health care institutions to provide psychosocial support services for nurses and ongoing efforts to screen them for traumatic and psychological distress symptoms. Implications for nursing management Nursing leaders and managers are in the forefront of responding to the unique needs of their workforces during the COVID-19 crisis. They need to implement stress-reduction strategies for nurses through providing consecutive rest days, rotating allocations of complex patients, arranging support services and being accessible to staff. They also need to ensure nurses' personal safety through securing and providing personal safety measures and undertake briefings to ensure their staff's physical and mental well-being, as well as providing referrals to appropriate psychological services.

Reviewing and exploring innovative ubiquitous learning tools in higher education

Abstract: In the higher education sector, a new era has begun with the advent of ubiquitous learning environments. Ubiquitous learning tools allow improving context-aware as well as learning experiences by offering seamless availability regardless of location all the time. They also help in establishing effortless interaction between authentic and digital learning resources and at the same time offering personalised learning opportunities as well. There are numerous available ubiquitous e-learning tools that can be employed in higher education. E-learning tools also offer training and higher education to many students that have different higher educational levels and come from diverse cultural backgrounds. However, if the capabilities of e-learning are underestimated, these may not be successful in higher education. Some of the people lack understanding about the limitations and weaknesses of e-learning, while some may have superfluous expectations. In this paper, various e-learning tools like Wikipedia, MOODLE, Web 2.0, Web 3.0 and Blackboard have been evaluated. We also comment on key aims regarding each tool and investigate the disadvantages and advantages. Based on this analysis, a global view regarding the current as well as future tendencies pertaining to ubiquitous e-learning tools is obtained and thus possible key comments are provided for employing e-learning tools like MOODLE, Web 2.0 and Web 3.0 in the classroom. Based on our teaching experience, MOODLE was found to be efficient in the development of e-learning. MOODLE was favoured by a majority of authors and practitioners rather than Blackboard. However, MOODLE cannot be considered a fully pure social software since it does not include social networks. In this review, the scope of employing ubiquitous learning environments has been presented in higher education contexts. However, it increases the requirement for transparent research that shows practical implications to generalise future development processes. Moreover, it was shown that e-learning 3.0 is one amongst the key trends employing Web 3.0 tools for social learning. Also, on the Internet, quick incorporation of new services into existing applications like integrating Wiki with Web 3.0 can be done easily. The primary risk here would be the fact that lecturers and students are not fully aware that these web services are not controlled by their universities. Since these servers have been installed in many different countries, the principles and privacy laws vary from country to country.

Cardiac Tumors: JACC CardioOncology State-of-the-Art Review.

Abstract: Cardiac masses are rare, but remain an important component of cardio-oncology practice. These include benign tumors, malignant tumors (primary and secondary) and tumor-like conditions (e.g...

Stress and behavioral changes with remote E-exams during the Covid-19 pandemic: A cross-sectional study among undergraduates of medical sciences.

Abstract: Emergence of coronavirus disease 2019 (COVID-19) forced the worldwide higher educational institutes to adopt distance learning mode. Further, remote electronic exams (E-exams) were considered as mode of assessment. Objectives: This cross-sectional study evaluated the students' experience of remote E-exams during the COVID-19 pandemic among Medical Sciences students in Jordan. Materials and Methods: A survey of 29 questions was prepared on Google forms and distributed among students at Faculties of Medical Sciences (Medicine, Dentistry, Pharmacy, Nursing and Applied Medical Sciences) at Jordan University of Science and Technology. The questions include students' demographics, stress experience, and factors contributing to stress as well as behavioral changes related to remote E-exams. Responses were analyzed using descriptive, cross tabulation and Chi-square tests. Results: Among 1019 respondents, 32% reported more stress with remote E-exams. This was associated with academic major and gender. Among students with more stress during remote E-exams, the exam duration, mode of questions navigation and technical problems (exam platform and internet connectivity) appeared as the main factors related to stress in 78%, 76% and >60%, respectively. Other factors include concern regarding the teaching methods, exam environment and students' dishonesty. Remote E-exams had negative impact on students' dietary habits (increase consumption of caffeine and high energy drinks, high sugar food, fast food), sleep (reduction in sleeping hours, more consumption of insomnia medications), physical activity (less exercises) and smoking habits (increase). Conclusion: Results suggested a negative impact of E-exams on students within Medical Faculties. Robust exam platform and remote mock E-exams are recommended to reduce students' potential stress. A stress-free environment is very essential to encourage students to adopt remote E-exams, particularly if the pandemic will take longer. Various awareness programs about students' habits related to dietary, sleep quality, physical activity and smoking are highly valuable for students' health benefits. This is of particular importance since the current students at Faculties of Medical Sciences are the future health care providers.

Distance education during the COVID-19 outbreak: A cross-sectional study among medical students in North of Jordan

Abstract: Introduction In the spot of the new emerging COVID-19 pandemic and its major impact worldwide on day-to-day activities many rules had to be changed in order to fight this pandemic. Lockdown started in Jordan and around the globe affecting several aspects of life including economy, education, entertainment, and government policies. Regarding education, the priority was to ensure the safety and progress of the educational process. Thus, new methods of teaching had to be applied using the online learning at Jordan University of Science and Technology (JUST), Faculty of Medicine. This study was done to assess (1) Class Experience (2) Students and Lecturers' Interaction (3) Online Learning Advantages & Disadvantages (4) Students’ Preference. Methods A cross sectional study was conducted Convenience sampling technique was used to collect the data from the participants using a survey composed of 18 questions on Google Forms platform. A link was sent to the undergraduate medical students at the Jordan University of Science & Technology via their e-learning accounts (n = 3700). The form was available from May 22nd, 2020 to May 30th, 2020 for 8 days long. Data analysis was done using SPSS V 23. Results 2212 out of 3700 students responded, (55.8%) of them were in the basic years and (44.2%) of them were in the clinical years. (55.8%) of students started to take online lectures after 3 weeks. (45.7%) used the hybrid teaching method (asynchronous and synchronous), (31.4%) used live classes, and 22.8% recorded classes. Zoom was the most used platform. (48.7%) and (57%) of clinical students and basic students express their interaction as bad, while the others had good and excellent interaction. Maintaining social distance was the most advantage of online teaching, while poor technical setup and no direct contact were the most disadvantage, furthermore inability to have real clinical access was a significant problem for clinical students (p Conclusion Most medical students at JUST preferred the traditional face-to-face teaching method over the solo online teaching methods with recommendations to convert to a more integrated educational system. Also, a well-established infrastructure should be done in involving online teaching.

The potential application of probiotics and prebiotics for the prevention and treatment of COVID-19.

Abstract: COVID-19 is a pandemic disease caused by the novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This new viral infection was first identified in China in December 2019, and it has subsequently spread globally. The lack of a vaccine or curative treatment for COVID-19 necessitates a focus on other strategies to prevent and treat the infection. Probiotics consist of single or mixed cultures of live microorganisms that can beneficially affect the host by maintaining the intestinal or lung microbiota that play a major role in human health. At present, good scientific evidence exists to support the ability of probiotics to boost human immunity, thereby preventing colonization by pathogens and reducing the incidence and severity of infections. Herein, we present clinical studies of the use of probiotic supplementation to prevent or treat respiratory tract infections. These data lead to promising benefits of probiotics in reducing the risk of COVID-19. Further studies should be conducted to assess the ability of probiotics to combat COVID-19.

Chest x-ray findings and temporal lung changes in patients with COVID-19 pneumonia.

Abstract: Chest CT scan and chest x-rays show characteristic radiographic findings in patients with COVID-19 pneumonia. Chest x-ray can be used in diagnosis and follow up in patients with COVID-19 pneumonia. The study aims at describing the chest x-ray findings and temporal radiographic changes in COVID-19 patients. From March 15 to April 20, 2020 patients with positive reverse transcription polymerase chain reaction (RT-PCR) for COVID-19 were retrospectively studied. Patients’ demographics, clinical characteristics, and chest x-ray findings were reported. Radiographic findings were correlated with the course of the illness and patients’ symptoms. A total of 88 patients (50 (56.8%) females and 38 (43.2%) males) were admitted to the hospital with confirmed COVID-19. Their age ranged from 3 to 80 years (35.2 ± 18.2 years). 48/88 (45%) were symptomatic, only 13/88 (45.5%) showed abnormal chest x-ray findings. A total of 190 chest x-rays were obtained for the 88 patients with a total of 59/190 (31%) abnormal chest x-rays. The most common finding on chest x-rays was peripheral ground glass opacities (GGO) affecting the lower lobes. In the course of illness, the GGO progressed into consolidations peaking around 6–11 days (GGO 70%, consolidations 30%). The consolidations regressed into GGO towards the later phase of the illness at 12–17 days (GGO 80%, consolidations 10%). There was increase in the frequency of normal chest x-rays from 9% at days 6–11 up to 33% after 18 days indicating a healing phase. The majority (12/13, 92.3%) of patients with abnormal chest x-rays were symptomatic (P = 0.005). Almost half of patients with COVID-19 have abnormal chest x-ray findings with peripheral GGO affecting the lower lobes being the most common finding. Chest x-ray can be used in diagnosis and follow up in patients with COVID-19 pneumonia.

Global injury morbidity and mortality from 1990 to 2017: results from the Global Burden of Disease Study 2017

Abstract: Background Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries. Methods We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs). Findings In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, agestandardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505). Interpretation Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in highburden populations, improving data collection and ensuring access to medical care.

A Profitable and Energy-Efficient Cooperative Fog Solution for IoT Services

Abstract: Fog-to-fog communication has been introduced to deliver services to clients with minimal reliance on the cloud through resource and capability sharing of cooperative fogs. Current solutions assume full cooperation among the fogs to deliver simple and composite services. Realistically, each fog might belong to a different network operator or service provider and thus will not participate in any form of collaboration unless self-monetary profit is incurred. In this paper, we introduce a fog collaboration approach for simple and complex multimedia service delivery to cloud subscribers while achieving shared profit gains for the cooperating fogs. The proposed work dynamically creates short-term service-level agreements (SLAs) offered to cloud subscribers for service delivery while maximizing user satisfaction and fog profit gains. The solution provides a learning mechanism that relies on online and offline simulation results to build guaranteed workflows for new service requests. The configuration parameters of the short-term SLAs are obtained using a modified tabu-based search mechanism that uses previous solutions when selecting new optimal choices. Performance evaluation results demonstrate significant gains in terms of service delivery success rate, service quality, reduced power consumption for fog and cloud datacenters, and increased fog profits.

GARUDA: Gaussian dissimilarity measure for feature representation and anomaly detection in Internet of things

Abstract: The objective of any anomaly detection system is to efficiently detect several types of malicious traffic patterns that cannot be detected by conventional firewall systems. Designing an efficient intrusion detection system has three primary challenges that include addressing high dimensionality problem, choice of learning algorithm, and distance or similarity measure used to find the similarity value between any two traffic patterns or input observations. Feature representation and dimensionality reduction have been studied and addressed widely in the literature and have also been applied for the design of intrusion detection systems (IDS). The choice of classifiers is also studied and applied widely in the design of IDS. However, at the heart of IDS lies the choice of distance measure that is required for an IDS to judge an incoming observation as normal or abnormal. This challenge has been understudied and relatively less addressed in the research literature both from academia and from industry. This research aims at introducing a novel distance measure that can be used to perform feature clustering and feature representation for efficient intrusion detection. Recent studies such as CANN proposed feature reduction techniques for improving detection and accuracy rates of IDS that used Euclidean distance. However, accuracies of attack classes such as U2R and R2L are not significantly promising. Our approach GARUDA is based on clustering feature patterns incrementally and then representing features in different transformation space through using a novel fuzzy Gaussian dissimilarity measure. Experiments are conducted on both KDD and NSL-KDD datasets. The accuracy and detection rates of proposed approach are compared for classifiers such as kNN, J48, naive Bayes, along with CANN and CLAPP approaches. Experiment results proved that proposed approach resulted in the improved accuracy and detection rates for U2R and R2L attack classes when compared to other approaches.

Harvesting of microalgae by centrifugation for biodiesel production: A review

Abstract: Biodiesel production from algal biomass is widely considered a sustainable alternative to petroleum fuels, especially in the transportation sector. However, the high energy consumption associated with the harvesting phase poses a significant impediment to the substantial commercialization of algal biodiesel. Centrifugation is among those harvesting methods that have a high efficiency close to 100% but can consume more energy than it produces. This review aims to address possible solutions for the issue of the high energy cost of centrifugation as an efficient harvesting technique. In addition, a detailed overview of the potential types of centrifugation that can be used to harvest microalgae with their pros and cons is provided. The most prevalent centrifugal devices that have been identified to be effectively useful to harvest algal biomass include disc-stack centrifuge, solid-bowl centrifuge, hydrocyclone, tubular centrifuge, and multi-chamber centrifuge. Overall, the analysis showed that centrifugation alone is not suitable for the harvesting of microalgae for biodiesel production. Nevertheless, coupling centrifugation with other harvesting technologies, e.g. with flocculation, as a primary pre-concentration step, can increase the energy output significantly thus, reducing the production cost.

Photocatalytic Activity of Graphene Oxide/Zinc Oxide Nanocomposites with Embedded Metal Nanoparticles for the Degradation of Organic Dyes.

Abstract: Nanocomposite materials based on metal nanoparticles and graphene oxide (GO) have gained increasing attention for their wide range of potential applications in various materials science fields. In this study, an efficient photocatalyst based on GO/ZnO nanocomposites with embedded metal nanoparticles was successfully synthesized via a simple one-pot method. The synthesized nanocomposites were characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), and Fourier transform infrared (FTIR) spectroscopy. The photocatalytic activity of the synthesized nanocomposites was tested in the degradation of methylene blue (MB) dyes, as a model of water pollutants. A catalytic activity of 84% was achieved using a nanocomposite with a percentage of 3.125% GO, after 90 min sunlight irradiation. Furthermore, embedded copper and silver nanoparticles were used as dopants to study their effects on the activity of the photocatalyst. The GO-ZnO-Cu nanocomposite showed that the activity toward MB degradation was decreased by 50%, while a significant increase in the activity of MB degradation was achieved by the GO-ZnO-Ag nanocomposite. The removal efficiency of MB by the GO-ZnO-Ag nanocomposite reached 100% after 40 min of sunlight irradiation. Thus, the GO-ZnO-Ag nanocomposite has the potential to be an efficient adaptable photocatalyst for the photodegradation of organic dyes in industrial wastewater.

Repositioning of the global epicentre of non-optimal cholesterol

Abstract: High blood cholesterol is typically considered a feature of wealthy western countries1,2. However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world3 and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health4,5. However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low- and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol—which is a marker of cardiovascular risk—changed from those in western Europe such as Belgium, Finland, Greenland, Iceland, Norway, Sweden, Switzerland and Malta in 1980 to those in Asia and the Pacific, such as Tokelau, Malaysia, The Philippines and Thailand. In 2017, high non-HDL cholesterol was responsible for an estimated 3.9 million (95% credible interval 3.7 million–4.2 million) worldwide deaths, half of which occurred in east, southeast and south Asia. The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and personal interventions to improve nutrition and enhance access to treatment throughout the world.

Pharmacy Students Perceptions of Their Distance Online Learning Experience During the COVID-19 Pandemic: A Cross-Sectional Survey Study

Abstract: Introduction:The COVID-19 pandemic imposed dramatic changes on educational practices worldwide. Many universities and schools have moved into the delivery of their courses and educational programs ...

A Review of Artificial Intelligence Methods for Condition Monitoring and Fault Diagnosis of Rolling Element Bearings for Induction Motor

Abstract: The fault detection and diagnosis (FDD) along with condition monitoring (CM) and of rotating machinery (RM) have critical importance for early diagnosis to prevent severe damage of infrastructure in industrial environments. Importantly, valuable industrial equipment needs continuous monitoring to enhance the safety, reliability, and availability and to decrease the cost of maintenance of modern industrial systems and applications. However, induction motor (IM) has been extensively used in several industrial processes because it is cheap, reliable, and robust. Rolling bearings are considered to be the main component of IM. Undoubtedly, any failure of this basic component can lead to a serious breakdown of IM and for whole industrial system. Thus, many current methods based on different techniques are employed as a fault prognosis and diagnosis of rolling elements bearing of IM. Moreover, these techniques include signal/image processing, intelligent diagnostics, data fusion, data mining, and expert systems for time and frequency as well as time-frequency domains. Artificial intelligence (AI) techniques have proven their significance in every field of digital technology. Industrial machines, automation, and processes are the net frontiers of AI adaptation. There are quite developed literatures that have been approaching the issues using signals and data processing techniques. However, the key contribution of this work is to present an extensive review of CM and FDD of the IM, especially for rolling elements bearings, based on artificial intelligent (AI) methods. This study highlights the advantages and performance limitations of each method. Finally, challenges and future trends are also highlighted.