Showing papers by "Najran University published in 2021"

Faculty’s and Students’ Perceptions of Online Learning During COVID-19

Abstract: COVID-19 pandemic has disrupted teaching in a vriety of institutions. It has tested the readiness of academic institutions to deal with such abrupt crisis. Online learning has become the main method of instruction during the pandemic in Jordan. After 4 months of online education, two online surveys were distributed to investigate faculty’s and Students’ perception of the learning process that took place over that period of time with no face to face education. In this regard, the study aimed to identify both faculty’s and students’ perceptions of online learning, utilizing two surveys one distributed to 50 faculty members and another 280 students were selected randomly to explore the effectiveness, challenges, and advantages of online education in Jordan. The analysis showed that the common online platforms in Jordan were Zoom, Microsoft Teams offering online interactive classes, and WhatsApp in communication with students outside the class. The study found that both faculty and students agreed that online education is useful during the current pandemic. At the same time, its efficacy is less effective than face-to-face learning and teaching. Faculty and students indicated that online learning challenges lie in adapting to online education, especially for deaf and hard of hearing students, lack of interaction and motivation, technical and Internet issues, data privacy, and security. They also agreed on the advantages of online learning. The benefits were mainly self-learning, low costs, convenience, and flexibility. Even though online learning works as a temporary alternative due to COVID-19, it could not substitute face-to-face learning. The study recommends that blended learning would help in providing a rigorous learning environment. © Copyright © 2021 Almahasees, Mohsen and Amin.

UHPC evolution, development, and utilization in construction: a review

Abstract: An advanced development in construction industry was achieved by applying ultra-high-performance concrete technology (UHPC). Intensive research efforts had been concentrated in construction to produced amazing levels of qualities with strength greater than 150 MPa and high durability that had never been thought possible before. With this technology, it is possible to construct structures beyond the usual designs but with limited use in construction since it is not commercially viable to replace conventional concrete in most applications. This is attributed to the high cost of materials, the lack of their availability, limited design codes, and complicated manufacturing and curing techniques. This paper reviews the evolution of UHPC and the suggested ideas to replace its expensive composites by cementitious materials. However, concrete made with these alternative materials will not be of the same quality as the standard UHPC. Another promising choice, which seems to be more practical and easier to promote UHPC technology in construction, is looming on the horizon. It is based on the utilization of UHPC in hybrid structures by combining UHPC with other construction materials. The cost of production will hopefully be reduced with such composite structures that have the advantages of the combined materials. Therefore, it is recommended to continue research into this choice which will increase the potential of UHPC to be more accepted in many different construction applications.

Advances in Responsively Conductive Polymer Composites and Sensing Applications

Abstract: Conductive polymer composites (CPCs) have attracted intensive attention for several decades because they can endow the materials with not only good processability but also various functionalities e...

Skin Cancer Detection: A Review Using Deep Learning Techniques

Abstract: Skin cancer is one of the most dangerous forms of cancer. Skin cancer is caused by un-repaired deoxyribonucleic acid (DNA) in skin cells, which generate genetic defects or mutations on the skin. Skin cancer tends to gradually spread over other body parts, so it is more curable in initial stages, which is why it is best detected at early stages. The increasing rate of skin cancer cases, high mortality rate, and expensive medical treatment require that its symptoms be diagnosed early. Considering the seriousness of these issues, researchers have developed various early detection techniques for skin cancer. Lesion parameters such as symmetry, color, size, shape, etc. are used to detect skin cancer and to distinguish benign skin cancer from melanoma. This paper presents a detailed systematic review of deep learning techniques for the early detection of skin cancer. Research papers published in well-reputed journals, relevant to the topic of skin cancer diagnosis, were analyzed. Research findings are presented in tools, graphs, tables, techniques, and frameworks for better understanding.

Sounds and acoustic emission-based early fault diagnosis of induction motor: A review study:

Abstract: Nowadays, condition-based maintenance (CBM) and fault diagnosis (FD) of rotating machinery (RM) has a vital role in the modern industrial world. However, the remaining useful life (RUL) of machiner...

Role of Hybrid Deep Neural Networks (HDNNs), Computed Tomography, and Chest X-rays for the Detection of COVID-19.

Abstract: COVID-19 syndrome has extensively escalated worldwide with the induction of the year 2020 and has resulted in the illness of millions of people. COVID-19 patients bear an elevated risk once the symptoms deteriorate. Hence, early recognition of diseased patients can facilitate early intervention and avoid disease succession. This article intends to develop a hybrid deep neural networks (HDNNs), using computed tomography (CT) and X-ray imaging, to predict the risk of the onset of disease in patients suffering from COVID-19. To be precise, the subjects were classified into 3 categories namely normal, Pneumonia, and COVID-19. Initially, the CT and chest X-ray images, denoted as 'hybrid images' (with resolution 1080 × 1080) were collected from different sources, including GitHub, COVID-19 radiography database, Kaggle, COVID-19 image data collection, and Actual Med COVID-19 Chest X-ray Dataset, which are open source and publicly available data repositories. The 80% hybrid images were used to train the hybrid deep neural network model and the remaining 20% were used for the testing purpose. The capability and prediction accuracy of the HDNNs were calculated using the confusion matrix. The hybrid deep neural network showed a 99% classification accuracy on the test set data.

Challenging of using CuO nanoparticles in a flat plate solar collector- Energy saving in a solar-assisted hot process stream

Abstract: Background Flat plate solar collectors (FPSCs) can meet the needs of low-temperature process industries by providing a hot flow stream. In this regard, the addition of nanoparticles can improve the energy-saving potential of the FPSCs. In this study, the effectiveness of using copper oxide (CuO) nanoparticles in a solar-assisted hot process stream was investigated. Methods Using transient-based numerical approaches, the efficacy of loading CuO nanoparticles at 0.1 vol.% into water on collector heat gain was examined. Using effectiveness–NTU method, the nanofluid efficacy was challenged by adding a two-pipe heat exchanger to diminish heating power usage in a hot process stream. Findings The results revealed that if a water-filled solar-assisted hot process stream was used, the energy-saving will be 670, 383 and 225 kWh m 2 . year at 60, 120 and 240 lit hr under Najran climate conditions. Taking into account energy-saving of 712, 415.5 and 242.5 kWh m 2 . year for nanofluid, it was found that incorporating CuO into a solar-assisted hot process stream has been successful. Owing to using CuO, the effectiveness of the solar-assisted hot process stream was improved within the range of 6-12.8%.

Depression and Anxiety in Patients With Cancer: A Cross-Sectional Study.

Abstract: Objectives Depression and anxiety persist in cancer patients, creating an additional burden during treatment and making it more challenging in terms of management and control. Studies on the prevalence of depression and anxiety among cancer patients in the Middle East are limited and include many limitations such as their small sample sizes and restriction to a specific type of cancer in specific clinical settings. This study aimed to describe the prevalence and risk factors of depression and anxiety among cancer patients in the inpatient and outpatient settings. Materials and Methods A total of 1,011 patients (399 inpatients and 612 outpatients) formed the study sample. Patients' psychological status was assessed using the Hospital Anxiety and Depression Scale (HADS), the Patient Health Questionnaire (PHQ-9), and the Generalized Anxiety Disorder 7-item (GAD-7) scale. The prevalence rate of depressive and anxious symptomatology was estimated by dividing the number of patients who exceeded the borderline score: 10 or more for each subscale of the HADS scale, 15 or more for the GAD-7 scale, and 15 or more in the PHQ-9 by the total number of the patients. Risk factors were identified using logistic regression. Results The prevalence of depressive and anxious symptomatology among all patients was 23.4% and 19.1-19.9%, respectively. Depressive symptomatology was more prevalent across patients who were hospitalized (37.1%) compared with patients in the outpatient setting (14.5%) (p < 0.001). Similarly, anxious symptomatology was more prevalent in the inpatient setting (p < 0.001). In the inpatient setting, depressive symptomatology was more prevalent among patients with bladder cancer, while severe anxious symptomatology was more prevalent across patients with lung cancer. In the outpatient setting, depressive and anxious symptomatology was more prevalent among breast and prostate cancer patients, respectively. Despite that, around 42.7% and 24.8% of the patients, respectively, reported that they feel anxious and depressed, and only 15.5% of them were using medications to manage their conditions. Conclusion Our study findings demonstrated a higher prevalence of depressive and anxious symptomatology in the inpatient setting and advanced disease stages. In addition, the underutilization of antidepressant therapy was observed. There is a need to consider mental disorders as part of the treatment protocol for cancer patients. Enhanced clinical monitoring and treatment of depression and anxiety of cancer patients are required.

Progress in nanomedicine-based drug delivery in designing of chitosan nanoparticles for cancer therapy

Abstract: Cancer is among the most dreadful fatal diseases globally, and the efficacy of recent chemotherapeutic approaches is limited due to many related drawbacks. The major limitation associated with canc...

Cubic shaped hematite (α-Fe2O3) micro-structures composed of stacked nanosheets for rapid ethanol sensor application

Abstract: Herein, the synthesis, characterization, and ethanol gas sensing properties of hematite iron oxide(α-Fe2O3) microstructures were investigated. Detailed examinations using different techniques confirmed the high-density growth and rhombohedral crystal structure of the synthesized Fe2O3 micro-structures with an average crystal size of 38.29 nm. The appearance of several Raman-active A1g(1), A1g(2), and Eg modes in Raman-scattering spectrum further revealed the formation of the hematite phase. The sensor device was fabricated using Fe2O3 micro-structures and tested for various gases such as ethanol, carbon monoxide (CO), and hydrogen (H2). It was observed that the fabricated sensor demonstrated a high response of 13.1for 100 ppm ethanol gas concentration at a temperature of 400 °C. Including the response and recovery times for the fabricated sensors, the transient response for various gases was also recorded and analyzed. The fabricated sensor exhibited a rapid gas response at 400 °C for ethanol gas (13.1) compared to CO (1.95) and H2 (1.71) gases for 100 ppm gas concentrations. A plausible ethanol sensing mechanism was also proposed and presented.

Design and Energy Requirements of a Photovoltaic-Thermal Powered Water Desalination Plant for the Middle East.

Abstract: Seawater or brackish water desalination is largely powered by fossil fuels, raising concerns about greenhouse gas emissions, particularly in the arid Middle East region. Many steps have been taken to implement solar resources to this issue; however, all attempts for all processing were concentrated on solar to electric conversion. To address these challenges, a small-scale reverse-osmosis (RO) desalination system that is in part powered by hybrid photovoltaic/thermal (PVT) solar collectors appropriate for a remote community in the Kingdom of Saudi Arabia (KSA) was designed and its power requirements calculated. This system provides both electricity to the pumps and low-temperature thermal energy to pre-heat the feedwater to reduce its viscosity, and thus to reduce the required pumping energy for the RO process and for transporting the feedwater. Results show that both thermal and electrical energy storage, along with conventional backup power, is necessary to operate the RO continuously and utilize all of the renewable energy collected by the PVT. A cost-optimal sizing of the PVT system is developed. It displays for a specific case that the hybrid PVT RO system employs 70% renewable energy while delivering desalinized water for a cost that is 18% less than the annual cost for driving the plant with 100% conventional electricity and no pre-heating of the feedwater. The design allows for the sizing of the components to achieve minimum cost at any desired level of renewable energy penetration.

Silica-Based Bioactive Glasses and Their Applications in Hard Tissue Regeneration: A Review.

Abstract: Regenerative medicine is a field that aims to influence and improvise the processes of tissue repair and restoration and to assist the body to heal and recover. In the field of hard tissue regeneration, bio-inert materials are being predominantly used, and there is a necessity to use bioactive materials that can help in better tissue–implant interactions and facilitate the healing and regeneration process. One such bioactive material that is being focused upon and studied extensively in the past few decades is bioactive glass (BG). The original bioactive glass (45S5) is composed of silicon dioxide, sodium dioxide, calcium oxide, and phosphorus pentoxide and is mainly referred to by its commercial name Bioglass. BG is mainly used for bone tissue regeneration due to its osteoconductivity and osteostimulation properties. The bioactivity of BG, however, is highly dependent on the compositional ratio of certain glass-forming system content. The manipulation of content ratio and the element compositional flexibility of BG-forming network developed other types of bioactive glasses with controllable chemical durability and chemical affinity with bone and bioactivity. This review article mainly discusses the basic information about silica-based bioactive glasses, including their composition, processing, and properties, as well as their medical applications such as in bone regeneration, as bone grafts, and as dental implant coatings.

Depression and anxiety during the COVID-19 pandemic in Saudi Arabia: A cross-sectional study.

Abstract: AIMS: The emergence of the COVID-19 global pandemic, with a high transmission and mortality rate, has created an extraordinary crisis worldwide. Such an unusual situation may have an undesirable impact on the mental health of individuals which, in turn, may influence their outcomes. This study aimed to explore the influence of the COVID-19 pandemic on the psychological disposition of residents of the Kingdom of Saudi Arabia. METHODS: A cross-sectional study using an online survey was conducted in Saudi Arabia between 27 March and 27 April 2020. The Patient Health Questionnaire (PHQ-9) and Generalised Anxiety Disorder-7 (GAD-7) were used to assess depression and anxiety. Logistic regression analysis was used to identify predictors of these. RESULTS: A total of 2081 individuals participated in the study. The prevalence of depression and anxiety among the study participants was 9.4% and 7.3% respectively. Non-Saudi residents, individuals aged 50 years and above, divorced people, retired people, university students and those with an income between 2000 and 10 000 SR were at higher risk of developing depression. Saudi individuals, married people, the unemployed and those with a high income (>10 000 RS) were at higher risk of developing anxiety. CONCLUSION: We found that there is a wide range of Saudi residents who are at higher risk of developing mental illness during the current COVID-19 pandemic. Policymakers and mental healthcare providers are advised to provide continuous monitoring of the psychological consequences during this pandemic and provide the required health support.

The Impact of COVID-19 Pandemic Lockdown on the Incidence of New-Onset Type 1 Diabetes and Ketoacidosis Among Saudi Children.

Abstract: Background: Overburdened healthcare systems during the coronavirus disease (COVID-19) pandemic led to suboptimal chronic disease management, including that of pediatric type 1 diabetes mellitus (T1DM) The pandemic also caused delayed detection of new-onset diabetes in children; this increased the risk and severity of diabetic ketoacidosis (DKA) We therefore investigated the frequency of new-onset pediatric T1DM and DKA in Saudi Arabia during the COVID-19 pandemic and compared it to the same period in 2019 Methods: We conducted a multicenter retrospective cohort study, including patients aged 1-14 years admitted with new-onset T1DM or DKA during the COVID-19 pandemic (March-June 2020) and the same period in 2019 We assessed factors including age, sex, anthropometric measures, nationality, duration of diabetes, diabetes management, HbA1c levels, glycemic control, cause of admission, blood gas levels, etiology of DKA, DKA complications, length of hospital stay, and COVID-19 test status Result: During the lockdown, 106 children, compared with 154 in 2019, were admitted to 6 pediatric diabetes centers Among the admissions, DKA was higher in 2020 than in 2019 (83% vs 73%; P=005; risk ratio=115; 95% confidence interval, 104-126), after adjusting for age and sex DKA frequency among new-onset T1DM and HbA1c levels at diagnosis were higher in 2020 than in 2019 (26% vs 134% [P=<0001] and 121 ± 02 vs 108 ± 025 [P<0001], respectively) Females and older patients had a higher risk of DKA Conclusion: The lockdown implemented in Saudi Arabia has significantly impacted children with T1DM and led to an increased DKA frequency, including children with new-onset T1DM, potentially owing to delayed presentation

A fuzzy fractional model of coronavirus (COVID-19) and its study with Legendre spectral method.

Abstract: The virus which belongs to the family of the coronavirus was seen first in Wuhan city of China. As it spreads so quickly and fastly, now all over countries in the world are suffering from this. The world health organization has considered and declared it a pandemic. In this presented research, we have picked up the existing mathematical model of corona virus which has six ordinary differential equations involving fractional derivative with non-singular kernel and Mittag-Leffler law. Another new thing is that we study this model in a fuzzy environment. We will discuss why we need a fuzzy environment for this model. First of all, we find out the approximate value of ABC fractional derivative of simple polynomial function ( t - a ) n . By using this approximation we will derive and developed the Legendre operational matrix of fractional differentiation for the Mittag-Leffler kernel fractional derivative on a larger interval [ 0 , b ] , b ⩾ 1 , b ∈ N . For the numerical investigation of the fuzzy mathematical model, we use the collocation method with the addition of this newly developed operational matrix. For the feasibility and validity of our method we pick up a particular case of our model and plot the graph between the exact and numerical solutions. We see that our results have good accuracy and our method is valid for the fuzzy system of fractional ODEs. We depict the dynamics of infected, susceptible, exposed, and asymptotically infected people for the different integer and fractional orders in a fuzzy environment. We show the effect of fractional order on the suspected, exposed, infected, and asymptotic carrier by plotting graphs.