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The growing number of people watching audiovisual products in languages other than their mother tongue necessitated translation to bridge the linguistic barriers and ensure complete comprehension as perceived by the source text audience. The translation of cultural references is an increasingly important issue in the translation field, specifically in audiovisual products, and the findings of this study will show the efficiency of applying the transcreation procedure to overcome such challenges. Moreover, the main aim of this paper is to analyze the applicability of the transcreation procedure in translating cultural references found in audiovisual materials, particularly in Masameer animated cartoons, to determine if implementing this procedure will result in a successful translation. The paper attempts to answer the question: How can the application of the transcreation procedure help convey the meaning and effect of the cultural reference found in the source text? This research paper has followed the qualitative method to analyze the implementation of the transcreation procedure on the examples that contain cultural-specific items. It is found that the application of transcreation is essential to fill the cultural gap in a creative way that preserves the meaning of the original. Thus, transcreation is valuable because it gives a sense of creativity, adapts the text culturally, and delivers accurate translation.

Background: Irritable bowel syndrome (IBS) is a common chronic gastrointestinal disease identified by frequent episodes of abdominal pain, bloating, and disturbance of bowel habits which are owed to several factors including environmental, stressors, and certain food and medications. This study aimed to estimate the prevalence of IBS among Princess Nourah Bint Abdulrahman University (PNU) students in health and non-health colleges and to determine its associated factors and impact. Methods: A cross-sectional study was conducted among 514 female students of PNU's health and non-health colleges. Participants were selected by simple random sampling. A self-administered questionnaire was used to collect data including sociodemographic data and the Rome IV scale, in addition to risk factors and impact-related variables. Results: The prevalence of IBS among PNU students was 31.9%. Health students had a higher prevalence as compared to non-health students (36.6% vs. 27.2%). Emotional stress and traumatic life events were more commonly reported among students with IBS (p < 001). The symptoms of IBS were aggravated by fatty food and dairy in most of the participants 46.3% and 43.9%, respectively. Symptoms affecting confidence, such as bloating, were the most reported impact statement (54.9%). Conclusion: About one-third of the participants had IBS, with a higher prevalence reported among health college students. The risk factors that had the highest impact on students with IBS were dairy and fatty food, emotional stress, traumatic life events, and medications which had a negative impact on the student's daily life.

Ghazwa B Korayem,1,&ast; Omar A Alshaya,2– 4,&ast; Nirvana Alnajjar,1 Ahad Alawad,1 Rand Alotaibi,1 Nader Bin Sheraim,5 Fatemah M Hakami,6 Ohud S Alsudyyes,6 Rahaf H Alsoghayer,6 Lina M Alhushan,6 Asma H Qudayr,6,7 Majed S Al Yami,2– 4 Omar A Almohammed6,8 1Department of Pharmacy Practice, College of Pharmacy, Princess Nourah bint Abdulrahman University, Riyadh, 11671, Saudi Arabia; 2Department of Pharmacy Practice, College of Pharmacy, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia; 3Pharmaceutical Care Department, King Abdulaziz Medical City, Riyadh, Saudi Arabia; 4King Abdullah International Medical Research Center, Riyadh, Saudi Arabia; 5Pharmaceutical Care Division, King Abdullah bin Abdulaziz University Hospital, Riyadh, Saudi Arabia; 6Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia; 7Department of Clinical Pharmacy, College of Pharmacy, Taif University, Taif, Saudi Arabia; 8Pharmacoeconomics Research Unit, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia&ast;These authors contributed equally to this workCorrespondence: Ghazwa B Korayem, Department of Pharmacy Practice, College of Pharmacy, Princess Nourah bint Abdulrahman University, P.O.Box 84428, Riyadh, 11671, Saudi Arabia, Tel +966504161649, Email gbkorayem@pnu.edu.sa Omar A Almohammed, Department of Clinical Pharmacy, College of Pharmacy, King Saud University, P.O. Box 2457, Riyadh, 11451, Saudi Arabia, Tel +966 555104065, Email oalmohammed@ksu.edu.saBackground: Although parenteral anticoagulation lead-in is not recommended with apixaban and rivaroxaban, parenteral anticoagulation is often used to replace apixaban or rivaroxaban lead-in doses for the initial phase treatment of VTE. Thus, our study compares the safety and effectiveness of lead-in parenteral anticoagulation to lead-in apixaban or rivaroxaban in patients who received apixaban or rivaroxaban for VTE treatment.Methods: A multi-center retrospective cohort study included adult patients (aged ≥  18 years) admitted to the hospital with acute VTE and treated with either apixaban or rivaroxaban. Patients were grouped depending on the lead-in anticoagulation received for initial VTE treatment into the “Direct oral anticoagulation (DOAC) lead-in” group if patients received an appropriate lead-in dose of apixaban and rivaroxaban and patients who received parenteral lead-in the “parenteral lead-in” group.Results: A total of 389 patients were included; the DOAC lead-in group included 296 patients, whereas 93 patients were in the parenteral lead-in group. VTE recurrence (rVTE) during hospitalization and within 30 days was numerically higher in the parenteral lead-in group compared to the DOAC lead-in group (3.3% vs 0.6%; p=0.09 and 1.1% vs 0.7%; p=0.560), with a significantly higher number of patients with rVTE at 90 days (5.4% vs 1.4%; p=0.039). However, none of the patient’s characteristics were significantly associated with the incidence of rVTE. In addition, the major bleeding rate during hospitalization was significantly higher among the parenteral lead-in group than in the DOAC lead-in group (14.0% vs 3.7%; p< 0.001).Conclusion: Parenteral anticoagulation lead-in before starting maintenance of apixaban and rivaroxaban showed a significantly higher risk of bleeding and a trend toward higher VTE recurrence than the DOAC lead-in. This study adds to the evidence supporting the utilization of the DOAC lead-in regimen in treating patients with VTE. Still, larger studies with robust designs are needed to confirm these findings.Keywords: rivaroxaban, apixaban, lead-in, parenteral anticoagulation, venous thromboembolism, recurrence

This study aims to investigatethe contextual performance and the interaction of its dimensions represented by the organizational commitment and organizational citizenship behavior of the working woman. The study followed the descriptive analytical approach and a questionnaire was designed and distributed to a sample of 92 clerks in the headquarters of the Ministry of Health in Gadarif State /Sudan. The results of the study found that the contextual performance is moderate (medium). Also, there is a statistically significant partial impact of organizational commitment on organizational citizenship behavior through emotional and normative commitments only. Interestingly, there is no significant impact of the continual commitment on organizational citizenship behavior at the individual and organizational levels. Finally, the study offers several recommendations that would help decision-makers in building and strengthening contextual performance to positively drive the overall performance.

Hypertension is the major risk factor for cardiovascular disease and early death worldwide. Early and prompt management of hypertension can significantly prevent complications. Owing to the extensive usage of antihypertensive drugs, worldwide mean blood pressure has stayed constant or declined to some extent during the previous four decades although high prevalence in reported in developing countries. CCBs are a class of drugs that are commonly used to lower blood pressure and are structurally and functionally diverse. They are generally well accepted and have less adverse effects. The purpose of this research is to review the available information about role and complication of existing and newer CCBs in hypertension treatment. As soon as CCBs were utilized to treat hypertension, they earned a reputation as potent antihypertensives that significantly and consistently lowered blood pressure in people of all ages and races in mono and combination therapy. CCBs work by reducing peripheral vascular resistance. Newly available CCBs may be therapeutically more effective in treatment of hypertensive individuals with chronic kidney disease than the L-type CCB. Lercanidipine is a third generation CCB that has fewer side effects and is used in people with a high risk of target organ damage and elderly patients. CCBs are associated with certain side effects including peripheral edema, hypotension, headaches, conduction abnormalities among various others. Some studies have also associated use of CCBs with modest risk increase for myocardial infarction and heart failure. Further clinical research is required to elaborately study the efficacy of CCBs in management of hypertension.

A variety of new pyrazolines, isoxazolines, and amide derivatives were designed, synthesized, and tested in vitro for their cytotoxic potential against the breast cancer cell line MCF-7. Nabumetone is a prodrug that is used as non-steroidal anti-inflammatory drug (NSAID). Before synthesis, the Molecular docking program (GOLD suite v. 5.7.1) was used to evaluate the selectivity for ER-α receptor, which demonstrated good agreement with the in vitro findings. Specifically, compounds 1e and 2e that target the ER- α receptor had the greatest PLP fitness values of (75.61 and 73.36), respectively, when compared to the tamoxifen reference medication, which had a PLP fitness of (92.78). The IC50 values for the synthesized compounds revealed that compound (1e) has a high IC50 value of 19 µM against MCF-7, compared to tamoxifen, which has an IC50 value of (18.02) µM.

Immune Thrombocytopenia (ITP) is an autoimmune disorder characterised by a low platelet countless than 100? ×? 10^9/L, purpura, and hemorrhagic episodes induced by antiplatelet autoantibodies without anemia or leukopenia. Immune thrombocytopenia (ITP) occurs in 2 to 4/100? 000 adults. A wide range of signs and symptoms, from modest mucocutaneous petechiae to severe, life-threatening organ haemorrhage, are seen in ITP patients. they may present to the emergency department (ED) with life-threatening bleeding as a result of their thrombocytopenia. ITP has two distinct clinical syndromes, manifesting as an acute condition in children and a chronic condition in adults. IgG autoantibodies make circulating platelets more sensitive. It causes these cells to be removed more quickly by antigen-presenting cells (macrophages) of the spleen, and occasionally the liver or other components of the monocyte-macrophage system. Current evidence supports alternatives to splenectomy for second-line management of patients with persistently low platelet counts and bleeding. By increasing platelet production, bone marrow compensates for platelet breakdown. Immune Thrombocytopenia most commonly arises within a few weeks after a viral infection in healthy children and young adults. Immunosuppressive treatment is usually effective in treating ITP. Many patients with ITP require no emergent treatment. However, the emergency physician should start treatment with a platelet transfusion, corticosteroids, and intravenous immune globulin (IVIG) as soon as the patient with suspected ITP arrives at the ED with serious haemorrhage.The diagnosis is usually made by ruling out all known causes of thrombocytopenia. This review aims to summarize current evidences regarding prevalence, causes, diagnosis and management of immune thrombocytopenia. Keywords

This paper proposes new improved binary versions of the Sine Cosine Algorithm (SCA) for the Feature Selection (FS) problem. FS is an essential machine learning and data mining task of choosing a subset of highly discriminating features from noisy, irrelevant, high-dimensional, and redundant features to best represent a dataset. SCA is a recent metaheuristic algorithm established to emulate a model based on sine and cosine trigonometric functions. It was initially proposed to tackle problems in the continuous domain. The SCA has been modified to Binary SCA (BSCA) to deal with the binary domain of the FS problem. To improve the performance of BSCA, three accumulative improved variations are proposed (i.e., IBSCA1, IBSCA2, and IBSCA3) where the last version has the best performance. IBSCA1 employs Opposition Based Learning (OBL) to help ensure a diverse population of candidate solutions. IBSCA2 improves IBSCA1 by adding Variable Neighborhood Search (VNS) and Laplace distribution to support several mutation methods. IBSCA3 improves IBSCA2 by optimizing the best candidate solution using Refraction Learning (RL), a novel OBL approach based on light refraction. For performance evaluation, 19 real-wold datasets, including a COVID-19 dataset, were selected with different numbers of features, classes, and instances. Three performance measurements have been used to test the IBSCA versions: classification accuracy, number of features, and fitness values. Furthermore, the performance of the last variation of IBSCA3 is compared against 28 existing popular algorithms. Interestingly, IBCSA3 outperformed almost all comparative methods in terms of classification accuracy and fitness values. At the same time, it was ranked 15 out of 19 in terms of number of features. The overall simulation and statistical results indicate that IBSCA3 performs better than the other algorithms.

Sliding mode (SM) has been selected as the controlling technique, and the state observer (SO) design is used as a component of active disturbance rejection control (ADRC) to reduce the knee position trajectory for therapeutic purposes. The suggested controller will improve the needed position performances for the Exoskeleton system when compared to the proportional-derivative controller (PD) and SMC as feed-forward in the ADRC approach, as shown theoretically and through computer simulations. Simulink tool is used in this comparison to analyze the nominal case and several disruption cases. The results of mathematical modeling and simulation studies demonstrated that SMC with a disturbance observer strategy performs better than the PD control system and SMC in feed-forward with a greater capacity to reject disturbances and significantly better than these controllers. Performance indices are used for numerical comparison to demonstrate the superiority of these controllers.

COVID-19 has affected all aspects of human life so far. From the outset of the pandemic, preventing the spread of COVID-19 through the observance of health protocols, especially the use of sanitizers and disinfectants was given more attention. Despite the effectiveness of disinfection chemicals in controlling and preventing COVID-19, there are critical concerns about their adverse effects on human health. This study aims to assess the health effects of sanitizers and disinfectants on a global scale. A total of 91,056 participants from 154 countries participated in this cross-sectional study. Information on the use of sanitizers and disinfectants and health was collected using an electronic questionnaire, which was translated into 26 languages via web-based platforms. The findings of this study suggest that detergents, alcohol-based substances, and chlorinated compounds emerged as the most prevalent chemical agents compared to other sanitizers and disinfectants examined. Most frequently reported health issues include skin effects and respiratory effects. The Chi-square test showed a significant association between chlorinated compounds (sodium hypochlorite and per-chlorine) with all possible health effects under investigation (p-value

Post-malaria neurological syndrome (PMNS) is a rare, self-limiting condition that presents with a wide range of neurological manifestations after clearance of malarial infection, especially Plasmodium Falciparum, most patients recover without residual deficits. Here we present a case of a 29-year-old, male with a recent history of malaria treated successfully, who presented due to a generalized tonic-clonic seizure, without any other neurological symptoms, the examination and labs were unremarkable, he underwent a computer tomography (CT) scan and Magnetic resonant imaging (MRI) which both showed two areas of vasogenic edema involving the subcortical white matter of left frontal and right posterior parasagittal regions, all autoimmune screens, infection workup from blood and CSF were negative, he underwent a brain biopsy that showed intense perivascular inflammation with neuronal loss and gliosis, findings are nonspecific and can be seen in a variety of condition. The patient’s condition improved, and he was discharged without any complications.

Wearable robots are commonly used for rehabilitation and they are made to fit the human body to assist persons who are unable to help themselves. The design of controllers became necessary to enhance the dynamic motion of these exoskeleton systems when worn by patients. In this study, active disturbance rejection control (ADRC) with reduced-order extended state observer (RESO) has been proposed for motion control of exoskeleton knee-assisting device to eliminate the phase lag induced by full-order extended state observer (FESO). The design analysis of RESO-based ADRC has been presented and a computer simulation has been conducted to verify the effectiveness of the proposed controller. A comparison study has been made between ADRC based on RESO and that based on FESO in terms of transient and robustness characteristics. The simulated results showed that the RESO-based ADRC gives better transient and load rejection capabilities compared to the controller with FESO.

This work focuses on design of trajectory-tracking control based on active disturbance rejection control (ADRC) controller for knee joint exoskeleton device. The device is worn by disable patients and it is actuated by ADRC to perform the exercises prescribed by physician doctor for rehabilitation of humanoid's lower limb. In order to improve the tracking performance and robustness characteristics of ADRC, minor modification has been made in its structure, which is represented by adding feed forward control signal to reference angular acceleration. The numerical simulations via MATLAB software environment have been conducted with various model uncertainties and external disturbances to assess the performance of modified control scheme. The proposed controller showed improvement in trajectory tracking error, rejection of exerted disturbances, and robustness against parameter uncertainties.

Background Aspirin is widely used as a cardioprotective agent due to its antiplatelet and anti-inflammatory properties. The literature has assessed and evaluated its role in hospitalized COVID-19 patients. However, no data are available regarding its role in COVID-19 critically ill patients. This study aimed to evaluate the use of low-dose aspirin (81-100 mg) and its impact on outcomes in critically ill patients with COVID-19. Method A multicenter, retrospective cohort study of all critically ill adult patients with confirmed COVID-19 admitted to intensive care units (ICUs) between March 1, 2020, and March 31, 2021. Eligible patients were classified into two groups based on aspirin use during ICU stay. The primary outcome was in-hospital mortality, and other outcomes were considered secondary. Propensity score matching was used (1:1 ratio) based on the selected criteria. Results A total of 1033 patients were eligible, and 352 patients were included after propensity score matching. The in-hospital mortality (HR 0.73 [0.56, 0.97], p = 0.03) was lower in patients who received aspirin during stay. Conversely, patients who received aspirin had a higher odds of major bleeding than those in the control group (OR 2.92 [0.91, 9.36], p = 0.07); however, this was not statistically significant. Additionally, subgroup analysis showed a possible mortality benefit for patients who used aspirin therapy prior to hospitalization and continued during ICU stay (HR 0.72 [0.52, 1.01], p = 0.05), but not with the new initiation of aspirin (HR 1.22 [0.68, 2.20], p = 0.50). Conclusion Continuation of aspirin therapy during ICU stay in critically ill patients with COVID-19 who were receiving it prior to ICU admission may have a mortality benefit; nevertheless, it may be associated with an increased risk of significant bleeding. Appropriate evaluation for safety versus benefits of utilizing aspirin therapy during ICU stay in COVID19 critically ill patients is highly recommended.

Abdulrhman Fahad Aljouie,1,2 Ahmed Almazroa,2,3 Yahya Bokhari,1,2 Mohammed Alawad,1,2 Ebrahim Mahmoud,4 Eman Alawad,4 Ali Alsehawi,5 Mamoon Rashid,1,2 Lamya Alomair,1,2 Shahad Almozaai,6 Bedoor Albesher,6 Hassan Alomaish,5 Rayyan Daghistani,5 Naif Khalaf Alharbi,2,7 Manal Alaamery,2,8– 10 Mohammad Bosaeed,2– 4 Hesham Alshaalan5 1Bioinformatics Section, King Abdullah International Medical Research Center, Riyadh, Saudi Arabia; 2King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia; 3Department of Imaging Research, King Abdullah International Medical Research Center, Riyadh, Saudi Arabia; 4Department of Medicine, Ministry of National Guard - Health Affairs, Riyadh, Saudi Arabia; 5Department of Medical Imaging, Ministry of National Guard - Health Affairs, Riyadh, Saudi Arabia; 6College of Pharmacy, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia; 7Department of Infectious Disease Research, King Abdullah International Medical Research Center, Riyadh, Saudi Arabia; 8Department of Developmental Medicine, King Abdullah International Medical Research Center, Riyadh, Saudi Arabia; 9KACST-BWH Center of Excellence for Biomedicine, Joint Centers of Excellence Program, King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia; 10King Abdulaziz City for Science and Technology (KACST)-Saudi Human Genome Satellite Lab at Abdulaziz Medical City, Ministry of National Guard Health Affairs (MNGHA), Riyadh, Saudi ArabiaCorrespondence: Mohammed AlawadBioinformatics Section, King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi ArabiaEmail malawad@sdaia.gov.saAhmed AlmazroaDepartment of Imaging Research, King Abdullah International Medical Research Center King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi ArabiaEmail almazroaah@ngha.med.saBackground: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in Wuhan, China, in late 2019 and created a global pandemic that overwhelmed healthcare systems. COVID-19, as of July 3, 2021, yielded 182 million confirmed cases and 3.9 million deaths globally according to the World Health Organization. Several patients who were initially diagnosed with mild or moderate COVID-19 later deteriorated and were reclassified to severe disease type.Objective: The aim is to create a predictive model for COVID-19 ventilatory support and mortality early on from baseline (at the time of diagnosis) and routinely collected data of each patient (CXR, CBC, demographics, and patient history).Methods: Four common machine learning algorithms, three data balancing techniques, and feature selection are used to build and validate predictive models for COVID-19 mechanical requirement and mortality. Baseline CXR, CBC, demographic, and clinical data were retrospectively collected from April 2, 2020, till June 18, 2020, for 5739 patients with confirmed PCR COVID-19 at King Abdulaziz Medical City in Riyadh. However, of those patients, only 1508 and 1513 have met the inclusion criteria for ventilatory support and mortalilty endpoints, respectively.Results: In an independent test set, ventilation requirement predictive model with top 20 features selected with reliefF algorithm from baseline radiological, laboratory, and clinical data using support vector machines and random undersampling technique attained an AUC of 0.87 and a balanced accuracy of 0.81. For mortality endpoint, the top model yielded an AUC of 0.83 and a balanced accuracy of 0.80 using all features with balanced random forest. This indicates that with only routinely collected data our models can predict the outcome with good performance. The predictive ability of combined data consistently outperformed each data set individually for intubation and mortality. For the ventilator support, chest X-ray severity annotations alone performed better than comorbidity, complete blood count, age, or gender with an AUC of 0.85 and balanced accuracy of 0.79. For mortality, comorbidity alone achieved an AUC of 0.80 and a balanced accuracy of 0.72, which is higher than models that use either chest radiograph, laboratory, or demographic features only.Conclusion: The experimental results demonstrate the practicality of the proposed COVID-19 predictive tool for hospital resource planning and patients’ prioritization in the current COVID-19 pandemic crisis.Keywords: COVID-19, mortality, NIV, X-rays, CBC, random forest, SMOTE; machine learning

This study investigates the effect of different types of local coarse aggregate, available in Saudi Arabia, on the strength of high-strength concrete. The utilized coarse aggregates are basalt and two different aggregates of limestone, denoted as limestone 1 and limestone 2. The results of 7 and 28 days compressive strength with different percentages of Micro Silica (MS) (i.e. range from 0 to 10%) show that the compressive strength of high strength concrete (HSC) is influenced by the type of coarse aggregate. Limestone 2 reaches the highest compressive strength followed by the types limestone 1 and then basalt. Properties of coarse aggregate influence the compressive strength of HSC, such as impact value (AIV), and texture. Also, the impact value variation between saturated surface dry (SSD) and dry conditions of the coarse aggregate affect significantly the compressive strength of HSC.

The body mass index (BMI) is commonly used in the assessment of obesity and overweight; however, its use in the diagnosis of adverse effects of obesity is questioned. This study aims to explore the agreement between the BMI and the calculated body fat percentage (BF%) in detecting obesity-induced ventilatory abnormalities. We carried out a cross-sectional study on a random sample of 150 healthy male students, aged 17 to 25, with a mean age of 20.8 ± 2.6 years. We measured the BMI, BF%, and pulmonary function of each participant. The students were classified into overweight-obese and normal groups based on the BMI and the BF% results. The Chi-square test was performed to analyze differences between the groups. About one-fifth of all participants had a fat mass ≥ 20%, among which 90% fulfilled the BMI definition of overweight and obesity (p < 0.05). The comparison between the two BF% groups showed that 20% of the overweight-obese group had a significant reduction in FEV1 (p= 0.025, Relative Risk= 3.00, 95% Confidence Interval= 1.13-7.99), and 23% of them had a significant reduction in FVC (p= 0.012, Relative Risk= 3.11, 95% Confidence Interval= 1.26-7.68). The changes in FEV1/FVC were statistically insignificant. The effects of the BMI categories on the dynamic lung volumes were statistically insignificant. The direct estimation of BF% is better than the calculation of BMI in the diagnosis of obesity-induced abnormalities in lung function. The use of BMI as an indicator of obesity in population health studies should be avoided.

This study revealed the system of a lower limb exoskeleton created for knee rehabilitation. The exoskeleton has been extensively used in rehabilitation robotic device research, but its practical applicability is limited due to its high nonlinearity and uncertain behavior. As a result, the control technique is critical in increasing the efficacy of rehabilitation devices. For the rehabilitation and help of a patient with a lower-limb condition, a sliding mode control (SMC) with proportional derivative (PD) control approach are used as parallel loops. Active disturbances rejection control (ADRC) is used by these controllers to cancel any external influences. To overcome the degradation of disturbance rejection and robustness caused by a failure to fully adjust for the entire disturbance, a (SMC) loop was introduced to the control regulation. By assessing performance indices related to the estimated inaccuracy, the results demonstrate the effectiveness of the suggested controller. Simulink is used for simulation and analysis.

The stock market is an exciting field of interest to many people regardless of their occupational background. It is a market where individuals with adequate knowledge can join and earn an additional income. Nowadays, life expenses have increased. Hence, the number of people investing in stocks is increasing dramatically. Anyone may indeed start participating in the stock market at any time, yet it is not ensured that they will profit from this investment. The stock market is a risky field of investment, given that it is unknown whether the stock will rise or fall. Stock market prediction using Artificial Intelligence techniques is a possible way to help people anticipate stock market directions. Current research showed that many factors aid in changing the stock market value in general and specifically in the Saudi stock market. To our knowledge, most research studies only consider historical data in predicting stock market trends. However, this research aims to enhance the accuracy of the daily closing price for three Saudi stock market sectors by considering historical and sentimental data. Several intelligent algorithms are considered, and their performance indicators are discussed and contrasted against each other. This research concluded that more accurate stock market prediction models could be produced by employing historical and sentimental data.

Background Previous studies have shown that non-critically ill COVID-19 patients co-infected with other respiratory viruses have poor clinical outcomes. However, limited studies focused on this co-infections in critically ill patients. This study aims to evaluate the clinical outcomes of critically ill patients infected with COVID-19 and co-infected by other respiratory viruses. Methods A multicenter retrospective cohort study was conducted for all adult patients with COVID-19 who were hospitalized in the ICUs between March, 2020 and July, 2021. Eligible patients were sub-categorized into two groups based on simultaneous co-infection with other respiratory viruses throughout their ICU stay. Influenza A or B, Human Adenovirus (AdV), Human Coronavirus (i.e., 229E, HKU1, NL63, or OC43), Human Metapneumovirus, Human Rhinovirus/Enterovirus, Middle East Respiratory Syndrome Coronavirus (MERS-CoV), Parainfluenza virus, and Respiratory Syncytial Virus (RSV) were among the respiratory viral infections screened. Patients were followed until discharge from the hospital or in-hospital death. Results A total of 836 patients were included in the final analysis. Eleven patients (1.3%) were infected concomitantly with other respiratory viruses. Rhinovirus/Enterovirus (38.5%) was the most commonly reported co-infection. No difference was observed between the two groups regarding the 30-day mortality (HR 0.39, 95% CI 0.13, 1.20; p = 0.10). The in-hospital mortality was significantly lower among co-infected patients with other respiratory viruses compared with patients who were infected with COVID-19 alone (HR 0.32 95% CI 0.10, 0.97; p = 0.04). Patients concomitantly infected with other respiratory viruses had longer median mechanical ventilation (MV) duration and hospital length of stay (LOS). Conclusion Critically ill patients with COVID-19 who were concomitantly infected with other respiratory viruses had comparable 30-day mortality to those not concomitantly infected. Further proactive testing and care may be required in the case of co-infection with respiratory viruses and COVID-19. The results of our study need to be confirmed by larger studies.

Motivation Biological processes are regulated by underlying genes and their interactions that form gene regulatory networks (GRNs). Dysregulation of these GRNs can cause complex diseases such as cancer, Alzheimer’s and diabetes. Hence, accurate GRN inference is critical for elucidating gene function, allowing for the faster identification and prioritization of candidate genes for functional investigation. Several statistical and machine learning-based methods have been developed to infer GRNs based on biological and synthetic datasets. Here, we developed a method named AGRN that infers GRNs by employing an ensemble of machine learning algorithms. Results From the idea that a single method may not perform well on all datasets, we calculate the gene importance scores using three machine learning methods—random forest, extra tree and support vector regressors. We calculate the importance scores from Shapley Additive Explanations, a recently published method to explain machine learning models. We have found that the importance scores from Shapley values perform better than the traditional importance scoring methods based on almost all the benchmark datasets. We have analyzed the performance of AGRN using the datasets from the DREAM4 and DREAM5 challenges for GRN inference. The proposed method, AGRN—an ensemble machine learning method with Shapley values, outperforms the existing methods both in the DREAM4 and DREAM5 datasets. With improved accuracy, we believe that AGRN inferred GRNs would enhance our mechanistic understanding of biological processes in health and disease. Availabilityand implementation https://github.com/DuaaAlawad/AGRN. Supplementary information Supplementary data are available at Bioinformatics online.

The authors aimed to extend the discharge of Sirolimus from the tablets with a blend of herbal and synthetic polymers. In this study, Sirolimus was taken as a model drug, Hydroxy Propyl Methyl Cellulose as a synthetic polymer and mucilage from Hibiscus rosa sinensis leaves as a natural polymer. Sirolimus is an orphan drug used to treat Lymphangioleiomyomatosis damage and to suppress body refuse towards the transplanted organs. Sirolimus matrix tablets made with the blend of Hibiscus rosa sinensis leaves mucilage and Hydroxy Propyl Methyl Cellulose. The blend was assessed for flow possessions and the designed tablets were categorized for official and non-official tests including Sirolimus discharge. The Sirolimus matrix tablets possess good Sirolimus content with passible pre and post-formulation parameters. The study concludes that there were no chemical interactions between Sirolimus with polymers used. The study also revealed that Hibiscus rosa sinensis leaves mucilage can be a good polymer in grouping with other polymers for prolonged drug discharge.

Blood is essential to life. The number of blood cells plays a significant role in observing an individual’s health status. Having a lower or higher number of blood cells than normal may be a sign of various diseases. Thus it is important to precisely classify blood cells and count them to diagnose different health conditions. In this paper, we focused on classifying white blood cells subtypes (WBC) which are the basic parts of the immune system. Classification of WBC subtypes is very useful for diagnosing diseases, infections, and disorders. Deep learning technologies have the potential to enhance the process and results of WBC classification. This study presented two fine-tuned CNN models and four hybrid CNN-based models to classify WBC. The VGG-16 and MobileNet are the CNN architectures used for both feature extraction and classification in fine-tuned models. The same CNN architectures are used for feature extraction in hybrid models; however, the Support Vector Machines (SVM) and the Quadratic Discriminant Analysis (QDA) are the classifiers used for classification. Among all models, the fine-tuned VGG-16 performs best, its classification accuracy is 99.81%. Our hybrid models are efficient in detecting WBC as well. 98.44% is the classification accuracy of the VGG-16+SVM model, and 98.19% is the accuracy of the MobileNet+SVM.

The spread of COVID-19 and its associated health risks have caused people to stay inside their homes for long periods, changing the home’s function from simply being a dwelling to a place that supports varied activities. These new activities were not planned for the original house design; the pandemic forced people to fit these activities within the available space during lockdowns. The purpose of this study was to identify how people adapted and interacted with their home designs during the COVID-19 pandemic. The research followed the screening process recommended in the PRISMA Statement by reviewing the literature on home design published during the pandemic to provide an overview of how people adapted and interacted with their home design in different countries. Five databases were searched, and 10 studies were ultimately included. The review showed that people adapted the available spaces by connecting the features of existing spaces with new activities. For example, the privacy of bedrooms allowed them to become learning or workspaces through the addition of appropriate furniture and accessories. Previously unused spaces also began to be occupied. People changed the way they view their homes. However, challenges remained for some activities because of the absence of appropriate infrastructure, leading to a lack of space, storage, privacy, lighting, quiet, views, and fresh air. This study’s contribution should help designers and those working in the housing sector to design flexible housing that is suitable for sudden and stressful conditions and guarantees its residents’ quality of life.

The emergence of genetic mutations in chromosomal genes and the transmissible plasmid-mediated colistin resistance gene may have helped in the spread of colistin resistance among various

Background :Telemedicine is a rapidly expanding technology used in healthcare settings, especially since the emergence of COVID-19. For this intervention to be implemented successfully, important skills are required from health professionals. Hence, this study seeks to determine the preparedness of African medical students for the use of telemedicine in healthcare delivery by assessing their knowledge, attitude, and skill set , Methods: This was a descriptive cross-sectional study. Data were collected online through a 33-item pre-tested, self-administered questionnaire from three selected medical schools in Africa. Data were analysed using descriptive and analytical statistics with a significant level of 0.05. Data analysis was done on SPSS version 20, Results : Only 559 respondents were eligible for the study. 338 (60.5%) were male and the most prevalent age range was 21-23 years (276, 49.4%). 346 (61.9%) had good knowledge while 461 (82.5%) expressed a good attitude toward telemedicine. Only 144 (25.8%) had a good skill set in using telemedicine. 513 (91.6%) respondents agreed and strongly agreed that the use of telemedicine should be included in medical training. There was a statistically significant association between the skill set of respondents and schools (p=0.001) and gender (pConclusions: The respondents have a good attitude but average knowledge and poor skill set of telemedicine usage in healthcare delivery. However, the majority are interested in learning about telemedicine in medical training. This study shows the need to incorporate telemedicine within the curricula of African medical schools.

Perforated peptic ulcer (PPU) treatment guidelines are still up for discussion. Due to the morbidity and mortality linked to each, the use of both operative and non-operative management, including conservative and endoscopic treatment, is still debatable. A standardized protocol has been used to write a best evidence topic. The discussion focused on whether operative management for PPU is preferable to non-operational management or vice versa. MEDLINE, the Cochrane Library, Scopus, and the Web of Science were the databases used to conduct an electronic search of the pertinent literature. We found 56 articles, out of these only 5 studies were found to be appropriate to answer the question. The outcome assessed was failure of management. The best evidence showed that both operative and non-operative management can be used with similar outcomes depending on the patient selection for each category.

Wireless Sensor Networks (WSNs) have a wide range of applications in human life. Accordingly, WSNs have beenthoroughly considered in research community to improve their performance and address their challenges. Eventreporting in WSNs has always been a major challenge in terms of energy consumption. Event reporting requiressensing the event and sending a reporting packet from the sensor to the centralized base station (BS). However,sensor’s energy is limited and stored in a non-rechargeable battery. Therefore, several event-reporting (or datacollection) protocols have been proposed to improve energy consumption in WSNs, and consequently, to extendtheir lifetime. In this paper, we propose an efficient event reporting protocol for WSNs called Event ReportingProtocol Based on Distributed Data Aggregation (ERP-DDA). This protocol mainly aims at reporting any event byno more than one sensor node such that energy saving is satisfied in the whole network. To achieve this goal, ERPDDAis mainly based on the following features: it is a cluster-based protocol, it is a multi-hop routing protocol, itapplies distributed data aggregation, and it employs variable clustering and cluster head selection. Simulationsshow that ERP-DDA significantly extends the lifetime of WSNs compared with other related protocols.

Bidirectional Encoder Representations from Transformers (BERT) and BERT-based approaches are the current state-of-the-art in many natural language processing (NLP) tasks; however, their application to document classification on long clinical texts is limited. In this work, we introduce four methods to scale BERT, which by default can only handle input sequences up to approximately 400 words long, to perform document classification on clinical texts several thousand words long. We compare these methods against two much simpler architectures - a word-level convolutional neural network and a hierarchical self-attention network - and show that BERT often cannot beat these simpler baselines when classifying MIMIC-III discharge summaries and SEER cancer pathology reports. In our analysis, we show that two key components of BERT - pretraining and WordPiece tokenization - may actually be inhibiting BERT's performance on clinical text classification tasks where the input document is several thousand words long and where correctly identifying labels may depend more on identifying a few key words or phrases rather than understanding the contextual meaning of sequences of text.

Introduction: Dental materials whenever used for restorations in the oral cavity can be subjected to dental erosion because of the gastric juices and can cause roughness and act as a nidus for the growth plaque. Aim of this study was to evaluate impact of artificial gastric acid on surface roughness of dental restorations, examining scientific studies published from 2010-2020. Materials and Methods: This study follows and complies with principles of PRISMA guidelines for a systematic review research methodology. In March 2020, an initial search was carried out in the MEDLINE (PubMed), Science Direct, Google Scholar, and Saudi Digital Library database of indexed journals from 2010-2020 using the keywords: impact,” “effect,” “gastric acid,” “gastric juice,” “indirect restorations,” “dental materials,” “dental ceramics,” “crowns,”. Bibliographic materials from these articles were then utilized to find other sources. Results: The MEDLINE (PubMed) search retrieved thirty articles, of which three were relevant to the study. Total articles found in Google scholar were 11,500 article, in which 11 were analyzed for further review and only seven matched the allocated inclusion and exclusion criteria. 512 articles were found in the Saudi Digital Library and only three of these articles followed the inclusion criteria of this study. Conclusions: It has been proved by numerous studies that acidic exposure significantly affects the surface roughness of dental ceramics negatively. There is lack of evidence to support the claim that Zirconia is the dental ceramic of choice for patients with intrinsic acid regurgitation. Thus, it is recommended to conduct further studies in order to assess and confirm the best material that can withstand such acidic environment.