ABSTRACT
There is a great interest in online learning systems, especially due to COVID-19 pandemic. However, there are a lot of limitations and challenges of online laboratory learning systems. This paper presents an efficient technique that provides an intelligent virtual tutor for online laboratory environment, as in engineering and science sectors. Based on the analysis of the student's mouse activities, the AI virtual Assistant or virtual tutor will automatically estimate the difficulties that the student stuck during conducting the steps of lab's experiment. Hence, the virtual tutor can assist the student, accordingly. The technique is based on multi-threshold that are used to discriminate different levels of difficulties. The values of these thresholds are estimated and optimized via the genetic algorithm. The experimental results show that discrimination between different student behaviors can be achieved accurately and efficiently. © 2022 IEEE.
ABSTRACT
During the recent COVID-19 outbreak, many educational institutions had to operate fully remotely and conduct examinations online. Conducting hands-on software lab exams online raises serious issues and concerns such as: 1) the heterogeneity of examinees' personal computers, 2) the computers may not be powerful enough to run the required software for the hands-on exam, especially hardware intensive programs, 3) cheating and plagiarism are hardly controllable since examinees are using their personal computers and they can look up whatever information they need. The paper proposes a highly available and scalable software cloud architecture that utilizes modern cloud technologies, DevOps principles, and infrastructure as code tools of various categories to facilitate the construction of a highly available and scalable architectural solution that automates the delivery of software lab exams. Evaluation and results of the proposed architecture illustrate that a cloud instance that is preconfigured with all the required exam material can be instantiated and completely ready to use in an average of 149 seconds. Moreover, deploying the backend server on a Kubernetes Cluster allowed the system to automatically scale and handle sudden loads due to Kubernetes' auto-scaling and self-healing features. © 2022 IEEE.
ABSTRACT
Dexamethasone (glucocorticoid) was recently shown to be a life-saving drug for the treatment of SARS-CoV-2 disease. Water and sediments can be contaminated by sewage treatment plants when this product is widely used. Accordingly, we evaluated the effects of dexamethasone as pharmaceutical residue on Clarias gariepinus, following exposure and post-exposure recovery on blood biochemical, antioxidant, and cytokine markers. Three experimental groups were examined. Control, fish exposed to 0.3 mg/L of dexamethasone, and fish exposed to 3 mg/L of dexamethasone for 7 days, followed by a 15-days recovery period. Hematological indices, such as red blood cell number, hemoglobin (Hb), platelets, mean corpuscular hemoglobin concentration, and large lymphocytes, were significantly declined following the exposure to dexamethasone compared to control. In contrast, hematocrit (Ht), mean corpuscular volume, monocytes, small lymphocytes, and mean corpuscular hemoglobin increased significantly depending on the dose–concentration. Liver and kidney functions, other biochemical parameters (albumin and globulin), cortisol, and cytokine (IL-1β and IL-6) concentrations increased significantly after exposure to dexamethasone compared to control. Antioxidants and acetylcholinesterase enzymes were significantly decreased in catfish treated with dexamethasone cumulatively with doses. After a recovery period, blood biochemical, antioxidant, and cytokine markers were still elevated compared with the control group. In conclusion, dexamethasone at concentrations present in water bodies causes deleterious effects on blood biomarkers, biochemical, and antioxidant as well as immune upregulation in catfish until after depuration period.
ABSTRACT
Online learning has emerged as powerful learning methods for the transformation from traditional education to open learning through smart learning platforms due to Covid-19 pandemic. Despite its effectiveness, many studies have indicated the necessity of linking online learning methods with the cognitive learning styles of students. The level of students always improves if the teaching methods and educational interventions are appropriate to the cognitive style of each student individually. Currently, psychological measures are used to assess students' cognitive styles, but about the application in virtual environment, the matter becomes complicated. The main goal of this study is to provide an efficient solution based on machine learning techniques to automatically identify the students' cognitive styles by analyzing their mouse interaction behaviors while carrying out online laboratory experiments. This will help in the design of an effective online laboratory experimentation system that is able to individualize the experiment instructions and feedback according to the identified cognitive style of each student. The results reveal that the KNN and SVM classifiers have a good accuracy in predicting most cognitive learning styles. In comparison to KNN, the enlarged studies ensemble the KNN, linear regression, neural network, and SVM reveal a 13% increase in overall total RMS error. We believe that this finding will enable educators and policy makers to predict distinct cognitive types in the assessment of students when they interact with online experiments. We believe that integrating deep learning algorithms with a greater emphasis on mouse location traces will improve the accuracy of our classifiers' predictions.
ABSTRACT
COVID-19 pandemic has led to a great interest in online learning systems. However, the lack of suitable online laboratory learning systems has posed a particular challenge for sectors that need laboratory experimentation activities as in engineering and science domains. This paper presents a simple but efficient technique for providing intelligent virtual tutor that can assist students in online laboratory experimentation environment. The proposed technique is based on analyzing and modelling the student's mouse interaction behavior for identifying the difficulties that the student faced during conducting the lab's experiment, and hence providing the suitable assistance. The different levels of difficulties will be detected using the trajectory of mouse movement activities. The obtained results verify accurate and very fast operation for identifying the student's difficulties.
ABSTRACT
The worldwide outbreak due to COVID-19 pandemic has led to a great interest in e-learning. However, the lack of suitable online laboratory management systems has posed a particular challenge for sectors that need laboratory activities such as engineering, science and technology. In this paper, the requirements and design for a flexible AI-based laboratory learning system (LLS) that can support online laboratory experimentations are presented. The elicitation of the LLS design requirements is decided based on a conducted survey for a set of LLS features. The LLS is designed with the flexibility to support various types of online experimentations such as virtual or remote controlled experiments using either desktop or web applications. The virtualization technique is used to manage the laboratory resources and allow multiple users to access the LLS. Moreover, the proposed LLS introduces the use of AI techniques to provide efficient virtual lab assistant and adaptive assessment process. © 2021 IEEE.
ABSTRACT
Background: PTEFb/CDK9-mediated transcription of short-lived anti-apoptotic survival proteins and oncogenes like MCL-1 and MYC plays a critical role in a variety of cancers. VIP152 (formerly BAY 1251152), a potent and highly selective CDK9 inhibitor, has been evaluated in a Phase 1 dose-escalation study in patients with advanced cancer. The maximum tolerated dose was 30 mg once weekly administered in consecutive 21-day cycles, based on neutropenia as the dose-limiting toxicity (JCO 2018;36:2507;NCT02635672). DHL is defined as dual rearrangement of the MYC gene and either the BCL2 or BCL6 genes;the resulting overexpression of MYC and BCL2/BCL6 make it particularly difficult to treat. Patients with DHL have a poor prognosis and no standard of care. Considering the impact of CDK9 inhibition on MYC, an exploratory cohort of patients with DHL was added to the study. Methods: Patients with refractory or relapsed DHL were eligible. VIP152 was administered once weekly as a 30-minute IV infusion on Days 1, 8 and 15 of a 21-day cycle. Tumor response was assessed according to the revised Cheson criteria (2007). Results: To date a total of 7 patients have been enrolled and were evaluable at the time of data cutoff (24NOV2020). The patients were mostly men (6/7 pts, 86%) with a median (range) age of 70 (58-84) years. All patients received ≥2 prior therapies, including 2 patients with bone marrow transplant. Three of 7 patients (29%) had ≥3 prior therapies. The median time on treatment was 22 days (range 8-1361 days). The most common adverse events of any grade were: constipation, fatigue, nausea (each 3/7 pts, 43%) and abdominal pain, diarrhea, lymphocyte count decrease, neutrophil count decrease, skin infection, tumor pain, and vomiting (each 2/7 pts, 29%). Most were Grade 1 and Grade 2. The Grade 3 adverse events were fatigue, lymphocyte count decrease, neutrophil count decrease (each 1/7 pts, 14%) and tumor pain (2/7 pts, 29%). One Grade 4 lymphocyte count decrease was reported. Two patients had a serious adverse event (Grade 3 syncope and Grade 3 tumor pain). Two patients had dosing held for an adverse event;however, no patient withdrew from treatment due to any adverse events. One death occurred due to disease progression. Pharmacodynamic biomarker analysis showed significant reduction of MYC, PCNA, and MCL-1 mRNA in all patients across multiple timepoints. Antitumor activity consisted of 2 complete metabolic responses in 7 patients (29%) based on investigator-assessed FDG-PET scans. Due to the COVID pandemic, the patients withdrew consent after 3.7 and 2.3 years, respectively, of treatment. Both patients were in complete metabolic response. Conclusions: VIP152 had a manageable safety profile, on-target pharmacodynamic activity and signs of durable monotherapy antitumor activity in patients with DHL. These encouraging results warrant further evaluation of VIP152 in patients with MYCdriven lymphoma and solid tumors.
ABSTRACT
OBJECTIVES: The aim of the present work was to explore the perspectives of Egyptian Rheumatology staff members as regards the coronavirus disease-19 (COVID-19) vaccine. METHODS: The survey is composed of 25 questions. Some questions were adapted from the global rheumatology alliance COVID-19 survey for patients. RESULTS: 187 rheumatology staff members across Egypt from 18 universities and authorizations actively participated with a valid response. The mean time needed to complete the survey was 17.7 ± 13 min. Participants were 159 (85%) females (F:M 5.7:1). One-third agreed that they will be vaccinated once available, 24.6% have already received at least one dose, 29.4% are unsure while 16% will not take it. Furthermore, 70.1% agreed that they will recommend it to the rheumatic diseases (RD) patients once available, 24.1% are not sure while 5.9% will not recommend it. RD priority to be vaccinated against COVID-19 in descending order include SLE (82.9%), RA (55.1%), vasculitis (51.3%), systemic sclerosis (39.6%), MCTD (31.6%), Behcet's disease (28.3%). The most common drugs to be avoided before vaccination included biologics (71.7%), DMARDs (44.4%), biosimilars (26.7%), IVIg (17.1%) and NSAIDs (9.1%). CONCLUSIONS: The results of the study and specifically the low rate of acceptability are alarming to Egyptian health authorities and should stir further interventions to reduce the levels of vaccine hesitancy. As rheumatic disease patients in Egypt were not systematically provided with the vaccine till present, making the vaccine available could as well enhance vaccine acceptance. Further studies to investigate any possible side effects, on a large scale of RD patients are warranted.
Subject(s)
Attitude of Health Personnel , COVID-19 Vaccines/administration & dosage , Rheumatology/methods , Vaccination/psychology , COVID-19 , COVID-19 Vaccines/adverse effects , Egypt , Female , Humans , Male , Pandemics , Rheumatic Diseases/drug therapy , Rheumatic Diseases/psychology , SARS-CoV-2 , Surveys and Questionnaires , Universities , Vaccination/statistics & numerical data , Vaccination Refusal/psychologyABSTRACT
COVID-19 is a newly discovered deadly disease with no proven definitive treatment until now. It is now proved that it can affect different body organs which necessitate intensive care management. Ozone (O3) therapy was used before for treating various viral infections like hepatitis B, human immune deficiency virus (HIV), and Ebola viruses. O3 also can manage hypoxia and increase tissue oxygenation, besides its anti-inflammatory and immunomodulatory properties which may have an important role in the management of cytokine storm. We used rectal O3 insufflation therapy assuming that it may have a beneficial role in the management of COVID-19 disease. Two sessions of rectal O3 therapy were given to a 60-year-old female patient who was confirmed COVID-19 positive. Before applying O3 therapy, she was hypoxic (sPO2:90%) despite mechanical ventilation with high fraction inspired oxygen (FiO2:90%). After therapy, she was markedly improved and discharged to the inpatient ward and then discharged home on day 10 post-admission. Another 40-year-old male patient who was confirmed COVID-19 positive and was home isolated received one session of O3 therapy. Before therapy, he was hypoxic (sPO2:85% on room air and 95% with O2 face mask 5 L/min). The patient showed gradual improvement over the next 3 days after therapy and becomes oxygen-independent (sPO2 became 94-97% on room air). No adverse effects were noticed in both cases. Rectal O3 insufflation can be used safely as adjuvant management for patients with COVID-19 disease.