A Case of X-Linked Moesin-Associated Immune Deficiency in a Pediatric Patient

Background: X-Linked Moesin-Associated Immune Deficiency (X-MAID) is a rare severe combined immunodeficiency (SCID) subtype that can present at any age due to its variability. Depending on severity, patients demonstrate failure to thrive, recurrent bacterial and viral infections, and increased susceptibility to varicella zoster. It has been characterized by marked lymphopenia with hypogammaglobulinemia and impaired T-cell migration and proliferation. Case Presentation: This is a report of a Cuban 7-year-old male with poor weight gain and facial dysmorphia. He had a history of recurrent bacterial gastrointestinal infections and pneumonia beginning at 4 months of age. He additionally had 4-6 upper respiratory tract and ear infections annually. While still living in Cuba, he was admitted for a profound EBV infection in the setting of significant leukopenia. A bone marrow biopsy confirmed no malignancy. After he moved to the United States, his laboratory work-up revealed marked leukopenia with low absolute neutrophil and lymphocyte count with low T and B cells, very low immunoglobulin levels IgG, IgA, and IgM, and poor vaccination responses to streptococcus pneumonia, varicella zoster, and SARS-CoV-2. Genetic testing revealed a missense pathogenic variant c.511C>T (p.Arg171Trp) in the moesin (MSN) gene associated with X-MAID. He was managed with Bactrim and acyclovir prophylaxis, and immunoglobulin replacement therapy, and considered for hematopoietic stem cell transplantation. Discussion(s): Diagnosis of X-MAID should be considered in patients with recurrent infections and profound lymphopenia. As with SCID, early diagnosis and intervention is of utmost importance to prevent morbidity and mortality. This case demonstrates the importance of genetic testing in identifying this disease as it may prompt an immunologist to consider HSCT if conservative management is suboptimal. In the current literature, HSCT appears promising, but the long-term outcomes have yet to be described.Copyright © 2023 Elsevier Inc.

Telemedicine in the Era of Covid-19: Teleconsultation Architecture Platform

Teleconsultation is a type of medical practice similar to face-to-face consultations, and it allows a health professional to give a consultation remotely through information and communication technologies. In the context of the management of the coronavirus epidemic, the use of teleconsultation practices can facilitate healthcare access and limit the risk of avoidable propagation in medical cabinets. This paper presents the monitoring of international teleconsultation referrals in the era of Covid-19 to facilitate and prevent the suspension of access to care, the most common architecture for teleconsultation, communication technologies and protocols, vital body signals, video transmission, and the conduct of teleconsultation. The aim is to develop a teleconsultation platform to diagnose the patient in real time, transmit data from the remote location to the doctor, and provide a teleconsultation. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Chinese Normal Students' Satisfaction of Emergency Remote Learning in Higher Education during COVID-19 Pandemic

Despite the widespread use of emergency remote learning (ERL) during the COVID-19 pandemic in higher education, little is known about the determinants of Chinese normal student satisfaction with ERL. This study uses a questionnaire survey method to examine how Chinese normal students' satisfaction with ERL during the COVID-19 pandemic. The results show that Chinese normal students prefer face-to-face teaching to online teaching to some extent. According to the findings, it is important to emphasize students' pre-class preparation, adjust course assessment methods, change teachers' teaching strategies, create a positive teaching environment, boost students' learning confidence, and help them deal with their anxiety during ERL to improve the online course experience for Chinese students at normal universities. © 2023 ACM.

Student Perspective of Online Pedagogy Post COVID-19. A Missed Opportunity?

The COVID-19 pandemic has significantly changed education and caused unprecedented disruptions. These changes may disappear once the schools resume face-to-face classes in full force. Likewise, a positive change may not be necessarily what we want in education. This may be due to the existence of digital divide among students which cannot be ignored. During the COVID-19 pandemic, OneNote Class Notebook is used as an interactive digital whiteboard and has been evident as one of the best alternatives to the traditional whiteboard in the teaching and learning process. In this study, we aim to analyze students' perceptions of OneNote Class Notebook and the level of their continuous intention to use OneNote Class Notebook as an interactive digital whiteboard to replace the traditional whiteboard when school reopens with face-to-face lessons in the classroom in full force. The findings show that the students perceived that OneNote Class Notebook is indeed a useful tool to be used for calculus learning. But, it cannot be perceived as suitability to continue to be used during post COVID-19 period, when school reopens with physical classes in full force. In this regard, it reminds educators of the importance of rethinking education in the new normal post COVID-19 era from the perspective of curriculum studies. © 2023 IEEE.

The effect of the emergency shift to virtual instruction on student team dynamics

In spite of the sudden onset of the COVID-19 pandemic, many instructors who used team-based pedagogies shifted them online rather than suspending them entirely, but with limited time and resources. To examine the difference in team dynamics and outcomes for courses in Spring 2019 and Spring 2020 of over 1500 first-year engineering students per semester, Wilcoxon signed-rank tests and random forests method were used. Results show that students reported less improvement in team-member effectiveness, lower psychological safety, and less satisfaction in the semester with the emergency transition. However, students also reported lower conflict. The most important factor predicting project grades shifted from 'Interacting with teammates' to 'Having relevant knowledge, skills, and abilities' amid the emergency shift, accompanied by a reduction in team interdependence. In spite of the collection of data during an emergency transition, the foundation of face-to-face interaction before moving to virtual cooperation represents a useful contribution to research that has focused exclusively on virtual learning circumstances.

Have students' perceptions of online education changed with the easing of COVID-19 restrictions?

This research examines student preference toward online and on-ground (i.e., face-to-face) course delivery methods in higher education as a result of the easing of COVID-19 pandemic restrictions. Over 130 undergraduate and graduate students enrolled in Computer and Information Systems courses at a university located in the northeastern United States were surveyed from April 2021 to May 2022. The study found that with the easing of COVID-19 restrictions in Spring 2022, students significantly preferred on-ground over online courses in comparison to their preferences when COVID-19 restrictions were still high in 2021. None of the potential influencing factors contributing to the changed preference, including students' perceptions of online course effectiveness, self-skills supporting online learning (e.g., work independently without supervision, prioritization and time management), and the usefulness of classroom interaction in learning, were found to have significant differences from the time when COVID-19 restrictions were high to the present easing of them. © 2023 Issues in Information Systems. All rights reserved.

Social Distance and Face Mask Detection using vision-based sensors and IP cameras

Healthcare systems all over the world are strained as the COVID-19 pandemic's spread becomes more widespread. The only realistic strategy to avoid asymptomatic transmission is to monitor social distance, as there are no viable medical therapies or vaccinations for it. A unique computer vision-based framework that uses deep learning is to analyze the images that are needed to measure social distance. This technique uses the key point regressor to identify the important feature points utilizing the Visual Geometry Group (VGG19) which is a standard Convolutional Neural Network (CNN) architecture having multiple layers, MobileNetV2 which is a computer vision network that advances the-state-of-art for mobile visual identification, including semantic segmentation, classification and object identification. VGG19 and MobileNetV2 were trained on the Kaggle dataset. The border boxes for the item may be seen as well as the crowd is sizeable, and red identified faces are then analyzed by MobileNetV2 to detect whether the person is wearing a mask or not. The distance between the observed people has been calculated using the Euclidian distance. Pretrained models like (You only look once) YOLOV3 which is a real-time object detection system, RCNN, and Resnet50 are used in our embedded vision system environment to identify social distance on images. The framework YOLOV3 performs an overall accuracy of 95% using transfer learning technique runs in 22ms which is four times fast than other predefined models. In the proposed model we achieved an accuracy of 96.67% using VGG19 and 98.38% using MobileNetV2, this beats all other models in its ability to estimate social distance and face mask. © 2023 IEEE.

Smart Watch to Avoid Face Touching During Pandemic Condition

The most dangerous Coronavirus, COVID-19, is the source of this pandemic illness. This illness was initially identified in Wuhan, China, in December 2019, and currently sweeping the globe. The virus spreads quickly because it is so simple to transmit from one person to another. Fever is one of the obvious signs of COVID-19 and is one of its prevalent symptoms. The mucosal areas, such as the nose, eyes, and mouth, are among the most significant ways to catch this virus. In order to prevent and track the corona virus infection, this research suggests a face-touching detection and self-health report monitoring system. Their hygiene will immediately improve thanks to this system. In this pandemic circumstance, people use their hands in dirty environments like buses, trains, and other surfaces, where the virus can remain active for a very long time. With an accelerometer and a pulse oximeter sensor, this system alerts the user when they are carrying their hands close to their faces. © 2023 IEEE.

Video-Based Online Interactive System Using CNN Segmentation Method

In recent years, the COVID-19 has made it difficult for people to interact with each other face-to-face, but various kinds of social interactions are still needed. Therefore, we have developed an online interactive system based on the image processing method, that allows people in different places to merge the human region of two images onto the same image in real-time. The system can be used in a variety of situations to extend its interactive applications. The system is mainly based on the task of Human Segmentation in the CNN (convolution Neural Network) method. Then the images from different locations are transmitted to the computing server through the Internet. In our design, the system ensures that the CNN method can run in real-time, allowing both side users can see the integrated image to reach 30 FPS when the network is running smoothly. © 2023 IEEE.

Face Recognition Attendance System

The conventional procedure used in all of India's major regions is attendance monitoring on paper with pens. Although the final data is computerized, it takes a long time to get from a classroom to a database. The effectiveness of the classes is directly impacted by the number of absences. The attendance takes up almost half of the lecture's allotted time. The alternative method that is being used involves using fingerprints, but even this approach is ineffective since it takes so long. Due to the illnesses (COVID-19) spreading over the world, however, the situation as it stands right now does not make this the best course of action. Therefore, it will be advisable to develop a contactless and more efficient. © 2023 IEEE.

Masked Face Recognition Model with Explainable AI

Due to the recent COVID-19 pandemic, people tend to wear masks indoors and outdoors. Therefore, systems with face recognition, such as FaceID, showed a tendency of decline in accuracy. Consequently, many studies and research were held to improve the accuracy of the recognition system between masked faces. Most of them targeted to enhance dataset and restrained the models to get reasonable accuracies. However, not much research was held to explain the reasons for the enhancement of the accuracy. Therefore, we focused on finding an explainable reason for the improvement of the model's accuracy. First, we could see that the accuracy has actually increased after training with a masked dataset by 12.86%. Then we applied Explainable AI (XAI) to see whether the model has really focused on the regions of interest. Our approach showed through the generated heatmaps that difference in the data of the training models make difference in range of focus. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Perception and Practice Towards Hand Hygiene during Pandemic among Patients Visiting OPD in A Private Institution

One of the most significant and well-publicized prevention practises for Covid 19 is hand cleanliness. Face masks and social withdrawal are useless without good hand hygiene. The healthcare professionals can only intervene and raise awareness to enhance the public's hand hygiene practises after they are aware of the public's perceptions of and barriers to hand hygiene. A private dental facility had 150 outpatients participate in this cross-sectional questionnaire survey. Ten questions addressing various facets of hand hygiene and perceived obstacles made up the survey. The information from Google Forms was then imported into SPSS Version 15 using Excel. Data were presented as frequencies and percentages after the chi square test, and a p value of 0.05 or less was regarded as statistically significant.. In our study, 92.62 percent of outpatients at a private facility said that they continue to take measures against COVID19. 83.89% of our patients agreed that good hand hygiene habits are crucial for preventing COVID19. Whereas 38.26% of outpatients claimed to only wash their hands for 30 seconds, 33.56% of outpatients claimed to wash their hands for a full minute. In contrast to the 48.32 percent who said hand sanitizer is best and important for hand hygiene, 51.68 percent of outpatients said soap and water is best and essential for hand hygiene. According to the study's findings, the participants had a reasonable understanding of hand hygiene and its significance. Yet, there is a need for greater awareness of the finishing details on touch surfaces. Thus, it is advised that media-based propaganda and awareness campaigns have a positive impact and should be kept up, with a stronger focus on the finer points. © 2023 IEEE.

Masked Student Dataset of Expressions

Facial expression recognition (FER) algorithms work well in constrained environments with little or no occlusion of the face. However, real-world face occlusion is prevalent, most notably with the need to use a face mask in the current Covid-19 scenario. While there are works on the problem of occlusion in FER, little has been done before on the particular face mask scenario. Moreover, the few works in this area largely use synthetically created masked FER datasets. Motivated by these challenges posed by the pandemic to FER, we present a novel dataset, the Masked Student Dataset of Expressions or MSD-E, consisting of 1,960 real-world non-masked and masked facial expression images collected from 142 individuals. Along with the issue of obfuscated facial features, we illustrate how other subtler issues in masked FER are represented in our dataset. We then provide baseline results using ResNet-18, finding that its performance dips in the non-masked case when trained for FER in the presence of masks. To tackle this, we test two training paradigms: contrastive learning and knowledge distillation, and find that they increase the model's performance in the masked scenario while maintaining its non-masked performance. We further visualise our results using t-SNE plots and Grad-CAM, demonstrating that these paradigms capitalise on the limited features available in the masked scenario. Finally, we benchmark SOTA methods on MSD-E. The dataset is available at https://github.com/SridharSola/MSD-E. © 2022 ACM.

Rapid exchange of a percutaneous gastrostomy tube during an early episode of COVID-19

We retrospectively report a case of rapid exchange of a percutaneous radiologic gastrostomy tube (balloon-occluded type catheter) via off-label use of a pigtail catheter for nutrition supply during a very early episode of coronavirus disease 2019 (COVID-19) in an outpatient clinic. This case demonstrates that minimally invasive percutaneous procedures might be provided safely and effectively under appropriate precautions for preventing COVID-19 transmission during the pandemic.Copyright © 2023, Society of Gastrointestinal Intervention.

Covid-19 and online classes: Measuring Indian parents' attitude towards online classes at kindergarten and junior school level

The study aims to examine the readiness of Indian parents towards online classes at kindergarten and junior school levels, by identifying the perceived barriers, perceived effectiveness and health impact of online classes on young children. The study is based on data collected across a random sample of 750 parents of students studying at junior and kindergarten levels in urban private schools which offer online classes. The data was analyzed through exploratory factor analysis, ANOVA and multiple regression analysis. Technological, infrastructural, and personal barriers related to students, and parents, were identified as perceived barriers by parents in availing online classes for their kids. Parents' attitude towards online classes at kindergarten and primary levels gets negatively influenced by the barriers they face, and the perceived negative impact of technology usage on their kids' health, while;perceived effectiveness was found to have a positive impact on the parents' attitude. The study is unique as it includes the interest of such young stakeholders of the education system. The study highlights the barriers faced by parents related to online classes and the health-related concerns which play a major role in the adoption of online mode of education for their kids. Research gives insights to school authorities and the government to work on these barriers and make the online education system effective which is the need of the hour during COVID-19.

Cross Infection Control Awareness During 5th Wave of Covid 19 Pandemic, Omicron Variant Amongst the Dental Health Care Professionals of Government Sector University in Karachi, Pakistan

Objective: The objective of this study is to evaluate the awareness of cross-infection control measures followed by DHCPs during the 5th wave of Covid-19 pandemic, Omicron variant in a government sector university of Karachi, Pakistan. Method(s): A Cross-sectional study was conducted from June till September 2022 at Sindh Institute of Oral Health Science during the 5th wave of Covid 19 pandemic, Omicron variant. Data was collected from 153 DHCPs from government sector university using a self-administered questionnaire, comprising of 20 closed ended question to assess the awareness and practice of cross infection protocols by DHCPs. Result(s): 98.7% of the participants were vaccinated against Covid 19. 96% of the participants used surgical gowns, face shields, and face masks as part of PPE during examining patients and while performing procedure. After treatment 99.3% of participants washed hands with hand wash, soap or used antiseptic solution. 77.1% of participants asked for Covid 19 test report and 68.6% of participants asked for proof of vaccination against covid 19 before treating patients. 96.1% of participants recommended disinfection of dental unit after every patient. 98% of participants changed glove after every patient. 88.2% of the participants said they would carry all elective and emergency procedures. Conclusion(s): The results of this study show that DHCPs practicing at government sector university have adequate knowledge regarding prevention of cross infection protocols and their importance to limit spread of infections. But their practice of prevention of cross infection during Covid 19 pandemic is not ideal as percentage of DHCPs requiring proof of vaccination or negative reports for Covid 19 were rather low and the percentage of DHCPs willing to carry elective procedures along with emergency ones was rather high.Copyright © 2023 Lahore Medical And Dental College. All rights reserved.

Face Mask Detector for Raspberry Pi Based on Computer Vision and Edge Computing

The pandemic of the coronavirus disease 2019 has shown weakness and threats in various fields of human activity. In turn, the World Health Organization has recommended different preventive measures to decrease the spreading of coronavirus. Nonetheless, the world community ought to be ready for worldwide pandemics in the closest future. One of the most productive approaches to prevent spreading the virus is still using a face mask. This case has required staff who would verify visitors in public areas to wear masks. The aim of this paper was to identify persons remotely who wore masks or not, and also inform the personnel about the status through the message queuing telemetry transport as soon as possible using the edge computing paradigm. To solve this problem, we proposed to use the Raspberry Pi with a camera as an edge device, as well as the TensorFlow framework for pre-processing data at the edge. The offered system is developed as a system that could be introduced into the entrance of public areas. Experimental results have shown that the proposed approach was able to optimize network traffic and detect persons without masks. This study can be applied to various closed and public areas for monitoring situations. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

The Impact of Embodiment on Training Effectiveness

Due to the COVID-19 pandemic and compulsory social distancing, researchers in educational fields started to investigate alternatives to face-To-face (F2F) training methods with greater focus, such as video conferencing (VC) and virtual reality (VR) applications. This study investigated the differences between VC, VR and F2F training conditions by evaluating the level of body ownership and agency perceived by trainees. An electrical circuit repair task and multiple surveys were used to gather data from 106 participants in the form of four dependent variables: A circuit knowledge test, task completion rate, number of the subtasks completed by failing participants, and test phase duration. The study included two visits by each participant to measure knowledge retention while there were no training and surveys in Visit 2. Results showed significantly higher circuit learning and knowledge retention scores in F2F and VR conditions than in VC. Also, regarding the retention of knowledge, participants had significantly better knowledge retention in Visit 1 than Visit 2. The authors hope the results of this study enable training developers to enhance the learning process in computer mediated communications. © 2023 IEEE.

The Benefits and Limitations of Teaching English for Specific Purposes Online and Face-to-Face: Sport and Health Sciences Students' Perspectives

The restrictions imposed to limit the spread of COVID-19 resulted in the switch from in-person to online teaching, including the teaching of foreign languages in 2020-2022. This study uses the feedback of students who have studied English for Specific Purposes (ESP) in virtual and classroom settings. The aim is to investigate the benefits and limitations of each approach for language acquisition in ESP for sport and health sciences. A questionnaire to ascertain students' experiences was distributed to 60 students in sport and health sciences who studied ESP at the Latvian Academy of Sport Education. It was found that online and face-to-face studies of ESP in sport and health sciences tended to facilitate the acquisition of different language skills. In the questionnaire, students reported consistent progress in the study of vocabulary and reading the texts related to their area of study during both online and face-to-face studies, but less improvement was reported in the areas of grammar and speaking skills. Overall, synchronous online live classes would facilitate the steady and continuous development of all language skills if supplemented by continuous support from the teaching personnel, regular offline meetings or classes, and access to specially designed online resources.

Heading for the Future After COVID-19: Reflections and Recommendations on Teaching Processes in a Rapidly Changing Learning Landscape

The COVID-19 pandemic posed numerous challenges for instructors and students. Professors, for example, struggled to quickly and effectively migrate face-to-face courses to remote teaching modalities. What had not been anticipated, however, were the additional challenges to be managed when returning to face-to-face and in-person teaching. This reflective essay provides some insight into how faculty at the University of Puerto Rico attempted to modify teaching practices to re-engage disengaged students as they returned to the campus classroom. Also, recommendations about how to move forward by applying a pedagogy of renewal are made.