A Framework for Real-time Remote ECG Monitoring and Diagnoses

Enabled by the fast development of Internet of Things (IoT) technologies in recent years, the healthcare domain has witnessed significant advancements in wearable devices that seamlessly collect vital medical information. With the availability of IoT devices serving the healthcare domain, extraordinary amounts of sensory data are generated in real-time, requiring immediate diagnoses and attention in critical medical conditions. The provision of remote patient monitoring (RPM) and analytics infrastructure proved to be fundamental components of the healthcare domain during the Coronavirus pandemic. Traditional healthcare services are digitized and offered virtually, where patients are monitored and managed remotely without the need to go to hospitals. This paper presents a comprehensive RPM framework for real-time telehealth operations with scalable data monitoring, real-time analytics and decision-making, fine-grained data access and robust notification mechanisms in emergencies and critical health conditions. We focus on the overall framework architecture, enabling technologies integration, various system-level integrations and deployment options. Furthermore, we provide a use case application for patients with chronic heart conditions for real-time electrocardiogram (ECG) monitoring. We are releasing the framework as open-source software to the active research community. © 2022 IEEE.

Parents' digital skills and their development in the context of the Corona pandemic.

We investigate parents' and guardians' digital skills and the extent of their development in the context of the spread of the Corona epidemic. In addition, we sought to explore the differences in digital skills between parents and their employment status, age, and responsibility in teaching children. We sought to rely on the descriptive-analytical approach and prepared a scale of eight theoretical dimensions with the participation of 250 students' Saudi parents. The application of the study was by online submission form (via Edit Submission). Our findings showed that there was a discrepancy in the performance of the sample, which was very high in the dimensions of operational skills, instrumental skills, and cognitive constructivism skills. There were also differences between the effect of computers on the instrumental skills and cognitive constructivism skills of the parents. Parents' dependence on alternative digital sources in exploring for information, formulating knowledge, manipulating it, and criticizing. The learner can reach the cognitive level in a more flexible manner, which allows him to gain learning objectives. The knowledge navigation can be developed because of different online outdoor exercises and software familiar. This requires self-organization to search for appropriate knowledge to use in the renewal of the cognitive structure.

Creutzfeldt-Jakob Disease After the Second Dosage of The Novel Pfizer-Biontech Messenger Ribonucleic Acid (Mrna) COVID-19 Vaccination: A Case Report

Uncommon, rapidly progressing, and eventually fatal neurological condition called human prion disease. While most occurrences are sporadic, many can be acquired or inherited. In the current study, we focus on the case of a 63-year-old man who initially had vision problems then exhibits difficulty using his right side for daily activities and who begins to experience frequent falls with gait instability about a week after receiving the second dosage of the novel Pfizer-BioNTech messenger ribonucleic acid (mRNA) COVID-19 vaccination. Confidential findings confirmed the fatal diagnoses of sporadic Creutzfeldt-Jakob disease following a thorough study.

COVID-19 the Gateway for Future Learning: The Impact of Online Teaching on the Future Learning Environment

The COVID-19 virus has altered the nature of education. These modifications may be reversed once universities reopen. Nevertheless, a few of these modifications afford novel options to match pre-COVID-19 suggestions. This study's purpose is to study staff members' perceptions of online teaching during COVID-19, describe future projections regarding teaching, and identify the drivers of change in the future learning environment. The study community represents faculty staff in Saudi universities. The sample consisted of 127 faculty staff in nine Saudi universities. Participants had positive perceptions of the usage of e-learning platforms during COVID-19 according to data analysis (though negative experiences existed). Future research must focus on the subtle challenges of aligning theoretical and methodological designs to appropriately analyze the phenomenon under inquiry while contributing to a well-executed body of research in the field of educational technology. Future study is required to determine how teachers perceive information and communications technology (ICT) trading strategies in the light of COVID-19.

IL-2 and IL-1ß Patient Immune Responses Are Critical Factors in SARS-CoV-2 Infection Outcomes.

BACKGROUND: Immune dysregulation has been linked to morbidity and mortality in COVID-19 patients. Understanding the immunology of COVID-19 is critical for developing effective therapies, diagnostics, and prophylactic strategies to control the disease. AIM: The aim of this study was to correlate cytokine and chemokine serum levels with COVID-19 disease severity and mortality. SUBJECTS AND METHODS: A total of 60 hospitalized patients from the Tabuk region of Saudi Arabia with confirmed COVID-19 were included in the study. At hospital admission, the IL-1 ß, IL-2, IL-8, IL-10, LT-B4, and CCL-2 serum levels were measured. The cytokine levels in COVID-19 patients were compared to the levels in 30 healthy matched control subjects. RESULTS: The IL-1 ß, IL-2, LTB-4, CCL-2, and IL-8 levels (but not IL-10) were significantly higher in all COVID-19 patients (47 survivors and 13 non-survivors) compared with the levels in the healthy control group. In the non-survivor COVID-19 patients, patients' age, D-dimer, and creatinine kinase were significantly higher, and IL-1 ß, IL-2, and IL-8 were significantly lower compared with the levels in the survivors. CONCLUSION: Mortality rates in COVID-19 patients are associated with increased age and a failure to mount an effective immune response rather than developing a cytokine storm. These results warrant the personalized treatment of COVID-19 patients based on cytokine profiling.

Sludge-based activated carbon from two municipal sewage sludge precursors for improved secondary wastewater-treatment discharge-effluent

This study investigated the use of sludge-based activated carbon (SBAC) sorbent as an integrated waste-to-resources approach for the removal of contaminants from wastewater. We measured the ability of SBAC sorbents from two types of municipal sewage sludge (SS) precursors (thickened waste SS “TWSS-SBAC” and biosolids “Bio-SBAC”) from a Canadian wastewater treatment plant (WWTP) to stabilise emerging contaminants (ECs) from precursor SS and to remove ECs from the discharged effluent. The ECs were from pharmaceutical and personal care products (PPCPs), including antibiotics, disinfectants, and antibacterial hand-sanitisers and soaps, which were commonly used during the COVID-19 (coronavirus disease of 2019) pandemic. We measured the removal efficacy of Bio-SBAC at two dosages (1g/L and 10g/L) and TWSS-SBAC at one dosage (1g/L) via 30-min batch adsorption tests for eleven PPCPs at mean concentrations of 2–2337ng/L in the discharged effluent, and compared the results with those of other techniques and sorbents reported in literature. At both dosages, Bio-SBAC removed PPCPs, including four blood regulator compounds that have been extensively used since the pandemic outbreak (furosemide, gemfibrozil, glyburide, and warfarin), with their levels decreasing below the detection limit. The percentage removal for ibuprofen, 2-hydroxy-ibuprofen, and naproxen were 91.6–99.8% using 1g/L. The antimicrobial compounds triclosan and triclocarban were completely removed at both dosages. Ninety-nine percentage of bisphenol A was removed at 1g/L dosage and was completely removed at 10g/L. TWSS-SBAC showed similar performance as Bio-SBAC in removing PPCPs from the final effluent to improve the quality of wastewater discharged from a WWTP.

Automatic classification Infectious disease X-ray images based on Deep learning Algorithms

Recent technological advancements allow deep learning to be employed in practically every aspect of life. Because deep learning techniques are so precise, they can be used in medicine to classify and detect various diseases. The coronavirus (SARSCoV2) epidemic has recently affected global health systems. One of the ways to diagnose SARSCoV2 is with a chest X-ray. This paper proposes a deep learning technique to distinguish SARSCoV2 positive and normal cases. In this study, we fine-Tuned the deep learning models and hyperparameters, and the fine-Tuned deep learning models performed significantly better. To classify X-ray images, we developed a system based on deep learning algorithms that includes five models: Xception, VGG19, ResNet50, DenseNet121, and Inception. We offer deep learning models and algorithms that have been trained and evaluated to support medical efforts and reduce medical staff workload when dealing with SARSCoV2. In addition, the classification model that was proposed yields positive results because it makes use of accurate classification of the SARSCoV2 disease based on medical images. Additionally, the performance of our proposed CNN classification method for medical imaging was evaluated using various edge-based neural networks. The accuracy of tertiary classification with CNN will decrease as the number of classes in the training network grows. In tertiary classification, which includes normal and SARSCoV2 positive images, the proposed model achieved a 0.9897 accuracy. The proposed algorithm achieves a high level of classification accuracy when using the DenseNet121 model for binary classification. © 2022 IEEE.

12-Lead ECG Platform for Real-time Monitoring and Early Anomaly Detection

In response to the rapid digital revolution and the COVID-19 pandemic, the healthcare landscape has significantly shifted from physical to virtual care and telemedicine. As a result, healthcare providers and patients have shown increased interest and adoption for up-to-date technologies to monitor ongoing health conditions, including cardiovascular diseases. Driven by the importance of an efficient remote cardiovascular monitor for virtual care, we present a platform that enables remote ECG testing and provides ubiquitous data access to patients and their healthcare providers. A patent-pending 12-lead data acquisition ECG patch is attached to the patient's body to simultaneously collect heart signals, perform binary classification, and transmit the data to healthcare providers for further analysis at a high rate of up to 480 samples per second. As a preliminary classification phase, the presented platform introduces a machine learning technique to classify ECG signals near the ECG patch. The classification function is optimized for power-constrained devices using machine learning techniques. Moreover, the preliminary results of the energy consumption profile show that the ECG patch provides up to 37 hours of continuous 12-lead ECG streaming. © 2022 IEEE.

Effects of the COVID-19 pandemic on the environment, waste management, and energy sectors: a deeper look into the long-term impacts.

The COVID-19 pandemic not only has caused a global health crisis but also has significant environmental consequences. Although many studies are confirming the short-term improvements in air quality in several countries across the world, the long-term negative consequences outweigh all the claimed positive impacts. As a result, this review highlights the positive and the long-term negative environmental effects of the COVID-19 pandemic by evaluating the scientific literature. Remarkable reduction in the levels of CO (3 - 65%), NO2 (17 - 83%), NOx (24 - 47%), PM2.5 (22 - 78%), PM10 (23 - 80%), and VOCs (25 - 57%) was observed during the lockdown across the world. However, according to this review, the pandemic put enormous strain on the present waste collection and treatment system, resulting in ineffective waste management practices, damaging the environment. The extensive usage of face masks increased the release of microplastics/nanoplastics (183 to 1247 particles piece-1) and organic pollutants in land and water bodies. Furthermore, the significant usages of anti-bacterial hand sanitizers, disinfectants, and pharmaceuticals have increased the accumulation of various toxic emerging contaminants (e.g., triclocarban, triclosan, bisphenol-A, hydroxychloroquine) in the treated sludge/biosolids and discharged wastewater effluent, posing great threats to the ecosystems. This review also suggests strategies to create long-term environmental advantages. Thermochemical conversions of solid wastes including medical wastes and for treated wastewater sludge/biosolids offer several advantages through recovering the resources and energy and stabilizing/destructing the toxins/contaminants and microplastics in the precursors.

COVID-19 the Gateway for Future learning: The Impact of Online Teaching on the Future Learning Environment (preprint)

COVID-19 has changed the shape of education. These changes may be undone once universities return, and not all of them are reforms. Yet, some of these changes offer unique opportunities matching pre-COVID-19 proposals.This study’s purposes are to study staff members' perceptions of online teaching during COVID-19 and identify the drivers of change in the future learning environment. The study community represents faculty staff in Saudi universities. The sample consisted of 127 faculty staff in 9 Saudi universities. Participants had positive perceptions of the usage of e-learning platforms during COVID-19, according to data analysis (though negative experiences existed). Future research must focus on the subtle challenges of aligning theoretical and methodological designs to appropriately analyze the phenomenon under inquiry while contributing to a well-executed body of research in the field of educational technology. Future research is needed to see how lecturers view ICT trading post-COVID-19 strategies.Originality/valueThis research is unique in that it entails cloud computing applications in future education, as well as remote/distance learning, which have not before been investigated in the literature.

Severe COVID-19 Pneumonia and Genetic Susceptibility: A Case Report and Literature Review.

Genetic susceptibility to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) morbidity and mortality continues to evolve. This report presents a case of an apparently healthy male adult who developed severe coronavirus disease 2019 (COVID-19) and a study on relevant genetic mutations, namely, angiotensin-converting enzyme 2 (ACE2-rs4646994 I/D) gene, glutathione S-transferase (GST) M1 and T1 gene, and miR-423 rs6505162 C>A gene polymorphism. Results showed that the ACE-DD genotype of ACE2, (GSTM1+/+) (GSTT1-/-) genotype of GST gene, and CA genotype (heterozygosity) of miR-423 rs6505162 genes, which were found in the patient, could be independent risk factors of severe COVID-19, even without comorbidities.

'Face time' for the first time: Video communication between relatives and junior doctors in the COVID-19 pandemic.

Working on a COVID-19 ward presents a number of challenges to staff, with communication between families, patients and staff being highlighted as a key challenge. Novel methods are needed to overcome the barriers presented by COVID-19, with many turning to technology to offer solutions. Recognising these challenges as an area for improvement on our own ward, we sought to introduce new methods of communication to improve patient, relative and staff understanding and wellbeing. Through our own experiences and a discussion of the literature on this topic, we have identified some key themes which we believe can assist in the development of communication strategies in the developing pandemic.

To scan or not to scan - D-dimers and computed tomography pulmonary angiography in the era of COVID-19.

The COVID-19 pandemic has had many ramifications on healthcare delivery and practice. As part of this, utilising biomarkers to risk stratify patients has become increasingly popular. During the COVID-19 pandemic the use of D-dimer has increased due to the evidence of COVID-19 induced thrombo-embolic disease. We evaluated the use of D-dimer on all hospital admissions during the peak of the pandemic and evaluated its sensitivity in diagnosing pulmonary embolic disease (PE). Patients without COVID-19 infection were as likely to have evidence of PE as their COVID-positive counterparts. However, the sensitivity of a D-dimer was higher in COVID-positive patients at a lower D-dimer level (>1,500 µg/L, sensitivity 81%, specificity 70%) than in those without clinical, immunological or radiological evidence of COVID-19 infection (D-dimer >2,000 µg/L, sensitivity 80%, specificity 76%). These data suggest higher D-dimer thresholds should be considered for the exclusion of pulmonary emboli.