Generating Masked Facial Datasets Using Dlib-Machine Learning Library

In 2020, the COVID-19 pandemic spread globally, leading to countries imposing health restrictions on people, including wearing masks, to prevent the spread of the disease. Wearing a mask significantly decreases distinguishing ability due to its concealment of the main facial features. After the outbreak of the pandemic, the existing datasets became unsuitable because they did not contain images of people wearing masks. To address the shortage of large-scale masked faces datasets, a developed method was proposed to generate artificial masks and place them on the faces in the unmasked faces dataset to generate the masked faces dataset. Following the proposed method, masked faces are generated in two steps. First, the face is detected in the unmasked image, and then the detected face image is aligned. The second step is to overlay the mask on the cropped face images using the dlib-ml library. Depending on the proposed method, two datasets of masked faces called masked-dataset-1 and masked-dataset-2 were created. Promising results were obtained when they were evaluated using the Labeled Faces in the Wild (LFW) dataset, and two of the state-of-the-art facial recognition systems for evaluation are FaceNet and ArcFace, where the accuracy of using the two systems was 96.1 and 97, respectively with masked-dataset-1 and 87.6 and 88.9, respectively with masked-dataset-2. © 2022 IEEE.

Applying the Autoregressive Model and the Integrative Moving Average ARIMA in Predicting the Levels of Infection with COVID-19 in Babil Province/ Iraq

One of the important statistical methods used in the analysis of time series, as the study of a particular phenomenon depends on time periods by identifying its pattern and its stable state with the possibility of predicting future values for future periods which contribute clearly to developing future plans given the importance of statistical studies of a predictive nature, one of the priorities of strategic planning. Through the application of data in the construction of the auto-regression model and moving means ARIMA matching the results with the theoretical basis turns out to be the appropriate model ARIMA (2,1,1) on the basis of "The International Assets Valuation Standards Committee". © 2022 American Institute of Physics Inc.. All rights reserved.

Improved Control System Based on PSO and ANN for Social Distancing for Patients With COVID-19

The World Health Organization has declared the COVID-19 pandemic, with most countries being affected by this virus both socially and economically. It thus became necessary to develop solutions to help monitor and control disease spread by controlling medical workers' movements and warning them against approaching infected individuals in isolation rooms. This paper introduces a control system that uses improved particle swarm optimization (PSO), and artificial neural network (ANN) approaches to achieve social distancing. The distance between medical workers carrying mobile nodes and the beacon node (isolation room) was determined using the ZigBee wireless protocol's received signal strength indicator (RSSI). Two path loss models were developed to determine the distance from patients with COVID-19: the first is a log-normal shading model (LNSM), and the second is a polynomial function (POL). The coefficient values of the POL model were controlled based on PSO to improve model performance. A random-nonlinear time variation controller-PSO (RNT-PSO) approach was developed to avoid the local minima of the conventional PSO. As a result, social distancing for COVID-19 can be accurately determined. The measured RSSI and the distance were used as ANN inputs, while three control signals (alarming, warning, and closing) were used as ANN outputs. The results revealed that the hybrid model between POL and RNT-PSO, called RNT-PSO-POL, improved the system's performance by reducing the mean absolute error of distance to 1.433 m, compared to 1.777 m for the LNSM. The results show that the ANN achieves robust performance in terms of mean squared error.

ADHERENCE THE PREVENTIVE MEASURE AGAINST FOR COVID-19AMONG TEACHERS AT UNIVERSITY OF MOSUL

Background: The only way to stop COVID-19 from spreading and wreaking havoc, especially in developing countries like Iraq, is to follow COVID-19 control and prevention methods Objectives: The goal of this study was to see how well teachers at the University of Mosul adhered to the COVID-19 prevention measures. Methodology: “A cross-sectional survey” was carried out among Teachers at university of Mosul - North Iraq, from January 11 to December 30, 2021. (480) teachers from Mosul University in various specializations were selected to participate in this survey. The instrument consist of 4 parts: Part 1: Demographical variables. Part two: Knowledge to COVID-19 preventive actions are all included in the questionnaire. Part 3: Attitude of teacher against to COVID-19 preventive measure. part 4: Adhered to the COVID-19 prevention measures. Results: This results of revealed that the study participants were 480 students between (20 - 61) or more years old, and mean age was 36.2 (SD = 2.02).(70%) of them, their attitude was about adhering to preventive measures against Corona, as well as (73.3%) their acquaintances were. Conclusion: Concluded of the study, the extent to which the university professor adhered to preventive measures and measures against Corona disease was well accepted and that the university professor’s attitudes were positive, as well as their high knowledge.

Adoptive Immune Responses to Sars-Cov2 Vaccination in CART19 Treated Patients

Background: The two FDA approved mRNA-based SARS-CoV2 vaccines have shown >90% efficacy at preventing COVID and eliciting protective immunity in nearly all healthy individuals. However, the extent of vaccine induced antibody and T cell immunity in immunocompromised patients is not well known. Our study objective is to determine if patients with hematologic malignancies treated with B-cell targeting chimeric antigen receptor (CAR) T cell therapies can mount antibody and T cell immune responses to SARS-CoV2 vaccines. A prospective single-center study to evaluate the SARS-CoV2 immune responses in immunocompromised individuals (COVAX Study) was initiated at University of Pennsylvania following the IRB guidelines. The study enrolled 8 healthy adults,12 patients are in remission after treatment (average of 40.6 months) with CART cells targeting either CD19 or CD19+CD22 and received both doses of SARS-CoV2 vaccine. Methods and Results: Serology to SARS-CoV2 spike-receptor binding domain (RBD) IgG, RBD-IgA, RBD-IgM and spike-specific T cell responses were measured prior to vaccination and serially up to 28 days after booster vaccination. RBD-IgG and RBD-IgA were detected in 8/8 and 7/8 healthy subjects compared to 5/12 and 2/12 CART patients, respectively (Figure A). In the CART cohort, several patients who demonstrated an induction of RBD-IgG (57.2/uL +/- 20.2) compared to those who were RBD-IgG-negative (9/uL +/- 10.1, ANOVA with multiple comparisons test p=0.017) have higher level of circulating B cells. No association was found with time since CART infusion, age, disease type, or vaccine manufacturer. All 8 healthy subjects demonstrated induction of SARS-Cov2 spike-specific CD4 + T cell immunity compared to 7 out of 11 CART patients (Figure B). RBD-IgG responses were not correlated with CD4 + T cell activation (Pearson correlation, R=0.21, p=0.53). Indeed, 3 CART patients demonstrated robust CD4 + T cell activation despite absence of antibody induction. Overall, 8/12 CART patients demonstrated induction of either or both humoral and T cell immune responses. Conclusions: We show that immune responses to SARS-CoV2 mRNA vaccines are induced in majority of patients who have been treated with CART therapies targeting B-cell lineage antigens. Induction of vaccine-specific antibody was strongly associated with the level of circulating B cells. However, in CART cohort patients despite severe humoral immune deficiency, strong CD4 + T cell responses were observed suggestive of a sufficient protective immunity. [Formula presented] Disclosures: Frey: Novartis: Research Funding;Sana Biotechnology: Consultancy;Kite Pharma: Consultancy;Syndax Pharmaceuticals: Consultancy. Garfall: Amgen: Honoraria;CRISPR Therapeutics: Research Funding;GlaxoSmithKline: Honoraria;Janssen: Honoraria, Research Funding;Novartis: Research Funding;Tmunity: Research Funding. Porter: American Society for Transplantation and Cellular Therapy: Honoraria;Genentech: Current equity holder in publicly-traded company, Ended employment in the past 24 months;ASH: Membership on an entity's Board of Directors or advisory committees;DeCart: Membership on an entity's Board of Directors or advisory committees;Incyte: Membership on an entity's Board of Directors or advisory committees;Janssen: Membership on an entity's Board of Directors or advisory committees;Kite/Gilead: Membership on an entity's Board of Directors or advisory committees;National Marrow Donor Program: Membership on an entity's Board of Directors or advisory committees;Novartis: Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding;Tmunity: Patents & Royalties;Wiley and Sons Publishing: Honoraria. June: AC Immune, DeCART, BluesphereBio, Carisma, Cellares, Celldex, Cabaletta, Poseida, Verismo, Ziopharm: Consultancy;Tmunity, DeCART, BluesphereBio, Carisma, Cellares, Celldex, Cabaletta, Poseida, Verismo, Ziopharm: Current equity holder in publicly-traded company;Novartis: Patents & Royalties.

COVID-19: Key global impacts on the construction industry and proposed coping strategies

The construction industry is an essential tributary of the global economy and an important resource in the overall product of the local economies. In December 2019, the construction industry was exposed to a shock beyond the local level as a result of COVID-19, which was classified by the World Health Organization as a global pandemic after its rapid and sudden spread in multiple countries. The nature of the effects of COVID-19 on the construction industry varied according to the diversity of its projects. The pandemic raised many challenges at the level of the workforce, low or halting productivity, production time and costs, as well as disputes in contractual formulas for construction projects. But some of the effects were more severe and caused consequences for all stakeholders in the construction sector. Researchers and those interested in the construction industry have dealt with the repercussions of COVID-19, but most of the publications focused on studying the impact of the pandemic on the local construction industry, so this paper attempts to shed light on the most prominent effects of COVID-19 on the construction industry around the world, and which were repeated with high frequency in previous studies and reports by following the methodology of review, analysis and selection, and then suggesting optimal coping strategies to reduce the damages of these effects. © The Authors, published by EDP Sciences, 2021.