At a time when the Nigerian schools are on a temporary closure following the outbreak of the COVID-19 pandemic, this paper looked inwards and reflected on the nature of the education system and revealed its myriads of problems. The COVID-19 pandemic indeed had a huge impact on the educational system in Nigeria. It brought about the cessation of all learning activities in Nigeria except for private universities and secondary schools that swiftly switched to virtual learning platforms. It also illuminated the digital divide between the Nigerian student and his counterparts in other climes. COVID-19 pandemic outbreak also offered an opportunity for the nation to realise the poor status of its educational system. Some of the major problems that have confronted the Nigerian education system, as revealed by this paper, include poor funding, inadequate and dilapidating infrastructure, inadequate teaching facilities, poor teachers welfare, poor research funding, poor quality of teachers, unconducive learning environment, and the like. The study recommends for the exhibition of sufficient political will by the political leadership for the transformation of the education system as well as the sustained commitment of other stakeholders such policymakers and educational administrators for the transformation of the system to give it its rightful place in our national life. ? 2021. Lifescience Global

The last financial crisis in 2008 has weakened the Euro-zone countries. Most of them were deeply affected, and their economic growths have not returned to their pre-crisis rates. Moreover, the inflation rate is still very low despite the European Central Banks interventions. Twelve years later, a health crisis occurred. The ECB have reacted to this event by using monetary tools. We can cite for example the famous temporary Pandemic Emergency Purchase Programme (PEPP) to save the Euro-zone countries from a systemic disaster. The current interest rate is negative, and it seems to raise some questions about the efficiency of policies and the threat to economic, monetary, and financial stability. Negative interest rate may also generate the next crisis. This paper is dedicated to recommendations based on the role of Central Banks in the health crisis management and, more generally, environmental crisis management instead of evaluating the impacts of the monetary policies on Eurozone countries because it is too early to measure with acuity the COVID-19 effects. ? 2021, University of National and World Economy. All rights reserved.

Artificial Intelligence (AI) has become a driving force in modern research, industry and public administration and the European Union (EU) is embracing this technology with a view to creating societal, as well as economic, value. This effort has been shared by EU Member States which were all encouraged to develop their own national AI strategies outlining policies and investment levels. This study focuses on how EU Member States are approaching the promise to develop and use AI for the good of society through the lens of their national AI strategies. In particular, we aim to investigate how European countries are investing in AI and to what extent the stated plans contribute to the good of people and society as a whole. Our contribution consists of three parts: (i) a conceptualization of AI for social good highlighting the role of AI policy, in particular, the one put forward by the European Commission (EC); (ii) a qualitative analysis of 15 European national strategies mapping investment plans and suggesting their relation to the social good (iii) a reflection on the current status of investments in socially good AI and possible steps to move forward. Our study suggests that while European national strategies incorporate money allocations in the sphere of AI for social good (e.g. education), there is a broader variety of underestimated actions (e.g. multidisciplinary approach in STEM curricula and dialogue among stakeholders) that can boost the European commitment to sustainable and responsible AI innovation.

In recent weeks, information on the potential use of chloroquine or hydroxychloroquine for the treatment of people with COVID-19 has been disseminated in academic Journals and public media Although there are now ongoing clinical trials testing the efficacy and safety of several medicines for COVID-19, as of the date of this document, there is a lack of quality evidence to demonstrate chloroquine and/or hydroxychloroquine are effective in the treatment of COVID-19 Evidence is recently emerging via small studies with sub-optimal methodologies that are conflicting In some countries in the Americas, chloroquine or hydroxychloroquine is readily available, in some cases as an over-the-counter medicine National authorities should take measures to control the use of these medicines and prevent self-medication The use of chloroquine and/or hydroxychloroquine outside of current guidelines and recommendations may result in adverse effects, including serious illness and death, and have a negative impact on other diseases where there is proven benefit Public health authorities are urged to prioritize resources on those interventions that are currently recommended for standard of care

Background: Coronavirus disease 2019 is an emerging respiratory disease that is caused by a novel coronavirus and was first detected in December 2019 in Wuhan, China. The world is affected by the Coronavirus Disease in 2019. In sub-Saharan Africa Including Ethiopia there is no study conducted level of Knowledge, Attitude and Associated Factors toward Coronavirus disease 2019 among Health care workers Specifically Nurses. Objective: This study aims to assess the level of Knowledge, Attitude and Associated Factors toward Coronavirus disease 2019 among Nurses Who Work in South Gondar Zone, Hospitals, Northwest Ethiopia, 2020. Methods: An Institution based cross-sectional study was conducted among 166 Nurses in South Gondar Zone, Ethiopia, From June 1st -30/2020. To select study participants after proportional allocation of study subjects to each Hospital, simple random sampling techniques was to be used. Data was entered into Epi info version 7.2.0.1, and exported to Statistical Package for Social Sciences window version 24 for analysis. Binary and Multivariable logistic regression was used to see the association between dependent and independent variables. Adjusted odds' ratio with 95% confidence interval was computed. P-value < 0.05 was used to declare association. Finally,; the result is presented in the form of texts, tables and graphs. Results: Of 166 Nurses, 166 (100% response rate) responded to the online interview questionnaire. From 166 nurses, 57.2% of the participants were Females and 42.8% were males, 41.6 % of the respondents were between the ages of 20 and 29 years. About 84.9 % had good knowledge and 63.3% favorable attitude of COVID-19. Wearing general medical masks can prevent one from acquiring infection by theCOVID-19 virus (AOR = 0.44, 95% CI =0.005-0.362 were factors of knowledge about COVID-19. Whereas, strongly agree for Medical staffs are ready to participate in anti-epidemic in the community (AOR =0.08, 95% CI = (0.003-1.76 Where factors of attitude about COVID-19. Conclusion: In this study, most of the nurses had good knowledge and favorable attitude regarding of COVID-19. Wearing general medical masks can prevent one from acquiring infection by theCOVID-19 virus were factors in association with knowledge OF nurses on COVID-19. Similarly, Medical staffs are ready to participate in anti-epidemic in the community factors association with attitudes of nurses on COVID-19.

OBJECTIVE Celecoxib (CEL) is a nonsteroidal anti-inflammatory drug (NSAID) showing selective cycloxygenase-2 inhibition. While effective as a pain reducer, CEL exerts some negative influence on renal and gastrointestinal parameters. This study examined CEL pharmacodynamics and pharmacokinetics following drug reformulation as a poly(lactic-co-glycolic) acid nanoparticle (NP). MATERIALS AND METHODS Rats were administered either vehicle (VEH) (methylcellulose solution), blank NP, 40 mg/kg CEL in methylcellulose, or an equivalent NP dose (CEL-NP). Plasma and urine (over 12 hrs) samples were collected prior to and post-treatment. The mean percent change from baseline of urine flow rate along with electrolyte concentrations in plasma and urine were assessed based on 100 g body weight. Using tissues collected 24 hrs post-treatment, gastrointestinal inflammation was estimated through duodenal and gastric prostaglandin E2 (PGE2) and duodenal myeloperoxidase (MPO) levels; while kidney tissue was examined for dilatation and necrosis. CEL concentration was assayed in renal tissue and plasma utilizing high-performance liquid chromatography. RESULTS Although there were significant changes when comparing CEL and CEL-NP to VEH in plasma sodium concentration and potassium excretion rate, there was no significant variation between CEL and CEL-NP. There was a significant reduction of protective duodenal PGE2 in CEL compared to VEH (p = 0.0088) and CEL-NP (p = 0.02). In the CEL-NP formulation, t1/2, Cmax, AUC0-, and Vd/F increased significantly when compared to CEL. CONCLUSIONS At the observed dosage and duration, CEL-NP may not affect CEL-associated electrolyte parameters in either plasma or urine; however, it does provide increased systemic exposure while potentially alleviating some gastrointestinal outcomes related to inflammation.

Granger causality is a commonly used method for uncovering information flow and dependencies in a time series. Here we introduce JGC (Jacobian Granger Causality), a neural network-based approach to Granger causality using the Jacobian as a measure of variable importance, and propose a thresholding procedure for inferring Granger causal variables using this measure. The resulting approach performs consistently well compared to other approaches in identifying Granger causal variables, the associated time lags, as well as interaction signs. Lastly, through the inclusion of a time variable, we show that this approach is able to learn the temporal dependencies for nonstationary systems whose Granger causal structures change in time.

In this article, we create a system called AI-EVL. This is an annotated-based learning system. We extend AI to learning experience. If a user from the main YouTube page browses YouTube videos and a user from the AI-EVL system does the same, the amount of traffic used will be much less. It is due to ignoring unwanted contents which indicates a reduction in bandwidth usage too. This system is designed to be embedded with online learning tools and platforms to enrich their curriculum. In evaluating the system using Google 2020 trend data, we were able to extract rich ontological information for each data. Of the data collected, 34.86% belong to wolfram, 30.41% to DBpedia, and 34.73% to Wikipedia. The video subtitle information is displayed interactively and functionally to the user over time as the video is played. This effective visual learning system, due to the unique features, prevents the user's distraction and makes learning more focused. The information about the subtitle text is displayed in multiple layers including AI-annotated topics, Wikipedia/DBpedia, and Wolfram enriched texts via interactive and visual widgets.

OBJECTIVE: This study examined the impact of the COVID-19 pandemic and subsequent social restrictions or quarantines on the mental health of the global adult population. METHOD: A sample of 6,882 individuals (Mage = 42.30; 78.8% female) from 59 countries completed an online survey asking about several pandemic-related changes in life and psychological status. RESULTS: Of these participants, 25.4% and 19.5% reported moderate-to-severe depression (DASS-21) and anxiety symptoms (GAD-7), respectively. Demographic characteristics (e.g. higher-income country), COVID-19 exposure (e.g., having had unconfirmed COVID-19 symptoms), government-imposed quarantine level, and COVID-19-based life changes (e.g., having a hard time transitioning to working from home; increase in verbal arguments or conflict with other adult in home) explained 17.9% of the variance in depression and 21.5% in anxiety symptoms. CONCLUSIONS: In addition to posing a high risk to physical health, the COVID-19 pandemic has robustly affected global mental health, so it is essential to ensure that mental health services reach individuals showing pandemic-related depression and anxiety symptoms.

ObjectivesTo determine aetiology of illness among children and adults presenting during outbreak of severe respiratory illness in Southern Province, Sri Lanka, in 2018 DesignProspective, cross-sectional study Setting1600-bed, public, tertiary care hospital in Southern Province, Sri Lanka Participants410 consecutive patients, including 371 children and 39 adults, who were admitted with suspected viral pneumonia (passive surveillance) or who met case definition for acute respiratory illness (active surveillance) in May to June 2018 ResultsWe found that cocirculation of influenza A (22 6% of cases), respiratory syncytial virus (27 8%) and adenovirus (AdV) (30 7%;type B3) was responsible for the outbreak Mortality was noted in 4 5% of paediatric cases identified during active surveillance Virus type and viral coinfection were not significantly associated with mortality ConclusionsThis is the first report of intense cocirculation of multiple respiratory viruses as a cause of an outbreak of severe acute respiratory illness in Sri Lanka, and the first time that AdV has been documented as a cause of a respiratory outbreak in the country Our results emphasise the need for continued vigilance in surveying for known and emerging respiratory viruses in the tropics

This study used the method of network pharmacology to study the multi-component,multi-target and multi-pathway mechanism of Qingfei Paidu Decoction in the treatment of COVID-19,in order to provide basis for related basic research and clinical application. First of all, according to the screening conditions of OB 30% and DL 0.18,302 active components and 148 related targets in Qingfei Paidu Decoction were screened by TCMSP database, screening of 362 COVID-19 -related targets by GeneCards database,23 intersection targets were obtained by Venn analysis. Then 10 significant effective compounds and 5 key targets were obtained by using the CentiScaPe plug-in of Cytoscape software, Further construct the network topology diagram. The results of molecular docking of significant effective compounds and key targets show that the binding ability and interaction ability between molecules are strong. Finally, the GO and KEGG pathway enrichment analysis of the key targets were done through the ClusterProfiler package of R software, key compounds such as quercetin,luteolin,naringin, kaempferol and baicalein have antitussive,expectorant,anti-inflammatory and antiviral effects to varying degrees, the key targets are mainly concentrated in 144 related signal pathways such as IL-17,Tuberculosis,TNF,MAPK,Th17,Pertussis,etc.It involves 28 biological functions such as phosphatase binding, MAP kinase activity and cytokine receptor binding to regulate metabolism, immune regulation, inflammation and other physiological processes. According to the above results,it is considered that the active components of Qingfei Paidu decoction have multi-target and multi-pathway regulating effect on the treatment of COVID-19.

Determining the protection an individual has to SARS-CoV-2 variants of concern (VoC) will be crucial for future immune surveillance and understanding the changing immune response. As further variants emerge, current serology tests are becoming less effective in reflecting neutralising capability of the immune system. A better measure of an evolving antigen-antibody immune response is needed. We describe a multiplexed, baited, targeted-proteomic assay for direct detection of multiple proteins in the SARS-CoV-2 anti-spike antibody immunocomplex. This enables a more sophisticated and informative characterisation of the antibody response to vaccination and infection against VoC. Using this assay, we detail different and specific responses to each variant by measuring several antibody classes, isotypes and associated complement binding. Furthermore, we describe how these proteins change using serum from individuals collected after infection, first and second dose vaccination. We show complete IgG1 test concordance with gold standard ELISA (r>0.8) and live virus neutralisation against Wuhan Hu-1, Alpha B.1.1.7, Beta B.1.351, and Delta B.1.617.1 variants (r>0.79). We also describe a wide degree of heterogeneity in the immunocomplex of individuals and a greater IgA response in those patients who had a previous infection. Significantly, our test points to an important role the complement system may play particularly against VoC. Where we observe altered Complement C1q association to the Delta VoC response and a stronger overall association with neutralising antibodies than IgG1. A detailed understanding of an individuals antibody response could benefit public health immunosurveillance, vaccine design and inform vaccination dosing using a personalised medicine approach.

The ACA shifted U.S. health policy from centering on principles of actuarial fairness toward social solidarity. Yet four legal fixtures of the health care system have prevented the achievement of social solidarity: federalism, fiscal pluralism, privatization, and individualism. Future reforms must confront these fixtures to realize social solidarity in health care, American-style.

SARS-CoV-2 has caused a historic pandemic of respiratory disease (COVID-19) and current evidence suggests severe disease is associated with dysregulated immunity within the respiratory tract. However, the innate immune mechanisms that mediate protection during COVID-19 are not well defined. Here we characterize a mouse model of SARS-CoV-2 infection and find that early CCR2-dependent infiltration of monocytes restricts viral burden in the lung. We find that a recently developed mouse-adapted MA-SARS-CoV-2 strain, as well as the emerging B. 1.351 variant, trigger an inflammatory response in the lung characterized by expression of pro-inflammatory cytokines and interferon-stimulated genes. scRNA-seq analysis of lung homogenates identified a hyper-inflammatory monocyte profile. Using intravital antibody labeling, we demonstrate that MA-SARS-CoV-2 infection leads to increases in circulating monocytes and an influx of CD45+ cells into the lung parenchyma that is dominated by monocyte-derived cells. We utilize this model to demonstrate that mechanistically, CCR2 signaling promotes infiltration of classical monocytes into the lung and expansion of monocyte-derived cells. Parenchymal monocyte-derived cells appear to play a protective role against MA-SARS-CoV-2, as mice lacking CCR2 showed higher viral loads in the lungs, increased lung viral dissemination, and elevated inflammatory cytokine responses. These studies have identified a CCR2-monocyte axis that is critical for promoting viral control and restricting inflammation within the respiratory tract during SARS-CoV-2 infection.

Understanding of the pathogenesis of the coronavirus disease-2019 (COVID-19) remains incomplete, particularly in respect to the multi-organ dysfunction it may cause We were the first to report the analogous biological and physiological features of COVID-19 pathogenesis and the harmful amplification loop between inflammation and tissue damage induced by the dysregulation of neutrophil extracellular traps (NETs) formation Given the rapid evolution of this disease, the nature of its symptoms, and its potential lethality, we hypothesize that COVID-19 progresses under just such an amplifier loop, leading to a massive, uncontrolled inflammation process Here, we describe in-depth the correlations of COVID-19 symptoms and biological features with those where uncontrolled NET formation is implicated in various sterile or infectious diseases General clinical conditions, as well as numerous pathological and biological features, are analogous with NETs deleterious effects Among NETs by-products implicated in COVID-19 pathogenesis, one of the most significant appears to be elastase, in accelerating virus entry and inducing hypertension, thrombosis and vasculitis We postulate that severe acute respiratory syndrome-coronavirus 2 (SARS-CoV2) may evade innate immune response, causing uncontrolled NETs formation and multi-organ failure In addition, we point to indicators that NETS-associated diseases are COVID-19 risk factors Acknowledging that neutrophils are the principal origin of extracellular and circulating DNA release, we nonetheless, explain why targeting NETs rather than neutrophils themselves may in practice be a better strategy This paper also offers an in-depth review of NET formation, function and pathogenic dysregulation, as well as of current and prospective future therapies to control NETopathies As such, it enables us also to suggest new therapeutic strategies to fight COVID-19 In combination with or independent of the latest tested approaches, we propose the evaluation, in the short term, of treatments with DNase-1, with the anti-diabetic Metformin, or with drugs targeting elastase (i e , Silvelestat) With a longer perspective, we also advocate a significant increase in research on the development of toll-like receptors (TLR) and C-type lectin-like receptors (CLEC) inhibitors, NET-inhibitory peptides, and on anti-IL-26 therapies

This qualitative study investigates the cognitive levels of the questions used in the English primary six leaving examinations administered in Rwandan schools from 2013 to 2019. We used the revised Blooms Taxonomy to scrutinize the cognitive levels of 574 exam questions. The findings revealed a remarkable predominance of the lower-order thinking skills (LOTS) (98.79%) over the higher-order thinking skills (HOTS) exam questions (1.21%). The study addresses the gap in the current literature on high-stake and accountability-driven assessment practices regarding the language educational policies involving the use of English as a classroom language and curriculum reforms in postcolonial contexts. In particular, the study provides education practitioners and decision-makers with a body of knowledge conducive to writing high-quality exams that are likely to boost effective instruction and higher student learning and success in schools and beyond.

T cells are important for effective viral clearance, elimination of virus-infected cells and long-term disease protection. To examine the full-spectrum of CD8(+) T cell immunity in COVID-19, we experimentally evaluated 3141 major histocompatibility (MHC) class I-binding peptides covering the complete SARS-CoV-2 genome. Using DNA-barcoded peptide-MHC complex (pMHC) multimers combined with a T cell phenotype panel, we report a comprehensive list of 122 immunogenic and a subset of immunodominant SARS-CoV-2 T cell epitopes. Substantial CD8(+) T cell recognition was observed in COVID-19 patients, with up to 27% of all CD8(+) lymphocytes interacting with SARS-CoV-2-derived epitopes. Most immunogenic regions were derived from open reading frame (ORF) 1 and ORF3, with ORF1 containing most of the immunodominant epitopes. CD8(+) T cell recognition of lower affinity was also observed in healthy donors toward SARS-CoV-2-derived epitopes. This pre-existing T cell recognition signature was partially overlapping with the epitope landscape observed in COVID-19 patients and may drive the further expansion of T cell responses to SARS-CoV-2 infection. Importantly the phenotype of the SARS-CoV-2-specific CD8(+) T cells, revealed a strong T cell activation in COVID-19 patients, while minimal T cell activation was seen in healthy individuals. We found that patients with severe disease displayed significantly larger SARS-CoV-2-specific T cell populations compared to patients with mild diseases and these T cells displayed a robust activation profile. These results further our understanding of T cell immunity to SARS-CoV-2 infection and hypothesize that strong antigen-specific T cell responses are associated with different disease outcomes.

The statistical correlation between meteorological parameters and the spread of Coronavirus Disease-2019 (COVID-19) was investigated in five provinces of Italy selected according to the number of infected individuals and the different trends of infection in the early stages of the epidemic: Bergamo and Brescia showed some of the highest trends of infections while nearby Cremona and Mantova, showed lower trends. PesaroCUrbino province was included for further investigation as it was comparably affected by the epidemic despite being the area far from the Po valley. Moving means of the variables were considered to take into account the variability of incubation periods and uncertainties in the epidemiological data. The same analyzes were performed normalizing the number of new daily cases based on the number of checks performed. For each province, the moving mean of adjusted and unadjusted new daily cases were independently plotted versus each meteorological parameter, and linear regressions were determined in the period from 29th of February 2020 to 29th of March 2020. Strong positive correlations were observed between new cases and temperatures within three provinces representing 86.5% of the contagions. Strong negative correlations were observed between the moving means of new cases and relative humidity values for four provinces and more than 90% of the contagions.

The information retrieval community has recently witnessed a revolution due to large pretrained transformer models. Another key ingredient for this revolution was the MS MARCO dataset, whose scale and diversity has enabled zero-shot transfer learning to various tasks. However, not all IR tasks and domains can benefit from one single dataset equally. Extensive research in various NLP tasks has shown that using domain-specific training data, as opposed to a general-purpose one, improves the performance of neural models. In this work, we harness the few-shot capabilities of large pretrained language models as synthetic data generators for IR tasks. We show that models finetuned solely on our unsupervised dataset outperform strong baselines such as BM25 as well as recently proposed self-supervised dense retrieval methods. Furthermore, retrievers finetuned on both supervised and our synthetic data achieve better zero-shot transfer than models finetuned only on supervised data. Code, models, and data are available at https://github.com/zetaalphavector/inpars .

OBJECTIVES: Protecting healthcare workers from psychological harm is an urgent clinical issue within the current COVID-19 pandemic. Research on early psychological programmes that aim to prevent or reduce mental health symptoms and that have been tested in frontline responders may assist service providers with choosing a suitable intervention for rapid dissemination in healthcare settings. DESIGN AND OUTCOME MEASURES: First, Embase, Web of Science, PsycINFO and Google Scholar were searched through a systematic literature review of early psychological interventions administered to frontline responders in the last 15 years. Interventions were included if they were designed to prevent or reduce psychological impact and had outcome measures of psychological distress (eg, general psychopathology, post-traumatic stress disorder and stress) and/or positive mental health domains (eg, resilience, self-efficacy and life satisfaction). Second, the suitability of these programmes for the healthcare workforce was evaluated according to the criteria of effectiveness, content applicability and feasibility. RESULTS: Of 320 articles retrieved, 12 relevant studies were included that described six early psychological interventions. Although the evidence base is limited, psychological first aid, eye movement desensitisation and reprocessing, and trauma risk management showed effectiveness across at least two studies each with frontline workers. Resilience and coping for the healthcare community; anticipate, plan, and deter; and resilience at work programmes found promising results in single studies. Concerning other suitability criteria, all programmes appear applicable to healthcare settings and have acceptable feasibility for rapid implementation. CONCLUSIONS: Despite the limited evidence, several interventions were identified as potentially suitable and useful for improving psychological functioning of healthcare workers across a variety of disaster situations. Service providers should continue to implement and evaluate early psychological interventions in frontline workers in order to refine best practices for managing the psychological impact of future disasters.