Based on Chinese CDCP report on COVID-19, 14% of patients presented severe disease and 5% critical conditions. The average case-fatality rate was 2.3%, but mortality was as high as 49% in patients with critical illness. Serious life threatening thromboembolic complications have been found in 71·4% of non-survivors and micro/macro angiopathic coagulopathy has been found, also at autopsy, with highly increased neutrophil number, fibrinogen, concentrations of D-dimer and FDPs and NETs, ATIII decrease and normal number of platelets. A cytokine storm and interaction between inflammation and coagulation has been advocated as explanation of hypercoagulability. In this paper, it’s hypothesised that SARS-CoV-2 infection of alveolar cells induces recruitment of innate responder neutrophils, which release proteases and NETs inducing endothelial damage/endotheliopathy and imbalance of the four major proteolytic cascades (coagulation, complement, fibrinolysis and kallikrein) with prevalence of activators over inhibitors and consequent thrombotic complications. Platelets adhesion to damaged endothelium and the presence of ULVWF multimers, due to decreased ADAMTS13, contributes to the state of hypercoagulability. Neutrophil innate “unfriendly fire” response can be identified as the trigger of a “proteolytic storm”, responsible for subsequent well known prothrombotic condition and “cytokine storm”. The hypothesis explains also the pathology of recently described systemic “Kawasaki Disease like” vasculitis cases in Covid-19 young ill patients.

The emerging new Coronaviridae member, nCoV 19, outbreak announced a pandemic by WHO with an increased morbidity and mortality rate worldwide. nCoV 19 known as the third highly pathogen coronavirus in the human population after the severe acute respiratory syndrome coronavirus (SARS-CoV) and the Middle East respiratory syndrome coronavirus (MERS-CoV), the nCoV 19. The renin-angiotensin (RAS) signaling pathway, oxidative stress and cell death, cytokines storm and endothelial dysfunction are four major pathways involved in the pathogenesis of nCoV 19. Acute respiratory distress syndrome (ARDS) generally develops with a massive oxidative/nitrosative stress following virus entry and RAS activation. The DNA damage subsequent to oxidative burst activates poly-ADP ribose polymerase-1 (PARP-1), viral macrodomain (NSP3) poly (ADP-ribose) glycohydrolase (PARG) and transient receptor potential channel, melastatin 2 (TRPM2) in a sequential manner ultimately leading to apoptosis and necrosis due to NAD and ATP depletion. Regarding the molecular mechanisms involved in nCoV 19 pathogenesis, angiotensin II receptor blockers and/or PARP, PARG and TRPM2 blockers could be engaged as therapeutic candidates for inhibition of RAS and quenching oxidative stress, respectively. In this review, the molecular aspects of nCoV 19 pathogenesis would be studied precisely and possible therapeutic targets would be proposed. It is recommended to evaluate the proposed drugs and supplements via registered clinical trials along with conventional guideline-based multi-drug regimen.

Climate change related issues, such as yield decline, quality losses, accelerated phenology, extreme abiotic stress, pose growers new challenges in olive growing areas. Main cultural solutions that could alleviate stress and improve long-term sustainability of modern olive orchards are here briefly reviewed. Selecting varieties that are more resistant to drought or high temperatures would be the optimal solution to mitigate the effects of climate change, but the available scientific information is relatively scarce. Sustainability of irrigation implies that the less water is used, the better. Best results in terms of saving water and uniform application are obtained using micro-irrigation methods. Water can also be saved by not fully satisfying the tree water needs and different deficit irrigation strategies have been developed and tested for olive orchards. The use of green covers and the application of organic mulches and shredded pruning materials should be encouraged as these practices tend to stock carbon, increase organic matter content and water holding capacity of the soil. Olive orchards are efficient CO2 sinks as they can store considerable amounts of carbon in their organs and permanent structures. Using environmental friendly practices improves the ecosystem carbon budget and contributes to mitigate climate change.

Long Covid has become a blight, its economic consequences overwhelming. But Long Covid (LC) may represent persistent Covid-19 in those with preexisting Candida overgrowth (CO). The features shared by both are striking. LC may be a growing subset of CO. The altered tryptophan metabolism encountered in LC is driven by IFN-γ in reaction to CO. Females are robust producers of IFN-γ, yet estrogen promotes CO.The consequent decline in serotonin and melatonin triggers the mood swings and sleeplessness respectively in LC. The low serotonin, the primary messenger in the gut brain axis, creates autonomic dysfunction. The CO induced gut dysbiosis and leaky gut initiate an autoimmune path. TNFα seen in both LC and this opportunistic yeast is at the center of the cytokine triad that leads to neurodegeneration. The Western diet, high in carbohydrates, alcohol, and glutamate, is exploited by this commensal turned parasite. Residual SARS CoV2 and Candida generate abundant ROS, inducing mitochondrial dysfunction. Alcohol tastes different for many with LC, because acetaldehyde requires functioning hepatic mitochondria. This article delves into the complex physiology and biochemistry that drive the symptoms of this conspicuous connection. Recent research has revealed innovative approaches that might address this global scourge, including D-mannose for the immune dysfunction and butyrate for the gut dysbiosis created by and seen in both LC and intestinal Candidiasis.

In recent years the field of computer science has experienced great changes, due to the incredible advances in the field of artificial intelligence. Deep Learning models are responsible for most of them since the biggest milestones occurred in 2012 when AlexNet won the image classification challenge called ImageNet. These models have demonstrated great performances in different types of complex tasks like image restoration, medical diagnosis or object recognition. Their disadvantages are related to their high data dependency, which forces experts in the field to follow a precise methodology to obtain accurate models. In this paper, we describe a complete workflow that begins with the management of the raw data until the in-depth interpretation of the performance of the models. This should be taken as a high-level consultation document describing good practices that should be applied. Apart from the step-by-step methodology, we present different use cases that correspond to the two main problems of the field: classification and regression.

The world is currently experiencing COVID-19, one of the worst pandemics that have happened in this century, affecting 10.7 million people worldwide. It has caused massive growth in the number of employees working from home. However, employees have minimal cybersecurity resources unlike organizations with security teams protecting them against attacks. Hence, cybersecurity plays an important role as users can be easily targeted by cybercriminals. This paper examines how cyberattacks have increased during this pandemic and shows how greatly they have affected health organizations, individuals and social networking applications. Results of the attacks include data breaches, false announcements and operations being disrupted. Attacks occurring during this pandemic and how they were handled are also critically discussed. The existing contributions do touch on related attacks but do not provide in-depth solutions regarding the issues. Even though there are many works and findings that were done previously, technology is ever evolving. Therefore, we need to be well versed with current and future issues and provide the latest mechanisms to prevent cybersecurity threats from occurring. On our share, we intend to present our findings on the challenges being faced by the population and its increasing threats as well as presenting unique solutions that can help organizations or related persons understand or spread awareness on the importance of cybersecurity. Through the research performed in this paper, it is found that there are many ways these issues can be alleviated. However, the issue is that there is significant lack of action and investment in terms of actual implementation and application of the available solutions.

The outbreak of Corona Virus effected negatively on the world’s economy which has already touched the maximum sectors. Readymade garments sector has the large contribution in Bangladesh’s economy. For increasing the locked down period, it is hitting badly by stopping production and cancellation of orders with some issues. This paper will represent the brief scenario and impacts of garments sector in recent days and the economy status of Bangladesh for the pandemic. The study is based on secondary data, collected from different authentic journals and web portals etc. Bangladesh’s garments earnings mostly depended on export but on these days, the buyers are cancelling their orders and the factories are being failed to give payments to the worker, some are being shut down also. As the duration of locked down is increasing, there is a huge chance to get unemployed and Bangladesh can be faced an undisciplined condition in near future. BGMEA and BKMEA are taking necessary steps to support the worker. Ensuring health security, the authorities are trying to reopen the factories limitedly to meet up the immediate needs. The government has taken the situation on most priority and introduce some improvement packages to run the economy smoothly and reduce the losses of the country for the pandemic.

Globally, an approximate of 380,000 patients succumbed to death due to the pandemic COVID-19 which also infected more than six million people since December 2019. Not sparing anyone, COVID-19 infections are widely reported among healthcare professionals, sanitation workers and researchers too while global leaders and various governments are providing their best in defending their citizens against this airborne and contact spread virus. In order to contain the virus and protect millions of lives from this deadly coronavirus, there is a need to have a combination of advanced engineering technology and medical facilities. Application of applied science, engineering and technology diffuse almost every aspect of contemporary living. Grasping the fundamentals to determine humanity's most imperative and forthcoming challenges is essential. Artificial Intelligence, the technology that learns, adapts and reciprocates the actions according to the situations, finds optimum position in the fight against corona virus and acts as a powerful tool against this pandemic. In this research article, the authors discusses how Artificial Intelligence (AI) can be leveraged to fight the deadly virus. The research paper further discusses the efficient utilization of AI across the globe to help in testing, treating and serving the population in these hard times. This manuscript focuses on the potential impact of the process in which AI can be implemented to prevent, test and treat.

Objective: To investigate social, economic, and environmental contributors to quit or continue smoking and vaping during the COVID-19 pandemic. Methods: A qualitative study design was adopted to identify smokers’ beliefs in a LMIC, using a small community sample. Results: 276 participants were primarily surveyed. Motivation to continue smoking included temporary pleasurable effects, working remotely, stress or anxiety, whereas a motivator to quit smoking was the overlap with COVID-19 symptomatology. There was a rise in social awareness regarding the potential harm of smoking and vaping during the pandemic yet those participants who were younger felt they were immune from its morbid complications. Conclusions: With paradoxical associations of COVID-19 with cigarette and vape usage, it is important to pay attention to biases in data in favor of educating its users of the increased risk of severe disease.

Coronavirus disease (COVID-19) has caused mankind serious confusion, economic havoc and psychological distress. This study evaluated the level of knowledge, attitude and perception about COVID-19 pandemic, infection control and impact among veterinarians in Nigeria. A cross-sectional online survey was used to collect data from consenting respondents during implementation of lockdown in the country (April 23 - May 31, 2020). Purposive and chain referral sampling techniques were used to recruit 368 respondents from various sectors of the profession. The proportion of respondents surveyed 197/368 (53.5 %) were from the public sector, 35.3 % from private sector, 1.1 % were unemployed and 0.8 % retired. Majority of the respondents were males (72.8 %), within 30 – 39 years (39.7 %) and had 1 – 10 years work experience. Respondents displayed good level of knowledge about COVID-19 (72.4 % ± 9.9 %, range 44.1-91.2 %), with information mostly derived from TV/Radio (81.5%) and social media (81.0 %). The overall attitude level was poor and various determinants for good attitude among respondents were if they were above 60 years (p = 0.013), possessed postgraduate qualification ( p = 0.031), worked over 30 years post DVM (p = 0.001), had household members between 5 and 10 (p = 0.012), and were resident in states on total lockdown (p = 0.024). There was no correlation between the knowledge level score and respondents’ attitude towards the pandemic (p = 0.12). With increasing rate of COVID-19 transmission, research data are needed to develop evidence-driven strategies, policies and effective risk mitigations to reduce the pandemic’s adverse impacts.

Coronaviruses are an extensive family of viruses that can cause disease in both animals and humans. The current classification of coronaviruses recognizes 39 species in 27 subgenera that belong to the family Coronaviridae. From those, at least seven coronaviruses are known to cause respiratory infections in humans. Four of these viruses can cause common cold-like symptoms, while others that infect animals can evolve and become infectious to humans. Three recent examples of this viral jumps include SARS CoV, MERS-CoV and SARS CoV-2 virus. They are responsible for causing severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS) and the most recently discovered coronavirus disease during 2019 (COVID-19).COVID-19, a respiratory disease caused by the SARS-CoV-2 virus, was declared a pandemic by the World Health Organization (WHO) on 11 March 2020. The rapid spread of the disease has taken the scientific and medical community by surprise. Latest figures from 14 April 2020 show more than 2 million people had been infected with the virus, causing more than 120,000 deaths in over 210 countries worldwide. The large amount of information we receive every day concerning this new disease is so abundant and dynamic that medical staff, health authorities, academics and the media are not able to keep up with this new pandemic. In order to offer a clear insight of the extensive literature available, we have conducted a comprehensive literature review of the SARS CoV-2 Virus and the Coronavirus Diseases 2019 (COVID-19).

A novel coronavirus (SARS-CoV-2), causing an emerging coronavirus disease (COVID-19), first detected in Wuhan City, Hubei Province, China has resulted in an outbreak in China which has taken a catastrophic turn with high toll rates in China and subsequently spreading across the globe. The rapid spread of this virus to more than 175 countries while affecting nearly 500,000 persons and causing more than 22,000 human deaths, it has resulted in a pandemic situation in the world. The SARS-CoV-2 virus belongs to the genus Betacoronavirus, like MERS-CoV and SARS-CoV, all of which originated in bats. It is highly contagious, causing symptoms like fever, dyspnea, asthenia and pneumonia, thrombocytopenia and the severely infected patients succumb to the disease. Coronaviruses (CoVs) among all known RNA viruses have the largest genomes ranging from 26 to 32 kb in length. Extensive research has been conducted to understand the molecular basis of the SARS-CoV-2 infection and evolution, develop effective therapeutics, antiviral drugs and vaccines, and to design rapid and confirmatory viral diagnostics as well as adopt appropriate prevention and control strategies. Till date, no clinically proclaimed, proven therapeutic antibodies or specific drugs and therapeutics, and vaccines have turned up. Several molecular diagnostic tests such as Real Time-PCR, isothermal loop-mediated amplification of coronavirus (i-LACO), full genome analysis by next-generation sequencing (NGS), multiplex nucleic acid amplification, and microarray-based assays are in use currently for the laboratory confirmation of this CoV infection. In this review article, we describe the basic molecular organization and phylogenetic analysis of the coronaviruses, including the SARS-CoV-2, and recent advances in diagnosis and vaccine development in brief and focusing mainly on developing potential therapeutic options that can be explored to manage this pandemic virus infection, which would help in valid countering of COVID-19.

Background: Covid-19 was first reported in Wuhan, China in Dec 2019. Since then, it has been transmitted rapidly in China and the rest of the world. While Covid-19 transmission rate has been declining in China, it is increasing exponentially in Europe and America. Although there are numerous studies examining Covid-19 infection, including an archived paper looking into the meteorological effect, the role of outdoor air pollution has yet to be explored rigorously. It has been shown that air pollution will weaken the immune system, and increase the rate of respiratory virus infection. We postulate that outdoor air pollution concentrations will have a negative effect on Covid-19 infections in China, whilst lockdowns, characterized by strong social distancing and home isolation measures, will help to moderate such negative effect. Methods: We will collect the number of daily confirmed Covid-19 cases in 31 provincial capital cities in China during the period of 1 Dec 2019 to 20 Mar 2020 (from a popular Chinese online platform which aggregates all cases reported by the Chinese national/provincial health authorities). We will also collect daily air pollution and meteorology data at the city-level (from the Chinese National Environmental Monitoring Center and the US National Climatic Data Center), daily inter-city migration flows and intra-city movements (from Baidu). City-level demographics including age distribution and gender, education, and median household income can be obtained from the statistical yearbooks. City-level co-morbidity indicators including rates of chronic disease and co-infection can be obtained from related research articles. A regression model is developed to model the relationship between the infection rate of Covid-19 (number of confirmed cases/population at the city level) and outdoor air pollution at the city level, after taking into account confounding factors such as meteorology, inter- and intra-city movements, demographics, and co-morbidity and co-infection rates. In particular, we shall study how air pollution affects infection rates across different cities, including Wuhan. Our model will also study air pollution would affect infection rates in Wuhan before and after the lockdown. Expected findings: We expect there be a correlation between Covid-19 infection rate and outdoor air pollution. We also expect that reduced intra-city movement after the lockdowns in Wuhan and the rest of China will play an important role in reducing the infection rate. Interpretation: Infection rate is growing exponentially in major cities worldwide. We expect Covid-19 infection rate is related to the air pollution concentration, and is strongly dependent on inter- and intra-city movements. To reduce the infection rate, the international community may deploy effective air pollution reduction plans and social distancing policies.

Background and Objectives: The COVID-19 pandemic influenced the management of patients with immune mediated rheumatic and musculoskeletal diseases (imRMDs) in various ways. The goal of our systematic review was to determine the influence of the first period of the COVID-19 pandemic on the management of imRMDs. Materials and Methods: Systematic literature search of PubMed, Cochrane and Embase databases, including studies with adult patients on the influence of the COVID-19 pandemic on management of imRMDs. There were no restrictions regarding to study-design except for systematic reviews and case reports that were excluded as well as articles on the disease outcomes in case of SARS-CoV-2 infection. Two reviewers screened the studies for inclusion, and, in case of disagreement, consensus was reached after discussion. Results: A total of 5969 potentially relevant studies were found, and, after title, abstract and full-text screening, 35 studies were included with data from 182’746 patients and 2018 rheumatologists. Non-availability of drugs, e.g., hydroxychloroquine and tocilizuab, was frequent (16–69% of patients). Further, medication non-adherence was reported among patients with different RMDs and between different drugs in 4–46% of patients. Changes to preexisting medication were reported in up to 33% of patients (e.g. reducing dose of steroids or cessation of biological disease-modifying antirheumatic drugs). Physical in-office consultations and laboratory testing decreased and as a consequence newly implemented remote consultations increased greatly with an increase of up to 80%. Conclusion: The COVID-19 pandemic influenced the management of imRMDs, especially at the beginning. Influences were wide-ranging, affecting availability of pharmacies, adherence to medication or medication changes, doctor visits and laboratory testing. New systems of care were set up, including virtual clinics and video consultations. These new forms of health care delivery should be spread and implemented worldwide to routine clinical practice to be ready for future pandemics.

COVID-19 greatly challenges human beings in the health sector and leaves behind a large amount of medical waste that poses many potential threats to the environment. In this paper, we compiled relevant data released by official agencies and the media, and conducted data supplementation based on previous studies to calculate the net value of medical waste production in Hubei Province during COVID-19 with the help of a neural network model. Then, we reviewed the data related to the environmental impact of medical waste per unit and designed four scenarios to estimate the environmental impact of new medical waste generated during the epidemic. The results showed that at a medical waste generation rate of\ 0.\ 5\ kg/(\ bed\ \cdot\ d) COVID-19 resulted in a net increase in medical waste volume of about 3366.99 tons in Hubei Province. In the four scenario assumptions, if the medical waste brought by COVID-19 is completely incinerated, it will have a large impact on the air quality. If it is disposed by distillation sterilization, it will produce a large amount of wastewater and waste residue. Based on the results of the study, three policy recommendations are proposed in this paper: strict control of medical wastewater discharge, reduction and transformation of the emitted acidic gases, and attention to the emission of metallic nickel in exhaust gas and chloride in soil. These policy recommendations provide a scientific basis for controlling medical waste pollution.

This study takes as a starting point the importance and dependence of the media (Ball-Rokeach & DeFleur, 1976) to obtain information about the pandemic. The dependency theory of the media system was developed in the 1970s when mass media were the dominant source of information. Today, at a time when media choices have become abundant, studies are needed to understand the phenomenon of media dependence in light of new dimensions made important by the transformations that have taken place in the social and media fields - where the coexistence of mass media with social media platforms stands out. As large-scale crises rarely occur and the media environment changes rapidly, it is important to analyze how media dependence relates to choose and trust in different media (traditional media vs. social media) in times of crisis. Several questions arise. What is the trust attributed by individuals to social media as sources of information about the COVID-19? How well informed are the individuals who choose these sources as the main sources of information? From a questionnaire administered to 240 individuals in Portugal, during the first week of the state of emergency (March 2020), this research seeks to identify how people gained access to information about the COVID-19, how they acted critically towards the various sources and how they assess the reliability of different media. Finally, it analyzes the association between the type of medium chosen and adherence to misinformation content about the virus. The results reveal the existence of a phenomenon of dependence on the media, with a strong exposure (both active and accidental) to informative content, with conventional media being privileged as the main source, and positively distinguished in terms of confidence. Finally, a statistically significant association of a positive sign was identified between the use of social media as the main source and the acceptance of misinformation.

(1) Background: COVID-19 was responsible for the latest pandemic, shaking and reshaping healthcare systems worldwide. Its late clinical manifestations make it linger in medical memory as a debilitating illness over extended periods. (2) Methods: Recent literature was systematically analyzed to categorize and examine the symptomatology and pathophysiology of Long COVID across various bodily systems, including pulmonary, cardiovascular, gastrointestinal, neuropsychiatric, dermatological, renal, hematological, and endocrinological aspects. (3) Results: The review outlines the diverse clinical manifestations of Long COVID across multiple systems, emphasizing its complexity and challenges in diagnosis and treatment. Factors such as pre-existing conditions, initial COVID-19 severity, vaccination status, gender, and age were identified as influential in the manifestation and persistence of Long COVID symptoms. This condition is highlighted as a debilitating disease capable of enduring over an extended period and presenting new symptoms over time. (4) Conclusions: Long COVID emerges as a condition with intricate multi-systemic involvement, complicating its diagnosis and treatment. The findings underscore the necessity for a nuanced understanding of its diverse manifestations to effectively manage and address the evolving nature of this condition over time.

Severe Acute Respiratory Syndrome Coronavirus - 2 (SARS-CoV-2), later renamed Coronavirus Disease 2019 (COVID-19) was first identified in Wuhan, China, in early December 2019. Initially, the China office of the World Health Organization was informed of numerous cases of pneumonia of unidentified etiology in Wuhan, Hubei Province on December 31, 2019. This would subsequently result in a global pandemic with over 76 million confirmed cases of COVID-19 and 6.9 million deaths reported to the WHO. We have analyzed most of the data published since the beginning of the pandemic to compile this comprehensive review of SARS-CoV-2. We look at the core ideas, such as the etiology, epidemiology, pathogenesis, clinical symptoms, diagnostics, histopathologic findings, consequences, therapies, and vaccines. We have also included the long-term effects and myths associated with some therapeutics of COVID-19. This study comprehensively assesses of the SARS-CoV-2 virology, vaccines, medicines, and significant variants identified during the pandemic. Our review article is intended to provide medical practitioners with a better understanding of the fundamental sciences, clinical treatment, and prevention of COVID-19. As of June 2023, this paper contains the most recent data made accessible.

In the wake of the Covid-19 crisis, a need has arisen to prevent and treat two related conditions, Covid vaccine injury and long Covid, both of which have a significant vascular component. Therefore, the management of these conditions require the development of strategies to prevent or dissolve blood clots and restore circulatory health. This review summarizes the evidence on strategies that can be applied to treat both long and vaccine injuries based on similar mechanisms of action.

The long-term laboratory aspects of the effects of COVID-19 on liver function are still not well understood. Therefore, this study aimed to evaluate the hepatic clinical-laboratory profile of patients with up to 20 months of long-term COVID-19. A total of 243 patients of both sexes aged 18 years or older hospitalised in the acute phase of COVID-19 were included in this study. Liver function analysis was performed. Changes were identified in the mean levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactate dehydrogenase (LDH), gamma-glutamyl transferase (GGT), and ferritin. Inflammatory markers such as ferritin > 300 U/L were observed in the group that presented more changes in liver function markers (ALT, AST, and GGT). Age ≥ 60 years, male sex, AST > 25 U/L, and GGT ≥ 50 or 32 U/L were associated with ALT > 29 U/L. There was a correlation between ALT and AST, LDH, GGT, and ferritin. Our findings suggest that ALT and AST levels may be elevated in patients with long-term COVID, especially in those hospitalised in the acute phase. In addition, ALT > 29 U/L was associated with other markers of liver injury, such as LDH, GGT, and ferritin.

With the widespread application of artificial intelligence technology in various industries, users' attention to privacy and data security has increased significantly. Federated learning, as a new technology paradigm combining privacy-enhanced computing and artificial intelligence, resolves the contradiction between data security and open sharing. This paper presents the benefits of federated learning in terms of privacy, real-time processing, model robustness, compliance and cross-industry applications. At the same time, when combined with Edge AI technology, federated learning promotes the decentralisation of intelligent systems, improving data privacy protection and model accuracy. This paper also discusses the application cases of federated learning in the medical field, through local data processing and model training, effectively protecting user privacy, realizing medical data sharing and model optimization, and promoting the development of artificial intelligence.

Electric Transformers make up some of the most critical components of a power system. Their reliable operation is critical for an efficient power grid as well as economic viability for the transformer operators and owners. Power transformers, like other High Voltage (HV) electrical equipment experience aging and insulation degradation due to chemical, mechanical and electrical forces during their operation. Partial Dischargers (PD) are localized electrical discharges that develop within insulation systems of HV electrical equipment such as transformers. In transformers, PD occurs in different forms and various locations and insulation both internal and external of the transformer. PD originates as small pulses but tends to increase in size and intensity which can result in complete insulation failure. Monitoring partial discharges has proven to provide valuable information on the state of the insulation systems of the power transformer, allowing transformer operators to make calculated decisions for the maintenance and life of plant plans. This systematic literature review aims to systematically examine the use of machine learning techniques in classifying PD in transformers to present a complete indicator to allow for future research in the field. The systematic review surveyed a total of 81 research literature published from 2010 to 2023 that fulfilled a specific methodology which was developed as part of this study. The results revealed that supervised learning has been the most widely used Artificial Intelligence (AI) algorithm utilized, primarily in the form of Support Vector Machine (SVM). Regarding PD, the survey revealed that most researchers tend to use numerous types of PD and compare them to one another. Furthermore, the use of artificial PD defect models to simulate the occurrence of PD is widely used versus the use of actual power transformers. Most of the literature tends to not specify the physical characteristics of PD, such as the magnitude of PD, PD inception voltage and PD extinction voltage.

Given the widespread use of AI language models such as ChatGPT, there is an urgent need 1 to understand their political biases in different languages. This study aims to uncover such biases. To 2 investigate this issue, we applied IDRLabs’ Political Coordinates Test to ChatGPT based on GPT-4 3 in four languages - English, French, German, and Italian. The results confirm previous studies that 4 identified a left-libertarian bias in ChatGPT. There was remarkable consistency in political orientation 5 across all four languages, although minor variations were found. Differences in ChatGPT response 6 distributions across languages could indicate culturally determined differences in interpretation 7 of political questions. The results highlight the need to diversify and optimize data collection and 8 model training methods to ensure greater fairness and neutrality and minimize the influence of bias. 9 Our study highlights the importance of cultural differences in the processing and interpretation of 10 political information by AI models.

Background: Atopic dermatitis (AD), a common dermatological condition, is often associated with significant economic and social burdens. Despite extensive studies globally, there is a gap in understanding the comprehensive impact of this condition in Romania. Objectives:This study evaluated the economic burden and quality of life impact of AD in Romania, considering both direct and indirect costs. Materials & Methods: A mixed methods cost of illness study was conducted from April to October 2023. A patient survey, expert reviews, and national health data analysis were used to assess direct medical costs (treatments, medical services), direct non-medical costs (transportation, accommodation), and indirect costs (productivity losses). Quality of life was evaluated using the EuroQol EQ-5D-5L instrument. Results: In 2022, the total cost of atopic dermatitis in Romania was 32.983.498 EUR for adults and 31.573.968 EUR for children. Adult costs included 24.534.603 EUR in direct and 8.429.884 EUR in indirect medical costs, with an average annual cost per patient of 447 EUR. Pediatric costs involved 15.026.781 EUR in direct and 16.516.410 EUR in indirect costs, averaging 290 EUR per patient annually. Conclusion: Care expenditure with AD management in Romania is substantially lower than in other countries, posing a significant economic burden, primarily driven by indirect costs. This study provides a foundation for future policy interventions and highlights the need for targeted management strategies for AD.

Background : Probiotics are composed of microorganisms that have positive effects on health when consumed in prescribed quantities. Lately, studies have attempted to establish this role of probiotics in enhancing health. Aim : The aim of this study was to compare the antifungal activity of 3 different probiotics against Candida albicans.Methodology :This was an in-vitro study. 3 types of commercially available probiotics - Bifilac, Pre pro HS and VSL-3 were cultured separately with Candida albicans and were placed under incubation. The maximum zone of inhibition was recorded for each of the probiotic solutions.Results : In this study, it was found that among the three probiotic products, Bifilac exhibited a maximum zone of inhibition of 13mm at concentration of 100µL against C. albicans, while Pre pro HS and VSL-3 showed zone of inhibition of 11mm at concentrations of 50µL and 100µL, respectively.Conclusion : Within the limits of the present study, This study could prove that probiotics can be considered as an alternative and safe treatment option for treatment of Oral candidiasis infections.

In order to search possible residual minor phases in Y-Ba-Cu-O family, powdered mixtures of Y₂O₃ + BaCO₃ + CuO and, independently, superconducting compound YBa₂Cu₃O_7-x have been treated in evacuated cells and elevated temperatures.YBa₂Cu₃O_7-x was reduced to YBa₂Cu₃O₅ by use of the special home designed Taconis-Knudsen vacuum device. A subsequent doping by oxygen converts produced insulator YBa₂Cu₃O₅ to semiconductor or metal YBa₂Cu₃O_5+x (0<x<0.3). In addition to YBa₂Cu₃O₅, 0.05 volume percent of the minor delafossite phase Y₂Cu₂O₄ was being spotted in the powder mixture 1/2 Y₂O₃ + 2BaCO₃+6Cu₂O, heated up to 818 °C in an inert gas atmosphere. An attempt to prepare the insulating bulk delafossite samples was successful, and subsequent doping by oxygen produces novel metallic phases.

Molecular docking, a computational method predicting how molecules bind to target proteins, is employed in this study to explore Polydatin's interactions with Ras-related protein Rab (Rab) proteins using the Mcule Database. This database validates the docking results and offers insights into the pharmacological properties of Polydatin. Notably, specific Rab proteins like Rab-5A, HRas, and Rab-18 exhibit robust interactions with Polydatin, indicated by favorable binding energies.These findings illuminate the potential roles of Polydatin in therapeutic and biological contexts, emphasizing its interaction with Rab proteins. The Mcule Database enhances the credibility of the study, providing additional perspectives on Polydatin's applications. The observed interactions, particularly with key proteins like HRas, present a promising avenue for modulating cellular signaling pathways. This modulation holds therapeutic potential, potentially addressing conditions associated with pathway overactivity, including specific cancer types.

Aedes aegypti and Aedes albopictus are responsible for transmitting major human arboviruses such as dengue, Zika, and Chikungunya, posing a global threat to public health. The lack of etio-logical treatments and efficient vaccines makes vector control strategies essential for reducing vector population density and interrupting pathogen transmission cycle. This study evaluated the impact of long-term pyriproxyfen exposure on the genetic structure and diversity of Ae. aegypti and Ae. albopictus mosquito populations. The study was conducted in Manaus, Amazonas, Bra-zil, where pyriproxyfen dissemination stations have been monitored since 2014 up to the present day. Double digest restriction-site associated DNA sequencing was performed, revealing that despite significant local population reductions, focal pyriproxyfen interventions have no signifi-cant impact on the population stratification of Ae. aegypti and Ae. albopictus in urban scenarios. The genetic structuring level of Ae. aegypti suggests it is more stratified and directly affected by PPF intervention, while for Ae. albopictus exhibits a more homogeneous and less structured popu-lation. The results suggest that although slight differences are observed among mosquitoes sub-populations, intervention focused on neighborhoods in a capital city is not efficient in terms of genetic structuring, indicating that larger-scale pyriproxyfen interventions should be considered for more effective urban mosquito control.

The gut microbiota plays a crucial role in maintaining host health and has a significant impact on human health and disease. In this study, we investigated the alpha diversity of gut microbiota in COVID-19 patients and analyzed the impact of COVID-19 variants, antibiotic treatment, type 2 diabetes (T2D), and metformin therapy on gut microbiota composition and diversity. We used a culture-based method to analyze the gut microbiota and calculated alpha-diversity using the Shannon H' and Simpson 1/D indices. We collected clinical data, such as length of hospital stay (LoS), C-reactive protein (CRP) levels, and neutrophil-to-lymphocyte ratio (NLR). We found that patients with T2D had significantly lower alpha-diversity than those without T2D. Antibiotic use was associated with a reduction in alpha-diversity, while metformin therapy was associated with an increase. We did not find significant differences in alpha-diversity between the Delta and Omicron groups. Length of hospital stay, CRP levels, and NLR showed weak to moderate correlations with alpha diversity. Our findings suggest that maintaining a diverse gut microbiota may benefit COVID-19 patients with T2D. Interventions aimed at preserving or restoring gut microbiota diversity, such as avoiding unnecessary antibiotic use and promoting metformin therapy, may improve patient outcomes.

Background: Signaling by toll like receptors (TLRs) initiates important immune responses against viral infection. The role of TLRs in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections is not well elucidated. Thus, we investigated the interaction of TLRs agonists and SARS-COV-2 antigens with immune cells in vitro. Material & methods: 30 coronavirus disease 2019 (COVID-19) patients (15 severe and 15 moderate) and 10 age and sex matched control (HC) were enrolled. Peripheral blood mononuclear cells (PBMCs) were isolated and activated with TLR3, 7, 8 and 9 agonists, the spike protein (SP) of SARS-CoV-2 and the Receptor Binding Domain (RBD) unit of SP. Frequencies of CD3⁺IFN-β⁺ T cells, and CD3⁺IFN-g⁺ T cells was evaluated by flow cytometry. Interferon (IFN)-b gene expression was assessed by qRT-PCR. Results: The frequency of CD3+IFN-β+ T cells was higher in moderate and severe patients at baseline in comparison with HCs. Stimulation of PBMCs from moderate patients with SP and TLR8 agonist significantly upregulated the frequency of CD3+IFN-β+ T cells (P=0.0005 and 0.0024, respectively) when compared to non-stimulated (NS) samples. The greatest increase in CD3⁺IFN-b⁺ T cell frequency in PBMCs from severe patients was seen with TLR8 and TLR7 agonists when compared to NS (P= 0.003 and 0.0167, respectively). TLR stimulation did not significantly enhance the frequency of CD3+IFN-g+ T cells generated from PBMCs from moderate and severe patients compared with unstimulated controls. However, the frequency of CD3+IFN-ɣ+ T cells in PBMCs from moderate patients was upregulated by agonists of TLR3, 8 and 9, SP and RBD when compared with NS samples from HCs. The expression of the IFN-β gene after stimulation of CD3⁺T cells with the TLR8 agonist was also up-regulated in moderate than severe patients (moderate vs. severe: p=0.0006). In addition, stimulation of CD3⁺ T cells with SP, up-regulated the expression of IFN-β gene expression in cells from patients with moderate disease (moderate vs. severe: p=0.01). Conclusion: Stimulation of PBMCs from COVID-19 patients with a TLR8 agonist and with SP enhanced IFN-b protein and gene levels. This may potentiate immune responses against SARS-CoV-2 infection and prevent viral replication and spread.

Access to health services compromises therapeutic adherence in patients with HTN, which is a risk factor for cardiovascular disease and premature death. The aim of the research is to determine the influence of access to health services on adherence to antihypertensive treatment during the COVID-19 pandemic. We included a cross-sectional analytical study. A survey was applied to 241 hypertensive patients at the Daniel Alcides Carrión Hospital, Callao-Peru. Data were analyzed using SPSS software. Absolute and relative frequencies were reported and the chi-square test was applied with a statistical significance level of p&lt;0.05. In addition, multiple logistic regression analysis was performed using the Stepwise method. An association was found between non-adherence to treatment and health expenses (ORa: 1.9 CI 95% 1.7-2.2), not receiving care due to lack of a doctor (ORa: 2.8 CI 95% 1.5-3.2), having difficulty with schedules (ORa: 3.7 CI 95% 2. 3-5.5), fear of receiving care at the hospital (ORa: 4.5 CI 95 % 2.7-6.8), trust in health personnel (ORa: 7.5 CI 95% 2.3-10.5) and considering that the physician does not have enough knowledge (ORa: 3.1 CI 95% 2.4-7.8). Therapeutic adherence was associated with physician availability for care, difficulty with schedules, fear of being seen in the hospital, trust in health personnel, and waiting time.

The coronavirus disease (COVID-19), an emerging viral infection, is impacting the social, economic and political patterns of the world. To contain the spread of this pandemic, Nigeria like many countries globally, has imposed drastic preventive measures such as physical distancing and lockdown/curfew. This study assessed the knowledge, attitude and perception (KAP) about COVID-19 among members of staff of a university community in southwest, Nigeria. A cross-sectional survey using an anonymous, self-designed, online KAP questionnaire was conducted from April 18 to May 31, 2020. Purposive and chain referral sampling techniques were used to recruit respondents from the teaching and non-teaching categories of the university. The KAP questionnaire consisted of ten knowledge questions regarding the identification of clinical characteristics, transmission and prevention of COVID-19. The questions on attitude (15) and perception (10) assessed respondents on adherence to policies and their views on government efforts to contain the spread of the infection respectively. A total of 125 (teaching) and 102 (non-teaching) staff responded. The respondents had scientific (78.8 %) and non-scientific (28.2 %) work background. Approximately 59.1 % of the respondents were males. The mean knowledge and positive attitude levels were 70.8 % (SD ± 9.6 %) and 83.1 % (SD ± 13.07 %) respectively. Significant differences in the knowledge mean scores were observed for demographic categories such as educational qualification (p = 0.0006), staff work category (p = <0.0001), work background (p = <0.0001), and type of lockdown (p = 0.0271). Most of the respondents (85.3 %) opined that COVID-19 was a biological weapon and viewed the lockdown as necessary (81.5 %). However, they thought that the Nigerian government was not doing enough to mitigate COVID-19 spread. The perception of COVID-19 in the university community bear implications across public health initiatives, compliance with precautionary behaviour and bilateral relations with foreign nations.

Watching the international COVID-19 epidemics unfold during February and early March 2020, we began to highlight how outbreaks in care homes were inevitable, given the vulnerable patients in close proximity, and pressures on social care to help relieve pressure on the NHS. We suggested public health measures would significantly impact on care homes. Specifically we felt all homes would have multiple individuals isolated within days of introduction of guidance requiring isolation of new cough (or fever), and that a clear definition of an outbreak would be needed that differentiated COVID19 from influenza. We share the experiences of a GP practice looking after 900 nursing or dual registration care homes in the London Borough of Ealing in the early stages of the COVID19 Pandemic 2020. We believe that the altered presentation of cases of COVID19 in care homes contributed to the size of outbreaks, and that keeping COVID19 out of homes is the only way to manage this disease, with early isolation and complete segregation of positive and negative cases. We have seen over 300 suspected cases resulting in four fold (n=175) average monthly death rates, three fold usual issue of anticipatory medications, and approximately 32% mortality rate (up to 43% in over 90’s). Discharge pathways from hospital and admissions to care homes must be clear and robust. COVID19 naïve patients should not be admitted to units with outbreaks and COVID19 positive patients should not be admitted to anything other than a designated “hot” home until risk of contagion is passed. Some patients are testing positive at over 30 days since initial mild symptoms.

The COVID-19 pandemic has forced Indian engineering institutions (EIs) to bring their previous half-shut shades completely down. Fetching new admissions to EI campuses during the pandemic has become a ‘now or never’ situation for EIs. During crisis situations, institutions have struggled to return to the normal track. The pandemic has drastically changed students’ behavior and family preferences due to mental stress and the emotional life attached to it. Consequently, it becomes a prerequisite, and emergencies need to examine the choice characteristics influencing the selection of EI during the COVID-19 pandemic. The purpose of this study is to critically examine institutional influence and pandemic influence due to COVID-19 that affects students’ choice about an engineering institution (EI) and consequently to explore relationships between institutional and pandemic influence. The findings of this quantitative research, conducted through a self-reported survey, have revealed that institutional and pandemic influence have governed EI choice under the COVID-19 pandemic. Second, pandemic influence is positively affected by institutional influence. The study demonstrated that EIs will have to reposition themselves to normalize pandemic influence by tuning institutional characteristics that regulate situational influence and new enrollments. It can be yardstick for policy makers to attract new enrollments under pandemic situations.

The phenomenon of vaccine hesitancy is a growing threat to public health with far-reaching implications. The widening gap between the vaccinated and the proportion needed for herd immunity raises two critical research questions that are of interest to practitioners, researchers, and policymakers: (1) What determines one’s decision to be vaccinated? and (2) What is the implication of COVID-19 vaccine hesitancy on economic recovery? In this study, we use empirical data in the context of South Africa to investigate factors affecting COVID-19 vaccine hesitancy and their implications for economic recovery. Findings reveal key socio-demographic and institutional drivers of COVD-9 vaccine hesitancy, which include age (the youth are more hesitant), inadequate information on the vaccine (those who perceive they have adequate information are vaccinated), trust issues in government institutions, conspiracy beliefs, vaccine-related factors, and perceived side effects associated with the vaccine. Additionally, an individual’s decision to remain hesitant about COVID-19 vaccination has implications for businesses and the economy by limiting movement and trade, increasing unemployment, and causing a resurgence of new variants. Based on the findings, action plans such as information dissemination, convenience vaccination centers, consistency communications, and targeted campaign strategies are recommended for improving vaccine intakes and a positive economic recovery.

Since December 2019, the world is fighting against coronavirus disease (COVID-19). This disease is caused by a novel coronavirus termed as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This work focuses on the applications of machine learning algorithms in the context of COVID-19. Firstly, regression analysis is performed to model the number of confirmed cases and death cases. Our experiments show that autoregressive integrated moving average (ARIMA) can reliably model the increase in the number of confirmed cases and can predict future cases. Secondly, a number of classifiers are used to predict whether a COVID-19 patient needs to be admitted to an intensive care unit (ICU) or semi-ICU. For this, classification algorithms are applied to a dataset having 5644 samples. Using this dataset, the most significant attributes are selected using features selection by ExtraTrees classifier, and Proteina C reativa (mg/dL) is found to be the highest-ranked feature. In our experiments, random forest, logistic regression, support vector machine, XGBoost, stacking and voting classifiers are applied to the top 10 selected attributes of the dataset. Results show that random forest and hard voting classifiers achieve the highest classification accuracy values near 98%, and the highest recall value of 98% in predicting the need for admission into ICU/semi ICU units.

Currently, the COVID‐19 has directly affected the millions of humans lives. The symptoms of the disease involving fever, malaise, chest infection, and breathing difficulties, were identified, and its existence is continuously becoming restructured. The World Health Organization (WHO) had mentioned the wide diagnostics test besides COVID-19 that would also assist medical facilities to recognize infectious diseases as well as currently focusing efficiently on preventing and afterward defeating this viral disease. The infection is usually transmitted among human beings in direct contact, greatest through the liquid bubbles generated through cough, sneeze, or speaking. This paper reviews the COVID 19 pandemic, its history, current updates, contact tracing applications, and use of emerging technologies like the Internet of Things (IoT) and Blockchain for stopping the spreading and provide service online to the patient from a distance.

The novel respiratory disease COVID-19 has reached the status of worldwide pandemic and large efforts are currently being undertaken in molecularly characterizing the virus causing it, SARS-CoV-2. The genomic variability of SARS-CoV-2 specimens scattered across the globe can underly geographically specific etiological effects. In the present study, we gather the 48,635 SARS-CoV-2 complete genomes currently available thanks to the collection endeavor of the GISAID consortium and thousands of contributing laboratories. We analyze and annotate all SARS-CoV-2 mutations compared with the reference Wuhan genome NC_045512.2, observing an average of 7.23 mutations per sample. Our analysis shows the prevalence of single nucleotide transitions as the major mutational type across the world. There exist at least three clades characterized by geographic and genomic specificity. In particular, the clade G, prevalent in Europe, carries a D614G mutation in the Spike protein, which is responsible for the initial interaction of the virus with the host human cell. Our analysis may drive local modulation of antiviral strategies based on the molecular specificities of this novel virus.

A novel coronavirus has been reported as the causative pathogen of the Coronavirus disease 2019 (COVID-19) outbreak Wuhan city, China in December 2019. Due to the rapid spreading of COVID-19 worldwide, it has been announced as a pandemic by the World Health Organization (WHO). Hospitalized patients in Wuhan are associated with the Huanan seafood wholesale market where live animals, such as poultry, bats, snakes, frogs, rabbits, marmots, and hedgehogs are sold in that market which suggests a possible zoonotic infection. Therefore, it is essential to identify the potential animal reservoir, and the possibility of infection for other animal species. This short review aims to provide an overview on the relation between severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2) infection and animals.

The recent pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread so rapidly and severely affected the people of almost every country in the world. The highly contagious nature of this virus makes it difficult to take control of the present pandemic situation. With no specific treatment available, the coronavirus disease 2019 (COVID-19) presents a threat to people of all ages including the elderly people and people with other medical complications as a vulnerable group to this disease. Better understanding of viral pathogenesis, appropriate preventive measures, early diagnosis and supportive treatments of the infected patients are now the general solutions to fight against this viral transmission. But, as an emerging disease, most about it remains still poorly understood. This article holds an overview on the origin and structure, pathogenesis, diagnosis and possible therapeutic options for the causative agent, SARS-CoV-2 and disease, COVID-19. However, few therapeutic options, laboratory experiments and other strategies proposed here need to be further clinically tested.

Abstract: COVID-19 in 2020 brought challenges to the Brazilian public health system with an emerging virus with respiratory contagion called SARS-CoV-2. There are few studies in Brazil and in some countries, on the increased incidence of certain viral respiratory infections, includ-ing H1N1 and coronavirus and their association with low levels of vitamin D, zinc and iron. The aim of this study was to demonstrate that the deficit of vitamin D, zinc and iron has an impact on the infectious process of patients with COVID-19 and to establish new forms of prevention for the worsening of COVID-19 in the human body. Data were collected from medical records and test results from patients being followed up during the treatment period for COVID-19. Patients with low blood levels of vitamin D, zinc and iron during the treatment period of COVID-19 had a higher percentage of worsening and complications requiring hospitalization in intensive care beds. The ingestion of vitamin D, zinc and iron in the treatment period of patients with COVID-19 in addition to being an immunological protector against SARS-CoV-2 and alleviating the process of worsening the disease can also act as a biomarker in cases of this disease.

Background Olfactory perception is an important physiological function for the human well-being and health. Loss of olfaction, or anosmia, caused by viral infections such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) received a considerable attention especially in the persistent cases that take long time to recover. Objectives This review discusses the integration of different components of the olfactory epithelium to serve as a structural and functional unit, and explores how they are affected during viral infections, leading to the development of olfactory dysfunction. Methods The review mainly focused on the role of receptors mediating the disruption of olfactory signal transduction pathways such as ACE2, TMPRSS2 protease, neuropilin 1 (NRP1), basigin (CD147), olfactory, TRPV1, purinergic, and interferon gamma receptors. Furthermore, the compromised function of the epithelial sodium channel (ENaC) induced by SARS-CoV-2 infection and its contribution in olfactory dysfunction is also discussed. Results Collectively, this review provides fundamental information about the many types of receptors that may modulate olfaction and participate in olfactory dysfunction. It will help to understand the underlying pathophysiology of virus-induced anosmia which may help in finding and designing effective therapies targeting molecules involved in viral invasion and in olfaction. Conclusion This wide and complex spectrum of receptors that mediates the pathophysiology of olfactory dysfunction reflects the many ways by which anosmia can be therapeutically managed.

This study discusses the application of deep learning technology in network intrusion detection systems (IDS) and focuses on a new model named CNN-Focal. First, through the review of traditional IDS technology, it analyzes its limitations in dealing with complex network traffic. Then, the design principle of the CNN-Focal model is described in detail, which uses threshold convolution and SoftMax multi-class classification technology to effectively improve abnormal traffic detection's accuracy and efficiency. The experimental results show that CNN-Focal performs well on the open data set, demonstrating the potential and advantages of its application in the natural network environment and providing a new perspective and method for further research of deep learning in the field of network security in the future.

This qualitative research explores the impact of Supplier Relationship Management (SRM) on e-commerce brand reputation, focusing on the strategic imperatives, operational challenges, and economic implications within digital supply chains. Trust emerges as a foundational element in effective SRM practices, facilitating consistent product quality, timely delivery, and consumer trust, thereby enhancing brand credibility and loyalty. Strategic alignment of SRM with organizational goals enables e-commerce brands to leverage supplier capabilities for mutual growth and innovation. Operational challenges such as technological constraints and logistical complexities underscore the importance of digital integration and proactive risk management strategies to optimize SRM effectiveness. Digital technologies, including AI and blockchain, play a transformative role in enhancing transparency, efficiency, and resilience in SRM strategies, enabling e-commerce firms to mitigate risks and capitalize on market opportunities. Emotional intelligence (EI) competencies among supply chain professionals facilitate effective communication, conflict resolution, and sustainable supplier relationships that bolster brand reputation resilience. Economically, effective SRM practices yield cost efficiencies, improved financial performance, and resilience against supply chain disruptions, supporting sustainable growth in competitive digital markets. This study contributes valuable insights for practitioners and scholars aiming to enhance SRM strategies, optimize supplier relationships, and strengthen brand reputation management in e-commerce. By prioritizing trust, strategic alignment, digital innovation, EI competencies, and proactive risk management, e-commerce brands can navigate complexities, capitalize on opportunities, and foster positive brand reputations in the evolving landscape of digital commerce.

The outbreak of Coronavirus, as well as its emerging potential consequences, has become a global challenge worldwide, demanding effective and controlled therapeutic strategies. Potential drug candidates could achieve that with minimal toxicity. The current investigation selected 2-Deoxy-D-glucose prescribed by Defense Research and Development Organization (DRDO), India. The derivative and modified form was tested through in silico analysis against COVID-19 main protease complex with N3 inhibitor. The derived form of 2-Deoxy-D-glucose was generated by replacing the hydroxy group with a hydrogen atom, and Cypate 2-Deoxy-D-glucose was chosen as a derivative against the COVID-19 main protease complex. A molecular docking approach was adopted to identify the stable and competent form among the modified and derivative forms of 2-Deoxy-D-glucose based on binding energy. By further promoting the stabilized complex, these compounds' toxicity was also scrutinized through ADMET analysis to predict the potential candidate. The current investigation suggested that the modified version of 2-Deoxy-D-glucose was more stable with minimal toxicity against COVID-19 main protease.

The COVID-19 pandemic has highlighted the adverse consequences created by an infodemic specifically on compliance with public health guidance and vaccine uptake. COVID-19 vaccine hesitancy is a complex construct that is related to health beliefs, misinformation exposure, and perceptions of governmental institutions. This study draws on theoretical models and current data on the COVID-19 infodemic to explore the association between perceived risk of COVID-19, levels of misinformation endorsement, and opinions about the government response on vaccine uptake. We surveyed a sample of 2,697 respondents from the US, Canada, and Italy using a mobile platform between 21-28 May, 2021. Using multivariate regression, we found that country of residence, risk perception of contracting and spreading COVID-19, perception of government response and transparency, and misinformation endorsement was associated with the odds of vaccine hesitancy. Higher perceived risk was associated with lower odds of hesitancy, while lower perceptions of government response, and higher misinformation endorsement were associated with higher hesitancy.

Epithelial barrier damage plays a central role in the development and maintenance of allergic inflammation. The rise in airways epithelial barrier permeability alters the tissue homeostasis and allows the allergen and other external agents penetration. Different factors contribute to barrier impairment, such as eosinophilic infiltrate and allergens proteases action: the eosinophilic cationic proteins and the allergens' proteolytic activity have a central role in contributing to epithelial damage. In the airways, the allergens proteases degrade the epithelial junctional proteins allowing the allergen penetration and the uptake by dendritic cells. The increase in allergen-immune system interactions induce the release of the alarmins and the activation of type 2 inflammatory pathways causing, or worsening, the main symptoms at skin, bowel and respiratory levels. We aim to highlight the molecular mechanisms underlying allergenic proteases-induced epithelial barrier damage and the role of immune response in allergic asthma onset, maintenance and progression. We further will explore clinical and radiological potential biomarkers of airways remodeling in allergic asthma patients.

The urgency of the COVID19 pandemic caused a surge in related scientific literature. This surge made the manual exploration of scientific articles time-consuming and inefficient. Therefore, a range of exploratory search applications have been created to facilitate access to the available literature. In this survey, we give a short description of certain efforts in this direction and explore the different approaches that they used.

Most striking observations in COVID-19 patients are the hints on pulmonary edema (also seen on CT scans as ground glass opacities), dry cough, fluid restrictions to prevent more severe hypoxia, the huge PEEP that is needed while lungs are compliant, and the fact that anti-inflammatory therapies are not powerful enough to counter the severity of the disease. We propose that the severity of the disease and many deaths are due to a local vascular problem due to activation of B1 receptors on endothelial cells in the lungs. SARS-CoV-2 enters the cell via ACE2, a cell membrane bound molecule with enzymatic activity that next to its role in RAS is needed to inactivate des-Arg⁹ bradykinin, the potent ligand of the bradykinin receptor type 1 (B1). In contrast to bradykinin receptor 2 (B2), the B1 receptor on endothelial cells is upregulated by proinflammatory cytokines. Without ACE2 acting as a guardian to inactivate the ligands of B1, the lung environment is prone for local vascular leakage leading to angioedema. Angioedema is likely a feature already early in disease, and might explain the typical CT scans and the feeling of people that they drown. In some patients, this is followed by a clinical worsening of disease around day 9 due to the formation antibodies directed against the spike (S)-antigen of the corona-virus that binds to ACE2 that could contribute to disease by enhancement of local immune cell influx and proinflammatory cytokines leading to damage. In parallel, inflammation induces more B1 expression, and possibly via antibody-dependent enhancement of viral infection leading to continued ACE2 dysfunction in the lung because of persistence of the virus. In this viewpoint we propose that a bradykinin-dependent local lung angioedema via B1 and B2 receptors is an important feature of COVID-19, resulting in a very high number of ICU admissions. We propose that blocking the B1 and B2 receptors might have an ameliorating effect on disease caused by COVID-19. This kinin-dependent pulmonary edema is resistant to corticosteroids or adrenaline and should be targeted as long as the virus is present. In addition, this pathway might indirectly be responsive to anti-inflammatory agents or neutralizing strategies for the anti-S-antibody induced effects, but by itself is likely to be insufficient to reverse all the pulmonary edema. Moreover, we provide a suggestion of how to ventilate in the ICU in the context of this hypothesis.

If an AI entity is conscious, then it deserves moral status and to have its welfare protected. Society has granted certain animals moral status and has legislation to protect animal welfare because these kinds of animals have been deemed to be sentient. This paper shows that for any entity that can be determined to be conscious, that entity deserves the same status and protection as sentient entities. The paper further develops a framework for how an AI entity's welfare can be protected, based on the Five Freedoms of Animal Welfare. The extant Five Freedoms are translated into terms more suitable for artificial entities, encompassing discomfort and harms, constraints on inherent functions, fear and distress, malfunction and degradation, and resource depletion. Each of the new Five Freedoms are justified using formalised arguments and supported using evidence from animal welfare literature. The paper concludes by presenting three formalised case studies to highlight the potential stressors conscious AI entities may face and how this ethical framework can work to protect the welfare of AI entities.

Background. The main impetus behind the worldwide Covid-19 vaccination campaign in 2021 was to reduce the mortality attributed to SARS-CoV-2 infection in the preceding year. Nevertheless, rigorous analyses of the mortality benefits conferred by this massive vaccination effort have been lacking. Methods Statistics offers us an essential methodological approach for measuring the impacts of Covid-19 vaccination on public health. The mathematical relation between vaccinated-alive groups can be repeated between vaccinated-dead groups with relatively high statistical reliability because of the large population numbers involved. This method also confers greater statistical usefulness because it eliminates the Simpson effect. Results Calculations were performed for each of the following five(5) four-week intervals: weeks 35-38 (2021), weeks 39-42 (2021), weeks 43-46 (2021), weeks 47-50 (2021), and weeks 50(2021)-1(2022). The results obtained confirm that the mortality of the vaccinated coronavirus-infected groups was 14.5% higher on average than the mortality of non-vaccinated coronavirus-infected groups. Conclusions Vaccinated infected groups appear to have higher average mortality than their non-vaccinated infected counterparts. The findings suggest the legitimacy of extending the statistics between vaccinated living and vaccinated dead individuals for different age groups. Calculating the impact of Covid-19 vaccination on the mortality rate is a necessary step towards satisfying the first principle of medicine: “Primum non nocere”, “Do no harm”.

Background: A novel virulent coronavirus is what causes Novel Corona-virus Disease 2019 (nCOVID 19). It results in severe respiratory distress syndrome and potentially fatal infectious pneumonia. On March 12, 2020, the World Health Organization first labeled it a pandemic, which was then followed on the same day by a community health emergency of global concern. Vaccines against this deadly virus are now being created. Many drugs with different uses have been repurposed and tested for the prevention and treatment of the infection. Objective: The purpose of this review is to provide an in-depth analysis of data on possible pharmacological targets and available coronavirus treatments. Methods: Following the review protocol, a literature search was conducted. Results: Chloroquine phosphate and hydroxychloroquine, Remdesivir, and Lopinavir-Ritonavir in combination with or without interferon and convalescent plasma therapy are the main treatment candidates, according to the World Health Organization. This review article has elaborated on the current evidence of prospective pharmacological targets and related ongoing research, including inflammatory chemicals, bioactive peptides, beta cells, platelets, and the Angiotensin I Converting Enzyme 2 Receptor. This information was gathered from published journals. In addition, stories of medications and biological products like interferons and vaccinations that are utilized or could be utilized have been provided. Conclusion: There are a variety of pharmacological targets and therapeutic strategies that need more study.

Laser Powder Bed Fusion (L-PBF)-based manufacturing is a growing area of research, with a particular focus on evaluating constraints in printed products. This research emphasises the importance of considering various factors—including mechanical properties and support structures—that influence the final product during the design phase. Specifically, the design of microchannel heat exchangers is highlighted, where all constraints are critical. This article will present a method for analysing channel pressure limitations and report findings about mechanical properties loss from examining tube porosity. This includes a summary of results and the establishment of an experimental device system.

This paper explores the transformative impact of computational pharmaceutics, integrating AI, multi-scale modeling, quantum computing, AI-driven drug discovery, and blockchain frameworks. Molecular dynamics simulations provide insights into atomic behaviors crucial for drug design. Quantum computing reduces computational costs for simulating protein-drug interactions. AI and Graph Neural Networks accelerate drug discovery and personalized medicine. Blockchain frameworks facilitate secure pharmacogenetic data sharing. These advancements revolutionize drug development, offering unprecedented efficiency, innovation, and personalized treatments.

We are proposing, for any interested investigator, a randomized open clinical trial for mild and mild-to-moderate Covid-19 comparing a treatment regimen with standard of care, and eventually with another investigational regimen, if ongoing or will be implemented. The patients could be hospitalized or ambulatory but not requiring admission to intensive care units and mechanical ventilation. The proposed therapeutic regimen consists of doxycycline (an antimicrobial having also anti-inflammatory properties, probable antioxidant and possible some antiviral effects), and pentoxifylline, a hemorheological compound used in occlusive arterial diseases but also having proven anti-inflammatory properties. Doxycycline is included in the WHO’s list of essential medicine being an effective, safe, widely available, and inexpensive medication and widely accessible. It will be administered at a dosage of 100 mg orally twice daily for ten days. Pentoxifylline, in clinical use since 1972, and also widely accessible, will be given at a dosage of 400 mg orally, also twice daily, for ten days. The primary outcome measures are: 1) Progression of disease to a severe form requiring intensive care admission and mechanical ventilation; 2) Fatality rates and 3) Time to clinical recovery.This proposal was presented to the National Directors and Core Leads meeting of the Canadian Trials Network (CTN) on May 6, 2020. The interventional trial template suggested by CTN was used for designing the trial.

Advanced Persistent Threats (APTs) are sophisticated cyberattacks aimed at stealing sensitive information or causing damage over an extended period. Detecting APTs is crucial for maintaining cybersecurity, and machine learning (ML) has emerged as a powerful tool in this domain. This paper explores the role of ML algorithms in detecting APTs, comparing their accuracy and effectiveness. We evaluate various algorithms, discuss the challenges in achieving superior accuracy, and suggest strategies for improvement. Our findings highlight the potential and limitations of ML in APT detection, emphasizing the need for continuous advancements in this field.

This paper provides an overview of modelling and simulation methods for complex systems, including queuing and life support systems. To realize and capture every aspect of a system or situation, a model is used in place of the actual one. Using a model and simulation, we may create scenarios and make decisions. Computer experiments with the model can save costs, time, and effort once its validity has been shown. A model of the thing under study is created by computer simulation, which then runs the model on a digital computer and examines the results. It's interesting to note that a knowledge base of data includes information about predicted behaviour of the model as well as coordinated determination of external variables and parameters. Selecting the precise model creation technique is the first and most difficult task in simulation. A review of techniques used in simulation model execution (serial and parallel discrete-event simulation), simulation model analysis (calibration, validation, verification, goal-seeking), and conceptual, declarative, functional, constraint, and multimodal design are presented in this paper.

Background: Research articles are essential for describing new ideas, techniques, and procedures and consolidating concepts. It creates an opportunity to expose studies and publicly assimilate published knowledge. Therefore, one of them is the most used and accepted index to verify the author’s scientific impact is the H-index or Hirsch index. It provides a robust single metric that combines quality and quantity. Therefore, it presents disadvantages, (1) researchers with shorter scientific carriers may have fewer articles and citations than those with longer scientific life; (2) it allows scientists to receive citations even if no new papers are published; (3) it is only useful for comparing the better scientists in a field; (4) this indicator can never decrease; (5) it is only weakly sensitive to the number of citations received; (6) the major and minor (or no) contributor in the research gained equal h-index. Then, the H-index ignores the total of citations and the time of a researcher's experience (“scientific age” [sa]). Objective: Thus, the goal of this study was to present a new index system (GFsa index ©) based on the two variables completely forgotten (total of citations and “scientific age”), introducing a new terminology “scientific age”, to evaluate the best-ranked researchers in Dentistry. Methods: The AD Scientific Index was used, and all researchers included in this study were cited in the AD Scientific Index (2024) in the Dentistry field and had the Google Scholar page accessible for a consultation to manually obtain the total of citations and calculate the “scientific age”. The information was retrieved by two authors (G.V.O.F. and J.C.H.F.), who assessed the data twice to avoid errors or mistakes. For inclusion: a minimum H-index value of 30; for exclusion: (i) the author did not have a Google Scholar page; (ii) duplicated author; or (iii) presented any suspicious activities about manipulation of articles. Then, a dataset of all researchers who were reported in Dentistry was prepared (name, H-index, i10 index, and publications). The formula developed and applied was GFsa=(total number of citations)/(“scientific age)². The Pearson correlation statistically evaluated the data obtained; the confidence interval was 95%. Results: A total of 9,093 researchers in Dentistry were recorded, of whom 1,020 were included. Then, we collected all 1,020 researchers' Google Scholar data (publications, citations, and indexes), and each researcher's total citations and “scientific age” were registered and calculated. The mean “scientific age” registered was 34.18 ± 13.34 (standard error of mean = 0.4181). With this information and data collected, GFsa index © was calculated, presenting a minimum value of 0.2186 and a maximum of 154.8 (mean = 10.33 ± 11.82; standard error of mean = 0.3706). Then, the data was organized and sorted following the ranking obtained in the GFsa index ©. The Pearson correlation showed that the H-index had a weakly positive association with the researcher’s “scientific age”; this fact means that the H-index will increase according to the “scientific age” increase. Otherwise, a moderately negative correlation between GFsa and “scientific age” was demonstrated, whereby a higher GFsa © had a lower “Scientific age”. This assessment shows that the variables introduced were fairly used. Moreover, a positive correlation was observed between both indexes (H-index and GFsa). Conclusion: It is possible to conclude that the new variable reported (“Scientific age”) and using the total citations brought a fairer and more feasible evaluation among the researchers. Thus, we are launching the new GFsa index © and the new information named “Scientific age” for the first time in the literature. The future perspective of the GFsa © application will be (1) the evaluation of the 9,093 researchers in Dentistry (total initially registered), including more authors/researchers in the Dentistry field, (2) expanding the exposition of this new index for other areas of the knowledge, and (3) provide free access of all data through the website (http://gfindex.us.to).

Delineating the epidemic of vaccine injury from the coterminous condition long covid is a challenging prospect, but one with many implications not just for treatment, but also has important legal considerations for settlements of vaccine injury. The shared etiological factor of the spike protein in both vaccine injury and long covid make differentiation difficult, and while treatment is largely similar between vaccine injury and long covid, there are important distinctions. Furthermore, diagnostics are important for monitoring treatment progress and assessing the extent of subclinical vaccine injury in population having received a covid-19 vaccine. The development of rigorous diagnostics is an important step towards the recognition of both long covid and vaccine injury, as those suffering these conditions have faced immense challenges in having their conditions recognized, treated, and compensated by insurance companies or national health services.

The COVID-19 is an exponentially growing disease that has intentioned nations to use technologies to detect the coronavirus infection. Several nations are working greatly to fight against COVID-19. Many nations have been using a range of devices to combat the pandemic, seeking information about growth, monitoring as well as the leaking the confidential information of the residents. This research aims to assist infected people online using the Internet of Things (IoT) and Blockchain technologies through smart devices. IoT-based healthcare devices gather useful information, provide additional insight through symptoms and behaviors, allow remote monitoring, and simply give people better self - determination and healthcare. Blockchain allows the secure transfer of patient health information, regulates the medical distribution network. A four-layer architecture is proposed using IoT and Blockchain to detect and prevent individuals to be COVID 19. This research provides a framework for patients with COVID-19 infectious disease and recognizes health issues and diagnoses online. Smart devices such as smartphones can install any mobile apps such as Aarogya Setu, Tawakkalna, and so on. These applications can track COVID-19 patients properly. The installation of mobile apps on smart devices focuses to reduce the time and cost and increase the performance of the infectious patient's condition. A four-layer architecture is proposed using IoT and Blockchain technologies. Many research works focus on investigating, analyzing, and highlighting the affected individuals through guiding the COVID-19 infection. Eventually, various mobile apps are recognized and addressed in this paper.

After the first weeks of vaccination against the SARS-CoV-2, several cases of acute thrombosis were reported. These news reports began to be shared frequently across social media platforms. The aim of this study was to conduct an analysis of Twitter data related to the overall discussion. Data was retrieved from 14th March to 14th April using the keyword ‘blood clots’. A dataset with n=266,677 tweets was retrieved, and a systematic random sample of 5% of tweets (n=13,334) were entered into NodeXL for further analysis. Social network analysis was used to analyse the data by drawing upon the Clauset-Newman-Moore algorithm. Influential users were identified by drawing upon the betweenness centrality metric. Text analysis was applied to identify the key hashtags and websites used at this time. More than half of the network was comprised of retweets and the largest groups within the network were broadcast clusters where a number of key users were retweeted. The most popular narratives were around highlighting the low risk of obtaining a blood clot from a vaccine and highlighting higher blood clot risks in medicines commonly consumed. A wide-variety of actors drove the discussion on Twitter ranging from writers, physicians, the general public academics, celebrities, and journalists. Twitter was used to highlight the low potential of obtaining a blood clot from a vaccine and encouraged vaccinations among the public.

The emergence of the COVID-19 outbreak has caused a pandemic situation in over 210 countries. Controlling the spread of this disease has proven difficult despite several resources employed. Millions of hospitalization and deaths have been observed, and thousands of cases daily with many measures in place. Due to the complex nature of COVID-19, we proposed a system of time-fractional equations to understand the transmission of the disease better. Nonlocality involved in the model has made fractional differential equations appropriate for modeling the behavior. However, solving these types of models is computationally demanding. Our proposed generalized compartmental COVID-19 model incorporates effective contact rate, transition rate (from exposed quarantine and recovered to susceptible and infected quarantined individuals), quarantine rate, disease-induced death rate, natural death rate, natural recovery rate, recovery rate of quarantine infected for a holistic study of the coronavirus disease. A detailed analysis of the proposed model is carried out, including the existence and uniqueness of solutions, local and global stability analysis of the disease-free equilibrium analysis, and sensitivity analysis. Furthermore, numerical solutions of the proposed model are obtained with the generalized Adam-Bashforth-Moulton method developed for the fractional order model. Our analysis and solutions profile show that each of these incorporated parameters is very important in controlling the spread of COVID-19, especially quarantining exposed and infected individuals and the effective contact rate. Based on the results with different fractional order, we observe that there seems to be a third or even fourth wave of the spike in cases of COVID-19, which is what is happening right now in many countries.

In this COVID-19 pandemic, the use and dependency on Internet has grown exponentially. The number of people doing online activities such as e-learning, remote working, online shopping and others have increased. This has also led to increased vulnerability to cyber crimes. Cyber security attacks have become a serious problem. The common types of cyber security attacks are phishing, malware, ransomware, social engineering, identity theft and denial-of-service. The attackers target the victims in order to get their credential information or financial benefits. Those people who are doing online activities are vulnerable to cyber threats. This is because the network is not safe. The attackers are able to code according to the weaknesses of the Internet. Once the attackers hack into the devices, they have the root access and can do whatever they want to do with the device. In this research paper, the concept of cyber security attack and detailed research about real attacks are discussed. This is followed by detailed review about the recent cyber security attacks with a critical analysis. Moreover, the research paper will be proposing the latest research contribution of cyber security during COVID-19 and the implementation scenario which will give the examples about how the companies maintain privacy as well as the limitations. Then, the paper will be discussing the reasons that people are vulnerable to cyber security and the unique solution to the problems stated. Finally, this paper will conclude with an in-depth analysis and future direction for cyber security research.

We analyze the Covid-19 mortality scenario in India and compare it with those in other large-population regions such as Asia-excluding-China, Africa, European Union, South America, and USA. We compare existing fatality data and offer an interpretation for low fatality based on immunity due to endemic malaria and TB. We identify the hot climate in the past summer as a possible cause for low death count in southern-hemisphere countries without endemic malaria and TB. We also make India-specific observations for easing the lockdown and estimations for the time required to attain herd immunity. Whatever optimism we present should be viewed as a guarded optimism. There should not be room for complacency.

Background: On late December 2019, a viral pneumonia known as coronavirus disease 2019 (COVID-19), was originated from China and spread very rapidly in the world. Therefore, COVID-19 became a global concern and health problem. Methods: We presented four patients in this study. They were selected from patients who presented with pneumonia symptoms and were suspicious for COVID-19 and referred to the intended centers for COVID-19 diagnosis and management of Shiraz University of Medical Sciences in the south of Iran. Two nasopharyngeal and oropharyngeal throat swab samples were collected from each patient and tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection by real-time reverse-transcriptase–polymerase-chain-reaction (RT-PCR), and also samples were sent for influenza viruses and all the respiratory panel. Results: In the present report, four patients were diagnosed in the starting days of COVID-19 disease in our center in south of Iran with co-infection of SARS-CoV-2 and influenza virus. Conclusions: This co-infection of COVID-19 and influenza highlights the importance of considering SARS-CoV-2 PCR assay regardless of other positive findings for other pathogens in the primary test during the epidemic.

Aerobic glycolysis in cancer cells, originally observed by Warburg 100 years ago, which involves production of lactate as the end product of glucose breakdown even in the presence of adequate oxygen, is the foundation for the current interest in cancer cell-specific reprograming of metabolic pathways. The renewed interest in cancer cell metabolism has now gone well beyond the original Warburg effect related to glycolysis to other metabolic pathways to include amino acid metabolism, one-carbon metabolism, pentose phosphate pathway, nucleotide synthesis, antioxidant machinery, etc. Since glucose and amino acids constitute the primary nutrients that fuel the altered metabolic pathways in cancer cells, the transporters that mediate the transfer of these nutrients and their metabolites not only across the plasma membrane but also across the mitochondrial and lysosomal membranes have become an integral component of expansion of the Warburg effect. In this review, we focus on the interplay between these transporters and metabolic pathways that facilitates the metabolic reprogramming which has become the hallmark of cancer cells. The beneficial outcome of this recent understanding of the unique metabolic signature surrounding the Warburg effect is the identification of novel drug targets for development of a new generation of therapeutics to treat cancer.

The startup ecosystem in Peru has experienced remarkable growth in recent years, driven by technol- ogy and innovation across various industries. This article presents a web application developed in PHP, designed to centralize and facilitate access to information about startups, incubators, and investors in Peru. The methodology employed encompasses several stages, from establishing prerequisites to data preprocessing, model selection and training, rigorous evaluation, and the technical development of the platform. The application offers key functionalities such as exploring a comprehensive database of star- tups, detailed access to information about incubators and accelerators, identification of investors, and advanced analysis tools for market proposal prediction. Additionally, it integrates educational resources and allows users to suggest new startups through detailed surveys. The results demonstrate that the ap- plication improves access to relevant data, fosters collaboration among ecosystem actors, and supports informed decision-making. The platform also stands out for its security and privacy measures, as well as its ability to drive innovation and competitiveness in the market. In conclusion, the application has a sig- nificant impact on the Peruvian entrepreneurial ecosystem, and its continuous improvement is essential for the sustainable growth of startups in Peru and globally.

In New Orleans, Louisiana the population’s poor baseline health led to its establishment as an early epicenter for severe acute COVID-19. Antici-pating future outbreaks of COVID-19 and other respiratory viruses, we need to identify correlates of outcome, from real clinical experience. 89 patients were recruited into the ClinSeqSer acute COVID-19 longitudinal observational study, from the beginning of the outbreak in March to July 2020. Patients admitted for acute COVID-19 were enrolled in person. The cohort is unique as it is 68% Black, 53% female, of average age of early 60s, and prevalence of obesity and hypertension respectively of 55% and 83%. The outcomes are: 53% severe (20% fatal, 33% non-fatal) and 47% non-severe, with severe defined as death or requiring mechanical ventila-tion or high flow oxygen. Obesity and admit systolic blood pressure (SBP) >140mmHg are each associated with severe outcome and, despite respective sensitivity of 71% and 76%, specificity ~66% for both, and ac-curacy of 60% and 70% by ROC analysis, would likely provide useful predictors of outcome in critically stressed health care systems. We discuss pathophysiologic hypotheses to explain why high admit SBP is observed only in half of patients with pre-COVID hypertension and is associated with severe outcome.

Leukocyte migration is an essential function of innate and adaptive immune responses. Chemokines and their receptors control the migration system. The abundance of chemokines is controlled by atypical chemokine receptors (ACKRs), chemokine receptor-like molecules that do not couple to the G protein signaling pathways. Among them, ACKR4 regulates dendritic cell migration by controlling the ligands and is involved in tumor development in mouse models. Because no anti-mACKR4 mAb for flow cytometry has been reported, this study aimed to develop a novel monoclonal antibody (mAb) for mouse ACKR4 (mACKR4). Among the established anti-mACKR4 mAbs, A₄Mab-1 (rat IgG_2b, kappa), A₄Mab-2 (rat IgG_2b, kappa), and A₄Mab-3 (rat IgG_2b, kappa) recognized mACKR4-overexpressed Chinese hamster ovary-K1 (CHO/mACKR4) by flow cytometry. The dissociation constant (K_D) values of A₄Mab-1, A₄Mab-2, and A₄Mab-3 for CHO/mACKR4 were determined as 3.5 × 10⁻⁹ M, 6.0 × 10⁻⁹ M, and 1.6 × 10⁻⁹ M, respectively. Furthermore, A₄Mab-1 and A₄Mab-2 could detect mACKR4 by western blotting. These results indicated that A₄Mab-1, A₄Mab-2, and A₄Mab-3 help to detect mACKR4 by flow cytometry and western blotting and obtain the proof of concept in preclinical models.

We demonstrate how a rigorous mathematical approach can be used to extract a current CMB temperature of 2.7276 ±0.0723 K from the 580 type Ia supernova data points in the Union2 database. Using redshift formula: z = Sqrt(Rh/R_t) − 1, incorporated into our new CMB redshift prediction redshift formula, we find that the above current CMB temperature value is a remarkably good match for this particular data set. In addition, we can alternatively start out with the measured current CMB temperature and extract the Hubble constant from all 580 supernovae. We then get an estimated Hubble constant of H0 = 66.8711+0.0019 km/s/Mpc when using the CMB temperature from the recent Dhal et al study [1] in combination with redshifts from all 580 supernovae. Furthermore, we get an estimated Hubble constant value of H_0 = 66.8943+0.0287 km/s/Mpc when using the CMB temperature measured by Fixsen [2]. In summary, our simple model essentially perfectly matches all 580 type Ia supernova redshifts while extracting H_0 or T_0 values. The Hubble constant we extract by this method fits very well with the Hubble constant extracted from the CMB by other studies. We believe that our new approach likely solves the Hubble tension problem, at least inside R_h = ct cosmology.

The C-C motif chemokine receptor 8 (CCR8) is highly and selectively expressed in regulatory T (Treg) cells and is associated with tumor progression. The massive accumulation of Treg cells into tumors suppresses the effector function of CD8⁺ cells against tumor cells. Therefore, selective depletion of Treg cells using anti-CCR8 monoclonal antibodies (mAbs) reinvigorates antitumor immune responses and improves responses to cancer immunotherapy. Previously, we developed an anti-mouse CCR8 (mCCR8) mAb, C₈Mab-2, using the Cell-Based Immunization and Screening (CBIS) method. In this study, the binding epitope of C₈Mab-2 was investigated using flow cytometry. The mCCR8 extracellular domain-substituted mutant analysis showed that C₈Mab-2 recognizes the N-terminal region (1–33 amino acids) of mCCR8. Next, 1×alanine (or glycine) scanning and 2×alanine (or glycine) scanning were conducted in the N-terminal region. The results revealed that the _17-DFFTAP_-22 sequence is important for the recognition by C₈Mab-2, and Thr20 is a central amino acid of the epitope. These results revealed the involvement of the N-terminus of mCCR8 in the recognition by C₈Mab-2.

AbstractBackground: Empowering Communities, Combating HIV/AIDS: The Indispensable Role of Community-Based Strategies in Awareness and PreventionObjective: Highlight the significance of community-based approaches in addressing the ongoing HIV/AIDS pandemic through enhanced awareness, reduced stigma, and effective prevention measures.Method: This article provides a theoretical analysis of community-based HIV/AIDS interventions, drawing upon key strategies and successful examples from diverse settings.Results: Community-based initiatives emerge as critical factors in empowering individuals and communities to take ownership of their health. Through culturally-sensitive education, accessible testing, and comprehensive support services, these initiatives effectively diminish the social stigma surrounding HIV/AIDS and promote preventative behaviors. Examples of successful programs illustrate the potential of community-driven approaches to achieve measurable reductions in transmission rates and improved health outcomes.Conclusion: The fight against HIV/AIDS necessitates robust community engagement. Community-based interventions, grounded in local knowledge and addressing specific needs, offer a promising pathway towards fostering health equity, reducing stigma, and ultimately curtailing the spread of the virus. Further research and investment in these initiatives are crucial to ensuring their scalability and sustained impact on global HIV/AIDS prevention efforts.

In the wake of increasing digital fraud, this paper introduces an innovative application of Artificial Intelligence (AI) in detecting fraudulent activities across finance, healthcare, and e-commerce sectors. It presents a detailed analysis of machine learning methodologies, specifically focusing on the advantages of supervised, unsupervised, and deep learning techniques. The paper addresses the challenges such as data imbalance, model interpretability, and ethical implications in AI-based fraud detection. It also discusses the necessity of high-quality datasets and advocates for the integration of traditional and advanced machine learning methods to enhance accuracy and adaptability in fraud identification. However, it acknowledges the limitations including computational demands and overfitting risks. The study underscores the importance of collaborative efforts between AI experts and industry professionals to develop ethical, efficient, and reliable AI solutions for fraud detection.

Through the ACE2, a main enzyme of the renin-angiotensin system (RAS), the SARS-CoV2 gains access into the cell, resulting in different complications which may extend beyond the RAS and impact the Arachidonic Acid (ArA) pathway. The contribution of the RAS through ArA pathways metabolites in the pathogenesis of COVID-19 is unknown. We investigated whether RAS components and ArA metabolites can be considered biomarkers of COVID-19. We measured the plasma levels of RAS and ArA metabolites using an LC-MS/MS. Results indicate that Ang1-7 levels were significantly lower, whereas Ang II levels were higher in the COVID-19 patients than healthy control individuals. The ratio of Ang1-7/Ang II as an indicator of the RAS classical and protective arms balance was dramatically lower in COVID-19 patients. There was no significant increase in inflammatory 19-HETE and 20-HETE lev-els. The concentration of EETs was significantly increased in COVID-19 patients, whereas the DHETs concentration was repressed. Their plasma levels were correlated with Ang II concentration in COVID-19 patients. In conclusion, evaluating the RAS and ArA pathway biomarkers could provide helpful information for the early detection of high-risk groups, avoid delayed medical attention, facilitate resource allocation and improve patient clinical outcomes to prevent long COVID incidence.

Vaccine hesitancy remains a public health challenge. It has been argued that the sources of vaccine-related information may serve as important condiments to one’s decision to be vaccinated. However, little empirical attention is given to the subject. We contribute to this debate by assessing the level of COVID-19 vaccine hesitancy and the role of information explaining hesitancy, using the Nelson Mandela Bay Municipality of South Africa as a case study. Findings confirm high level of vaccine hesitancy, representing 78.8 percent of the respondents (which is above the national level of 41%). Furthermore, findings reveal that vaccination decisions are influenced by family, which is the most trusted among all institutions in the society, especially on sensitive matters and those shrouded by myths and misinformation. Additionally, the majority trusts health care workers and mass media as sources of health-related and general information; however, the use of popular personalities to convey health information is not supported. The findings reveal key socio-demographic and institutional drivers of COVD-9 vaccine hesitancy, such as age, inadequate information on the vaccine, trust issues, conspiracy beliefs, vaccine-related factors, and perceived side effects associated with the vaccine. Recommendations based on the findings are provided.

The Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) first emerged in 2019 in China and has resulted in millions of human morbidities and mortalities across the globe. It has been shown that this novel virus originated in animals, mutated, and made the cross-species jump to humans. At the time of this communication, the Coronavirus disease (COVID-19) may be on way to an endemic form, however the threat of the virus is more for susceptible (older people and immunocompromised) people. The human body has more bacterial cells than its own, thus making us more bacterial than humans. As a consequence, the bacteriomes in the human body heavily influence human health and disease. The bacteriomes in the body and the immune system seem to be in constant association during bacterial and viral infections. In this review, we identify various bacterial spp. in major bacteriomes (oral, nasal, lung, and gut) of the body in healthy humans and compare them with dysbiotic bacteriomes of COVID-19 patients. We try to identify key bacterial spp. that have a positive effect on the functionality of the immune system and human health. These select bacterial spp. could be used as potential probiotics to counter or prevent COVID-19 infections. In addition, we try to identify key metabolites produced by probiotic bacterial spp. that could have potential anti-viral effects against SARS-CoV-2. These metabolites could be subject to future therapeutic trials to determine their anti-viral efficacy.

SMEs constitute the backbone of the Syrian economy which have suffered manifold challenges due to the continuous Syrian war. Covid-19 added further pressures on Syrian SMEs and force them to take certain adaptation strategies to survive. This paper aims to investigate the main challenges that face Syrian SMEs during the pandemic and illustrate how they respond to adversities emerged from governmental intervention to control the spread of the virus. It also discusses the measures initiated by the government to support SMEs during the pandemic. Through interviewing persons from the Syrian SMEs ecosystem, we find that high interest rates on SMEs loans, decline on demand as well as high inflation represent the main challenges. SMEs respond to these challenges by marketing products online, stock procurement, and strengthen connections with stakeholders. We recommend the Syrian authorities reduce lending rates and increase loan size available to SMEs to help them overcome the pandemic adversities. Moreover, SMEs will immensely benefit from training on digital tools to enhance their expansion and survival opportunities. Furthermore, bazars should be organized around the year to give SMEs the opportunity to gain continuous access to markets. In addition, incubation services should be revised, particularly, to SMEs with great potential to grow to create the suitable environment for them to scale and flourish.

The novel coronavirus named by WHO and Coronavirus Study Group (CSG) as SARS-COV-2 is the etiological agent of the newly emerged Coronavirus disease (COVID-19). COVID-19 has become a pandemic threat as the WHO declared it a public health emergency of international concern. Early and precise detection of the virus is important for effective diagnosis and treatment. Various testing kits and assays, including real-time reverse Transcriptase PCR, thermal screening guns, ELISA-based immunoassays, and Point-of-Care (POC), have been implemented or are being explored to detect the virus and/or characterise cellular and antibody responses to the infection. However, these approaches have inherent limitations such as non-specificity, high cost, characterize by long turnaround times for test results, and can be labour intensive. Aptamers, which are single-stranded oligonucleotides, generated artificially by SELEX (Evolution of Ligands by Exponential Enrichment) may offer the capacity to generate high affinity bioprobes for monitoring relevant SARS-COV 2 and COVID-19 biomarkers. This article discusses the prospects of implementing aptasensing technologies for rapid point-of-care detection of SARS-COV-2.

Light is dispersive in gravitational field. It results in that, under the condition of strong gravitational field, the observed numbers, size, distance and spectrogram of a celestial object is different from the real ones. Therefore, the observed jets of the Sgr A* and M87 need be understood further with the orbit of the stars around them. And, the observed orbits of the S-stars around the Sgr A* is different from the real ones. It implies that the observed optical images of the distant celestial body with strong gravitational field need be further understood with other observations and physics laws to accurately and precisely know the real physical configuration of it.

Millions of children in developing countries face preventable deaths due to inadequate vaccination and malnutrition, in part due to insufficient monitoring and the absence of official identification. A reliable fingerprint recognition system can be a practical solution to address this issue. However, the scarcity of longitudinal fingerprint datasets for young children leads to unresolved questions regarding the earliest age for fingerprint biometric use, the frequency of enrollment required for reliable recognition, and the methods to accommodate agerelated changes. A few recent studies introduced high-resolution fingerprint scanners and showed promising recognition performance for young children. However, these studies were conducted on a small dataset over a shorter period with limited diversity; further evaluation of their finding is essential. This study assessed the effectiveness of a high-resolution contactless scanner in a controlled, diverse longitudinal dataset of children (0-15 years). Our results indicate that infants can be enrolled at five days old and reliably recognized after two months with a TAR= 100% @ FAR = 0.1%, and children aged 4-15 years can be recognized after one year with a TAR= 98.72% @ FAR = 0.1%.

A long time has passed since COVID-19 was discovered and widely disseminated. Both machine learning and deep learning have moved towards the research of diagnosing COVID-19. Compared to deep learning, traditional machine learning-based methods can also achieve good diagnostic results if they are improved based on innovative points. And deep learning remains a more popular research object. Based on the deep neural network in the field of deep learning, the convolutional neural network, recurrent neural network, long and short-term memory network, and Transformer model have been extended. These models improve the performance and processing power of neural networks by introducing new structures and algorithms. This paper will introduce the basic concepts of machine learning and deep learning, as well as the details of using the relevant methods of both to help diagnose COVID-19.

Using publicly available data for 28 EU/EES countries from Eurostat and Our World in Data, we investigate how the current rate of Covid vaccination in a country compares to its average rate of excess mortality (EM) in the pandemic to date. We find that, in the linear regression, the correlation between average EM and vaccination rate is strongly negative, a priori evidence to support the claim that the Covid vaccines have saved many lives. However, a closer analysis of the timeline suggests otherwise. The correlation was already strongly negative before the vaccines were rolled out and is only weakly negative thereafter. In theory, survivor bias could still explain this shift, especially since waves of EM closely align with Covid waves. However, we find in addition that about half of our 28 countries experienced higher EM in 2022 than in 2021, and all that did so have higher than average vaccination rates. This is something which survivor bias cannot explain and raises the real possibility that the vaccines have not just failed to save many lives, but may have already caused net harm. Moreover, any such harm may be ongoing since we find that EM and vaccination rates have been consistently positively correlated since April 2022. We show that all these findings are robust to several different ways of measuring EM and/or vaccination rates. Finally, using public data from Worldometers, we show that the correlation over time of official Covid mortality rates with current vaccination rates closely tracks that of EM rates, even as Covid mortality has waxed and waned and even in the post-omicron period.

Given that population COVID-19 vaccination does not appreciably reduce SARS-CoV-2 transmission, instead, the potential to reduce hospitalization has been used to justify coercive vaccine passports. We aim to use a recently published research study as an example in order to demonstrate how data can be misinterpreted and result in deriving misleading ethical and policy implications. Bagshaw et al wrote that unvaccinated patients with COVID-19 in Alberta, Canada “had substantially greater rates of ICU admissions, ICU bed days, and ICU related costs than vaccinated patients did. This increased resource use would have been potentially avoidable had these unvaccinated patients been vaccinated.” The authors in Bagshaw et al then concluded that their findings “have important implications for discourse on the relative balance of increasingly stringent public health protection (restrictions), including mandatory vaccination policies, and the sustainability and function of health system infrastructure and capacity during the ongoing COVID-19 pandemic.” Here we show the following. First, the effect of vaccination on intensive care admissions were grossly over-estimated due to several limitations of this and almost all other vaccine studies. Second, an effect of vaccination on access to acute care and on all-cause excess deaths was grossly over-stated due to several more likely causes being omitted from discussion and from the common narrative. Third, policy implications were overstated and at best unclear due to missing consideration of more relevant aspects required to inform policy. Overall, the data cannot support what Bagshaw et al called “increasingly stringent public health protection (restrictions), including mandatory vaccination policies”.

Background Several vaccines have been approved for prevention of the coronavirus disease discovered on 31st December in Wuhan, China. Pakistan procured vaccines from various countries. However, the lack of knowledge and reluctance of the general population to embrace the use of the vaccines are considered to be the major determinants of the slow vaccination rate. Hence, it is necessary to evaluate the willingness of the general population about their perception of the COVID-19 vaccination. Methods A cross sectional survey based on a self-structured questionnaire comprising 18 questions was conducted (from April 21-June 21) on 400 Pakistani participants to evaluate their knowledge, attitude and perception towards the COVID-19 vaccination. Chi-square independent t-test and one-way Anova including a multiple step wise linear regression were used to draw conclusions about the results. P< 0.05 was considered significant. Results A total of 400 participants responded in the KAP survey of which 46.5% were female and 53.5% were male. The mean age of participants was 36.08 years. This survey showed a poor knowledge (50.5%), a fair attitude (75.1%) and a poor perception (58.1%) towards the COVID-19 vaccination. Higher mean knowledge and attitude scores was reported in the age group 21-40, females and unmarried urban citizens. Regression analysis showed that age, education, residence and employment status influenced the knowledge and perception score to a considerable extent. Conclusions The findings reflect an inadequate knowledge and perception on the one hand but a better attitude towards the COVID-19 vaccination. This KAP survey will help in better understanding the opinion of the general population towards vaccination and will be useful for policy makers and health care authorities aiming to increase the vaccination rate.

This paper aims to contribute to the advancement of scientific knowledge about the impact of the COVID-19 pandemic on social workers and the social work profession in Romania. Research has shown that social work is a profession at high risk for developing the burnout syndrome, which has many detrimental effects on both social workers and the clients that they serve. Two conceptual models are used to frame the discussion: the theoretical framework of VUCA (volatility, uncer-tainty, complexity, and ambiguity) to discuss the challenges of the unprecedented context the COVID-19 pandemic has created for social workers; stress and burnout to explain the negative impact of this period of time. Based on convergent mixt methods, the study sample consisted of 83 social workers employed in statutory and private social services in Romania, from different fields of intervention. Results show that 25,3% of respondents suffer from a high level of burnout and 44.6% scored in a range that indicate a medium level of burnout. A group of 31.1% have managed to handle stress factors in a healthy manner. Main stressors found are especially personal (fear of contamination, personal and family) and work-related factors (workload, new legislative rules and decisions, inconsistency, instability, ambiguity of managerial decisions, or even their absence or non-assumption, lack of clarity of working procedures, limited managerial and supervisory support, limited financial resources), less than client related factors (lack of direct contact, risk of contami-nation in two ways, managing beneficiaries fears, difficulties related to technology and digital skills). Study results point to the importance of organizational support and developing a self-care plan that help protect against occupational stress and burnout. Recommendations are made putting forward the voice of fieldworkers and managers fostering initiatives and applications of sustainability-based measures and activities designed to deal with the challenges of the VUCA environment.

Coronavirus disease of 2019 (COVID-19) is the clinical manifestation of the respiratory infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). While primarily recognized as a respiratory disease, it is clear that COVID-19 is systemic illness impacting multiple organ systems. One defining clinical feature of COVID-19 has been the high incidence of thrombotic events. The underlying processes and risk factors for the occurrence of thrombotic events in COVID-19 remain inadequately understood. While severe bacterial, viral or fungal infections are well recognized to activate the coagulation system, COVID-19 associated coagulopathy is likely to have unique mechanistic features. Inflammatory-driven processes are likely primary drivers of coagulopathy in COVID-19, but the exact mechanisms linking inflammation to dysregulated hemostasis and thrombosis are yet to be delineated. Cumulative findings of microvascular thrombosis has raised question if the endothelium and microvasculature should be a point of investigative focus. Von Willebrand Factor (VWF) and its protease, ADAMTS13 play important role in the maintenance of microvascular hemostasis. In inflammatory conditions, imbalanced VWF-ADAMTS13 characterized by elevated VWF levels and inhibited and/or reduced activity of ADAMTS13 has been reported. Also, an imbalance between ADAMTS13 activity and VWF antigen is associated with organ dysfunction and death in patients with systemic inflammation. A thorough understanding of VWF-ADAMTS13 interactions during early and advanced phases of COVID-19 could help better define the pathophysiology, guide thromboprophylaxis and treatment and improve clinical prognosis.

Background: Lung CT provides an effective modality to evaluate patients with suspected COVID-19. However, overlapping imaging findings with cardiogenic pulmonary oedema have been reported. Reports comparing lung CT features of these diseases have not been elaborated. Thus, we aimed to investigate these gaps in the knowledge regarding low-dose lung CT features of patients with COVID-19 pneumonia with those with acute heart failure (HF). Methods: This retrospective analysis enrolled hospitalized patients with COVID-19 (n=10) and acute heart failure (n=9) that exclusively underwent low-dose lung CT scans within 24-hours of admission. Clinical and lung CT characteristics were collected and analysed. Results: Ground-glass-opacities (GGO) appearance has been recorded in all subjects in HF and COVID-19 group. There was no significant statistical difference between the two groups for rounded morphology, consolidation, crazy paving pattern, lesion distribution, parenchymal band (P> 0.05). However, diffuse lesions were more frequent in HF cases (55.6% vs. 0%) than in COVID-19 pneumonia, which had predominantly multifocal pattern. Notably, CT images in HF patients were more likely to have signs of interstitial tissue thickening such as the interlobular septums, fissures and peribronchovascular interstitium (55.6% vs 0%, 88.9% vs 20% and 44.4% vs 0%,respectively), as well as cardiomegaly (77.8% vs 0%), increased artery to bronchus ratio (55.6% vs 0%), and pleural effusions (77.8% vs 0%). Conclusions: Major overlaps of lung CT imaging features existed between COVID-19 pneumonia and acute HF cases. However, signs of fluid redistribution are clues that favour HF over COVID-19 pneumonia.

Amid the covid-19 pandemic, other diseases, including viruses, are still acting to the detriment of their seasonality and risk factors for contagion. For this reason, it is interesting to know the degree of impact of other viruses, mainly respiratory, in which they have similar symptoms, in diagnoses for contamination by the new coronavirus based on epidemiological surveys, via epidemiological weeks, in Brazil. To what extent there may be a hypothesis of confusion of contaminated data, harming the health system, with regard to the need for intensive care units and control of viruses, and negatively or positively implying in the control or uncontrolling of viruses in general.

Coronavirus disease 2019 (COVID-19) has been first appeared in Wuhan, China but its fast transmission, led to its widespread prevalence in various countries and make it a global concern. In addition, lack of a definitive treatment is another concern that needs to be attention. Researchers have come up with several options, which are not certain, but protease inhibitor and some antiviral agent are in the forefront. In this study a virtual screening procedure employing docking of different databases including 1615 FDA approved drugs was used to identify new potential small molecule inhibitors for protease protein of COVID-19. The docking result indicates that among all, simeprevir (Hepatitis C virus (HCV) NS3/4A protease inhibitor) could fit well to the binding pocket of protease and because of some other positive features including ADME profile, might be a helpful treatment option for COVID-19.

COVID-19 has brought unprecedented challenges and exacerbated existing work-related struggles resulting in heightened occupational stress and impacted work performance among health caregivers. This study utilised the transactional model of stress and coping to explore the coping strategies adopted by radiology health caregivers during the pandemic with the aim to provide baseline data for enhancing preparedness and development of interventions to support staff during future health crises. A qualitative, interpretative phenomenological analysis (IPA) methodology coupled with constructivist and interpretivist philosophical views were utilised in a multi-method context to conduct semi-structured interviews and focus group discussions among 24 radiology health caregivers in the eThekwini district of KwaZulu-Natal, South Africa. Data were transcribed verbatim and manually analysed using the IPA framework. The radiology health caregivers highlighted resilience, adaptability and identified emotion-focused and problem-focused coping as their mostly preferred strategies of dealing with COVID-19 related mental distress. These included accepting professional responsibilities and duties, social coping, spiritual therapy, adaptive behavioural coping, escape-avoidance and solution-oriented approaches. The findings can guide radiology departments in developing bespoke mental health interventions to support radiology health caregivers during any future health crises.

The novel coronavirus disease 19 (COVID-19) has resulted in an estimated 20 million excess deaths and the recent resurgence of COVID-19 in China is predicted to result in up to 1 million deaths over the next few months. With vaccines unable to halt transmission it is important to continue our quest for safe, effective, affordable drugs that will be available to all countries. Drug repurposing is one of the strategies being explored in this context. Recently, out of 7,817 approved drugs, 214 candidates were systematically down-selected using a combination of 11 filters including approval status, assay data against SARS-CoV-2, pharmacokinetic, pharmacodynamic and toxicity profiles. These drugs were subjected in this study to virtual screening against various targets of SARS-CoV-2 followed by molecular dynamic studies of the best scoring ligands against each target. The chosen molecular targets were Spike receptor binding domain, Nucleocapsid protein RNA binding domain, and key non-structural proteins 3, 5, 12, 13 and 14. Four drugs approved for other indications — alendronate, cromolyn, natamycin and treprostinil — look sufficiently promising from our in silicostudies to warrant further in vitro and in vivo investigations as appropriate to ascertain their extent of anti-viral activities.

The Covid-19 pandemic has resulted in the closure of schools at every level, globally, forcing education to move online. Meeting the needs of students online for Science Lab classes, in particular, is a challenge since the physical labs are not available to the teachers or students. OLabs is a virtual Science Lab providing a complete learning environment of theory, experimental procedures, videos, animations, simulations, and assessments that capture real lab experiences with the relevant pedagogy. This study looks at the acquisition and behaviors of users, on the OLabs platform, during pre and Covid-19 times. Using Google Analytics, we observe that, during the pandemic time, users increasingly adopted OLabs as a new learning pedagogy for performing experiments as indicated by parameters like the number of users; the number of unique pages viewed per session; time spent on viewing content; bounce rate; and preference for content types such as theory, simulations, videos, and animations.

Diabetic foot is a serious complication that poses significant risks for diabetic people. The resulting reduction in protective sensitivity in the plantar region requires early detection to prevent the imminent ulceration and amputation. The primary method employed for evaluating this sensitivity loss is the 10 g f Semmes-Weinstein monofilament test, commonly used as a first-line procedure. However, the lack of calibration in existing devices often introduces decision errors due to unreliable feedback. In this paper, a new equipment designed to address these limitations and enhance the assessment of the sensitivity loss using the 10 g f monofilament is introduced. The proposed system automates metrological verification and evaluation processes, ensuring accurate and reliable results. Furthermore, it simulates the practitioner’s procedure, serving both as a valuable training tool and a means to provide force-feedback information. An analytical model of the monofilament buckling and deflection is also presented. The obtained results showed that the tested monofilaments had a very high error compared to the 10 g f declared by the manufacturers. It is aimed, by introducing this advanced equipment, to improve the precision and reliability of assessing the sensitivity loss. The integration of automated verification, simulation capabilities, and precise measurements shows great promise for diabetic patients, reducing the likelihood of adverse outcomes such as ulceration and amputation.

: Cytokine storm is usually described as one of the main reasons behind COVID-associated mor-tality. Cytokines are essential protein molecules engaged in immune responses; they play a critical role in protection against infections. However, they also contribute to inflammatory reactions and tissue damage, becoming a double-edged sword in the context of COVID-19. Recent studies have suggested various cytokines and chemokines that play a crucial role in the immune response to SARS-CoV-2 infection. One such cytokine is Interleukin 27 (IL-27), which has been found to be elevated in the blood plasma of patients with COVID-19. Within this study, we will explore the role of IL-27 in immune responses and address our own findings concerning this cytokine in COVID-19. It affects a wide variety of immune cells; regardless of the pathological process it is involved in, IL-27 is critical for upholding the necessary balance between tissue damage and cytotoxicity against in-fectious agents and/or tumors. In COVID-19, it is involved in multiple processes, including antiviral cytotoxicity via CD8+ cells, IgG subclass switching, and even the activation of Tregs.

The Covid-19 pandemic and the initial focus on handwashing measures have again highlighted the importance of water access as an essential service in protecting human health. Yet, especially in southern cities, uneven geographies of water access – often mediated by fragmented and unequal infrastructure systems – may hamper the fight against infectious diseases. The spread of SARS-CoV-2 presented a dilemma for water providers as well as residents in water-deprived urban areas as they had to adhere to new hygiene standards and requirements, despite limited access to basic water infrastructure. Therefore, a deeper understanding of pandemic urban waterscapes – the infrastructure and governance systems as well as everyday practices and technologies – is necessary for ongoing debates on (post-) pandemic or zoonotic cities. In our paper, we focus on changes in urban (water) governance and government water projects in Nairobi since early 2020. We show that Covid-19 has contributed to changes in Nairobi’s waterscape but only in conjunction with recent changes in the city’s overall governance structure. However, if these waterscape changes lead to greater equity in water access, and if they have helped to curb the spread of SARS-CoV-2, is more than questionable.

In Mexico, it is estimated that due to the economic system the overexploitation of natural resources, environmental impacts and health have been generated, with high rates of overweight and obesity. This review analyzes the impacts on food safety, environmental health, and the economy in Mexico before and during the COVID-19 contingency. Derived from the analysis, among the lessons learned we can include: the health contingency due to COVID-19 had negative repercussions on food security, environmental health and the economy, which require the promotion of public policies (health, environment and economy) and migrate to a health prevention system and an agroecological model, which includes multidisciplinary and intersectoral interventions (government, academia, researchers, civil society organizations, business groups and citizens themselves) to reform and enforce the right to enjoy adequate food and a healthy environment. The contingency due to COVID19 has shown us that this must go from an ideology to being a reality and the lessons learned will have to focus on promoting an innovative and ethical culture of generating an economy, with a gender balance, resilience to climate change, management transparent technology and a priority in health and this will lead to progress in the food security of the population.

In the present time, the biggest problem of the world is the outbreak of novel coronavirus. Novel coronavirus (COVID-19), this one name has become a part of our daily lives over the past few months. Beyond the boundaries of medical science, coronavirus is now the main subject of research in all fields like Applied Mathematics, Economy, Philosophy, Sociology, Politics upto living room. The epidemic has brought unimaginable changes in our traditional habits and daily routines. Thousands of people in our country are fighting with the rest of the world to survive in various new situations. There are different kinds of coronavirus appeared in different times. In this time, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is responsible for the coronavirus disease of 2019 (COVID-19). This virus was first identified towards the end of 2019 in the city of Wuhan in the province of Hubei in China. Within very short duration of time and very fast, it has spread throughout a large part of the world. In this study, the main aim is to investigate the spreading rate, death rate, recovery rate due to corona virus infection and to study the future of the coronavirus in India by using mathematical modeling based on the previous data. Mathematical models, in this situation, are the important tools in recruiting effective strategies to fight this epidemic. India is at high risk of spreading the disease and is facing many losses in socio-economic aspects. With current infection rates and existing levels of personal alertness, the number of infected people in India will increase at least in the next three months. Proper social awareness, maintain of social distance, large rate of testing and separation may break the chain of the Coronavirus-2.

It is highly likely that the wearing of face masks reduces the rate of respiratory infections (e.g. SARS-CoV-2), to protect both the user and those around them. This paper sets out to review the areas that effect the efficacy of masks, the materials, design, hygiene and fit testing, in order to make recommendations as to how to make mask from resources found in most homes for when commercial models are unavailable. This paper finds that a mask constructed with a filter made from high thread count cotton is likely to provide a reasonable level of protection (~70% filtration) and that if a layers of other materials such as chiffon or silk is added the filtration may be much higher (~90%). There is also some promise in less available materials such as vacuum cleaner bags and air conditioner filters. Examples of fabric and rigid designs are reviewed but most are limited by the fit to the users which is hard to determine in a home setting. It would be extremely helpful if a method was devised for people to test or be tested for the fit of home made masks. In the mean time careful thought should be given to whether the user judges a good fit. Users should also be careful to practice other means of hygiene and distancing.

The study sought to gauge the impact of COVID-19 pandemic in unleashing digital transformation in the education sector in South Africa. In order to gauge the impact, the study tracked the rate at which the 4IR tools were used by various institutions during the COVID-19 lockdown. Data were obtained from secondary sources, mainly newspaper articles, magazines and peer-reviewed journals. The findings are that, in South Africa, during the lockdown, a variety of 4IR tools were unleashed from primary education to higher and tertiary education where educational activities switched to remote learning (online learning). These observations point to the fact that South Africa generally has, some pockets of excellence to drive the education sector into the 4IR, which has the potential to increase access. Access to education, particularly at a higher education level, has always been a challenge due to a limited number of spaces available. Much as this pandemic has brought with it massive human suffering across the globe, there is an opportunity to assess successes and failures of deployed technologies, costs associated with them, and scaling these technologies to improve access.

This article conducts a bibliometric analysis focusing on the influence of globalization and technology in the academic context. Previous studies have focused on analyzing the relationship between the number of research citations and international collaboration, but no study has explored it in the scope of consumer behavior and retail. Leveraging the Scopus database, the research analyzes a significant corpus of 2,111 documents from 1971 to 2022. The findings reveal a distinct surge in academic output related to the topic of technology, reflecting a growing interest in understanding the interaction between technological factors and consumer behavior. The study also explores trends in international collaboration in publications as well as its impact on citation counts.