The science around the use of masks by the general public to impede COVID-19 transmission is advancing rapidly. Policymakers need guidance on how masks should be used by the general population to combat the COVID-19 pandemic. In this narrative review, we develop an analytical framework to examine mask usage, considering and synthesizing the relevant literature to inform multiple areas: population impact; transmission characteristics; source control; PPE; sociological considerations; and implementation considerations. A primary route of transmission of COVID-19 is via respiratory droplets, and is known to be transmissible from presymptomatic and asymptomatic individuals. Reducing disease spread requires two things: first, limit contacts of infected individuals via physical distancing and other measures, and second, reduce the transmission probability per contact. The preponderance of evidence indicates that mask wearing reduces the transmissibility per contact by reducing transmission of infected droplets in both laboratory and clinical contexts. Public mask wearing is most effective at reducing spread of the virus when compliance is high. The decreased transmissibility could substantially reduce the death toll and economic impact while the cost of the intervention is low. Given the current shortages of medical masks we recommend the adoption of public cloth mask wearing, as an effective form of source control, in conjunction with existing hygiene, distancing, and contact tracing strategies. Because many respiratory droplets become smaller due to evaporation, we recommend increasing focus on a previously overlooked aspect of mask usage: mask-wearing by infectious people ("source control") with benefits at the population-level, rather than mask-wearing by susceptible people, such as health-care workers, with focus on individual outcomes. We recommend that public officials and governments strongly encourage the use of widespread face masks in public, including the use of appropriate regulation.

Objective: To describe outcomes of patients with coronavirus disease 2019 (COVID-19) in the outpatient setting after early treatment with zinc, low dose hydroxychloroquine, and azithromycin (the triple therapy) dependent on risk stratification. Design: Retrospective case series study. Setting: General practice. Participants: 141 COVID-19 patients with laboratory confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in the year 2020. Main Outcome Measures: Risk-stratified treatment decision, rate of hospitalization and all-cause death. Results: Of 335 positively PCR-tested COVID-19 patients, 127 were treated with the triple therapy. 104 of 127 met the defined risk stratification criteria and were included in the analysis. In addition, 37 treated and eligible patients who were confirmed by IgG tests were included in the treatment group (total N=141). 208 of the 335 patients did not meet the risk stratification criteria and were not treated. After 4 days (median, IQR 3-6, available for N=66/141) of onset of symptoms, 141 patients (median age 58 years, IQR 40-67; 73% male) got a prescription for the triple therapy for 5 days. Independent public reference data from 377 confirmed COVID-19 patients of the same community were used as untreated control. 4 of 141 treated patients (2.8%) were hospitalized, which was significantly less (p<0.001) compared with 58 of 377 untreated patients (15.4%) (odds ratio 0.16, 95% CI 0.06-0.5). Therefore, the odds of hospitalization of treated patients were 84% less than in the untreated group. One patient (0.7%) died in the treatment group versus 13 patients (3.5%) in the untreated group (odds ratio 0.2, 95% CI 0.03-1.5; p=0.16). There were no cardiac side effects. Conclusions: Risk stratification-based treatment of COVID-19 outpatients as early as possible after symptom onset with the used triple therapy, including the combination of zinc with low dose hydroxychloroquine, was associated with significantly less hospitalizations and 5 times less all-cause deaths.

More than 700 thousand human deaths from mosquito bites are observed annually in the world. It is more than 2 times the number of annual murders in the world. In this regard, the invention of new more effective methods of protection against mosquitoes is necessary. In this article for the first time, comprehensive studies of mosquito neutralization using machine vision and a 1 W power laser are considered. Developed laser installation with Raspberry Pi that changing the direction of the laser with a galvanometer. We developed a program for mosquito tracking in real. The possibility of using deep neural networks, Haar cascades, machine learning for mosquito recognition was considered. We considered in detail the classification problems of mosquitoes in images. A recommendation is given for the implementation of this device based on a microcontroller for subsequent use as part of an unmanned aerial vehicle. Any harmful insects in the fields can be used as objects for control.

This paper investigates how Islamic tolerance contributes to solve religious conflict today that has impacted on various aspects such as economic collapse, insecurity in life, lack of professional society, academic retrogressions, and so on. Knowledge of these issues has become an urgent to build a community that is full of peace, harmony and unity. The paper suggests that Quranic views on tolerance should be understood and practiced in order to avoid disunity in society which is due to failure to appreciate tolerance values in association. The paper concludes problems or misunderstandings always occur in different religious societies, since every religion has its own teachings and principles, as well as each of them is interpreted in different ways.

The effect of the COVID-19 pandemic in a developing country like Bangladesh is enormous. A research conducted by South Asian network of Economic Modelling predicted that the pandemic could double the poverty. But it is not that only the socioeconomic condition is dropping in Bangladesh, the impact of COVID-19 pandemic is manifold. The poor condition of Bangladesh's health sector has also been exposed due to the pandemic. People are not getting proper treatment due to lack of isolation beds, oxygen, ICU etc. The health sector of Bangladesh is not much developed and now with this pandemic it has become impossible to provide treatment facility for all the patients. Education sector, which is the backbone of a country,has also been greatly affected by the pandemic. We know that different types of cultural occasions are an inherited tradition of Bangladesh, COVID-19 have not even spared these traditions, all the cultural programes and festivals have been cancelled due to this pandemic.In this paper, our aim is to present the present status of all these sectors.

The article reveals distinctive features of the interaction between architectural and structural solutions for the design of tall buildings as well as spotlights the most distinctive cases of expression. In the contemporary world, interaction is turning into the antithesis of the formerly dominant utilitarian attitude and standardization of tall buildings architectural solutions. Meanwhile, the search for rational structural solutions leads to new possibilities of architectural expression. This necessitates the transformation of a structural solution and its adaptation to the need of a modern architect to be exceptional and noticed. Interaction covers the current as well as retrospective and perspective periods. SWOT analysis was used by the authors of the article to assess the interaction between architectural and structural solutions in tall buildings design, select the most important criteria that could be used searching for rational architectural and structural solutions in future by applying multi-criteria decision making methods.

Machine learning (ML) methods has recently contributed very well in the advancement of the prediction models used for energy consumption. Such models highly improve the accuracy, robustness, and precision and the generalization ability of the conventional time series forecasting tools. This article reviews the state of the art of machine learning models used in the general application of energy consumption. Through a novel search and taxonomy the most relevant literature in the field are classified according to the ML modeling technique, energy type, perdition type, and the application area. A comprehensive review of the literature identifies the major ML methods, their application and a discussion on the evaluation of their effectiveness in energy consumption prediction. This paper further makes a conclusion on the trend and the effectiveness of the ML models. As the result, this research reports an outstanding rise in the accuracy and an ever increasing performance of the prediction technologies using the novel hybrid and ensemble prediction models.

SARS-CoV-2 (2019-nCoV), a novel coronavirus, caused the pneumonia outbreak in China and continue to expand. The host receptor for 2019-nCoV Angiotensin-converting enzyme 2 (ACE2), is the same as the host receptor for SARS-CoV. Targeting ACE2 holds the promise for preventing and inhibiting 2019-nCoV infection. Chinese Medicine herbs could be a valuable pool for identifying active compounds for treating infection of 2019-nCoV. In this study, we summarize several active compounds, including baicalin, Scutellarin, Hesperetin, Nicotianamine and glycyrrhizin that could have potential anti-2019-nCoV effects. We conduct molecular docking to predict their capacity for binding ACE2, which may prevent the 2019-nCoV infection. We propose that these selected compounds worth further investigation for preventing 2019-nCoV.

In past few years, unmanned aerial vehicles (UAV) or drones has been a hot topic encompassing technology, security issues, rules and regulations globally due to its remarkable advancements and uses in remote sensing and photogrammetry applications. This review paper highlights the evolution and development of UAV, classification and comparison of UAVs along with Hardware and software design challenges with diverse capabilities in civil and military applications. Further, safety and security issues with drones, existing regulations and guidelines to fly the drone, limitations and possible solutions have also been discussed.

There is a long trail of research studies testing the in vitro and in vivo efficacy of chloroquine and its derivatives in treating and preventing infection by various coronavirus species. More recent findings have highlighted the possibility of treating patients infected with the 2019 novel coronavirus, SARS-CoV-2. This review describes the mechanism of coronavirus infection, the mechanism of action of chloroquine, and summarizes the available literature highlighting the efficacy of chloroquine as an anti-coronavirus agent. These findings should encourage the wider scientific community to conduct thorough research on the possible efficacy of chloroquine and its derivatives in treating and preventing SARS-CoV-2 infection.

This paper presents an exact solution to the Timoshenko beam theory (TBT) for first-order analysis, second-order analysis, and stability. The TBT covers cases associated with small deflections based on shear deformation considerations, whereas the Euler–Bernoulli beam theory (EBBT) neglects shear deformations. Thus, the Euler–Bernoulli beam is a special case of the Timoshenko beam. The moment-curvature relationship is one of the governing equations of the EBBT, and closed-form expressions of efforts and deformations are available in the literature. However, neither an equivalent to the moment-curvature relationship of EBBT nor closed-form expressions of efforts and deformations can be found in the TBT. In this paper, a moment-shear force-curvature relationship, the equivalent in TBT of the moment-curvature relationship of EBBT, was presented. Based on this relationship, first-order and second-order analyses were conducted, and closed-form expressions of efforts and deformations were derived for various load cases. Furthermore, beam stability was analyzed and buckling loads were calculated. Finally, first-order and second-order element stiffness matrices were determined.

We primarily study a possible link between 2021 COVID-19 vaccination uptake in Europe and monthly 2022 excess all-cause mortality, i.e., mortality higher than before the pandemic. Analyses of 31 countries weighted by population size show that all-cause mortality during the first nine months of 2022 increased more the higher the 2021 vaccination uptake; a one percentage point increase in 2021 vaccination uptake was associated with a monthly mortality increase in 2022 by 0.105 percent (95% CI, 0.075-0.134). When controlling for alternative explanations, the association remained robust, and we discuss the result emphasizing causality as well as potential ecological fallacy. Also, the study shows that 2021 all-cause mortality was lower the higher the vaccination uptake, but this association became non-significant when controlling for alternative explanations.

Low vitamin D status in winter permits viral epidemics. During winter, people who do not take vitamin D supplements are likely to have low serum 25-hydroxyvitamin D [25(OH)D] concentrations. Vitamin D can reduce the risk of viral epidemics and pandemics in several ways. First, higher 25(OH)D concentrations reduce the risk of many chronic diseases, including cancers, cardiovascular disease, chronic respiratory tract infections (RTIs), diabetes mellitus, and hypertension. Patients with chronic diseases have significantly higher risk of death from RTIs than otherwise healthy people. Second, vitamin D reduces risk of RTIs through three mechanisms: maintaining tight junctions, killing enveloped viruses through induction of cathelicidin and defensins, and reducing production of proinflammatory cytokines by the innate immune system, thereby reducing the risk of a cytokine storm leading to pneumonia. Observational and supplementation trials have reported higher 25(OH)D concentrations associated with reduced risk of dengue, hepatitis, herpesvirus, hepatitis B and C viruses, human immunodeficiency virus, influenza, respiratory syncytial virus infections, and pneumonia. Results of a community field trial reported herein indicated that 25(OH)D concentrations above 50 ng/ml (125 nmol/l) vs. <20 ng/ml were associated with a 27% reduction in influenza-like illnesses. From the available evidence, we hypothesize that raising serum 25(OH)D concentrations through vitamin D supplementation could reduce the incidence, severity, and risk of death from influenza, pneumonia, and the current COVID-19 epidemic.

Regression models form the core of the discipline of econometrics. One of the basic assumptions of classical linear regression model is that the values of the explanatory variables are fixed in repeated sampling. However, in most of the real life cases, particularly in economics the assumption of fixed regressors is not always tenable. Under a non-experimental or uncontrolled environment, the dependent variable is often under the influence of explanatory variables that are stochastic in nature. There is a huge literature related to stochastic regressors in various aspects. In this paper, a historical perspective on some of the works related to stochastic regressor is being tried to pen down based on literature search.

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.

The COVID-19 has caused gigantic negative effects on populace wellbeing, society, education, and the economy in Bangladesh. The aim is to deliver a comprehensive overview of the observed and the possible impacts that could appear in the coming days. The study is based on secondary information. During the early period, due to a lack of accurate facts about the case affected and death tension up-and-down among the nations. The total number of confirmed cases is increasing following geometric patterns in Bangladesh. Dairy farmers, vegetable producers, pharmaceuticals, poultry farmers are in deep crisis due to lower prices. Also, the pandemic has seriously affected educational systems, banking, FDI, ready-made garments, remittances, etc Finally, it is not possible to mitigate the effects of pandemic individually but the integrated effort from the state authority as well as concern people of all sectors need to come forward.

In this paper we propose a novel self-supervised approach of keywords and keyphrases retrieval and extraction by an end-to-end deep learning approach, which is trained by contextually self-labelled corpus. Our proposed approach is novel to use contextual and semantic features to extract the keywords and has outperformed the state of the art. Through the experiment the proposed approach has been proved to be better in both semantic meaning and quality than the existing popular algorithms of keyword extraction. In addition, we propose to use contextual features from bidirectional transformers to automatically label short-sentence corpus with keywords and keyphrases to build the ground truth. This process avoids the human time to label the keywords and do not need any prior knowledge. To the best of our knowledge, our published dataset in this paper is a fine domain-independent corpus of short sentences with labelled keywords and keyphrases in the NLP community.

More than 15,000 prescriptions and over the counter drugs are available according to the US Food and Drug Administration website. Moreover, several herbal medicines and dietary supplements are readily available to add to the list of possible drugs, which can potentially cause adverse drug interactions. These are a pressing concern for all as they can interfere with many dental procedures. Additionally, the number of geriatric patients seen in routine dental practice has increased over time. This implies that there are more patients with multiple diseases and health conditions like hypertension, diabetes, problems associated with the cardiovascular, renal and gastrointestinal systems, arthritis, osteoporosis, etc. All these require patients to be on certain medications. Furthermore, advancement in the dental field has led to more complex dental procedures (implants, grafts) being carried out in a general dental practice. These advanced and slightly more invasive treatments require the use of certain drugs before, during and after the treatment like local anesthetics, vasoconstrictors, anxiolytics, analgesics and antibiotics. All of these can possibly interact with medications a patient is already taking and can also interfere with the current dental treatment and create complications. This article aims to provide necessary information about commonly encountered systemic diseases and associated treating medications, their mechanism of action, possible complications and their management. The classes of drugs discussed include anti-platelet agents, vitamin K antagonists, novel oral anticoagulants, bisphosphonates, disease-modifying anti-rheumatic drugs and oral contraceptives.

Anemia is a condition of decreased red blood cell number or hemoglobin concentration, or of disturbance in their function, ultimately leading to decreased oxygen transport to tissues. Many factors and diseases may lead to anemia, with wide manifestations systemically as well as orally. Therefore, a sound understanding of this condition is essential for the dental practitioner, with emphasis on alerting signs, dental management and proper communication with patient’s physician.

The Foreign Exchange rate is very much crucial for determining the economic health level of the country. The foreign exchange rate provides financial stability, enhances purchasing power and allows global trades. This rate usually fluctuates due to the market forces which control the supply and demand of the currency. Nominal and relative inflation and income level have a substantial effect on determining the exchange rates. Government measures, international situations, natural disasters or any unexpected situation like Covid-19, Rohingya crisis etc. can affect the exchange rates. Besides this, the interaction between the factors can create different reasoning to affect the market. This study tries to identify some factors with relevant examples.

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused the Coronavirus Disease 2019 (COVID-19) worldwide pandemic in 2020. In response, most countries in the world implemented lockdowns, restricting their population’s movements, work, education, gatherings, and general activities in attempt to ‘flatten the curve’ of COVID-19 cases. The public health goal of lockdowns was to save the population from COVID-19 cases and deaths, and to prevent overwhelming health care systems with COVID-19 patients. In this narrative review I explain why I changed my mind about supporting lockdowns. First, I explain how the initial modeling predictions induced fear and crowd-effects [i.e., groupthink]. Second, I summarize important information that has emerged relevant to the modeling, including about infection fatality rate, high-risk groups, herd immunity thresholds, and exit strategies. Third, I describe how reality started sinking in, with information on significant collateral damage due to the response to the pandemic, and information placing the number of deaths in context and perspective. Fourth, I present a cost-benefit analysis of the response to COVID-19 that finds lockdowns are far more harmful to public health than COVID-19 can be. Controversies and objections about the main points made are considered and addressed. I close with some suggestions for moving forward.

Currently, the world is struggling with the coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Prion-like domains are critical for virulence and the development of therapeutic targets; however, the prion-like domains in the SARS-CoV-2 proteome have not been analyzed. In this in silico study, using the PLAAC algorithm, we identified the presence of prion-like domains in the SARS-CoV-2 spike protein. Compared with other viruses, a striking difference was observed in the distribution of prion-like domains in the spike protein, since SARS-CoV-2 was the only coronavirus with a prion-like domain found in the receptor-binding domain of the S1 region of the spike protein. The presence and unique distribution of prion-like domains in the SARS-CoV-2 receptor-binding domains of the spike protein is particularly interesting, since although the SARS-CoV-2 and SARS-CoV S proteins share the same host cell receptor, angiotensin-converting enzyme 2 (ACE2), SARS-CoV-2 demonstrates a 10- to 20-fold higher affinity for ACE2. Finally, we identified prion-like domains in the α1 helix of the ACE2 receptor that interact with the viral receptor-binding domain of SARS-CoV-2. Taken together, the present findings indicate that the identified PrDs in the SARS-CoV-2 receptor-binding domain (RBD) and ACE2 region that interact with RBD have important functional roles in viral adhesion and entry.

Novel coronavirus disease (COVID-19) has affected nearly 7 million individuals and claimed more than 0.4 million lives to date. There are several reports of gender differences related to infection and death due to COVID-19. This raises important questions such as “Whether there are differences based on gender in risk and severity of infection or mortality rate?” and “What are the biological explanation and mechanisms underlying these differences?” Emerging evidence has proposed sex-based immunological, genetic, and hormonal differences to explain this ambiguity. Besides biological differences, women have also faced social inequities and economic hardships due to this pandemic. Several recent studies have shown that independent of age males are at higher risk for severity and mortality in COVID-19 patients. Although susceptibility to SARS-CoV-2 was found to be similar across both genders in several disease cohorts, a disproportionate death ratio in men can be partly explained by the higher burden of pre-existing diseases and occupational exposures among men. From an immunological point of view, females can engage a more active immune response, which may protect them and counter infectious diseases as compared to men. This attribute of better immune responses towards pathogens is thought to be due to high estrogen levels in females. Here we review the current knowledge about sex differences in susceptibility, the severity of infection and mortality, host immune responses, and the role of sex hormones in COVID-19 disease.

Sentinel-1 SAR data preprocessing is essential for several earth observation applications, including land cover classification, change detection, vegetation monitoring, urban growth, natural hazards, etc. The information can be extracted from the 2x2 covariance matrix [C2] of Sentinel-1 dual-pol (VV-VH) acquisitions. To generate the covariance matrix from Sentinel-1 single look complex (SLC) data, several preprocessing steps are required. The ESA SNAP S-1 toolbox can be used to preprocess the data to generate a [C2] matrix. The polarimetric analysis in respective application fields often starts with the covariance matrix. However, due to limited availability of Sentinel-1 SLC data preprocessing workflow standards for polarimetric applications in contemporary research methods, downstream applications unable to comply with these workflows directly. In this paper, we propose a couple of generic practices to preprocess Sentinel-1 SLC data in SNAP S-1 toolbox, which would be beneficial for the radar remote sensing user community.

The symptoms most commonly reported by patients affected by coronavirus disease 2019 (COVID-19) include cough, fever, and shortness of breath. However, other major events usually observed in COVID-19 patients (e.g. high blood pressure, thrombosis, pulmonary embolism) seem to suggest that the virus is targeting the endothelium, one of the largest organs in the human body. Herein, we report both clinical and preclinical evidence supporting the hypothesis that the endothelium is a key target organ of COVID-19.

Artificial Intelligence (AI) is one of the key technologies of the Fourth Industrial Revolution (Industry 4.0), which can be used for the protection of Internet-connected systems from cyber-threats, attacks, damage, or unauthorized access. To intelligently solve today's various cybersecurity issues, popular AI techniques involving Machine Learning (ML) and Deep Learning (DL) methods, the concept of Natural Language Processing (NLP), Knowledge Representation and Reasoning (KRR), as well as the concept of knowledge or rule-based Expert Systems (ES) modeling can be used. Based on these AI methods, in this paper, we present a comprehensive view on "AI-driven Cybersecurity" that can play an important role for intelligent cybersecurity services and management. The security intelligence modeling based on such AI methods can make the cybersecurity computing process automated and intelligent than the conventional security systems. We also highlight several research directions within the scope of our study, which can help researchers do future research in the area. Overall, this paper's ultimate objective is to serve as a reference point and guidelines for cybersecurity researchers as well as industry professionals in the area, especially from an AI-based technical point of view.

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.

Accurate and reliable project cost estimates are fundamental to achieve successful municipal capital improvement (CIP) programs. Engineering cost estimates typically represent critical information for key decision makers to authorize and efficiently allocate the necessary funds for construction, budgeting, to generate a request for proposals, contract negotiations, scheduling, etc. for these reasons, cost estimators are using different estimating methods and approaches that allow for required levels of accuracy. As the project’s scope becomes more detailed and the potential risks are identified and/or the project design stage progresses these cost estimates are revised and updated. In this paper, the most common project cost estimation methods and approaches were collected and categorized into two main groups of (1) probabilistic and (2) deterministic methods. Under these groups overall ten different methods were identified and discussed addressing their requirements, advantages, and shortcomings, including the potential risk that can positively or negatively affect the project’s cost outcome. This paper will be a good resource for professionals who are in budget development and/or are seeking to a better understanding of different methods in determining an appropriate base cost margin and produce a meaningful and reliable project cost estimate.

RAxML-NG is a new phylogentic inference tool that replaces the widely-used RAxML and ExaMLtree inference codes. Compared to its predecessors, RAxML-NG offers improvements in accur-acy, flexibility, speed, scalability, and user-friendliness. In this chapter, we provide practicalrecommendations for the most common use cases of RAxML-NG: tree inference, branch supportestimation via non-parametric bootstrapping, and parameter optimization on a fixed tree topo-logy. We also describe best practices for achieving optimal performance with RAxML-NG, inparticular, with respect to parallel tree inferences on computer clusters and supercomputers. AsRAxML-NG is continuously updated, the most up-to-date version of the tutorial described inthis chapter is available online at: https://cme.h-its.org/exelixis/raxml-ng/tutorial .

The novel coronavirus 2019 (COVID-19) pandemic is rapidly advancing despite public health measures. Pharmaceutical prophylaxis is an established approach to potentially control infectious diseases and is one solution to the urgent public health challenge posed by COVID-19. Screening and development of new vaccines and antivirals is expensive and time consuming while the repositioning of available drugs should receive priority attention as well as international government and agency support. Here we propose an old drug chloroquine (CQ) to be urgently repositioned as an ideal antiviral prophylactic against COVID-19. CQ has ability to block viral attachment and entry to host cells. Its proven clinical efficacy against a variety of viruses including COVID-19 and its current deployment in COVID-19 therapeutic trials strengthens its potential candidacy as a prophylactic. Furthermore, CQ has a long safety record, is inexpensive and widely available. Here we reviewed CQ's antiviral mechanisms, its laboratory efficacy activity against COVID-19, as well as CQ's pharmacokinetics in its established use against malaria and autoimmune diseases to recommend safe and potentially efficacious dose regimens for protection against COVID-19: a pre-exposure prophylaxis of 250-500mg daily and post-exposure prophylaxis at 8mg/kg/day for 3 days. We recommend further urgent research on CQ for COVID-19 prevention and urge that the above regimens be investigated in parallel with mass deployment by relevant agencies in attempts to contain the pandemic without unnecessary regulatory delays as benefits far outweigh risks or costs.

Although the phenomenon of serial killers has received great attention from media, governments, and public, very little information is known about them and very few theories are presented by researchers specifically their definition and motives for killing. Through cross tabulation analysis of top ninety-eight serial killers, this present study poses six questions that investigate the correlations between, offender's gender, offender's level of education, time span of killing, killing severity, number of victims, killer's type of abuse, motives for killing, and victim's profile. Findings show that males kill more than females and for longer time, less educated serial killers kill more horribly, female serial killers consider their family members easy target, and finally males kill most for enjoyment and sex and females kill for financial gains.

The severity and outcome of coronavirus disease 2019 (COVID-19) largely depends on a patient’s age. Over 80% of hospitalizations are of those over 65 years of age with a 23-fold greater risk of death. In the clinic, COVID-19 patients most commonly present with fever, cough and dyspnea. Particularly in those over 65, it can progress to pneumonia, lung consolidation, cytokine release syndrome, endotheliitis, coagulopathy, multiple organ failure and death. Comorbidities such as cardiovascular disease, diabetes, obesity and hypertension increase the chances of fatal disease, but they alone do not explain the variability in COVID-19 symptoms. Here, we present the molecular differences between the young, middle-aged and elderly that may determine whether COVID-19 is a mild or life-threatening illness. We also discuss several biological age clocks that could be used in conjunction with genetic tests to identify both the mechanisms of the disease and individuals most at risk. Finally, based on these mechanisms, we discuss treatments that could increase survival in the elderly, not simply by inhibiting the virus, but by restoring patients’ ability to clear the infection.

Plant male sterility refers to the failure in the production of fertile pollen. It occurs spontaneously in natural populations and may be caused by genes encoded in the nuclear (genic male sterility; GMS) or mitochondrial (cytoplasmic male sterility; CMS) genomes. This feature has great agronomic value for the production of hybrid seeds and has been widely used in crops, such as corn, rice, wheat, citrus, and several species of the family Solanaceae. Mitochondrial genes determining CMS have been uncovered in a wide range of plant species. The modes of action of CMS have been classified in terms of the effect they produce in the cell, which ultimately leads to a failure in the production of pollen. Male fertility can be restored by nuclear-encoded genes, termed restorer-of-fertility (Rf) factors. CMS from wild plants has been transferred to species of agronomic interest through somatic hybridization. Somatic hybrids have also been produced to generate CMS de novo upon recombination of the mitochondrial genomes of two parental plants or by separating the CMS cytoplasm from the nuclear Rf alleles

In the past decades, several new diseases have emerged in new geographical areas, with pathogens including Ebola, Zika, Nipah, and coronaviruses (CoVs). Recently, a new type of viral infection has emerged in Wuhan City, China, and initial genomic sequencing data of this virus does not match with previously sequenced CoVs, suggesting a novel CoV strain (2019-nCoV), which has now been termed as severe acute respiratory syndrome CoV-2 (SARS-CoV-2). Although Coronavirus disease 2019 (COVID-19) is suspected to originate from an animal host (zoonotic origin) followed by human-to-human transmission, the possibility of other routes such as food-borne transmission should not be ruled out. Compared to diseases caused by previously known human CoVs, COVID-19 shows less severe pathogenesis but higher transmission competence, as is evident from the continuously increasing number of confirmed cases globally. Compared to other emerging viruses such as Ebola virus, avian H7N9, SARS-CoV, or MERS-CoV, SARS-CoV-2 has shown relatively low pathogenicity and moderate transmissibility. Codon usage studies suggest that this novel virus may have been transferred from an animal source such as bats. Early diagnosis by real-time PCR and next-generation sequencing has facilitated the identification of the pathogen at an early stage. Since, no antiviral drug or vaccine exists to treat or prevent SARS-CoV-2, potential therapeutic strategies that are currently being evaluated predominantly stem from previous experience with treating SARS-CoV, MERS-CoV, and other emerging viral diseases. In this review, we address epidemiological, diagnostic, clinical, and therapeutic aspects, including perspectives of vaccines and preventive measures that have already been globally recommended.

Background: COVID-19 vaccines have been linked to myocarditis which in some circumstances can be fatal. This systematic review aims to investigate potential causal links between COVID-19 vaccines and death from myocarditis using post-mortem analysis. Methods: We performed a systematic review of all published autopsy reports involving COVID-19 vaccination-related myocarditis through July 3^rd, 2023. All autopsy studies that include COVID-19 vaccine-induced myocarditis as a possible cause of death were included, without imposing any additional restrictions. Causality in each case was determined by three independent reviewers with cardiac pathology experience and expertise. Results: We initially identified 1,691 studies and, after screening for our inclusion criteria, included 14 papers that contained 28 autopsy cases. The cardiovascular system was the only organ system affected in 26 cases. In 2 cases, myocarditis was characterized as a consequence from multisystem inflammatory syndrome (MIS). The mean and median number of days from last COVID-19 vaccination until death was 6.2 and 3 days, respectively. Most of the deaths occurred within a week from the last injection. We established that all 28 deaths were causally linked to COVID-19 vaccination by independent adjudication. Conclusions: The temporal relationship, internal and external consistency seen among cases in this review with known COVID-19 vaccine-induced myocarditis, its pathobiological mechanisms and related excess death, complemented with autopsy confirmation, independent adjudication, and application of the Bradford Hill criteria to the overall epidemiology of vaccine myocarditis, suggests there is a high likelihood of a causal link between COVID-19 vaccines and death from suspected myocarditis in cases where sudden, unexpected death has occurred in a vaccinated person. Urgent investigation is required for the purpose of risk stratification and mitigation in order to reduce the population occurrence of fatal COVID-19 vaccine-induced myocarditis.

GPT-4 was released in March 2023 to wide acclaim, marking a very substantial improvement across the board over GPT-3.5 (OpenAI's previously best model, which had powered the initial release of ChatGPT). Despite the genuinely impressive improvement, however, there are good reasons to be highly skeptical of GPT-4's ability to reason. This position paper discusses the nature of reasoning; criticizes the current formulation of reasoning problems in the NLP community and the way in which the reasoning performance of LLMs is currently evaluated; introduces a collection of 21 diverse reasoning problems; and performs a detailed qualitative analysis of GPT-4's performance on these problems. Based on the results of this analysis, the paper argues that, despite the occasional flashes of analytical brilliance, GPT-4 at present is utterly incapable of reasoning.

Research has shown that second language reading is the bridge that leads to developing otherlanguage skills such as speaking, writing, and vocabulary acquisition. Hence, the present studyaimed to explore adult language learners’ perspectives regarding the most effective andbeneficial reading strategies that can be used to develop their reading competency. Using aqualitative research method, the study examined what specific reading strategies languagelearners believe is effective in developing their reading skills. Analysis of the focus groupsrevealed five different reading strategies mentioned by the participants. These strategies were:Reading Aloud, Silent Reading, Shared Reading, Scanning or Skimming, and Timed Reading. Findings suggest that understanding the use of different reading strategies is important, solanguage teachers need to devote more learning time to introduce reading strategies during ESL classes.

This paper aimed to use social media impact on student studies in higher education. Apart from enjoyment and academic purposes, many educational practices and processes have been influenced by social networks. This paper highlighted the use of media tools in higher education as well as indicates out some of the factors. Moreover, through a literature review of related articles, we aim to provide insights into the impacts of a social network on educational quality, actual use of social media, and performance impact in higher education. A questionnaire survey on constructivism was circulated among a total of 206 university students as the key method for collecting data. This research hypothesizes educational quality and actual social media use indicates a positive effect in education, all of which also hypothesizes constructivism for educational quality and actual social media that in turn improve students’ satisfaction, and performance impact. Moreover, all research findings were attained through a quantitative method using the Structural Equation Modeling (SEM-AMOS). Findings of this research to indicate a positive effects students on their academic through behavioral intention to utilize social media to actual social media use for teaching and learning on higher education. Moreover, the results mention the use of social media for learning purpose, as well as social media to enables the sharing of knowledge, discussions, and information to enhance students' learning activities, Further studies are recommended which universities educators should take this into consideration when planning their curricula; it comes to the inclusion of technology in the teaching process.

Since there is no vaccine or regulatory approved therapy available for treatment of SARS-CoV-2 infection, the medical need to prevent the transition of a mild into the severe COVID-19 stage of infection is of outmost importance. Among several drug candidates, Chloroquine (CQN) and Hydroxy-Chloroquine (H-CQN) have been tested most intensively. However, the therapeutic effect of H-CQN and CQN has been discussed controversially in the light of severe side effects. Originally, H-CQN descended from the natural substance Quinine, a medicinal product used since the Middle Ages and is now regulatory approved for various indications. We hypothesized that Quinine also exerts anti-SARS-CoV-2 activity. First, virus production in Vero B4 cells was analyzed by Western blot, showing that Quinine exerts antiviral activity against SARS-CoV-2 that at 10 µM was even stronger than that of H-CQN or CQN. Second, fluorescence end-point and time lapse analysis of SARS-CoV-2-mNeonGreen-infected Caco-2 cells could confirm a similar antiviral effect of Quinine in a human-derived cell line. Thereby, our in vitro studies revealed, that the antiviral effect appears to be specific, since in Vero cells Quinine impacted cell viability at approximately 50-fold higher concentration, while the therapeutic window of H-CQN and CQN was approximately 10-fold lower. In Caco-2 cells no toxic effect was observed while complete block of infection occurred between 50 and 100 µM at high MOIs. In conclusion, our data indicate that Quinine would have the potential of a well tolerable and widely used treatment option for SARS-CoV-2 infections, with a predictable and significantly better toxicological profile when compared to H-CQN or CQN.

This study investigated the psychosocial factors influencing substance abuse among undergraduates. The study was conducted in Ekiti State university Ado Ekiti. 150 participants who are undergraduates of the university were used in this research. They consist of 82 males and 68 females selected from all faculties in the institution. 3 questionnaires were administered to respondent to measure the factors influencing substance abuse and the level at which they are abused. Independent T-test, multiple regression and Pearson Correlation method were used to analyze the data collected. Five hypotheses were tested: hypothesis 1, 2, 3 and 4 were significant while hypothesis 5 was insignificant. It was observed that there was significant influence of religiosity on substance abuse among undergraduates, the result also revealed that there was a significant influence of self-esteem on substance abuse among undergraduates, it also revealed that religiosity and self-esteem jointly predicted substance abuse among undergraduates, likewise the result also show that there was significant influence of sex on substance abuse among undergraduates and finally the result revealed there was no significant relationship between religiosity and self-esteem among undergraduates. The results were discussed in line with relevant empirical literatures, while conclusion and recommendations subsequently followed.

A review of the concept of "fitness" as it is used in evolutionary theory.

We present an Arduino-based automatic robotic system which is used for cutting grass or lawns, mostly healthy grass which needs to cut neatly like in a public park or a private garden. The purpose of this proposed project is to design a programmable automatic pattern design grass cutting robot with solar power which no longer requires time-consuming manual grass-cutting, and that can be operated wirelessly using an Android Smartphone via Bluetooth from a safe distance which is capable of cutting the grass in indeed required shapes and patterns; the cutting blade can also be adjusted to maintain the different length of the grass. The main focus was to design a prototype that can work with a little or no Physical user interaction. The proposed work is accomplished by using an Arduino microcontroller, DC geared Motors, IR obstacle detection sensor, motor shield, relay module, DC battery, solar panel, and Bluetooth module. The grass-cutting robot system can be moved to the location in the lawn remotely where the user wants to cut the grass directly or in desired patterns. The user can press the desired pattern button from the mobile application, and the system will start cutting grass in the similar design such as a circle, spiral, rectangle, and continue pattern. Also, with the assistance of sensors positioned at the front of the vehicle, an automatic barrier detection system is introduced to enhance safety measurements to prevent any risks. IR obstacle detector sensors are used to detect obstacles, if any obstacle is found in front of the robot while traveling; it avoids the barrier by taking a right/right turn or stop automatically appropriately, thereby preventing the collision. Also, the main aim of this project is the formation of a grass cutter that relieves the user from mowing their own grasses and reduces environmental and noise pollution. The proposed system is designed as a lab-scale prototype to experimentally validate the efficiency, accuracy, and affordability of the systems. The experimental results prove that the proposed work has all in one capability (Simple and Pattern based grass cutting with mobile-application, obstacle detection), is very easy to use, and can be easily assembled in a simple hardware circuit. We note that the systems proposed can be implemented on a large scale under real conditions in the future, which will be useful in robotics applications and cutting grass in playing grounds such as cricket, football, and hockey, etc.

To extend the calculation power of tensor analysis, we introduce four new definition of tensor calculations. Some useful tensor identities have been proved. We demonstrate the application of the tensor identities in continuum mechanics: momentum conservation law and deformation superposition.

After a long waited span, the whole world could see the ray of covid-19 vaccine to resist the planet to watch the death procession. But some country people especially the people of Bangladesh keep them aside to take the vaccination. This study aims to understand the perception towards the COVID-19 vaccination program in Bangladesh and the targeted subject is the university student as they are suffering highly depression nowadays. Higher education has been affected globally as a result of the COVID-19 pandemic in 223 countries. Moreover, for this pandemic situation, the university students can not complete their graduation which binds them to enter their professional career. Alike all of the developed countries, as well as developing countries, Bangladesh, also considered vaccination as an effective measure to protect the peoples from the Covid-19 virus. This study targeted three psychological factors of the university students and surveyed 322 students from the different universities in Bangladesh to understand their perception regarding vaccines. Moreover, it is seen that most of the students doubt the effectiveness of the vaccine which interrupts them from taking the vaccine willingly.

Since it was proposed, the Robot Operating System (ROS) has fostered solutions for various problems in robotics in the form of ROS packages. One of these problems is Simultaneous Localization and Mapping (SLAM), a problem solved by computing the robot pose and a map of its environment of operation at the same time. The increasingly availability of robot kits ready to be programmed and also of RGB-D sensors often pose the question of which SLAM package should be used given the application requirements. When the SLAM subsystem must deliver estimates for robot navigation, as is the case of applications involving autonomous navigation, this question is even more relevant. This work introduces an experimental analysis of GMapping and RTAB-Map, two ROS compatible SLAM packages, regarding their SLAM accuracy, quality of produced maps and use of produced maps in navigation tasks. Our analysis aims ground robots equipped with RGB-D sensors for indoor environments and is supported by experiments conducted on datasets from simulation, benchmarks and from our own robot.

In this paper, we study the usage of machine learning models for sales time series forecasting. The effect of machine learning generalization has been considered. A stacking approach for building regression ensemble of single models has been studied. The results show that using stacking technics, we can improve the performance of predictive models for sales time series forecasting.

The insurance industry plays an important role for European economic stability and the threats and opportunities it faces should be carefully determined. In this paper we highlight the main challenges by using a PEST analysis. This work applies conventional actuarial thought on this area by focusing strictly on the European sector.

In this paper we have discussed the importance of human resource management in project management. As a concept human resource management emerged in 1980 [9]. It is very important to utilize resources effectively in any organization. Like triple constrains (cost, quality, scope) human resources are also considered as one of the most important factor for the success of any project. Management of human resources involve hiring experienced workers, giving appropriate training, acknowledgement about the significance of the project and the effective use of techniques and tools in order to get the project done productively with in time and budget. It becomes the responsibility of the project manager to effectively manage human resources as it is more challenging than managing other technical resources. In this paper we have also discussed the challenges that an organization faced during the management of the resources and use of some strategic human practices in order to overcome these challenges.

Background: Coronavirus disease 2019 (COVID-19) is a new viral respiratory disease and whether pregnant women are at increased risk of infection is unknown. Viral pneumonia is an important indirect cause of maternal death. Little is known about the effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during pregnancy. Objective: To describe the clinical characteristics of COVID-19 in pregnancy and their newborn infant, and we sought to explored whether the SARS-CoV-2 can be intrauterine vertically transmitted. Study Design: The study was a case series study conducted in the obstetric ward of Tongji Hospital affiliated to Huazhong University of science and technology, Wuhan, China. Demographic, clinical, laboratory and radiological profiles of the SARS-CoV-2 infection case series. A systematic testing procedure for SARS-CoV-2 infection using oropharyngeal swab, placenta tissue, vaginal mucus, and breast milk of mothers. and oropharyngeal swab, umbilical cord blood, and serum of newborns was conducted. Results: We have conducted the most thorough virological assessment to date, and we include a longer clinical observation in mother-infant dyads during hospitalization. The clinical course and outcomes of three pregnant women who acquired SARS-CoV-2 infection late pregnancy are described in mother-infant dyads. Two had caesarean delivery in their third trimester. All patients showed an uneventful perinatal course, and a successful outcome. No infants became infected by vertical transmission or during delivery. Conclusion: No evidence to suggest the potential risk of intrauterine vertical transmission in the case series and further in-depth study is needed. Both the pregnancy woman and infant showed fewer adverse maternal and neonatal outcomes.

The evolution of knowledge in biological and medical areas which made possible scientific and technological advances are attributed to anatomical studies, physiology and immunology in animals, contributing to the discovery of prophylactic measures and treatments of diseases that affect humans and animals. Currently, substitution is suggested by alternative methods that do not use laboratory animals, however in vitro methods may never be able to provide similar results to in vivo methods. Mice and rats are the most used animals in experimental researches, the anatomical, histological and genetic differences between species should be carefully evaluated, to better apply the study model and avoid unnecessary waste avoid. This study, aimed at an anatomical comparative and histological relationship between a rat´s and a mouse´s organs, is of great importance in experimental studies. For such, 30 Mus musculus (Swiss) mice and 15 Rattus norvegicus (Wistar) male and heterogenic rats, were used. All animals were kept free of pathogenic microorganisms, with the absence of surgical interventions that could cause anatomical and physiological changes. It was possible to observe significant anatomical and histological differences between spleens, brains, hearts, stomachs and intestines, livers, eyes, lungs and kidneys among species, which will serve as a basis to assist in choosing the most satisfactory research model. Few studies relate specific characteristics among laboratory animals, being restricted to a few veterinary and zoology books. The greater the organic, physiological and anatomical similarities are with the human being, the greater is the applicability of the animals in studies. However, it is not possible to lay down general rules to validate the extrapolation from one species to another.

The conventional machine learning (ML) algorithms are continuously advancing and evolving at a fast-paced by introducing the novel learning algorithms. ML models are continually improving using hybridization and ensemble techniques to empower computation, functionality, robustness, and accuracy aspects of modeling. Currently, numerous hybrid and ensemble ML models have been introduced. However, they have not been surveyed in a comprehensive manner. This paper presents the state of the art of novel ML models and their performance and application domains through a novel taxonomy.

As the echoes of ChatGPT's remarkable success continue to permeate the AI community, its formidable successor, GPT-4, has emerged, showing off a wealth of novel features. In this concise paper, we elucidate the capabilities of GPT-4 and conduct a comparative analysis with its predecessor, ChatGPT, offering insights into their relative strengths and advancements in the rapidly evolving field of generative AI. We also present a comprehensive summary of the major performance results reported by OpenAI on GPT-4 across various Natural Language Processing (NLP) tasks. We place great emphasis on the innovative advancements offered by GPT-4 in comparison to its predecessors. Our focus is on highlighting its remarkable performance while also mentioning its limitations. The purpose of this paper is to deliver a succinct understanding of the new features and performance benchmarks of GPT-4.

The open source CFD code OpenFOAM has emerged as one of the most popular alternative to commercial CFD solvers. The recent version of OpenFOAM supports overlapping grids, so called Overset mesh. In this type of mesh, one or more sub-collection of control volumes (or cells) are allowed to overlap with other set of cells. This allows for great flexibility in modelling Fluid Structure Interaction (FSI) problems. Fluid mesh can be standard structured mesh of a rectangular/cuboidal/or cylindrical domain. The structure mesh can be generated separately by creating multiple layers around a given body. The overset mesh functionality allows for overlapping or immersing this structured mesh inside the fluid mesh and a relevant FSI or moving dynamics problems can be solved. The idea of overset mesh has been around since eighties but its support in OpenFOAM is very recent. Most CFD codes which support overset mesh have either been in-house or commercial CFD codes. OpenFOAM's support for overset is the first major open source code resource available for CFD problems. The aim of this research is to solve a classical benchmark airfoil problem using OpenFOAM overset mesh and compare the numerical results with experimental result. We report here flow simulations results around NACA 0018. The result obtained from overset mesh compares convincingly well with experimental results. Computations have been carried out for Reynolds numbers in the range of 10⁵ with angle of attack ranging from α= 5 degree to α= 30 degree with an interval of 5 degree. Turbulence is incorporated using k - ε turbulence model. This study helps developing confidence in using OpenFOAM overset support for more complicated flows and moving dynamics. This report is complemented with a brief description of finite volume discretization using overset mesh.

In this review, we provide an overview of the current knowledge on the different sexual systems and sex determining mechanisms in bivalves, with a focus on the various epigenetic and genetic factors that may be involved. The final section of the review provides recent discoveries on sex-specific mitochondrial genes in bivalves possessing the unconventional system of doubly uniparental inheritance of mitochondria (which is found in several members of the orders Mytiloida, Unionoida, Veneroida and Nuculanoida). The genes involved in this developmental pathway could represent the first sex determination system in animals in which mitochondrially-encoded genes are directly involved.

New class of biologically active and non-active compounds can be synthesized via transition metal mediated Suzuki cross coupling reaction that has a great impact on the advancement of organic chemistry. These resulted products can lend a helping hand in pharmaceutical and polymer chemistry for the betterment of mankind. Suzuki-Miyaura cross coupling reaction is one of the best tools through which many natural and non-natural compounds can be synthesized.

The coronavirus pandemic will deeply affect the tourism and travel sector. It is already clear now that its economic impact would be more severe that in the case of the Severe Acute Respiratory Syndrome (SARS) in 2002-2003. Although not as deadly as SARS, coronavirus infection has a longer incubation period and leaves about 85% of the infected without any (or with just mild) symptoms which makes it more difficult to track and to contain. Moreover, it appears to be much more contagious than its predecessor. The goods news is that most people recover from the disease and develop antibodies that can protect them from getting infected again (natural vaccination). Those cured might become the key element for the post-virus recovery strategies of tourism organisations. People with the acquired immunity to the virus would be capable of travelling freely without spreading the disease. Airlines, hotels and gastronomy should aim at this group offering them discounts and special offers. However, the problem is how to effectively ensure that everyone who claims to be cured from COVID-19 is telling the truth. Health tracking bracelets, apps, and other advanced technological solutions should be put in place. Recent best practices from Hong Kong, mainland China, or India might be applied.

The spread of 2019 novel coronavirus disease (COVID-19) throughout the world has been a severe challenge for public health. The human angiotensin-converting enzyme 2 (ACE2) has a remarkably high affinity binding to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). By the search for network database and re-analysis of pubic data, we found the level of ACE2 expression in adipose tissue was higher than that in lung tissue, which indicated the adipose tissue might be vulnerable to SARS-CoV-2 as well; the levels of ACE2 expressed by adipocytes and adipose progenitor cells were similar between non-obese individuals and obese individuals, but obese individuals have more adiposes so as to increase the number of ACE2-expressing cells; the expression of ACE2 in tumor tissues posed by five different types of cancers increased significantly compared with that in adjacent tissues. Thus, we suggest that more attentions might be given to obese individuals and the five types of cancer patients during the outbreak of COVID-19.

Wetlands benefits can be summarized but are not limited to their ability to store floodwaters and improve water quality, providing habitats for wildlife and supporting biodiversity, as well as aesthetic values. Over the past few decades, remote sensing and geographical information technologies has proven to be a useful and frequent applications in monitoring and mapping wetlands. Combining both optical and microwave satellite data can give significant information about the biophysical characteristics of wetlands and wetlands` vegetation. Also, fusing data from different sensors, such as radar and optical remote sensing data, can increase the wetland classification accuracy. In this paper we investigate the ability of fusion two fine spatial resolution satellite data, Sentinel-2 and the Synthetic Aperture Radar Satellite, Sentinel-1, for mapping wetlands. As a study area in this paper, Balikdami wetland located in the Anatolian part of Turkey has been selected. Both Sentinel-1 and Sentinel-2 images require pre-processing before their use. After the pre-processing, several vegetation indices calculated from the Sentinel-2 bands were included in the data set. Furthermore, an object-based classification was performed. For the accuracy assessment of the obtained results, number of random points were added over the study area. In addition, the results were compared with data from Unmanned Aerial Vehicle collected on the same data of the overpass of the Sentinel-2, and three days before the overpass of Sentinel-1 satellite. The accuracy assessment showed that the results significant and satisfying in the wetland classification using both multispectral and microwave data. The statistical results of the fusion of the optical and radar data showed high wetland mapping accuracy, with an overall classification accuracy of approximately 90% in the object-based classification. Compared with the high resolution UAV data, the classification results give promising results for mapping and monitoring not just wetlands, but also the sub-classes of the study area. For future research, multi-temporal image use and terrain data collection are recommended.

As part of the Copernicus programme of the European Union (EU), the European Space Agency (ESA) has developed and is currently operating the Sentinel-2 mission that is acquiring high spatial resolution optical imagery. This paper provides a description of the calibration activities and the current status of the mission products validation activities. Measured performances, from the validation activities, cover both Top-Of-Atmosphere (TOA) and Bottom-Of-Atmosphere (BOA) products. Results presented in this paper show the good quality of the mission products both in terms of radiometry and geometry and provide an overview on next mission steps related to data quality aspects.

More than 179,000 individuals have fallen ill of the Coronavirus disease (COVID-19) caused by the SARS-CoV-2 virus, which first emerged in China less than four months ago in December 2019. As of today, there exist no approved treatments against COVID-19. Vaccines are being developed, but they will take time, at least one year, to reach the population. Drug repositioning represents a fast track because already approved medicines have been broadly tested through multiple trials. We developed a repositioning strategy that mostly leads to candidates that are commonly used. The advantages are that they will facilitate proof of concept in humans through a “real-world evidence” approach and should be rapidly available to the population. We focus on the established research results that the unfolded protein response (UPR) and autophagy pathways of the host cells are essential to the life cycle of previously known coronaviruses. We performed the relevant bioinformatics analysis to understand and confirm if SARS-CoV-2 may interact with these druggable pathways. Based on these considerations, we prioritized two additional druggable pathways, which are important to the viral life cycle and tightly connected to UPR/autophagy signaling: the mitochondrial permeability transition pores (MPTP) and NLRP-3 inflammasome pathways. These four important pathways are perturbed in most major common diseases and have therefore been targeted by numerous broadly prescribed drugs. We have identified 97 approved drugs that are known to modulate these four identified pathways, and which represent, therefore, interesting repositioning candidates. Although it is indisputable that these drugs should never be used for immediate self-medication against COVID-19, we notice that some of them could also be prescribed to individuals who have COVID-19 comorbidities (e.g., hypertension). It is debated if these comorbidities are linked to the pathology itself (e.g., hypertension) or the drugs used to treat the pathology (e.g., sartans). Therefore, relevant preclinical tests and massive electronic health records (i.e., real-world evidence) must be used to pre-screen them and check the COVID-19 prognosis of individuals taking these drugs.

This review will explore the four major pillars required for design and development of an saRNA vaccine: antigen design, vector design, non-viral delivery systems, and manufacturing (both saRNA and lipid nanoparticles (LNP)). In will report on the major innovations, preclinical and clinical data reported in the last five years and will discuss future prospects.

Objectives Assess rates of adverse events (AE) after COVID-19 vaccines experienced by women of reproductive age, focusing on pregnancy and menstruation, using data collected by the US Centers for Disease Control and Prevention (CDC) Vaccine Adverse Events Reporting System (VAERS) database. Design Population-based retrospective cohort study. Setting US and global entries in US Centers for Disease Control and Prevention (CDC) Vaccine Adverse Events Reporting System (VAERS). Participants CDC VAERS entries from January 1, 1998 to June 30, 2022. Interventions None. Main Outcome Measures A proportional reporting ratio analysis is performed using data in the VAERS system comparing adverse events (AE) reported post-COVID-19 vaccines with that of post-Influenza vaccines. Results COVID-19 vaccines, when compared to the Influenza vaccines, are associated with a significant increase in AE with all proportional reporting ratios of > 2.0: menstrual abnormalities, miscarriage, fetal chromosomal abnormalities, fetal malformation, fetal cystic hygroma, fetal cardiac disorders, fetal arrhythmias, fetal cardiac arrest, fetal vascular malperfusion, fetal growth abnormalities, fetal abnormal surveillance, fetal placental thrombosis, low amniotic fluid, preeclampsia, premature delivery, preterm premature rupture of membrane, fetal death/stillbirth, and premature baby death (all p values were much smaller than 0.05). When normalized by time-available, doses-given, or persons-received, all COVID-19 vaccine AE far exceed the safety signal on all recognized thresholds. Conclusions Pregnancy complications and menstrual abnormalities are significantly more frequent following COVID-19 vaccinations than Influenza vaccinations. A worldwide moratorium on the use of COVID-19 vaccines in pregnancy is advised until randomized prospective trials document safety in pregnancy and long-term follow-up in offspring.

Mind and brain/matter interaction is one of the important and controversial issues in Islamic philosophy. In fact, in the resources of Islamic philosophy, one of the basic parts of philosophical discussions is related to mind’s nature and its interaction with the brain. Especially, in Avicenna’s philosophy, there are many articles and books which have addressed the topic of mind and brain and the relation between them. Avicenna was a profound philosopher, an expert physicist and a proficient physician of his time. Because of his experimental proficiency in medicine and surgery and his deep philosophical analysis, his discussion about mind and brain is very interesting for our time, due to recent advances in neuroscience. In this article, we have explained one of Avicenna’s arguments (in his famous opus “al-Isharat”) about the incorporeity of mind (self), which is very close to modern neuroscience and physics literature. In addition, we explain his model of mind and brain interaction. Avicenna described the mechanism of the causal effect of mind on the brain via a third identity, which works as an interface between them (in his main book “al-Shifa”). We try to illustrate his model by the use of some examples, inspired from modern physics. Also, we explore the philosophical constraints which must be considered in any model of mind-matter interaction, within the Islamic philosophy framework. In fact, we propose a new understanding of Avicenna’s philosophy which is in agreement with modern physics and neuroscience.

Music therapy has served as complementary and alternative medicine for various neurological disorders. Five Phases Music Therapy (FPMT) employs the theory of five phases and five music scales or tones (宫Gong (do), 商Shang (ri), 角Jue (mi), 徵Zhi (so) and 羽Yu (la)) to analyze and treat mind-body illness. In Chinese Medicine (CM), the five music scales are used to connect the human body and the universe, interpret personalities and constitution and analyze the influences of climatic changes on health. FPMT has a self-contained theory and routine of practice application. Large amounts of clinical and fundamental reports have been available and clinical benefits have been obtained. However more systemic clinic research esp. evidence-based and random controlled trials must be performed to validate and optimize its routines and biological and neurological mechanism must be further explored. It’s reasonable to believe that the effective music therapy will attract more attention from the world outside China with the introduction of FPMT.

A new lateral force-resisting wall panel is presented for applications in mid-rise prefabricated lightweight steel construction in seismic prone regions. This panelised system is composed of a hot-rolled frame and cold-formed studs and tracks, which works as a lateral force resisting system in lightweight steel framing. The proposed hybrid panel system exhibits proper ductility and energy dissipation behaviour. The hysteretic responses of full-scale panel experiments demonstrate that the system can safely resist high cyclic loads. The hot-rolled steel part, on the other hand, can significantly improve the initial lateral stiffness of the total system that will control the maximum allowable drift of multi-story buildings. Finally, in a case study, by applying the proposed system to the design of a mid-rise building in a high seismic area, the performance of the hybrid panels, are compared with those of fully hot-rolled systems (moment resisting frames) and fully cold formed systems. The findings indicate that applying hybrid panels will result in lower weights and better performance in seismic prone regions.

Weather forecast has a big impact on the global economy, accurate and timely weather forecast is required by all, it affects many aspects of human livelihood and lifestyle, it also plays a critical role in decision making for severe weather management and for primary and secondary sectors like agriculture, transportation, tourism, and industry as they rely on good weather conditions for production and operations. The erratic and uncertain complex nature of the weather makes traditional weather forecasting tedious and a challenging task, traditional weather forecast involves applying technology and scientific knowledge on numerical weather prediction (NWP), and weather radar to solve complex mathematical equations to obtain forecasts based on current weather conditions. These traditional processes utilize expensive, complex physical and computational power to produce forecasts, which can be inaccurate and have various catastrophic impacts on society. In this research, a machine learning-based weather forecasting model was proposed, the model was implemented using 4 classifier algorithms which include Random Forest classifier, Decision Tree Algorithm, Gaussian Naïve Bayes model, and Gradient Boosting Classifier, these algorithms were trained using a publicly available dataset from Kaggle for the city of Seattle for the period 2012 to 2015. The model’s performance was evaluated; the Gaussian Naive Bayes algorithm proved to be the best performing algorithm with a predictive accuracy of 84.153 %.

Though the share of the world population living in extreme poverty declined to 10 percent in 2015, from 16 percent in 2010 and 36 percent in 1990, data shows that the world is not on track in achieving the target of less than 3 percent of people living in extreme poverty by 2030. Hence the study sought to investigate the influence of AI on poverty reduction. Using content analysis one of the unobtrusive research techniques, the study found out that, the availability of relevant data is making AI be able to deliver value to humanity and AI has a strong influence on poverty in areas of relevant data collection through poverty maps, its ability to revolutionize agriculture, education, and the financial sector through digital financial inclusion. The study also discovered that many countries especially developing nations are not collecting as much data to identify the number of poor people and the regions where these people are located. However, the existence of AI is assisting to change this, or instance the study discovered that the research team at Stanford University is using satellite images to provide an alternative to map poverty, to identify the regions where poverty is more concentrated. Also, various robotics and AI programs such as Google and Stanford University’s Sustainability and Artificial Intelligence Lab, are coming forth with AI programs in agriculture which are doing a lot to improve farming, through the identification of diseases, prediction of crop yields, and location of areas prone to a scarcity among several other notable signs of progress in education. Therefore, the study recommends that governments, development institutions and other organizations that are striving to fight poverty to invest more in AI as well as adopting and scaling up its use as it presents benefits in the quest to ensure that poverty is reduced.

The most recent outbreak of 2019 novel coronavirus, named as COVID-19, caused pneumonia epidemic in Wuhan with 2,121 deaths cases as of February 20^th 2020. Identification of effective antiviral agents to combat the novel coronavirus is urgently needed. Citrus fruit peel or wild citrus are rich in flavonoid, and is clinically documented for roles in relief of cough and promotion of digestive health. Therefore, citrus fruits are assumed to possess antivirus activities or enhance the host immunity. A previous study found that hesperetin could act as a high potent inhibitor of SARS-CoV 3CLpro. We determined six flavonoid compounds content of in three citrus species by using LC-MS technique. The content of naringin and naringenin was at higher levels in pummelo. Hesperetin and hesperidin were highly accumulated in mandarin and sweet orange. The subsequent in vitro and in vivo experiments indicated that naringin could inhibit the expression of the proinflammatory cytokines (COX-2, iNOS, IL-1β and IL-6) induced by LPS in Raw macrophage cell line, and may restrain cytokine through inhibiting HMGB1 expression in a mouse model. The results revealed that naringin may have a potential application for preventing cytokine storm. We simulated molecular docking to predict the binding affinity of those flavonoids to bind Angiotensin-converting enzyme 2 (ACE 2), which is a receptor of the coronavirus. Consideration of the potential anti-coronavirus and anti-inflammatory activity of flavonoids, the citrus fruit or its derived phytochemicals are promising in the use of prevention and treatment of 2019-nCoV infection.

The objective of the study was to evaluate the risk factors associated with lower COVID-19 vaccination rates in the United States. The study evaluated the effect of red-blue political affiliation and the effect of the US state's average educational aptitude score and per capita income on states' vaccination rates. The study found that states with concomitantly lower income along with lower educational aptitude scores are less vaccinated while the states with higher income have higher vaccination rates even among those with lower educational aptitude scores. These findings stayed significant after adjusting for red-blue political affiliation where states with red political affiliation have lower vaccination rates. Further study is needed to evaluate how to stop online misinformation among states with low income and low educational aptitude scores; and whether such an effort will increase overall vaccination rates in the United States.

The production of lithium-ion battery cells is characterized by a high degree of complexit due to numerous cause-effect relationships between process characteristics. Knowledge about the multi-stage production is spread among several experts, rendering tasks such as failure analysis challenging. In this paper, a method is presented, which includes expert knowledge acquisition in production ramp-up by combining Failure Mode and Effects Analysis (FMEA) with a Bayesian Network. We show the effectiveness of this holistic method by building up a large scale, cross-process Bayesian Failure Network in lithium-ion battery production. Using this model, we are able to conduct root cause analyses as well as analyses of failure propagation. The former support operators in identifying root causes once a cell possesses a specific failure by calculating most-probable explanations matched to the individual battery cell data. The latter enable us to analyze propagation of failures and deviations in the production chain and thus provide support for placement of quality gates, leading to a significant reduction in scrap rate. Moreover, it gives an insight into which process steps are key drivers for which final product characteristics.

Nail surgery for the permanent removal of all or part of the nail unit can be performed via incisional or physically ablative techniques for conditions such as ingrown, mycotic, or dystrophic toenails. In the United Kingdom podiatric community, where phenol techniques are the standard of care for ablation of the matrix, there remains confusion about the management of patients undergoing nail surgery who are concurrently taking antithrombotic medication(s). The aim of this paper was to review the literature describing treatment strategies for antithrombosed patients undergoing nail surgery. However, having found limited evidence, the authors considered relevant and associated literature in the field of cutaneous/dermatological surgery and extrapolated those findings for patients undergoing nail avulsion surgery. A case-by-case risk assessment is warranted in all patients but as a general rule, the podiatrist can perform nail surgery without the patientceasing their antithrombotic medication.

We are witnessing a progressive divestment of some institutions with strong traditions and skills in physical modelling and their consequent impoverishment, to the detriment of numerical modelling. For many reasons, the economic imperatives and the exponential growth of computational means and numerical methods should certainly not be excluded. In this work, we aimed to highlight the new requirements of the recent sophisticated developments in physical modelling, precisely due to the new needs imposed on them by mathematical and numerical modelling and the growing risks in civil construction works. In this context, reflections are reported, justified by scientific and real-world examples, on the need for maintenance and reinforcement of investments in physical modelling, both to support the scientific community and to design buildings of significant economic, social and environmental impact.

This paper gives an overview of the large-scale tectonic styles encountered in orogens worldwide. Thin-skinned and thick-skinned tectonics represent two end member styles recognized in mountain ranges. Both styles are encountered in former passive margins of continental plates. Thick-skinned style including the entire crust and possibly the lithospheric mantle are associated with intracontinental contraction. Delamination of subducting continental crust and horizontal protrusion of upper plate crust into the opening gap occurs in the terminal stage of continent-continent collision. Continental crust thinned prior to contraction is likely to develop relatively thin thrust sheets of crystalline basement. A true thin-skinned type requires a detachment layer of sufficient thickness. Thickness of the décollement layer as well as the mechanical contrast between décollement layer and detached cover control the style of folding and thrusting within the detached cover units. In subduction-related orogens, thin- and thick-skinned deformation may occur several hundreds of kilometers from the plate contact zone. Basin inversion resulting from horizontal contraction may lead to the formation of basement uplifts by the combined reactivation of pre-existing normal faults and initiation of new reverse faults. In most orogens thick-skinned and thin-skinned structures both occur and evolve with a pattern where nappe stacking propagates outward and downward

Long-haul COVID-19 illness first gained widespread recognition among social support groups and later in scientific and medical communities. This illness is mysterious as it affects COVID-19 survivors at all levels of disease severity, even younger adults and children. While the precise definition may be lacking, the defining symptoms are fatigue, dyspnea, and headache that last for months after hospital discharge. The less typical symptoms may include cognitive impairments, chest and joint pains, myalgia, smell and taste dysfunctions, cough, mood changes, and gastrointestinal and cardiac issues. Presently, there is limited literature discussing the possible pathophysiology, risk factors, and treatments in long-haul COVID-19, which the current review aims to address. In brief, long-haul COVID-19 may be driven by long-term lung and brain damage and unresolved inflammation from multiple sources. The associated risk factors may include female sex, more than five early symptoms, early dyspnea, and specific biomarkers like D-dimer. While only rehabilitation training has been useful for long-haul COVID-19, therapeutics repurposed from mast cell activation syndrome, myalgic encephalomyelitis/chronic fatigue syndrome, and pulmonary fibrosis also hold potential. In sum, this review hopes to provide the current understanding of what is known about long-haul COVID-19.

Wetlands are recognized as one of the world’s most valuable natural resources. With the increasing world population, human demands on wetland resources for agricultural expansion and urban development continue to increase. In addition, global climate change has pronounced impacts on wetland ecosystems through alterations in hydrological regimes. To better manage and conserve wetland resources, we need to know the distribution and extent of wetlands and monitor their dynamic changes. Wetland maps and inventories can provide crucial information for wetland conservation, restoration, and management. Geographic Information System (GIS) and remote sensing technologies have proven to be useful for mapping and monitoring wetland resources. Recent advances in geospatial technologies have greatly increased the availability of remotely sensed imagery with better and finer spatial, temporal, and spectral resolution. This chapter presents an introduction to the uses of GIS and remote sensing technologies for wetland mapping and monitoring. A case study is presented to demonstrate the use of high-resolution light detection and ranging (LiDAR) data and aerial photographs for mapping prairie potholes and surface hydrologic flow pathways.

Mode locked pulse generation has been reported using both active and passive mode locking schemes. Active mode locking technique has been proven to be an effective way to generate high-repetition-rate pulses by incorporating a modulator inside the laser cavity. Compared to actively mode locked lasers, passively mode locked lasers can generate pulse train at ultrashort pulse width but with relatively lower repetition rate. Thus, it is a brilliant idea to build a hybrid mode locked system combining both active and passive mode lockers. In this review, several hybrid mode locked fiber ring laser systems are discussed and summarized. Hybrid mode locking is a promising method to generate high speed ultrashort optical pulses for fiber-optic telecommunication system.

Personality changes have been reported to occur following organ transplantation, and most commonly among heart transplant recipients. We set out to examine whether personality changes do occur following transplantation, and specifically, what types of changes occur among heart transplant recipients compared to other organ recipients. A cross-sectional study was conducted in 2022, in which 47 participants (23 heart recipients and 24 other organ recipients) completed an online survey. In this study, 89% of all transplant recipients reported experiencing personality changes after receiving their organ transplant, which was similar for heart and other organ recipients. With the exception of physical attributes, the types of personality changes reported were similar between the two groups. These finding indicate that heart transplant recipients are not unique in their reported experience of personality changes following organ transplantation. Further studies are needed to deepen our understanding of what causes these personality changes following organ transplantation.

Dump design and scheduling are critical elements to effective mine planning, especially if several of them are required in large-scale open pit mines. Infrastructure capital and transportation costs are considerable from an early stage in the mining project, and through the life-of-mine as these dumps gradually become immense structures. Delivered mining rates, as well as certain spatial and physical constraints, provide a set of parameters of mathematical and economic relationship that creates opportunities for modelling and thus facilitates the measuring and optimization of ultimate dump design by using programming and empirical techniques while achieving economic objectives. This paper presents a methodology to model and optimize the design of a mine dump by minimizing the total haulage costs. The proposed methodology consists on: (i) Formulation of a dump model based on a system of equations relying on multiple relevant parameters; (ii) Solves by minimizing the total cost using linear programming and determines a ‘preliminary’ dump design; (iii) Through a series of iterations, modifies the ‘preliminary’ footprint by projecting it to the topography and creates the ultimate dump design. Finally, an example application for a waste rock dump illustrates this methodology.

Green development ensures the socioeconomic development that incorporates environmental issues while remaining economically viable for owners and tenants. Government as the authority of the state should provide favorable incentives, policy and regulatory pressure for green development. The present study aims to investigate the government policies and regulations for green development in Bangladesh and make a critical discussion of the initiatives. The study is descriptive in nature and collects secondary information. Evidence suggests that environmental degradation and climate change related risks and vulnerabilities have intensified in Bangladesh. The government of Bangladesh (GOB) is concerned about green development and formulates various Acts, regulations and policy initiatives since 2010. Major green development initiatives observed in the financial institutions due to the mandatory requirements by Bangladesh Bank but green bond and green insurance in capital market are yet to be developed. The GOB required taking proper policy initiatives for the garments and leather industries to ensure pollution free production system which ensures green trade initiatives. The environmental taxes and ecological compensation mechanisms should be revised. Urban green space and Government green procurement are still less concerning matter. The GOB should make effective collaboration with all related stakeholders to ensure the green development.

In this working paper we intended to address the emergence of what, potentially, will be a central concept in the very near future, Society 5.0 and that arises politically in (with) following the implementation of the concept of Industry 4.0. Society 5.0 proposes to deepen the potential of the individual-technology relationship in the promotion of the improvement of the quality of life of all people through a super smart society, is an extremely recent concept as a guiding social development that can have a profound impact in societies at all levels, such as quality of life and sustainability. It is a presentation that is based on very recent3 publications, but which also has a prospective component, which always generates some indetermination and uncertainty. Also, for this reason, it is a contribution that seeks above all else to contribute to this very urgent and necessary discussion.

The COVID-2019 disease caused by the SARS-CoV-2 virus (aka 2019-nCoV) has raised significant health concerns in China and worldwide. While novel drug discovery and vaccine studies are long, repurposing old drugs against the COVID-2019 epidemic can help identify treatments, with known preclinical, pharmacokinetic, pharmacodynamic, and toxicity profiles, which can rapidly enter Phase 3 or 4 or can be used directly in clinical settings. In this study, we presented a novel network based drug repurposing platform to identify potential drugs for the treatment of COVID-2019. We first analysed the genome sequence of SARS-CoV-2 and identified SARS as the closest disease, based on genome similarity between both causal viruses, followed by MERS and other human coronavirus diseases. Using our AutoSeed pipeline (text mining and database searches), we obtained 34 COVID-2019-related genes. Taking those genes as seeds, we automatically built a molecular network for which our module detection and drug prioritization algorithms identified 24 disease-related human pathways, five modules and finally suggested 78 drugs to repurpose. Following manual filtering based on clinical knowledge, we re-prioritized 30 potential repurposable drugs against COVID-2019 (including pseudoephedrine, andrographolide, chloroquine, abacavir, and thalidomide) . We hope that this data can provide critical insights into SARS-CoV-2 biology and help design rapid clinical trials of treatments against COVID-2019.

Over the past few decades, aircraft Ground Handling Operations (GHO) have been investigated by numerous researchers. Some aspects of GHO have been more focused on than others due to their importance in the GH processes. For instance, GHO performance has been tackled from different perspectives while workers and vehicles allocation suffer from the lack of research in the area. This paper is a literary review of the research that has been conducted in different areas of GHO. It sheds light on GHO performance, resource allocation and scheduling, operations scheduling, vehicle routing, and workers and vehicles allocation.

As a result of identity prejudice, certain individuals are at higher risk for conflict and violence when they are in the field. At-risk individuals include minority identities of the following: race/ethnicity, sexual orientation, disability, gender identity, and/or religion. Everyone deserves to conduct fieldwork as safely as possible; therefore, it is paramount for anyone conducting fieldwork to be informed of the increased risk certain populations face when conducting field research and to define informed strategies. Research groups should adhere to best practices to minimize risk for all individuals who go into the field. Here we provide strategies that 1) acknowledge that some individuals encounter dangerous situations in the field due to their identity(ies), and 2) minimize the chance of conflict between and among researchers and other communities present at field sites. The inclusion of this document as a key resource in a research lab, a university department, or any active research or work environment sends a positive signal to at-risk individuals that their professional community acknowledges their risk and is willing to implement actions to ensure their safety. We suggest that this document be made freely available to anyone who is directly or indirectly involved in fieldwork. Supervisors who support the information in this document should publicly commit to promote a diverse and inclusive environment in order to maintain the safety of their researchers.

Precast concrete sandwich panels (PCSP) are energy efficient building system that is achieved through an insulation layer created between the concrete wythes. The insulation layer is usually of low bearing strength material making it more applicable for non-structural building systems. Hence, shear connectors are introduced to improve its structural capacity, which subsequently degrades it thermal performance by serving as thermal bridges across the panel. This article review researches of alternative materials and methods used to improve the thermal efficiency as well as reduced the strength loss due to insulation in PCSP. The alternative materials are basalt fibre reinforced polymer (BFRP), carbon fibre reinforced polymer (CFRP), glass fibre reinforced polymer (GFRP), and foam concrete which are selected due to their low thermal conductivity for use in shear connection. While thermal path method has been used to prevent the effect of thermal bridges. Although, some of these materials have successfully achieved the desirable behaviours, however, several undesirable properties such as brittleness, bond slip, the sudden crushing of the panel system, and FRP failure below its ultimate strength were observed. Hence, the practicality of the alternative materials is still questionable despite its higher cost compared to the conventional steel and concrete used in the PCSP system.

Superstition is a belief that is not based on scientific knowledge. Traditional healers usually use superstition in their practices to manage human health problems and diseases; such practices create a conflict with the medical profession and its evidence-based practices. Medical professionals confirm that this kind of practice is not safe to human health as it is done by untrained people (e.g., tradition healers) utilizing unsterilized instruments within unhygienic environments. Most of the cases eventually develop a variety of complications, which are sometimes fatal. Female genital mutilation, uvulectomy, oral mutilation (tooth bud extraction to cure “Ibyinyo”), and eyebrow incisions are examples of the many different types of superstitious practices which occur commonly in different parts of the world. We described how these traditional practices of superstition have been and continue to be performed in various parts of the world, their complications on oral and general health, and the ways such practices hinder modern medical practices. This paper aims to increase the awareness of these superstition-driven traditional and potentially harmful practices by promoting the importance of evidence-based medical practices.

Pipelines are widely used for transportation of hydrocarbon fluids over millions of miles over the world. The structures of the pipelines are designed to withstand several environmental loading conditions to ensure safe and reliable distribution from point of production to the shore or distributions deport. However, leaks in pipeline networks are one of the major causes of innumerable losses in pipeline operators and nature. Incidents of pipeline failure can result in serious ecological disasters, human casualties and financial loss. In order to avoid such menace and maintain safe and reliable pipeline infrastructure, substantial research efforts have been devoted to implementing pipeline leak detection and localisation using different approaches. This paper discusses on pipelines leakage detection technologies and summarises the state-of-the-art achievements. Different leakage detection and localisation in pipeline systems are reviewed and their strengths and weaknesses are highlighted. Comparative performance analysis is performed to provide a guide in determining which leak detection method is appropriate for particular operating settings. In addition, research gaps and open issues for development of reliable pipeline leakage detection systems are discussed.

COVID-19 pandemic represents an unprecedented sanitary threat: antiviral and host-directed medications to treat the disease are still urgently needed.A great effort has been paid to find drugs and treatments for hospitalized, severely ill patients. However, medications used for the domiciliary management of initial symptoms, notwithstanding their importance, have not been and are not presently regarded with the same attention. In analogy with other respiratory viral infections, COVID-19 patients in the early phase require specific antivirals (still lacking) and non-etiotropic drugs to lower pain, fever and control inflammation. Non-steroidal antinflammatory drugs (NSAIDs) and paracetamol (PAC) are widely used as non-etiotropic agents in these conditions and hence are both theoretically repurposable for COVID-19. However, a warning from some research reports and National Authorities raised NSAIDs safety concerns because of the supposed induction of ACE2 protein levels (the receptor used by SARS-CoV2 to enter host airways cells), the risk of bacterial superinfections and masking of disease symptoms. As a consequence, the use of NSAIDs was, and is, strongly discouraged while the alternative adoption of paracetamol is still preferred.On the basis of novel data and hypothesis on the possible role of scarce glutathione (GSH) levels in the exacerbation of COVID-19 and of the GSH depleting activity of PAC, this commentary raises the question of whether PAC may produce an oxidative imbalance which could be detrimental in COVID-19 clinical outcomes.

The thyroid gland secretes essential hormones for the growth regulation and the metabolic activity of the body. Thyroid dysfunction includes many conditions that can indirectly affect dental treatments. Therefore, the practitioner must be aware of these pathologies and their signs and symptoms in order to elaborate specific dental treatment plans, thus avoiding any per- and/or postoperative complications. Moreover, the dentist can help in the screening of undiagnosed thyroid dysfunction among patients.

Graph theory plays significant role in every field of science as well as technology. Every situation can be articulated in terms of suitable graphs by using various approaches of graph theory. Considering the recent pandemic in the world and the precautions taken for prevention of the COVID 19, it is the most appropriate way to exercise the graph models with theoretical as well as practical aspects to control this epidemic. This paper defines the variable set, variable graphs and their types with respect to variable vertex sets and variable edge sets. Depending upon the nature of the pandemic, there are four types of Virus graphs. Virus graph I and III are not so perilous for all living beings. Although, Virus graphs II and IV are extremely hazardous for the harmony of the world. In view of different aspects for expand of pandemic, growth types of virus graphs are divided in 1-1, 1-P and 1-all growth types. The COVID19 initially was in Virus graph-I type, but presently it is in Virus graph-II types. We present the table involving the number of infected people after n days with respect to different values of P and growth rates with I0 = 100. Moreover, the country wise starting dates of stages of the virus graph-I and II are specified. The concept of cut sets is applicable for prevention of COVID19 and the whole world is using the same analogy.

Anomaly detection is an active area of research with numerous methods and applications. This survey reviews the state-of-the-art of data-driven anomaly detection techniques and their application to the the aviation domain. After a brief introduction to the main traditional data-driven methods for anomaly detection, we review the recent advances in the area of neural networks, deep learning and temporal-logic based learning. We cover especially unsupervised techniques applicable to time series data because of their relevance to the aviation domain, where the lack of labeled data is the most usual case, and the nature of flight trajectories and sensor data is sequential, or temporal. The advantages and disadvantages of each method are presented in terms of computational efficiency and detection efficacy. The second part of the survey explores the application of anomaly detection techniques to aviation and their contributions to the improvement of the safety and performance of flight operations and aviation systems. As far as we know, some of the presented methods have not yet found an application in the aviation domain. We review applications ranging from the identification of significant operational events in air traffic operations to the prediction of potential aviation system failures for predictive maintenance.

Background: The incidences of COVID-19 related suicide among adolescents and youths have been reported across the world. There is no cumulative study focusing on nature, patterns, and causative factors that lead to the present investigation. Methods: A purposive sampling of google news between 15 February to 6 July was performed. After excluding duplicate reports, the final list comprised a total of 37-suicide cases across 11 countries. Results: More male suicides were reported (21-cases, i.e., 56.76%), and the mean age of the total victims was 16.6±2.7 years (out of a total of 29-cases). About two-thirds of the suicides were from three countries named India (11-cases), United Kingdom (8-cases), and the USA (6-cases). Out of 23-student victims, 14 were school-going students. Hanging was the most common suicide method accounting in 51.4% of cases. The most common suicide causalities were related to mental sufferings such as depression, loneliness, psychological distress, etc., whereas either online schooling or overwhelming academic distress was placed as the second most risk factors followed by TikTok addiction-related psychological distress, and tested with COVID-19. Conclusion: The finding of the temporal distribution of suicides concerning lockdowns may help in exploring and evolving public measures to prevent/decrease pandemic-related suicides in young people.

Postdocs who land faculty jobs at research-intensive institutions need to juggle several new large-scale tasks: identifying space and equipment needs for their lab, negotiating the hiring package, outfitting the lab with supplies, building a team, and learning to manage time in ways that can promote productivity and happiness. Here we share tips to help new hires think clearly about each of these tasks.

The proposed research methodology aims to design a generally implementable framework for providing a house owner/member with the immediate notification of an on-going theft (unauthorized access to their premises). For this purpose, a rigorous analysis of existing systems was undertaken to identify research gaps. The problems found with existing systems were that they can only identify the intruder after the theft, or cannot distinguish between human and non-human objects. Wireless Sensors Networks (WSNs) combined with the use of Internet of Things (IoT), Cognitive Internet of Things, Internet of Medical Things, and Cloud Computing are expanding smart home concepts and solutions, and their applications. The primary objective of the present research work was to design and develop IoT and cloud computing based smart home solutions. In addition, we also propose a novel smart home anti-theft system that can detect an intruder, even if they have partially/fully hidden their face using clothing, leather, fiber, or plastic materials. The proposed system can also detect an intruder in the dark using a CCTV camera without night vision facility. The fundamental idea was to design a cost-effective and efficient system for an individual to be able to detect any kind of theft in real-time and provide instant notification of the theft to the house owner. The system also promises to implement home security with large video data handling in real-time.

This paper shows a method for pipeline leak detection using a transient-based method with MATLAB® functions. The simulation of a pipeline systems in the time domain are very complex. In the case of the dissipative model, transfer functions are hyperbolic Bessel functions. Simulating a pipeline system in the frequency domain using a dissipative model we could find an approximate transfer function with equal frequency domain response to in order get the pipeline system's time domain response. The method described in this paper can be used to detect, by comparison, to detect a leak in a pipeline system model.

Trophoblast cell-surface antigen 2 (Trop 2) is a transmembrane glycoprotein that is highly expressed in various cancer types with relatively low or no baseline expression in most of normal tissues. Its overexpression is associated with tumor growth and poor prognosis; Trop 2 is therefore, an ideal therapeutic target for epithelial cancers. Several Trop 2 targeted therapeutics have recently been developed for the treatment of cancers, such as anti-Trop 2 antibodies and antibody-drug conjugates (ADCs), as well as Trop 2-specific cell therapy. In particular, the safety and clinical benefit of Trop 2-based ADCs have been demonstrated in clinical trials across multiple tumor types, including those with limited treatment options, such as triple-negative breast cancer, platinum-resistant urothelial cancer, and heavily pretreated non-small cell lung cancer. In this review, we elaborate on recent advances in Trop 2 targeted modalities and provide an overview of novel insights for future developments in this field.

Pakistan is an important country located in South Asia and ranks the world's sixth most populous country. It has diverse landscapes with their own specific vegetation. The country specific vegetative diversity has a great ecological and economic impact on the conservation of local fauna. It has huge potential for sustainable beekeeping industry if properly exploited. Beekeeping in Pakistan is mainly focused in Khyber Pakhtunkhwa and central and north regions of Punjab provinces but nowadays it is growing rapidly across the country. Honey produced in Pakistan enjoys good repute in the Middle East due to its unique taste and quality. Pakistan exports around 4000 tons of the honey with the worth of about $ 23.00 million to Arab countries every year.

The market of natural and organic cosmetics has been growing in last decades. The increase in interest in this type of product is a consequence of the concern that consumers have been presenting in relation to the environment and health. In addition to the appreciation the use of sustainable ingredients in cosmetic formulations, the consumers are also concerned about pollution caused by the use of plastics, which leads industries to reinvent themselves and rethink about the composition of packaging. The factor that most drives the purchase of natural and organic cosmetics is the fact that the consumer, in addition to contributing to the preservation of the environment, is also using a sustainable product. The growing demand for natural and organic cosmetics results in a concern of the brands with the organic issue, with the decreased use of animal derived ingredients and with the updating the parameters required for certification of a cosmetic as natural or organic. Due to the few studies available in this area, the importance of clarifying the definitions and concepts of natural and organic cosmetics is evident, in order to contribute with accurate information for the cosmetic sector.

Deep learning (DL), which is originated from an artificial neural network (ANN), is one of the major technologies of today's smart cybersecurity systems or policies to function in an intelligent manner. Popular deep learning techniques, such as Multi-layer Perceptron (MLP), Convolutional Neural Network (CNN or ConvNet), Recurrent Neural Network (RNN) or Long Short-Term Memory (LSTM), Self-organizing Map (SOM), Auto-Encoder (AE), Restricted Boltzmann Machine (RBM), Deep Belief Networks (DBN), Generative Adversarial Network (GAN), Deep Transfer Learning (DTL or Deep TL), Deep Reinforcement Learning (DRL or Deep RL), or their ensembles and hybrid approaches can be used to intelligently tackle the diverse cybersecurity issues. In this paper, we aim to present a comprehensive overview from the perspective of these neural networks and deep learning techniques according to today's diverse needs. We also discuss the applicability of these techniques in various cybersecurity tasks such as intrusion detection, identification of malware or botnets, phishing, predicting cyber-attacks, e.g. denial of service (DoS), fraud detection or cyber-anomalies, etc. Finally, we highlight several research issues and future directions within the scope of our study in the field. Overall, the ultimate goal of this paper is to serve as a reference point and guidelines for the academia and professionals in the cyber industries, especially from the deep learning point of view.

Hybrid machine tools combining additive and subtractive processes have arisen as a solution to the increasing manufacture requirements, boosting the potentials of both technologies, while compensating and minimizing their limitations. Nevertheless, the idea of hybrid machines is relatively new and there is a notable lack of knowledge in the field. Therefore, in the present paper, an insight into the advancements of hybrid machines is given, identifying their real capabilities, together with the latest developments from an industrial context. In addition, the current situation and future perspectives of hybrid machines from the point of view of process planning, monitoring and inspection are discussed. Finally, the challenges that must be overcome and the opportunities that the hybrid machines will provide in the forthcoming years are presented.

Wireless communication has proliferated due to the colossal augmentation of smart phones, mobile phones, tablets and laptops etc. Multimedia applications such as live videos, audios, still images, animated graphics and live communications all requires accompaniments of quality of service (QoS) as well as reliable end-to-end transfer of data. Information about the availability of resources in channel is must in order to improve the QoS. QoS can be determined in terms of capacity of channel, available bandwidth (ABW), and bulk transfer capacity (BTC). Bandwidth availability is a key check for improving the QoS in a network. The performance of a multimedia application is directly affected by the bandwidth availability. One of the most important QoS characteristic is ABW at a wireless route and it can be demarcated as least unused capacity of links instituting a network route. Since now there have been many bandwidth estimation techniques are available in the literature to increase the network performance. Bandwidth estimation techniques have been arranged into three leading classifications: i) Active probing bandwidth estimation techniques, ii) Passive bandwidth estimation technique and iii) Model based bandwidth estimation techniques. Each of these techniques are briefly discussed in this paper.