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Local scientists and developers have also developed rapid diagnostic test kits, ventilators, and solar-powered handwashing machines. This paper highlights Ghana's innovativeness, scientific, and technological breakthroughs achieved so far in the fight against the pandemic.COVID-19 pandemic has ultimately brought down the world in a status of standstill as a result of lockdown as one of the measures to combat the situation and to prevent cross transmission. On the other hand, it has raised issues like ethical obligation of medical doctors and other staff to attend COVID-19 patients without proper PPE and resources increasing the risk to the staff and their family. In addition, it has resulted in compromise of the services provided to the people like non-availability of medical services to chronic and non-urgent patients. Non-COVID-19 patients attending 'Fever Clinic' were harmed due to inappropriate management. Medical staff dealing with testing or working in hospitals, isolation wards or quarantine centres have been stigmatized as 'possibly infected' and even denied food and accommodation.In this study, gross final energy consumption (GFEC), energy consumption of renewable energy sources (RES) and its share in France, Germany, Italy, Spain, Turkey and the United Kingdom (UK) are forecasted by 2030. A novel model is proposed in this study which is called optimized fractional nonlinear grey Bernoulli model, briefly as OFANGBM(1,1). In this model, three parameters, which are background value λ, power index value γ and fractional order value r, are optimized by genetic algorithm (GA) method. Results of OFANGBM(1,1) show that GFEC in France, Germany, Italy, Spain, Turkey and UK will reach to 151.7 Mtoe, 227.6 Mtoe, 110.8 Mtoe, 84.5 Mtoe, 173.4 Mtoe and 132.2 Mtoe, respectively, in 2030. Additionally, energy consumption from RES in France, Germany, Italy, Spain, Turkey and UK is forecasted as 28.5 Mtoe, 53.8 Mtoe, 22.2 Mtoe, 23.2 Mtoe, 26.1 Mtoe and 39.3 Mtoe, respectively, for the year 2030. Results of this study are compared with the national target of these countries on the share of RES in GFEC. Moreover, it is estimated that RES can satisfy 18.8%, 23.6%, 20.0%, 27.5%, 15.1% and 29.7% of GFEC in France, Germany, Italy, Spain, Turkey and UK in 2030, respectively.Coronavirus Disease 2019 (COVID-19) may spread through respiratory droplets released by infected individuals during coughing, sneezing, or speaking. Given the limited supply of professional respirators and face masks, the U.S. https://www.selleckchem.com/products/chir-99021-ct99021-hcl.html Centers for Disease Control and Prevention (CDC) has recommended home-made cloth face coverings for use by the general public. While there have been several studies on aerosol filtration performance of household fabrics, their effectiveness at blocking larger droplets has not been investigated. Here, we ascertained the performance of 11 common household fabrics at blocking large, high-velocity droplets, using a commercial medical mask as a benchmark. We also assessed the breathability (air permeability), texture, fiber composition, and water absorption properties of the fabrics. We found that most fabrics have substantial blocking efficiency (median values >70%). In particular, two layers of highly permeable fabric, such as T-shirt cloth, blocks droplets with an efficiency (>94%) similar to that of medical masks, while being approximately twice as breathable. The first layer allows about 17% of the droplet volume to transmit, but it significantly reduces their velocity. This allows the second layer to trap the transmitted droplets resulting in high blocking efficacy. Overall, our study suggests that cloth face coverings, especially with multiple layers, may help reduce droplet transmission of respiratory infections. Furthermore, face coverings made from materials such as cotton fabrics allow washing and reusing, and can help reduce the adverse environmental effects of widespread use of commercial disposable and non-biodegradable facemasks.The dataset deals with the air quality perceived by citizens before and during the enforcement of COVID-19 restrictions in ten countries around the world Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa and the United States. An online survey conveniently translated into Chinese, English, Italian, Norwegian, Persian, Portuguese collected information regarding the perceived quality of air pollution according to a Likert scale. The questionnaire was distributed between 11-05-2020 and 31-05-2020 and 9 394 respondents took part. Both the survey and the dataset (stored in a Microsoft Excel Worksheet) are available in a public repository. The collected data offer the people's subjective perspectives related to the objective improvement in air quality occurred during the COVID-19 restrictions. Furthermore, the dataset can be used for research studies involving the reduction in air pollution as experienced, to a different extent, by populations of all the ten countries.This dataset presents a survey data describing COVID-19 awareness, knowledge, preparedness and related behaviors among breast cancer patients in Indonesia. The data were collected from breast cancer patients through a survey distributed by an online questionnaire, assesing social-demographic characteristics (6 items), COVID-19 awareness (5 items), knowledge (2 items), preparedness (2 items) and related behaviors (2 items), from 20th June until 14th July 2020. The samples were gathered 500 breast cancer patients in Indonesia who were willing to fill an online questionnaire. SPSS version 23.0 was used to analyzed the data by descriptive and inferential statistics and SmartPLS 3 to created the partial least square path modeling. The data will help in preventing the transmission of COVID-19 among breast cancer patients and can support for health education and promotion interventions.Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the COVID-19 pandemic. It was first detected in China and was rapidly spread to other countries. Several thousands of whole genome sequences of SARS-CoV-2 have been reported and it is important to compare them and identify distinctive evolutionary/mutant markers. Utilizing chaos game representation (CGR) as well as recurrence quantification analysis (RQA) as a powerful nonlinear analysis technique, we proposed an effective process to extract several valuable features from genomic sequences of SARS-CoV-2. The represented features enable us to compare genomic sequences with different lengths. The provided dataset involves totally 18 RQA-based features for 4496 instances of SARS-CoV-2.