Notes

Hydroxychloroquine as well as COVID-19: are we able to gain knowledge from the utilization of rituximab within endemic lupus erythematosus?
65 × 1010 MJ damage to resources. Besides, annual medical face mask production results in 5.88 × 104 TJ demand for exergy. On the other hand, if used makes are not appropriately handled, they can lead to 4.99 × 105 Pt/yr additional damage to the environment in 2020 as determined by the EDIP 2003. Replacement of fossil-based plastics with bio-based plastics, at rates ranging from 10 to 100%, could mitigate the product's total yearly environmental damage by 4-43%, respectively. Our study calls attention to the environmental sustainability of PPE used to prevent virus transmission in the current and future pandemics.An increase in the number of patients and death rates make Covid-19 a serious pandemic situation. This problem has effects on health security, economical security, social life, and many others. The long and unreliable diagnosis process of the Covid-19 makes the disease spread even faster. Therefore, fast and efficient diagnosis is significant for dealing with this pandemic. Computer-aided medical diagnosis systems are very common applications and due to the importance of the problem, providing accurate predictions is required. In this study, blood samples of patients from Einstein Hospital in Brazil has collected and used for prediction on the severity level of Covid-19 with machine learning algorithms. The study was constructed in two stages; in stage-one, no preprocessing method has applied while in stage-two preprocessing has emphasized for achieving better prediction results. At the end of the study, 0.98 accuracy was obtained with the tuned Random Forest algorithm and several preprocessing methods.We investigate how the economic consequences of the pandemic and the government-mandated measures to contain its spread affect the self-employed - particularly women - in Germany. For our analysis, we use representative, real-time survey data in which respondents were asked about their situation during the COVID-19 pandemic. Our findings indicate that among the self-employed, who generally face a higher likelihood of income losses due to COVID-19 than employees, women are about one-third more likely to experience income losses than their male counterparts. We do not find a comparable gender gap among employees. Our results further suggest that the gender gap among the self-employed is largely explained by the fact that women disproportionately work in industries that are more severely affected by the COVID-19 pandemic. Our analysis of potential mechanisms reveals that women are significantly more likely to be impacted by government-imposed restrictions, e.g., the regulation of opening hours. We conclude that future policy measures intending to mitigate the consequences of such shocks should account for this considerable variation in economic hardship.The energy efficiency and delay performance of PON are two inversely related phenomena. Higher sleep time of the Optical Network Units (ONUs) results in higher upstream (US) delays due to increased traffic queues during the ONU Asleep state. Although an efficient dynamic bandwidth and wavelength assignment (DWBA) scheme can decrease US delays by minimizing the bandwidth waste and improving the fairness of bandwidth distribution among the ONUs. However, the conventional DWBA schemes are not designed to work with cyclic sleep mode (CSM) and they keep on assigning bandwidth to ONUs even if the ONU is in Asleep state leading to wastage of bandwidth and degraded CSM performance. Therefore, in this work a sleep aware DWBA scheme for TWDM PON is presented to coordinate with CSM mode. It only assign bandwidth to Active ONUs during the guaranteed phase, surplus phase and excess phase allocation phases which minimizes the bandwidth waste and the bandwidth lost at the ONU end. The wavelength switching process is also improved by only considering the Active state ONUs to balance the traffic load on all the wavelengths. The simulation results support our claim as the SA-DWBA scheme on average achieves DWBA schemes due to up to 50% to 65% higher energy savings compared to other due to longer ONU Asleep times. However, the increased upstream delays of all the traffic classes in SA-DWBA scheme remain within the set delay limit of 50 ms.The Coronavirus disease (COVID-19) is an infectious disease caused by the newly discovered Severe Acute Respiratory Syndrome Coronavirus two (SARS-CoV-2). Most of the people do not have the acquired immunity to fight this virus. There is no specific treatment or medicine to cure the disease. The effects of this disease appear to vary from individual to individual, right from mild cough, fever to respiratory disease. It also leads to mortality in many people. As the virus has a very rapid transmission rate, the entire world is in distress. see more The control and prevention of this disease has evolved as an urgent and critical issue to be addressed through technological solutions. The Healthcare industry therefore needs support from the domain of artificial intelligence (AI). AI has the inherent capability of imitating the human brain and assisting in decision-making support by automatically learning from input data. It can process huge amounts of data quickly without getting tiresome and making errors. AI technologies and tools significantly relieve the burden of healthcare professionals. In this paper, we review the critical role of AI in responding to different research challenges around the COVID-19 crisis. A sample implementation of a powerful probabilistic machine learning (ML) algorithm for assessment of risk levels of individuals is incorporated in this paper. Other pertinent application areas such as surveillance of people and hotspots, mortality prediction, diagnosis, prognostic assistance, drug repurposing and discovery of protein structure, and vaccine are presented. The paper also describes various challenges that are associated with the implementation of AI-based tools and solutions for practical use.Online food delivery companies, nowadays, allow a customer to place an order for a combination of dishes from one or more restaurants. To meet a customer's demand, the company then arranges for the pickups from different restaurants, perhaps located distantly, before delivering them to the customer. The company caters to a set of such customers, through a fleet of capacitated vehicles. In this paper, we propose an augmented two-index formulation to find least cost vehicle routes to satisfy the set of customer requests under the constraints of time windows of the pickup and delivery locations along with the capacity constraints of the fleet of vehicles. We use branch-and-cut algorithm to solve the benchmark problem instances. The proposed formulation and the problem specific valid inequalities lead to more efficient solution performance as against the existing formulations. The computational experiments indicate that the proposed approach can solve a majority of benchmark problem instances with 25, 35 and 50 nodes, many of which were reported unsolved using exact solution approaches in the extant literature.
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