Notes

Phase 2 review involving ipilimumab and nivolumab within leptomeningeal carcinomatosis.
Finally, to predict the total number of COVID-19 infected until the end of the epidemic, the Gompertz, Logistic and inverse Artificial Neural Network model were used, predicting 469,917, 59,470 and 70,714 cases, respectively.Coronavirus disease-2019 (COVID-19) poses a significant threat to the population and urban sustainability worldwide. The surge mitigation is complicated and associates many factors, including the pandemic status, policy, socioeconomics and resident behaviours. Modelling and analytics with spatial-temporal big urban data are required to assist the mitigation of the pandemic. This study proposes a novel perspective to analyse the spatial-temporal potential exposure risk of residents by capturing human behaviours based on spatial-temporal car park availability data. Near real-time data from 1,904 residential car parks in Singapore, a classical megacity, are collected to analyse car mobility and its spatial-temporal heat map. The implementation of the circuit breaker, a COVID-19 measure, in Singapore has reduced the mobility and heat (daily frequency of mobility) significantly at about 30.0%. It contributes to a 44.3%-55.4% reduction in the transportation-related air emissions under two scenarios of travelling distance reductions. Urban sustainability impacts in both environment and economy are discussed. The spatial-temporal potential exposure risk mapping with space-time interactions is further investigated via an extended Bayesian spatial-temporal regression model. The maximal reduction rate of the defined potential exposure risk lowers to 37.6% by comparison with its peak value. The big data analytics of changes in car mobility behaviour and the resultant potential exposure risks can provide insights to assist in (a) designing a flexible circuit breaker exit strategy, (b) precise management via identifying and tracing hotspots on the mobility heat map, and (c) making timely decisions by fitting curves dynamically in different phases of COVID-19 mitigation. The proposed method has the potential to be used by decision-makers worldwide with available data to make flexible regulations and planning.Sustainability certification schemes such as FAIRTRADE, FLO, WFTO and FT-USA have gained increasing markets. The significant growth of the fair trade (FT) movement in the last decades draws attention to ethical consumption. FT's aim at improving the livelihoods of producers in developing countries and promotion of social change is considered a model that shows the benefits of trade to development. Although conveying a large number of publications, important questions about the movement remain under-explored. The literature is prolific on coffee, cacao, flowers, wine, and gold. In contrast, the engagement with staple foods - a prominent globally traded food category - seems minor. Elafibranor of this review was to map the existing literature about FT and staple foods; then, to investigate the role of staple foods in the FT movement. The search strategy was designed to retrieve publications on the intersection of FT and staple foods. To date, there is no review about FT and staple foods nexus. Our systematic review addressed this gap considering FT as an alternative capable of addressing unsustainable food consumption and production impacts. Our research protocol included keywords searching across four databases, screening, and comparative analysis. From 283 documents retrieved, 49 were deemed relevant to reflect the role of staple foods in the FT movement. This systematic review discusses challenges and opportunities for the FT model to further engage with staples and recommends improvement of its environmental credentials. The present study can contribute by informing decision makers, policy makers, businesses, NGOs, producers, and consumers.Currently, the "2019-CoV-2" has been raging across the world for months, causing massive death, huge panic, chaos, and immeasurable economic loss. Such emerging epidemic viruses come again and again over years, leading to similar destructive consequences. Air-borne transmission among humans is the main reason for the rapid spreading of the virus. Blocking the air-borne transmission should be a significant measure to suppress the spreading of the pandemic. Considering the hospital is the most probable place to occur massive cross-infection among patients as emerging virus usually comes in a disguised way, an air distribution optimization of a general three-bed hospital ward in China is carried out in this paper. Using the Eulerian-Lagrangian method, sneeze process from patients who are assumed to be the virus carrier, which is responsible for a common event to trigger cross-infection, is simulated. The trajectory of the released toxic particle and the probability of approaching others in the same ward are calculated. Two evaluation parameter, total maximum time (TMT) and overall particle concentration (OPC) to reflect the particle mobility and probability to cause cross-infection respectively, are developed to evaluate the proposed ten air distributions in this paper. A relatively optimized air distribution proposal with the lowest TMT and OPC is distinguished through a three-stage analysis. #link# Results show that a bottom-in and top-out air distribution proposal is recommended to minimize cross-infections.This study explores the response to COVID-19 from investigators, editors, and publishers and seeks to define challenges during the early stages of the pandemic. A cross-sectional bibliometric review of COVID-19 literature was undertaken between 1 November 2019 and 24 March 2020, along with a comparative review of Middle East respiratory syndrome (MERS) literature. Investigator responsiveness was assessed by measuring the volume and type of research published. Editorial responsiveness was assessed by measuring the submission-to-acceptance time and availability of original data. Publisher-responsiveness was assessed by measuring the acceptance-to-publication time and the provision of open access. Three hundred and ninety-eight of 2,835 COVID-19 and 55 of 1,513 MERS search results were eligible. Most COVID-19 studies were clinical reports (n = 242; 60.8%). The submission-to-acceptance [median 5 days (IQR 3-11) versus 71.5 days (38-106); P less then  .001] and acceptance-to-publication [median 5 days (IQR 2-8) versus 22.
Read More: https://www.selleckchem.com/products/elafibranor.html