In this paper, we present a systematic analysis of large-scale human mobility patterns obtained from a passive Wi-Fi tracking system, deployed across different location typologies. We have deployed a system to cover urban areas served by public transportation systems as well as very isolated and rural areas. Over 4 years, we collected 572 million data points from a total of 82 routers covering an area of 2.8 km2. In this paper we provide a systematic analysis of the data and discuss how our low-cost approach can be used to help communities and policymakers to make decisions to improve people's mobility at high temporal and spatial resolution by inferring presence characteristics against several sources of ground truth. Also, we present an automatic classification technique that can identify location types based on collected data.The world health care community continues to heroically rise to the challenge of the coronavirus disease 2019 (COVID-19) pandemic, from the frontline care givers to informatics professionals. Within the world of COVID-19, clinical informatics' response can be compared to Marvel's X-Men, where evolution normally taking place over long years took place in a few short weeks. Major forward leaps in data use, utilizing big data for research because traditional studies that take years were not options, predictive analytic functionality retooled to help predict COVID-19, deployment of testing and medication research trials at a supersonic pace, design and launch of new telehealth care models, and exponential growth in information technology infrastructure were driven by the need to develop a "new normal" for safe and effective care for all patients. This article explores many of the rapid evolution improvements driven by the COVID-19 response. The environment of loosened regulations, support of collaborative practice between health systems and their vendors, and a global pressure to come up with solutions created the right primordial ooze for innovation to evolve at astonishing rates. From keeping up with the daily changes in regulations to the day-by-day support for an exhausted bedside clinician, informaticists are key contributors to a successful strategy to address the pandemic. The article also outlines several of the challenges informatics has been able to help with and how technology is being leveraged to help respond.Key challenges for the application of biodiesel include their high acid value, high viscosity, and low ester content. It is essential to develop later-generation biodiesel from unexploited non-food resources for a more sustainable future. Reuse of biowaste is critically important to address these issues of food safety and sustainability. Thus, the co-transesterification of waste cooking oil (WCO), algal oil (AO) and dimethyl carbonate (DMC) for the synthesis of fatty acid methyl esters (FAMEs) was investigated over a series of nanoparticle catalysts containing calcium, magnesium, potassium or nickel under mild reaction conditions. Nanoparticle catalyst samples were prepared from biowaste sources of chicken manure (CM), water hyacinth (WH) and algal bloom (AB), and characterized using XRD, Raman and FESEM techniques for the heterogeneous production of biodiesel. The catalyst was initially prepared by calcination at 850 °C for 4 h in a major presence of CaxMgyCO3, KCl and K2CO3. The WCO and AO co-conversion of 98% and FAMEs co-selectivity of 95% were obtained over CM nanoparticle catalyst under the reaction conditions of 80 °C, 20 mins and DMC to oil molar ratio of 61 with 3% catalyst loading and 3% methanol addition. Under the optimum condition, the density, viscosity, and cetane number of the biodiesel were in the range of diesel standards. Nanoparticle catalysts have been proven as a promising sustainable material in the catalytic transesterification of WCO and AO with the major presence of calcium, magnesium and potassium. This study highlights a sustainable approach via biowaste utilization for the enhancement of biodiesel quality with high ester content, low acid value, high cetane number, and low viscosity.In recent years, virtual reality (VR) technologies have been applied to the field of journalism, where the concept of immersive VR news has been proposed. However, despite the fanfare, strong response, and sensational effect caused by its advent, immersive VR news remains a novel journalism paradigm that faces new challenges in its production process. Currently, there is a lack of a unified design framework, and, since most studies in this area have focused on non-interactive VR news, the understanding of the effects of more interactive VR technologies on the news consumer remains inadequate. In this study, we propose a more practical design framework for immersive VR news products. Following this framework, we designed a VR news application and conducted user evaluation in terms of media effects and user experience. Based on the experimental findings, which demonstrated that non-interactive VR news products resulted in a distracting user experience and less immersion, while interactive VR news offered improved media effects and user experience, we then derived concrete design guidelines for immersive VR news design. selleck kinase inhibitor Finally, we highlight that this study provides a theoretical and practical reference framework for the further study of VR news.Being able to replicate research results is the hallmark of science. Replication of research findings using computational models should, in principle, be possible. In this manuscript, we assess code sharing and model documentation practices of 7500 publications about individual-based and agent-based models. The code availability increased over the years, up to 18% in 2018. Model documentation does not include all the elements that could improve the transparency of the models, such as mathematical equations, flow charts, and pseudocode. We find that articles with equations and flow charts being cited more among other model papers, probably because the model documentation is more transparent. The practices of code sharing improve slowly over time, partly due to the emergence of more public repositories and archives, and code availability requirements by journals and sponsors. However, a significant change in norms and habits need to happen before computational modeling becomes a reproducible science.