ABSTRACT
A unified framework that connects emissions with satellite‐observed column amounts is derived from first principles. The emission information originates from the inner product of the horizontal wind and the gradient of column amount, which is more accurate than the horizontal flux divergence as used in previous studies. Additionally, the topographical and chemical effects are accounted for through fitted scale height and chemical lifetime. This framework is applied to derive NOx and CO emissions over the CONUS from TROPOspheric Monitoring Instrument NO2 and CO observations. High‐resolution (0.04°) emission mapping over the CONUS reveals unprecedented details, including CO emissions in major cities and NOx emissions from large cities, power plants, and major roadways. Monthly resolved NOx emissions show decrease and rebound after the COVID‐19 pandemic. This framework is integrated with the physical oversampling algorithm and can be readily applied to other products from the new‐generation satellite instruments.Alternate :Plain Language SummarySatellites usually measure the vertically integrated column amount of atmospheric species from space. For short‐lived species like nitrogen oxides, the observed column amount indicates location and strength of emission sources. However, atmospheric dispersion smears the relationship between emission and column amount as the lifetime of species gets longer. This study directly maps emission based on the principle of mass balance. Namely, the spatial gradient of column amount should align with horizontal wind if there is an emission. Additionally, topography and chemical reaction may cause spatial gradients of column amount that are unrelated to emissions and are accounted for. Unprecedented details in the emission of air pollutants are unveiled by applying this approach to the TROPOspheric Monitoring Instrument products.
ABSTRACT
Modern information technology infrastructure is highly complex, and its monitoring requires the integration of different monitoring tools and management systems. This is especially important for businesses that must be able to provide their digital services in crisis situations, such as the COVID-19 pandemic. This paper identifies research methods suitable to evaluate algorithms for integrated processing of graphs and vertex metrics in data streams. They are identified by means of a literature review. The research finding will serve as an input for further research activities on methods and technological solutions that enable the creation of resilient digital services that are able to adapt to changing contexts and crises, combining big data analysis, knowledge management, business data, and knowledge ecosystems. © 2022 IEEE.
ABSTRACT
The paper analyses the grades assigned by the professors of the University of Milan to their students at the end of written exams, comparing what happened in academic year 2018-19 and in academic year 2020-21, i.e., before and during the crisis caused by the Covid-19 pandemic. In March 2020, the lockdown closed the classrooms, stopping face-to-face interactions among professors and students: it became then necessary to identify possible scenarios for carrying on written exams online, suitably monitoring student behaviors, and to propose them to the University professors. Main purpose of the analysis reported in this paper is a preliminary evaluation of the effectiveness of these scenarios, through comparison of the grades the professors assigned to their students. © Proceedings of the International Conference on E-Learning 2022, EL 2022 - Part of the Multi Conference on Computer Science and Information Systems 2022, MCCSIS 2022. All rights reserved.
ABSTRACT
The work analyzed the polymorphisms of the HLA-DRB1 and IL28 genes in 100 patients who underwent COVID-19 with the development of infection with varying degrees of severity. To a mild degree of severity were patients without complications in the form of infectious pneumonate, to moderate and severe degrees — with the development of pneumonate with varying degrees of lung damage. In general, the distribution of alleles in patients with COVID-19 did not differ from the distribution of average values in Russia. However, the HLA-DRB1 *01 и *07 alleles were more common. Comparison of the frequency of HLA-DRB1 alleles in patients with COVID-19 with varying severity revealed more common alleles of *13 and *07 in the severety severe group. However, with OR of 3.2 and 1.8, their confidence intervals (CL) were in the range of 0.9–9.8 and 0.7–4.5 respectively. At severe severity, the presence of homozigotic variants of allele *07 is noted. (Fisher exact test, r.0.04). As for the IL28B gene, no statistically significant dif-ferences from the control group were found. © 2021, Human Stem Cell Institute. All rights reserved.