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Introduction: Modern reality gave human civilization a new challenge - the COVID-19 pandemic. Under these circumstances, distance learning has become the only opportunity to maintain an uninterrupted educational process. The authors share their experience of increasing productivity at foreign languages classes through applying their original techniques. Materials and methods: In their research, the authors used the following theoretical, empirical and mathematical methods: studying the literary sources accumulated by the Russian and foreign scientific communities;observing;survey;interpreting statistical data;building graphs. Results: Following the traditional guidelines in teaching a foreign language - comprehensive listening, speaking, reading, and writing - the authors tried to adjust the conventional methods to distance learning conditions. The aim was to reduce costs caused by the lack of face-to-face contact, ant to enjoy the advantages of students' continuous access to the Internet resources. Having analyzed their experience gained from April, 2020, to May, 2021, the authors came to the conclusion that the most tangible results had been gained through practicing such techniques as "chain retelling", "mute listening", "cross dialogue", and "analytical review of modern scientific content". While the former three helped to mostly sharpen students' comprehensive listening and speaking skills at practical classes, the latter was of special value by teaching theoretical linguistic disciplines. Such original approach to working with scientific literature gives Bachelor students a favourable chance to use the information from the shared bank for conducting their further research at all university levels. Conclusions: The proposed techniques have been tested in four leading Russian Universities, namely: Financial University under the Government of the Russian Federation, Plekhanov Russian University of Economics, Moscow City University, Moscow Financial and Industrial University "Synergy". The aspects improved are reflected in the graph compiled based on the students' survey results.
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BACKGROUND AND AIMS: The global pandemic with SARS-CoV-2 virus and Covid-19 threatened hemodialysis patients as vulnerable category with high risk for fatal outcome. The aim of the study was to determine the prevalence and risk factors for mortality in hemodialysis (HD) patients with confirmed Covid-19. METHOD: This study was retrospective, multicentric, and included all HD patients with positive PCR test for SARS-CoV-2 during the period of 10 months from March 1-December 31/2020. The outcome of patients with positive PCR test for SARS CoV-2 was evaluated. The following clinical parameters were compared in two groups of patients (the deceased and alive): age, sex, hemodialysis vintage, type of vascular access, BMI, Hemoglobin, WBC, Platelets, CRP, LDH, D-dimer, s-albumin, radiological findings, smoking abuse, therapy with ACE and ARBs, presence of symptoms and comorbidities: hypertension (HTA), diabetes mellitus (DM), coronary artery disease (CAD), chronic pulmonary disease (CPD), dyslipidemia, atrial fibrillation (AFF), malignancy, treatment in hospital and intensive care unit (ICU) with oxygen support and mechanical ventilation, and anticoagulant therapy. Statistical analysis was performed by SPSS, continued variables with ANOVA and categorical variables with Pearson Chi-square test and logistic regression. RESULTS: Of total 631 hemodialysis patients during the period of 10 months 162 patients (113 Mand 49 F) or 25,67% were with positive PCR test for SARS-CoV-2, they have had mean age 62,47±13,14 years and HD vintage 71,93±68,01 months. During the observed period 38 patients with Covid-19 (25 Mand 13 F) deceased, that represents mortality of 23,45%, 8 patients deceased at home and 30 patients in hospital. The mortality in patients with age range 18-49 years was 8%, with 50-59 years 18,9%, with 60-69 years 22,2%, with 70-79 years 31,2% and in patients with ≥ 80 years was 50%. Clinical parameters showed that the deceased patients compared with alive patients have had statistically significant higher age (67,7±10,57 vs 60,85±13,46 years;p=0.004), biochemical findings WBC (9,13±4,07 vs 6,45±3,0;p<0.001), LDH (394±4,07 vs 294±143;p=0.032), D-dimer (3699±4,07 vs 2025±2628;p=0.041), lower s-albumin (25,03±4,0 vs 34,57±6,89;p<0.001), and less hospital days (9,87±12,15 vs 16,24±14,31;p=0.04). Regarding comorbidities the mortality in the deceased patients was significantly higher in patients with chronic pulmonary disease (CPD) in comparison to patients without CPD (56,3% vs 19,9%;p=0.001), and in patients with malignancy in comparison to patients without malignancy (57,1% vs 21,9%;p=0.032). The mortality in hospitalized patients was significantly higher in comparison to treated patients at home (25,8% vs 10,5%;p<0.001) and was significantly higher in patients treated in ICU in comparison to patients treated at hospital (40,7% vs 25%;p<0.001). By logistic regression model it was determined that presence of chronic pulmonary disease (HR=6,178;p=0.008), ICU treatment (HR=5,311;p=0.01) and malignancy (HR=16,766;p=0.01) were the most predictive risk factors for mortality. CONCLUSION: Our study showed that mortality is high in HD patients with Covid-19 and amounts 23,45%, which is in accordance with other larger studies of ERACODA and ERA-EDTA registry regarding mortality of hemodialysis patients with Covid-19 (25% vs 20%). The mortality in HD patients with Covid-19 was associated with advanced age, high level of WBC, LDH and D-dimer, and low level of s-albumin. In contrast to general population, no association with gender, diabetes and cardiovascular disease, but significant association of mortality with presence of chronic pulmonary disease, malignancy, hospital and ICU treatment was found.
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This paper outlines the approach of team DIPS towards solving the CheckThat! 2021 Lab Task 2 - a semantic textual similarity problem for retrieving previously fact-checked claims. The task is divided into two subtasks, where the goal is to rank a set of already fact-checked claims based on their relevance to an input claim. The main difference between the two is the data sources, i.e., Task 2A's claims are tweets, while Task 2B - debates and speeches. For solving the task, we combine variety of algorithms - BM25, S-BERT, a custom classifier, and RankSVM into a claim retrieval system. Moreover, we show that data preprocessing is critical for such tasks and can lead to significant improvements in MRR and MAP. We have participated in the English edition of both subtasks and our system was ranked third in Task 2A, and first in Task 2B. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).