Learning from Covid: How Can we Predict Mobility Behaviour in the Face of Disruptive Events? – How to Investigate the Mobility of the Future

Introduction: With the beginning of the COVID-19 outbreak and the restrictions put in place to prevent an uncontrolled spread of the virus, the circumstances for daily activities changed. A remarkable shift in the modal split distribution was observed [Ank21]. Moreover, the changes in mobility during the COVID-19 pandemic had multiple impacts on road traffic [Yas21]. By now, several researchers have looked at the impact of COVID-19 as a disruptive event on mobility behaviour. This workshop within the 4th Symposium on Management of Future Motorway and Urban Traffic Systems aimed to discuss insights from these research projects and how they enable experts to transfer this newfound knowledge to future disruptive events such as climate change, rising energy costs and events related to a possible energy transition. Thus, the research question this workshop investigated reads as follows: What can we learn from the pandemic to be able to predict how different future disruptive events can shape the mobility of tomorrow

Pneumocystis pneumonia mimicking COVID-19

Background. The new coronavirus infection COVID-19 caused by a SARS-CoV-2 zoonotic beta-coronavirus has radically transformed the conventional concept of the immune systems participation in an infectious process. The successful application of anti-interleukin monoclonal antibodies and inhibitors of Janus kinases in COVID-19, traditionally contraindicated in infections, testifies that the immune response to the pathogen may be more dangerous than the infection itself. However, when prescribing the immunosuppressive therapy to COVID-19 patients, one should not forget that some interstitial pneumonias caused by opportunistic microflora, such as Pneumocystis Jirovecii, have similar clinical and radiological manifestations. Clinical case description. A 29-year old female patient was admitted to the infectious disease hospital with complaints of a febrile temperature, shortness of breath at rest, low-productive cough, pronounced weakness. She had been ill for 14 days, the SARS-CoV-2 RNA was detected at the pre-hospital stage. After the admission, a chest CT scan was performed showing a subtotal lung damage with the characteristic radiological manifestations of interstitial pneumonia in the form of ground glass opacity regions, presence of air traps, that was initially attributed to bilateral viral pneumonia (СТ-3/4). The subsequent examination confirming primary HIV infection and a sputum analysis positive for P. Jirovecii allowed us to establish a correct clinical diagnosis of pneumocystis pneumonia against the background of HIV infection and a mild COVID-19 course, administer a co-trimoxazole therapy and obtain a favorable outcome. Conclusion. This observation demonstrates the necessity of applying an individual approach to each patient admitted to a COVID hospital and performing a differential diagnosis, even when COVID-19 is confirmed by the laboratory work, in order not to miss other interstitial pneumonias, in particular, pneumocystis pneumonia appearing against the background on immunodeficiency

Safety and efficacy of convalescent plasma for COVID-19: the preliminary results of a clinical trial

Background. The lack of effective etiotropic therapy for COVID-19 has prompted researchers around the globe to seekr various methods of SARS-CoV-2 elimination, including the use of convalescent plasma. Aim. The aim of this work was to study the safety and efficacy of the convalescence plasma treatment of severe COVID-19 using the plasma containing specific antibodies to the receptor binding domain (RBD) of SARS-CoV-2 S protein in a titer of at least 1:1000. Methods. A single-center, randomized, prospective clinical study was performed at the FRCC FMBA of Russia with the participation of 86 patients who were stratified in two groups. The first group included 20 critically ill patients who were on mechanical ventilation the second group included 66 patients with moderate to severe COVID-19 and with spontaneous respiration. The patients in the second group were randomized into two cohorts in a ratio of 2:1. In the first cohort (46 patients), pathogen-reduced convalescent plasma was transfused (twice, 320 ml each), in the second cohort (20 patients) a similar amount of non-immune freshly frozen plasma was transfused to the patients. Results. The use of plasma of convalescents in patients with severe COVID-19 being on mechanical ventilation does not affect the disease outcome in these patients. The mortality rate in this group was 60%, which corresponds to the average mortality of COVID patients on mechanical ventilation in our hospital. In the second group, clinical improvement was detected in 75% and 51%, for convalescent and non-immune plasma, respectively. Of the 46 people who received convalescent plasma, three patients (6.5%) were transferred to mechanical ventilation, two of them died. In the group receiving non-immune plasma, the need for mechanical ventilation also arose in three patients (15%), of which two died. The hospital mortality in the group of convalescent plasma was 4.3%, which is significantly lower than the average COVID-19 hospital mortality at our Center (6.73%) and more than two times lower than the hospital mortality in the control group (n=150), matched by age and by the disease severity. Conclusions. Thus, we demonstrated a relative safety of convalescent plasma transfusion and the effectiveness of such therapy for COVID-19 at least in terms of the survival of hospitalized patients with severe respiratory failure without mechanical ventilation. In the absence of bioengineered neutralizing antibodies and effective etiotropic therapy, the use of hyperimmune convalescent plasma is the simplest and most effective method of specific etiopathogenetic therapy of severe forms of COVID-19

Genetic landscape in Russian patients with familial left ventricular noncompaction

BackgroundLeft ventricular noncompaction (LVNC) cardiomyopathy is a disorder that can be complicated by heart failure, arrhythmias, thromboembolism, and sudden cardiac death. The aim of this study is to clarify the genetic landscape of LVNC in a large cohort of well-phenotyped Russian patients with LVNC, including 48 families (n=214).MethodsAll index patients underwent clinical examination and genetic analysis, as well as family members who agreed to participate in the clinical study and/or in the genetic testing. The genetic testing included next generation sequencing and genetic classification according to ACMG guidelines.ResultsA total of 55 alleles of 54 pathogenic and likely pathogenic variants in 24 genes were identified, with the largest number in the MYH7 and TTN genes. A significant proportion of variants −8 of 54 (14.8%) −have not been described earlier in other populations and may be specific to LVNC patients in Russia. In LVNC patients, the presence of each subsequent variant is associated with increased odds of having more severe LVNC subtypes than isolated LVNC with preserved ejection fraction. The corresponding odds ratio is 2.77 (1.37 −7.37; p <0.001) per variant after adjustment for sex, age, and family.ConclusionOverall, the genetic analysis of LVNC patients, accompanied by cardiomyopathy-related family history analysis, resulted in a high diagnostic yield of 89.6%. These results suggest that genetic screening should be applied to the diagnosis and prognosis of LVNC patients

A Multifaceted Quantification of Bias in Large Language Models

Language models are rapidly developing, demonstrating impressive capabilities in comprehending, generating, and manipulating text. As they advance, they unlock diverse applications across various domains and become increasingly integrated into our daily lives. Nevertheless, these models, trained on vast and unfiltered datasets, come with a range of potential drawbacks and ethical issues. One significant concern is the potential amplification of biases present in the training data, generating stereotypes and reinforcing societal injustices when language models are deployed. In this work, we propose methods to quantify biases in large language models. We examine stereotypical associations for a wide variety of social groups characterized by both single and intersectional identities. Additionally, we propose a framework for measuring stereotype leakage across different languages within multilingual large language models. Finally, we introduce an algorithm that allows us to optimize human data collection in conditions of high levels of human disagreement

Development strategies for small and medium-sized enterprises with limited investment resources

The main source of investment resources for small and medium-sized enterprises is their own profit. The dynamic development of these enterprises is possible only with a strategic program aimed at implementing independent discrete measures. The following tasks are relevant: development of a set of program measures; optimization of measures; maintenance of the financial stability of the enterprise by adjusting development program indicators. The indicators are strategic guidelines for the development. The target functions of the effectiveness of strategic management are minimization of the period of implementation of the development program and the maximum asset growth rate. To assess the effectiveness of development, the following indicators developed by the authors can be used: the coefficient of innovation management, which characterizes the average geometric growth rate of assets attracted during the initial period; the index of innovation management, which characterizes the quality of management by comparing the average geometric growth rate of assets of the optimal and basic variants of the development program

Learning from Covid: How Can we Predict Mobility Behaviour in the Face of Disruptive Events? – How to Investigate the Mobility of the Future

Introduction: With the beginning of the COVID-19 outbreak and the restrictions put in place to prevent an uncontrolled spread of the virus, the circumstances for daily activities changed. A remarkable shift in the modal split distribution was observed [Ank21]. Moreover, the changes in mobility during the COVID-19 pandemic had multiple impacts on road traffic [Yas21]. By now, several researchers have looked at the impact of COVID-19 as a disruptive event on mobility behaviour. This workshop within the 4th Symposium on Management of Future Motorway and Urban Traffic Systems aimed to discuss insights from these research projects and how they enable experts to transfer this newfound knowledge to future disruptive events such as climate change, rising energy costs and events related to a possible energy transition. Thus, the research question this workshop investigated reads as follows: What can we learn from the pandemic to be able to predict how different future disruptive events can shape the mobility of tomorrow

Learning from Covid: How Can we Predict Mobility Behaviour in the Face of Disruptive Events? – How to Investigate the Mobility of the Future

Introduction: With the beginning of the COVID-19 outbreak and the restrictions put in place to prevent an uncontrolled spread of the virus, the circumstances for daily activities changed. A remarkable shift in the modal split distribution was observed [Ank21]. Moreover, the changes in mobility during the COVID-19 pandemic had multiple impacts on road traffic [Yas21]. By now, several researchers have looked at the impact of COVID-19 as a disruptive event on mobility behaviour. This workshop within the 4th Symposium on Management of Future Motorway and Urban Traffic Systems aimed to discuss insights from these research projects and how they enable experts to transfer this newfound knowledge to future disruptive events such as climate change, rising energy costs and events related to a possible energy transition. Thus, the research question this workshop investigated reads as follows: What can we learn from the pandemic to be able to predict how different future disruptive events can shape the mobility of tomorrow

Transcranial Direct Current Stimulation Modulates Neuronal Networks in Attention Deficit Hyperactivity Disorder

Anodal transcranial direct current stimulation (tDCS) of the prefrontal cortex has been repeatedly shown to improve working memory (WM). Since patients with attention deficit hyperactivity disorder (ADHD) are characterized by both underactivation of the prefrontal cortex and deficits in WM, the modulation of prefrontal activity with tDCS in ADHD patients may increase their WM performance as well as improve the activation and connectivity of the WM network. In the present study, this hypothesis was tested using a double-blind sham-controlled experimental design. After randomization, sixteen adolescents with ADHD underwent either anodal tDCS over the left dorsolateral prefrontal cortex (DLPFC, 1 mA, 20 min) or sham stimulation with simultaneous fMRI during n-back WM task. Both in one-back and two-back conditions, tDCS led to a greater activation (compared with sham stimulation) of the left DLPFC (under the electrode), left premotor cortex, left supplementary motor cortex, and precuneus. The effects of tDCS were long-lasting and influenced resting state functional connectivity even 20 min after the stimulation, with patterns of strengthened DLPFC connectivity after tDCS outlining the WM network. In summary, anodal tDCS caused increased neuronal activation and connectivity, not only in the brain area under the stimulating electrode (i.e. left DLPFC) but also in other, more remote brain regions. Because of moderate behavioral effects of tDCS, the significance of this technique for ADHD treatment has to be investigated in further studies.Fil: Sotnikova, Anna. Universitat Marburg; AlemaniaFil: Soff, Cornelia. Universitat Marburg; AlemaniaFil: Tagliazucchi, Enzo Rodolfo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Becker, Katja. Universitat Marburg; AlemaniaFil: Siniatchkin, Michael. Christian-albrechts-universitat Zu Kiel; Alemani

Design of The Learning Environment Considering the Gender Characteristics of Students

In this study, the motivation and cognitive characteristics of students in the implementation of a gender-based approach to teaching and their consideration in the educational process of boys and girls are presented. The purpose of the study is to verify empirically the effectiveness of the design of the learning environment considering the gender characteristics of students by analyzing the cognitive characteristics of children studying in different types of classes. In the study, the following methods were used: “Amthauer Intelligence Structure Test” adapted by L. A. Yasyukova , “Test for assessing the formation of reading skills”, “Test for assessing the independence of thinking”, test “Determining the level of school motivation and emotional attitude to learning (Spilberg-Andreeva)”, as well as observation, comparison and assessment. It is shown that children studying in same-sex classes show a higher motivation for learning; their cognitive abilities manifest themselves differently than in mixed classes