Mass Media as a Mirror of the COVID-19 Pandemic

The media plays an important role in disseminating facts and knowledge to the public at critical times, and the COVID-19 pandemic is a good example of such a period. This research is devoted to performing a comparative analysis of the representation of topics connected with the pandemic in the internet media of Kazakhstan and the Russian Federation. The main goal of the research is to propose a method that would make it possible to analyze the correlation between mass media dynamic indicators and the World Health Organization COVID-19 data. In order to solve the task, three approaches related to the representation of mass media dynamics in numerical form—automatically obtained topics, average sentiment, and dynamic indicators—were proposed and applied according to a manually selected list of search queries. The results of the analysis indicate similarities and differences in the ways in which the epidemiological situation is reflected in publications in Russia and in Kazakhstan. In particular, the publication activity in both countries correlates with the absolute indicators, such as the daily number of new infections, and the daily number of deaths. However, mass media tend to ignore the positive rate of confirmed cases and the virus reproduction rate. If we consider strictness of quarantine measures, mass media in Russia show a rather high correlation, while in Kazakhstan, the correlation is much lower. Analysis of search queries revealed that in Kazakhstan the problem of fake news and disinformation is more acute during periods of deterioration of the epidemiological situation, when the level of crime and poverty increase. The novelty of this work is the proposal and implementation of a method that allows the performing of a comparative analysis of objective COVID-19 statistics and several mass media indicators. In addition, it is the first time that such a comparative analysis, between different countries, has been performed on a corpus in a language other than English.

“When the Music’s Over” then “Dancing with a Partner Will Help You Find the Beat”

Responses to brain injury sit in the intersection between neuroscience and an ethic of care, and require sensitive and dynamic indicators of how an individual with brain injury can learn how to live in the context of a changing environment and multiple timescales. Therapeutic relationships and rhythms underpinning such a dynamic approach are currently obscured by existing models of brain function. Something older is required and we put forward narrative types articulating outcomes of brain injury over various periods and starting points in time. Such storytelling challenges a static neuropsychological paradigm and moves from an ethics that focuses on patient autonomy into one that is reflective of the cognitive supports and therapeutic relationships that underpin ways that the patient can re-find the beat that proves the music is not over.

Modernization Processes Development in the Implementation of Intellectual Capital in a Crisis

The article constructs the economic system modernization process, which reflects the qualitative influence of the intellectual capital features on the sequence of modernization transformation of the economic system: "resource supply" - "intellectualization" - "capitalization" - "modernization potential" - "modernization"; the system of infrastructure sphere modernization efficiency dynamic indicators at the enterprises is constructed and the analysis of its coherence is carried out; the modernization activity integrated indicators and intellectualization of the transport enterprises modernization process in the infrastructure sphere are substantiated and the assessment with their application is carried out.

Understanding the Abrupt Effect of Spousal Bereavement on Mortality: an Application of Complex Dynamic Systems Theory

BackgroundThe process of aging renders older people susceptible for adverse outcomes upon stress. Various indicators derived from complex systems theory have been proposed for quantifying resilience in living organisms, including humans. We investigated the ability of system-based indicators in capturing the dynamics of resilience in humans who suffer the adversity of spousal bereavement and tested their predictive power in mortality as a finite health transition.MethodsUsing longitudinal register data on weekly healthcare consumption of all Danish citizens over the age of 65 from January 1st, 2011, throughout December 31st, 2016, we performed statistical comparisons of the indicators ‘average’, ‘slope’, ‘mean squared error’, and ‘lag-1 autocorrelation’ one year before and after spousal bereavement, stratified for age and sex. The relation between levels of these indicators before bereavement and mortality hazards thereafter was determined by time to event analysis and the added value for mortality prediction was estimated by the time dependent area under the receiver operating characteristic curve.ResultsThe study included 934,003 citizens of whom 51,890 experienced spousal bereavement and 2862 died in the first year thereafter. Values of all dynamic indicators were significantly higher with increasing age, in men compared to women, and except lag-1 autocorrelation, higher in the year after bereavement (all p-values < 0.001). All dynamic indicators before bereavement were positively related with mortality hazards thereafter (all p-values < 0.001). The area under the curve of the final model to predict mortality, including all relevant indicators, was 77.7% for males and it was 81.8% for females.ConclusionsIt is concluded that healthcare consumption is increased, more volatile and accelerating with aging and in men compared to women. High values of these dynamic indicators before bereavement indicate loss of resilience as manifested by their predictive value to predict mortality when mourning after spousal loss.

From Classical Machine Learning to Deep Neural Networks: A Simplified Scientometric Review

There are promising prospects on the way to widespread use of AI, as well as problems that need to be overcome to adapt AI&ML technologies in industries. The paper systematizes the AI sections and calculates the dynamics of changes in the number of scientific articles in machine learning sections according to Google Scholar. The method of data acquisition and calculation of dynamic indicators of changes in publication activity is described: growth rate (D1) and acceleration of growth (D2) of scientific publications. Analysis of publication activity, in particular, showed a high interest in modern transformer models, the development of datasets for some industries, and a sharp increase in interest in methods of explainable machine learning. Relatively small research domains are receiving increasing attention, as evidenced by the negative correlation between the number of articles and D1 and D2 scores. The results show that, despite the limitations of the method, it is possible to (1) identify fast-growing areas of research regardless of the number of articles, and (2) predict publication activity in the short term with satisfactory accuracy for practice (the average prediction error for the year ahead is 6%, with a standard deviation of 7%). This paper presents results for more than 400 search queries related to classified research areas and the application of machine learning models to industries. The proposed method evaluates the dynamics of growth and the decline of scientific domains associated with certain key terms. It does not require access to large bibliometric archives and allows to relatively quickly obtain quantitative estimates of dynamic indicators.

INFLUENCE OF LATERAL DISPLACEMENT OF BOGIES ON THE FREIGHT CAR DYNAMICS

Purpose. The work is aimed at determining the influence of the lateral displacement of a freight car bogie, taking into account the value of the movement speed on its main dynamic indicators and interaction indicators of the rolling stock and the track. Methodology. The quantitative assessment of dynamic indicators was obtained by the method of mathematical and computer modeling. The design scheme of the car takes into account the interaction peculiarities of cars as part of the train: the possibility of all modes of body vibration in space, the transmission of longitudinal force from neighboring cars in vertical and horizontal directions, taking into account the technical condition of individual parts of the car and their design features, as well as various operating conditions. Findings. During the research, a mathematical model of a coupling of five freight cars was applied to study the dynamic loading of a gondola car and a track. Main dynamic and interaction indicators of the rolling stock and the track in case of transverse bogie displacement when moving along curved track sections assessment were assessed. The maximum possible values of the lateral displacement of the freight car bogie were substantiated. Originality. The mathematical model of the coupling of freight cars in the train has been improved. In the calculation schemes describing the vibrations of the cars, the peculiarities of the freight car bogies, lozenging of the bogie side frames are taken into account. The model makes it possible to study the effect of changing rotation angle of the central axis of the car body, which in turn leads to the lateral displacement of bogies relative to each other, on the main dynamic and interaction indicators of the rolling stock and the track. For the first time, the influence of transverse displacement of the bogie was investigated, taking into account the wear of its parts and assemblies when moving on track sections with unevenness. Practical value. The calculation results can be used to assess the influence of the bogie transverse displacement on the dynamic qualities of the rolling stock and interaction indicators of the rolling stock and the track, taking into account the wear of parts and units of the bogie when moving in straight and curved track sections with irregularities. The application of the results obtained will contribute to an increase in the stability of freight rolling stock in the conditions of increasing travel speeds, which in turn will allow developing technical conditions for the implementation of resource-saving technologies for transporting goods that meet the safety requirements of train traffic.